The Political Economy of Military Spending in the United States

THE POLITICAL ECONOMY OF MILITARY SPENDING IN THE UNITED STATES THE POLITICAL ECONOMY OF MILITARY SPENDING IN THE UNI...

Author: Alex Mintz

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THE POLITICAL ECONOMY OF MILITARY SPENDING IN THE UNITED STATES

THE POLITICAL ECONOMY OF MILITARY SPENDING IN THE UNITED STATES

Edited by

Alex Mintz

London and New York

First published 1992 by Routledge 11 New Fetter Lane, London EC4P 4EE This edition published in the Taylor & Francis e-Library, 2003. Simultaneously published in the USA and Canada by Routledge a division of Routledge, Chapman and Hall, Inc. 29 West 35th Street, New York, NY 10001 ©1992 Alex Mintz All rights reserved. No part of this book may be reprinted or reproduced or utilized in any form or by any electronic, mechanical or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. British Library Cataloguing in Publication Data The political economy of military spending in the United States I. Mintz, Alex 336.73 ISBN 0-203-22164-8 Master e-book ISBN

ISBN 0-203-22380-2 (Adobe eReader Format) ISBN 0-415-07595-5 (Print Edition) Library of Congress Cataloging-in-Publication Data Has been applied for ISBN 0-415-07595-5

Contents Notes on the contributors

page vii

1 Introduction: Political Economy and National Security

Alex Mintz 1

Part I: Cycles in Military Spending 2 Elections, Business Cycles, and the Timing of Defense Contract Awards in the United States Kenneth R.Mayer 3 Do Leaders Make a Difference? Posture and Politics in the Defense Budget William K.Domke 4 Too Little, but Not For Too Long: Public Attitudes on Defense Spending Richard J.Stoll 5 Risky Business: US–Soviet Competition and Corporate Profits Michael D.Ward and David R.Davis 6 On the Domestic Political-Economic Sources of American Military Spending Thomas R.Cusack

15 33 52 65 103

Part II: The Political Economy of Military Spending and Military Action 7 Military Buildup, War Escalation, and Business Confidence: Wall Street’s Reaction to the Vietnam Conflict Steve Chan 8 The Political Economy of Military Actions: The United States and Israel Bruce Russett and Gad Barzilai

135 155

Part III: Defense Spending and Economic Performance 9 ‘Guns’ vs ‘Butter’: A Disaggregated Analysis Alex Mintz 10 Guns, Butter, and Debt: Balancing Spending Tradeoffs between Defense, Social Programs, and Budget Deficits Jin Whyu Mok and Robert D.Duval 11 Defense Budgeting, Fiscal Policy, and Economic Performance Stephen J.Majeski 12 Military Burden and Economic Hegemonic Decline: The Case of the United States Chi Huang and Francis W.Hoole v

185

196 217

238

CONTENTS

vi

Part IV: Issues in Defense Spending 13 Issues in Defense Spending: Plausibility and Choice in Soviet Estimates Robin F.Marra and Charles W.Ostrom, Jr 261 14 Expectations and the Dynamics of US Defense Budgets: A Critique of Organizational Reaction Models John T.Williams and Michael D.McGinnis 282 15 Conclusions: If the Times Are A’changing Davis B.Bobrow

305

Appendix: The Political Economy of Defense Spending Data Set Alex Mintz and Chi Huang

319

Index

325

Notes on the Contributors Gad Barzilai teaches Political Science at Tel Aviv University, Israel. He holds a PhD degree from the Hebrew University of Jerusalem. His scholarly interests are in the fields of International Relations, Methodology, Middle East Politics, and Israeli Politics. He is the author of Wars and Social Order in Israeli Politics (forthcoming), and of articles and chapters in the Journal of Comparative Strategy, Middle East Contemporary Survey, and the Elections in Israel— 1988. Davis B.Bobrow is Dean of the Graduate School of Public and International Affairs, University of Pittsburgh, where he is also Professor of Public and International Affairs and of Political Science. He has been associated with the US Defense Science Board since 1972 and previously held senior positions in the Advanced Research Projects Agency, and in the Office of the Director of Defense Research and Engineering. Steve Chan is Professor of Political Science at the University of Colorado (Boulder). His most recent book is East Asian Dynamism (Westview). He has also published articles in journals such as the American Political Science Review, Comparative Political Studies, International Studies Quarterly, Journal of Conflict Resolution, and World Politics. He is the 1988 recipient of the Karl W.Deutsch award of the International Studies Association. Thomas R.Cusack is Group Leader of the International Relations Research Group at the Wissenschaftszentrum Berlin fuer Sozialforschung. He has published extensively in the areas of international relations, comparative public finance, and defense economics. David R.Davis is Assistant Professor of political science at Emory University. His dissertation, “The Defense Ledger,” is concerned with the political and economic consequences of military spending in the NICs. He has recently published articles in the Journal of Conflict Resolution, the Journal of Peace Research and Comparative Political Studies.

vii

viii

THE CONTRIBUTORS

William K.Domke is a research scientist in the International Assessments Section of the Lawrence Livermore National Laboratory, University of California. His research focuses on national security and defense policy in advanced industrial democracies. He is the author of War and the Changing Global System (1988). His work has also appeared in the American Political Science Review and World Politics. Robert D.Duval is currently an Associate Professor of Political Science at West Virginia University, and Director of the Graduate Program in Public Policy. He has published in the American Journal of Political Science, the Journal of Conflict Resolution, the British Journal of Political Science, and the American Journal of Cardiology. Her is currently engaged in research on arms race models and writing a book on global climate change. Francis W.Hoole is Professor of Political Science, Professor (part-time) of Public and Environmental Affairs, and Associate Dean for Research at the University Graduate School at Indiana University, Bloomington. His scholarly interests are in the fields of international relations, methodology, and public policy. He is author of Politics and Budgeting in the World Health Organization (Bloomington, Indiana: Indiana University Press, 1976) and Evaluation Research and Development Activities (Beverly Hills, California: Sage Publications, 1978), editor (with Dina A.Zinnes) of Quantitative International Politics: An Appraisal (New York: Praeger, 1976) and editor (with Robert L.Friedheim and Timothy M.Hennessey) of Making Ocean Policy: The Politics of Government Organization and Management (Boulder, Colorado: Westview Press, 1981). Professor Hoole is author or co-author of numerous chapters in books and articles in journals such as the American Journal of Political Science, International Organization, International Studies Quarterly, Journal of Politics and the Journal of Conflict Resolution. Chi Huang is Associate Professor of Political Science at Texas A&M University. His research interests focus on political methodology, the political economy of development, and the guns-butter tradeoff. He is author or co-author of articles published in Comparative Political Studies (1989), Journal of Conflict Resolution (1989), International Studies Notes (1990), American Political Science Review (1990), American Journal of Political Science (1991), and Defence Economics (1991). Michael D.McGinnis is Associate Professor of Political Science at Indiana University. His research on rational models of international conflict and cooperation in superpower and regional rivalry systems has appeared in articles in the American Political Science Review, American Journal of Political Science,

The Contributors

ix

International Studies Quarterly, the Journal of Conflict Resolution, and International Interactions. He is currently working on a book with John T.Williams on the dynamics of superpower rivalry. Stephen Majeski is an Associate Professor of Political Science at the University of Washington. He has published numerous articles on defense budgeting and arms races. He is currently working on a project on how foreign policies are constructed. Robin F.Marra is Assistant Professor of Political Science at Southern Methodist University. He holds a Ph.D. degree from Michigan State University and publishes in the areas of international politics and methodology. He is currently doing research on the political use of force. Kenneth R.Mayer is Assistant Professor of Political Science at the University of Wisconsin Madison. Prior to joining the faculty at UW, he was a contract specialist for the Naval Air Systems Command in Washington D.C. (1985– 86), a John M.Olin Dissertation Fellow at Harvard University’s Center for International Affairs (1987–88), and a consultant for the RAND Corporation. Author of The Politics of Defense Contracting (Yale University Press, forthcoming). Jin W.Mok is an Assistant Professor of Public Administration at West Virginia University. He has published recently in Policy Studies Journal and Knowledge in Society. He is currently engaged in research on issues in defense spending in non-Western Nations. Charles W.Ostrom, Jr. is Professor of Political Science at Michigan State University. He holds a Ph.D. degree from Indiana University and publishes in the areas of international politics, methodology, and presidential popularity. He is currently doing research on the presidency and foreign policy. Bruce Russett is Dean Acheson Professor of International Relations and Political Science at Yale University, and Editor of the Journal of Conflict Resolution. He has held visiting appointments in England, Belgium, Israel, the Netherlands, and was president of the International Studies Association and the Peace Science Society (International). His most recent book is Controlling the Sword: The Democratic Governance of National Security (Harvard University Press, 1990). Richard J.Stoll is Professor of Political Science at Rice University in Houston, Texas. His research interests include the quantitative study of international conflict, American defense policy, and the use of computer simulation. He is author of U.S. National Security Policy and the Soviet Union: Persistent

x

THE CONTRIBUTORS

Regularities and Extreme Contingencies, published by the University of South Carolina Press, and (along with Thomas R.Cusack) co-author of Exploring Realpolitik: Probing Internation Relations Theory with Computer Simulation, published by Lynne Rienner. In addition, he has co-redited Power in World Politics (with Michael Ward), published by Lynne Rienner, and Choices in World Politics: Sovereignty and Interdependence (with Bruce Russett and Harvey Starr), published by W.H.Freeman. Michael D.Ward is Professor of Political Science at the University of Colorado, Boulder where he is also a member of the professional staff at the Institute of Behavioral Science. Most of his current work concentrates on the political economy of the defense sector in developed and developing societies. John T.Williams is Associate Professor of Political Science at Indiana University. His research on the US political economy and superpower rivalry has appeared in articles in the American Political Science Review, American Journal of Political Science, American Politics Quarterly, Political Methodology, and the Journal of Conflict Resolution. He is currently working with Michael McGinnis on a book on the dynamics of superpower rivalry.

CHAPTER 1

Introduction: Political Economy and National Security Alex Mintz

In a recent report on the state of security studies, Joseph S.Nye and Sean Lynn-Jones argue (1988:25) that the division between the fields of national security and political economy is ‘one of the most serious problems within the discipline of political science.’ According to Nye and Lynn-Jones, scholars on each side of the divide have often ignored the work done on the other side. Barnett (1990:3) has similarly pointed out that too often ‘the study of national security has treated “high politics”, a state’s security relations vis-a-vis other states in the international system, [separately from] “low politics”, societal pressures and the domestic political economy.’ According to Barnett, most studies almost uniformly assume ‘that the domestic political economy and national security issues are separate and distinct spheres.’ In light of the current debate on the size of the defense budget and the “peace dividend”, it is particularly important to integrate the contributions of national security with those of political economy. The state is situated within the domestic and global political economies, and its national security policy is typically shaped not only by security considerations, but also by domestic, political and economic factors. While several scholars have indeed shown that domestic societal forces are an important determinant of the state’s foreign economic policy, these insights have not been transferred to the security field (Barnett 1990:3–4; Brown and Korb 1982). National security policy often extends beyond the superpowers’ rivalry, regional conflicts, deterrence, and arms control to include domestic political and economic issues (Nye and Lynn-Jones 1988). Work on defense spending has begun, therefore, to focus also on political economic determinants of military spending (see e.g. Cusack and Ward 1981; Griffin et al. 1982; Mintz and Hicks 1984; Nincic and Cusack 1979; Russett and Hanson 1975). This 1

INTRODUCTION

2

approach has recently been transferred to the analysis of defense spending of other countries, including several developing and newly industrialized countries (see Chan’s work 1988 on Taiwan; Agbese 1988 on Nigeria; and Park 1986 and Ward and Park 1989 on Korea). Military spending policy often results from the interplay of political and economic factors (Mintz 1985, 1988 and Mintz and Ward 1989). As one contributor to this volume has noted (see Mayer, Chapter 2), political and economic factors often induce higher levels of defense spending than are ‘necessary’ for national security. A political economy perspective on defense spending is therefore introduced in this volume.

THREE PERSPECTIVES ON DEFENSE SPENDING Two approaches have dominated the study of military spending since the early 1960s: (1) (2)

the arms race approach, based on the work of Richardson (1960), Ostrom (1977), Ward (1984), and Zinnes and Gillespie (1973); the organizational politics/incremental approach (see Davis, Dempster, and Wildavsky 1966; Wildavsky 1964).

A third perspective is represented by the collection of articles included in this volume. The arms race approach Samuel Huntington (1958:41) defined an arms race as ‘a progressive competitive peace time increase in armament by two states or coalitions of states resulting from conflicting purposes or mutual fears.’ At the core of the arms race model is the idea that nations react to changes in the behavior of rival countries. Former Secretary of Defense Caspar W. Weinberger explained in one of his annual reports to Congress that the US attempts to determine the nature and extent of the threats to its vital national security interests, and to formulate its defense budget accordingly (US Department of Defense 1983:4). Bruce Russett and Harvey Starr (1989:322–30) identified four distinct periods in the US–USSR arms race in the post-World War II era: 1945–50— the period of US nuclear monopoly; 1951–57—the period of US nuclear dominance; 1958–66—US preponderance; 1967 to the late 1980s—the period of essential equivalence. George Rathjens (1975) noted several examples of the superpower arms race: US over-reaction to uncertainty at the time of the

Introduction

3

so-called ‘missile gap’ in 1960 led to the massive growth of the US missile forces during the succeeding decade; the scale of this deployment may have led, in turn, to the large Soviet buildup in strategic offensive forces and the deployment of a limited anti-ballistic missile (ABM) system surrounding Moscow. The United States responded to the possible nationwide extension of the Moscow ABM system (and the deployment of a Soviet anti-aircraft system) by equipping US Minuteman III and Poseidon missiles with multiple reentry vehicle (MIRV) warheads. The corresponding Soviet reaction to the counter-force threat posed by the MIRVs was the development of land mobile inter-continental ballistic missiles (ICBMs) and the development and deployment of Soviet MIRVs (on SS-18 and SS-19 ICBMS and on SS-20 intermediate-range missiles). Western reports indicated that, during the 1970s, the Soviets were engaged in a massive military buildup: whereas US military strength declined by about 20 percent during that period, the Soviets increased the level of funding of their programs by about 50 percent. According to Pentagon officials, the Reagan buildup was intended to arrest the relative decline in US military power in the 1970s and the apparent change in the superpower military balance. In reaction to US developments of air-, ground, and sea-launched cruise missiles, the Soviets announced emplacement of their own cruise missiles. Ward (1984) noted that the United States reduces defense spending in reaction to decreases in the level of international tension. The collapse of the Warsaw Pact and easing of tensions between East and West, have indeed led to proposed cuts in US troops and budgets (Mintz and Huang 1990). In contrast to the examples supporting the arms race thesis, many studies suggest that arms races provide only a relatively weak explanation of US military spending policies (see, for example, Cusack and Ward 1981; Fischer and Crecine 1979; Gillespie et al 1977; Griffin et al 1982). Gillespie et al (1977:237) showed that US military expenditures are not well explained by Soviet spending levels but are rather the product of incremental processes. Incrementalism National security priorities and goals are reflected in the Department of Defense (DoD) budget—a complex document comprising more than 5,000 line items (Brown and Korb 1982:583). The scope of this budget is thus too vast for the small number of actors involved in the budgeting process to handle coherently. Because of the budget’s complexity, the time constraints imposed on budget reviewers, and the technical expertise required from them, the budget is almost never reviewed as a whole every year. Instead, budgetary decisions in the DoD take the form of ‘marginal adjustments to an existing allocation pattern’ (Crecine 1971:218; Stromberg 1970).

4

INTRODUCTION

The defense budgeting process is a multistage process involving such key players as the services, the President, Congress, and the Department of Defense. According to Crecine (1971), these organizations tend to follow established procedures, emphasizing regularity over time. This regularity is best preserved by a routinized sequence of decisions, the pursuit of standard operating procedures, and some simple decision rules, such as the use of incremental calculations. According to the incremental model, budgetary policy makers rely heavily on the record of past expenditures, with only marginal adjustments of previous appropriations. Budgetary calculations proceed from the previous year’s base, while policy makers focus only on a narrow range of increases or decreases which are supposed to be distributed fairly among various programs (Wildavsky 1964). DoD policy makers often pursue incremental policies (Allison 1982). Incrementalism preserves regularity in DoD budgeting and reflects political, economic, and national security related pressures to increase the budget as well as the potential costs associated with reducing spending levels drastically. Allison (1982) has noted that some of the most important weapon development decisions were likewise made in increments. For example, the 1965 decision to deploy MIRVs on Poseidon and Minuteman systems clearly stemmed from the 1964 decision to advance development and engineering of MIRV systems. Ostrom (1977) compared a Davis, Dempster and Wildavsky-type organizational politics/incremental model of the US defense spending process with a Richardson-type arms race model, and found that neither provides an accurate explanation of US defense spending. Ostrom (1978), Majeski (1983), and Ostrom and Marra (1986) have integrated the arms race and organizational politics models by developing and testing ‘reactive linkage’ models of defense spending. The political economy of military spending A third approach to the study of defense spending is presented in this volume. It integrates the fields of national security and political economy. Political economy has a variety of meanings. Gilpin (1987) has noted that classical economists used it to mean what today is called economics. Frieden and Lake (1987) define it as ‘the study of the interplay of economics and politics.’ Downs (1957) and Frey (1978) see it as the application of the rational choice approach of formal economics, to human behavior (Gilpin 1987:8). Alt and Chrystal (1983) see the fundamental questions of political economy as involving the role of the government in the economy. And Gilpin (1987:9) uses the term to indicate ‘a set of questions…generated by the interaction of

Introduction

5

the state and the market as the embodiment of politics and economics in the modern world.’ Frieden and Lake (1987:1) argue that, for some, political economy ‘refers primarily to the study of the political basis of economic actions, the ways in which government policies affect market operations. For others, the principal preoccupation is the economic basis of political action, the ways in which economic forces mold government policies.’ Many political economists divide the political economy field into unitlevel domestic political economy and system-level international political economy (see Alt and Chrystal 1983; Katzenstein 1976; Krasner 1985; Strange 1970; Wendt and Barnett 1989; to name just a few). Three intellectual perspectives dominate the study of political economy (Gilpin 1987: Ch. 2; Frieden and Lake 1987: Ch. 1): liberalism, Marxism, and realism. Liberals claimed that economic wellbeing is best served by allowing ‘free and unrestricted exchange between individuals in both the domestic and international economies.’ For liberals, then, governments must only provide ‘for the defense of the country, protect property rights and prevent unfair collusions or concentrations of power within the market’ (Frieden and Lake 1987:6–7). Central to the liberal perspective are the assumptions that individuals are the dominant actors in the political economy; individuals are rational, utilitymaximizing players; and individuals maximize utility by exchanging goods with other individuals (Frieden and Lake 1987). The role of the government is limited to managing the market. Marxists obviously use class-based explanations of economic activity. For Marxists, ‘the nature of politics and the fundamental cleavages within and between societies are rooted in economics.’ Classes are the principal actors within the political economy, and ‘act to maximize the economic wellbeing of the class as a whole’ (Frieden and Lake 1987:8–9). The basis of the capitalist economy is the exploitation of labor by capital and the relationship between capitalists and workers is zero-sum and conflictual (Frieden and Lake 1987; Gilpin 1987). Realists argue, in contrast, that ‘in the pursuit of power, nation-states shape the international economy to best serve their desired interests’ (Frieden and Lake 1987:11). Realists assume that nation-states are the most important actors in the political economy (Keohane and Nye 1977). Nation-states are rational and power maximizers (Frieden and Lake 1987). They use force as an instrument of foreign policy, and politics is conflictual. Realist political economy ‘is therefore primarily concerned with how changes in the distribution of power in the international system affect the global political economy’ (ibid.). Thus, while, for realists, politics determines economics, for Marxists, economics determines

6

INTRODUCTION

politics, and, for liberals, economics and politics are autonomous spheres. Whereas the unit of analysis of Marxists is generally classes, the one for liberals is individuals, and the one for realists is the nation-state. Three theories of international political economy have gained considerable influence in recent years (Gilpin 1987:66–80): (1) (2) (3)

the theory of the dual economy (Averitt 1968; Bowring 1986; Mintz and Russett 1992); the theory of the modern world system (Frank 1969; Wallerstein 1974); the theory of hegemonic stability (Keohane 1984; Kindleberger 1981; Snidal 1985).

Some political economists argue that US national security policy is largely determined by changes in the American position in the global economy. Others claim that the causes can be found in the domestic political and economic structure. The interaction between political-economic and security affairs has been overlooked by many scholars in the national security field. There is a need to include both systemic and state-societal factors when explaining national security policy. There is little doubt that various aspects of political economy theories have considerable relevance to the field of national/international security in general, and defense spending policy in particular. Whereas political ‘inter-ference’ with economic trends is one of the most important reasons to go beyond marketbased, purely economic explanations of social behavior, so is the political and economic interference with national security policy. Politicians, interest groups, and government bureaucrats have considerable stake in military spending. Global as well as domestic economic interests and constraints likewise shape national security policy. Some of the notable examples are: •

•

•

the impact of the dual economy on the evolution of military expenditures and the aggressive use offeree (Mintz and Russett 1992); the role of the military-industrial complex in shaping societal preferences and goals (Pursell 1972; Rosen 1973); the state of the economy, popularity of governments, and the use offeree (Mintz and Russett 1992); industrial dependence on the economy of war (Melman 1971); the political business cycle (Tufte 1978; Alt and Chrystal 1983): electoral cycles in military spending; political ‘interference’ in military spending policy (Nincic 1982; Nincic and Cusack 1979); the theory of hegemonic stability: the position of the US in the global economic and political system; the rise of the Third World (Hoole and Huang 1989; Rasler and Thompson 1988); the erosion of the hierarchy of the global security system;

Introduction

•

7

the world-system approach: the relationship of the ‘core’ and ‘periphery’ in the international system as affected by arms production and arms transfer policy (Wendt and Barnett 1989); economic relations among nations as affecting their defense policy.

In recent years, theoretical and empirical work has increasingly focused on the relationship of political economy and national and international security. Hoole and Huang (1989) have examined the relationship between various aspects of the global political economy (the size of the global economy, the interdependence of the economy, and changes in hegemonic power in the global economy) and the global conflict process. Wendt and Barnett (1989) have studied the impact of core-periphery relations on patterns of militarization in the Third World. Rasler and Thompson (1988) have examined the impact of systemic factors on patterns of military spending. Mintz (1985, 1988) and Mintz and Ward (1989) have studied the impact of the militaryindustrial complex, electoral cycles, and corporate profits on the evolution of Israel’s military spending. Mintz and Russett (1992) have studied the impact of electoral cycles and the state of the economy on Arab and Israeli use offeree. While the national security and political economy fields deal with different sets of issues and tend to use different methodologies, there is also considerable overlap and mutual relevance. This book attempts to incorporate the political economy into the analysis of defense spending. As such, the book sees defense spending policy not only as a by-product of the arms race and involvement in wars, but also as an outgrowth of political and economic processes. Defense spending policy also affects jobs, sales, corporate profits, wages, and other aspects of the economy and produces considerable political benefits (DeGrasse et al. 1983; Russett and Hanson 1975). The contributors to this volume emphasize the interplay of political and economic factors influencing US defense spending. The War in the Gulf, the downgrading of the Soviet bloc’s threat to Western security, and the debate on the size of the defense budget make these factors especially important. The book can be viewed as dealing with both the constraints on potential reductions in US defense spending and the effects of defense spending on economic growth and social welfare. The chapters by Kenneth Mayer (Chapter 2) and Thomas Cusack (Chapter 6) emphasize the role of electoral cycles in shaping military expenditures in the US, as well as the use of defense spending and DoD contract awards as countercyclical instruments to combat poor economic conditions. William Domke (Chapter 3) relates changes in military spending and DoD resource allocation to changes in political leadership, Richard Stoll (Chapter 4) examines the determinants of public opinion on military spending, and Michael Ward and David Davis (Chapter 5) link the US–Soviet nuclear and conventional rivalry to corporate profits. Steve Chan (Chapter 7)

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INTRODUCTION

focuses on the relationship between military buildup, the use of force, and stock prices; Bruce Russett and Gad Barzilai (Chapter 8) show that low-level military actions are initiated most frequently before elections and when the economy is weak, and that this is the case not only in the United States but also in other democracies, such as Israel. My chapter (Chapter 9) evaluates the impact of different components of the defense budget (personnel, research and development, procurement etc.) on welfare spending, i.e. the famous ‘gunsbutter’ tradeoff. Jin Mok and Robert Duval (Chapter 10) focus on the role deficits play in alleviating such a tradeoff. Stephen Majeski (Chapter 11) examines the impact of military spending on fiscal policy and macroeconomic performance, and Chi Huang and Francis Hoole (Chapter 12) test Paul Kennedy’s argument on the relationship between defense spending and US economic hegemony. Robin Marra and Charles Ostrom (Chapter 13) discuss (and offer solutions to) a variety of problems associated with estimates of Soviet military spending. John Williams and Michael McGinnis (Chapter 14) criticize the organizational politics model and offer an alternative, and Davis Bobrow (Chapter 15) translates the empirical analyses presented by the other contributors to this volume into a ‘what does it all mean’ political discussion. Together, the chapters by Cusack, Domke, Mayer, Stoll, Russett and Barzilai, and Ward and Davis refute the mythology that military spending policy is solely determined by security threats and is apolitical. The chapters by Chan, Huang and Hoole, Majeski, Mok and Duval, and myself demonstrate that such a policy has, in turn, widespread implications for economic wellbeing, social welfare, and US hegemonic position. Finally, the chapters by Ostrom and Marra and Williams and McGinnis examine some of the conceptual and methodological problems associated with research on these issues. The book is divided into four major parts: (1) cycles in military spending; (2) the political economy of military action and military spending; (3) military expenditures and economic performance; and (4) general issues in defense spending. Note: This chapter is partially based upon work supported by the National Science Foundation under Grant No. SES-8911030.

REFERENCES Agbese, P.O. 1988. Defense expenditures and private capital accumulation in Nigeria. Journal of Asian and African Studies 23 (3–4): 270–86. Allison, G.T. 1982. What fuels the arms race? In J.F.Reichart and S.R.Sturm (eds), American Defense Policy, 5th edn, pp. 463–80. Baltimore, MD: Johns Hopkins University Press. Alt, J. and Chrystal, A. 1983. Political Economics. Berkeley, CA: University of California Press. Averitt, R.T. 1968. The Dual Economy. New York: W.W.Norton.

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Barnett, M. 1990. High politics is low politics: The domestic and systemic sources of Israeli security policy, 1967–77. World Politics 42. Bowring, J. 1986. Competition in the Dual Economy. Princeton, NJ: Princeton University Press. Brown, G.F. and Korb, L.J. 1982. The economic and political restraints on force planning. In J.F.Reichart and S.R.Sturm (eds), American Defense Policy, 5th edn, pp. 578–85. Baltimore,MD : Johns Hopkins University Press. Chan, S. 1988. Defense burden and economic growth: unraveling the Taiwanese enigma. American Political Science Review 82:913–20. Crecine, J.P. 1971. Defense budgeting. In R.I.Byrne, A.Charnes, W.W.Cooper, O.A. Davis, and D.Gilford (eds), Studies in Budgeting, pp. 210–61. Amsterdam: North Holland. Cusack, T.R. and Ward, M.D. 1981. Military spending in the United States, Soviet Union, and the People’s Republic of China. Journal of Conflict Resolution 25:429–69. Davis, O.A., Dempster, M.A.H., and Wildavsky, A. 1966. A theory of the budgetary process. American Political Science Review 60:529–47. DeGrasse, R.W., McGuiness, E., and Ragen, W. 1983. Military Expansion, Economic Decline. New York: Council on Economic Priorities. Downs, A. 1957. An Economic Theory of Democracy. New York: Harper & Row. Fischer, G.W. and Crecine, J.P. 1979. Defense budgets, fiscal policy, domestic spending and arms races: a positive model of the great budgetary tradeoffs. Paper presented at the 1979 annual meeting of the American Political Science Association, Washington, DC. Frank, A.G. 1969. Capitalism and Under development in Latin America: Historical Studies of Chile and Brazil. New York: Monthly Review Press. Frieden, J.A. and Lake, D.A. 1987. International Political Economy. New York: St Martin’s Press. Frey, B. 1978. Modern Political Economy. New York: Wiley. Gillespie, J.V., Zinnes, D.A., Tahim, G.S., Schrodt, P.A., and Rubison, M.R. 1977. An optimal control model of arms races. American Political Science Review 71:226–44. Gilpin, R. 1987. The Political Economy of International Relations. Princeton, NJ: Princeton University Press. Griffin, L.J., Devine,J., and Wallace, M. 1982. Monopoly capital, organized labor, and military expenditures: military Keynesianism in the United States, 1949–1976. American Journal of Sociology 88: S113–53. Hoole, F.W. and Huang, C. 1989. The global conflict process and the global economy. Paper presented at the annual meeting of the International Studies Association, London. Huntington, S. 1958. Arms races: prerequisites and results. Public Policy 8:41–86. Katzenstein, P.J. 1976. International relations and domestic structures: foreign economic policies of advanced industrial states. International Organization 30:1–45. Keohane, R. 1984. After Hegemony. Princeton, NJ: Princeton University Press. Keohane, R. and Nye, J.S. Jr. 1977. Power and Interdependence: World Politics in Transition. Boston, MA: Little, Brown. Kindleberger, C.P. 1981. Dominance and leadership in the international economy: exploitation, public goods, and free rides. International Studies Quarterly 25:242–54. Krasner, S. 1985. Structural Conflict. Berkeley, CA: University of California Press.

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INTRODUCTION

Majeski, S.J. 1983. Mathematical models of the US military expenditure decision-making process. American Journal of Political Science 27:485–514. Melman, S. (ed.) 1971. The War Economy of the United States. New York: St Martin’s Press. Mintz, A. 1985. The military-industrial complex: American concepts and Israeli realities. Journal of Conflict Resolution 29:623–39. Mintz, A. 1988. Electoral cycles and military spending: a comparison of Israel and the United States. Comparative Political Studies 21:368–81. Mintz, A. and Hicks, A. 1984. Military Keynesianism in the United States, 1949–1976: disaggregating military expenditures and their determination. American Journal of Sociology 90: 411–17. Mintz, A. and Huang, C. 1990. Defense expenditures, economic growth and the ‘peace dividend’. American Political Science Review 84:1283–93. Mintz, A. and Russett, B.M. 1992. The dual economy and Arab-Israeli use of force: a transnational system? In S.Chan and A.Mintz (eds), Defense, Welfare and Growth. London: Routledge. Mintz, A. and Ward, M.D. 1989. The political economy of military spending in Israel. American Political Science Review 83:521–33. Nincic, M. 1982. The Arms Race: The Political Economy of Military Growth. New York: Praeger. Nincic, M. and Cusack, T.R. 1979. The political economy of U.S. military spending. Journal of Peace Research 16:297–317. Nye, J.S. Jr and Lynn-Jones, S. 1988. International security studies: a report of a conference on the state of the field. International Security 12 (4): 5–27. Ostrom, C.W. Jr. 1977. Evaluating alternative decision-making models: an empirical test between an arms race model and an organizational politics model. Journal of Conflict Resolution 21:235–66. Ostrom, C.W. Jr. 1978. A reactive linkage model of the US defense expenditure policy making process. American Political Science Review 72:941–57. Ostrom, C.W. Jr. and Marra, R.F. 1986. US defense spending and the Soviet estimate. American Political Science Review 80:819–42. Park, T.W. 1986. Political economy of the arms race in Korea: queries, evidence, and insights. Asian Survey 26 (8): 839–50. Pursell, C.W. (ed.) 1972. The Military-Industrial Complex. New York: Harper & Row. Rasler, K. and Thompson, W.R. 1988. Defense burdens, capital formation, and economic growth: the systemic leader case. Journal of Conflict Resolution 32:61–86. Rathjens, G. 1975. Changing perspectives on arms control. Daedalus, Summer: 201–14. Richardson, L.F. 1960. Arms and Insecurity: A Mathematical Study of the Causes and Origins of War. Pittsburgh, PA: Boxwood Press. Rosen, S. (ed.) 1973. Testing the Theory of the Military-Industrial Complex. Lexington, MA: Lexington Books. Russett, B.M. and Hanson, E.C. 1975. Interest and Ideology: The Foreign Policy Beliefs of American Businesses. San Francisco: Freeman. Russett, B.M. and Starr, H. 1989. World Politics: The Menu for Choice, 3rd edn. New York: Freeman.

Introduction

11

Snidal, D. 1985. The limits of hegemonic stability theory. International Organization 39: 579– 614. Strange, S. 1970. International economics and international relations: a case of mutual neglect. International Affairs 46 (2): 304–15. Stromberg, J.1970. The Internal Mechanisms of the Defense Budgetary Process: Fiscal 1953– 1968. Santa Monica, CA: Rand Corporation. Tufte, E.R. 1978. The Political Control of the Economy. Princeton, NJ: Princeton University Press. US Department of Defense. 1983. Annual Report of the Secretary of Defense to Congress. Washington, DC: US Government Printing Office. Wallerstein, I. 1974. The Modern World-System: Capitalist Agriculture and the Origins of the European World-Economy in the Sixteenth Century. New York: Academic Press. Ward, M.D. 1984. Differential paths to parity: a study of the contemporary arms race. American Political Science Review 78:297–317. Ward, M.D. and Park, K. 1989. Dynamics of national security in the Korean peninsula. Paper presented at the International Academic Conference on Military Security and Defense Spending in the Two Koreas at the Sejong Institute, Seoul, Korea. Wendt, A. and Barnett, M. 1989. The international system and Third World militarization. Paper presented at the meeting of the American Political Science Association, Atlanta. Wildavsky, A. 1964. The Politics of the Budgetary Process. Boston, MA: Little, Brown. Zinnes, D.A. and Gillespie, J.V. 1973. Analysis of arms race models: U.S. vs U.S.S.R. and NATO vs WTO. In W.G.Vogt and M.H.Mickle (eds), Modeling and Simulation, pp. 145–8. Pittsburgh, PA: University of Pittsburgh Press.

PART I

Cycles in Military Spending

CHAPTER 2

Elections, Business Cycles, and the Timing of Defense Contract Awards in the United States Kenneth R.Mayer

Military expenditures have long played an important role in the American political economy, if for no other reason than that they are by a wide margin the largest category of discretionary federal spending. Because of the size and relative controllability of the defense budget, suspicion lingers that it is used for political and economic purposes unrelated to national security. One possibility is that defense spending is used countercyclically to mitigate the effects of recessions and spur economic recovery. Another is that defense spending is used as an explicitly electoral tool, with spending levels rising just before elections to stimulate the economy and improve incumbents’ electionday prospects. That defense budgets are sure to shrink in the 1990s makes the question more important. The impending budget squeeze is a consequence of the virtual disappearance of the Soviet–Warsaw Pact military threat in Europe, and the tantalizing prospect of friendly superpower relations. The military, like it or not, is being forced to conclude that the Soviet menace—its budgetary raison d’être—is going away. It therefore becomes that much more important to understand the domestic political and economic factors which drive military spending. Previous research into these questions has attempted to tie changes in the annual defense budget to both changes in the macroeconomy and the timing of elections. The results are mixed, with some scholars (Griffin et al. 1982a, b; Mintz and Hicks 1984; Nincic and Cusack 1979) finding evidence of electoral or economic cycles in annual US defense spending levels, and others 15

16

I: CYCLES IN MILITARY SPENDING

disputing the political argument (Krell 1981), or finding a bureaucratic explanation entirely adequate (Ostrom 1978). Conclusions about the political-economic use of defense spending should be tempered with the important caveat that not all forms of defense spending are equivalent; some are more amenable to manipulation than others, and some are altogether uncontrollable. Budget authority, obligations, and outlays are not interchangeable, nor are military pay and procurement accounts. They measure different quantities, and are subject to varying degrees of timing discretion. This is a critical distinction, because, in devising a plausible model of how defense spending is used to political or electoral ends, research must show how such decisions can be implemented. In particular, the annual defense budget is a poor place to look for cyclical manipulation, because the budget is crafted over a long interval of political and bureaucratic activity far in advance of the economic effects it generates. This work involves a different approach to the question of defense budget tinkering, and focuses on monthly prime contract awards to US firms instead of yearly levels of defense spending. Monthly contract awards analysis has several important advantages. First, it can uncover month-to-month variations within years that annual analysis will overlook. Second, policy makers can easily control the level and timing of contract awards, something they cannot do with either the aggregate defense budget or other types of defense spending; this makes tinkering more likely. Third, prime contract obligations have by far the most rapid economic effects of any kind of defense spending. Contract awards thus meet the requirements of an effective political-economic policy instrument: controllability and swift effects. Without question, there is an electoral cycle in US defense contract awards. Between $3 and $4 billion in additional prime contracts are awarded in the two months preceding presidential and congressional elections, a pattern that has remained constant since 1954. There is less compelling support for the proposition that prime contracts are used as a countercyclical economic tool. Although countercyclical patterns are clear for the 1950–65 period, the growth since the mid-1960s of non-defense economic policy tools (primarily transfer payments and other social programs) have rendered defense spending less important as a way of responding to short-term economic conditions. Because of the enormous acceleration in contract awards needed to significantly affect national economic conditions, the value of aptly timed contract awards appears to be primarily political, with economic stimulation more of a side-benefit. As such, contracts are less useful in counteracting economic downturns than they are in raising the political stock of incumbents.

Elections, business cycles, defense contracts

17

THE POLITICAL USE OF DEFENSE SPENDING The major economic benefit of defense spending is jobs. Every $1 billion in defense expenditures creates between 25,000 and 55,000 jobs, depending on whether the calculation includes indirect employment effects.1 Defense spending thus produces something of substantial potential usefulness to incumbents, whether in the White House or Congress. Members of Congress consistently work to protect defense-related jobs in their home districts, and presidential candidates take pains to stress their pro-defense orientation to groups who rely on defense contracts for their livelihoods.2 The political success of incumbent presidents, and members of their political party, is closely tied to their ability to avoid recessions and unemployment. One need not be a genius to detect the American electorate’s tendency to be ruthless to presidents unfortunate enough to preside over periods of economic hardship (Kernell 1978). Since Kramer’s (1971) original contribution, evidence has continued to emerge that the electoral success of the President’s party is strongly related to economic conditions. Tufte (1978) made the connection between economic conditions and incumbent behavior, finding evidence that presidents tinker with the economy before elections to improve their chances at the polls. Presidents, it seems, pump up the economy with transfer payments, tax cuts, and other activities designed to improve the electorate’s financial condition as elections approach. The defense budget is a tempting candidate for this kind of manipulation. Increasing the budget before an election would inject money into the economy, create and preserve jobs, and protect against recessions. After the election, the budget could be cut back to guard against the onset of inflationary pressures. Presidents could also increase defense spending as a way to help bring the economy out of recessions, which are never good for presidential popularity. The contradictory results of research into whether this in fact occurs are in large part due to an exclusive focus on annual levels of defense spending as the dependent variable. While the yearly defense budget does change in response to long-term domestic economic and political trends, it cannot be manipulated quickly enough to produce the timely response required of electoral or Keynesian fiscal instruments. Three characteristics of the defense budget process make this clear. First, the process is too long. Over two years elapse between the Joint Chiefs’ initial spending requests and final congressional action (assuming Congress can consider the budget before the fiscal year begins, something it did three times between 1953 and 1984).3 Department of Defense (DoD) budget planning for fiscal year 1988 (which actually began in October 1987) started in October 1985, 16 months before the President formally submitted

18


his total budget package in February 1987.4 Even if the President could foresee future political or economic events that might call for budget tweaking, he could not be sure that the budget would ultimately reflect his own policy desires. Many different organizations and actors influence the final form of the defense budget. Far from representing presidential fiat, defense budgets are the result of a complicated bargaining process involving the individual services, various departments within the Office of the Secretary of Defense, the Office of Management and Budget (OMB), Congress, and the White House itself. Some actors may share the President’s political agenda, but there are no guarantees. Even within the Reagan administration, DoD and OMB often clashed over the budget levels. OMB director David Stockman grew wary of the mounting deficit in 1981, and pushed for defense budgets smaller than those Secretary of Defense Weinberger advocated (Stubbing 1986:377). Moreover, Congress has historically modified defense budget requests, adding or cutting back unpredictably. The time lag and diffused responsibility for the budget make it difficult to craft and implement decisions in response to events that may not occur until the budget process is well underway. Second, major parts of the defense budget are not susceptible to manipulation. Personnel expenditures, for example, are relatively uncontrollable. Expenditures are determined by the number of people in uniform, their distribution in rank, and salary levels, all of which are fairly stable from year to year (the pay budget and force levels alone are highly correlated, with r=.92). Manipulating this account would require changes in overall force levels—an implausible instrument for short-term manipulation. Third, the economic effects of one year’s defense budget are not felt immediately. Few jobs are created until money is actually obligated (Greenberg 1967; Maw 1970), a phase that may lag actual budget adoption by as long as five years.5 Less than three-fourths of procurement funds are actually obligated in the year in which they are budgeted (US Department of Defense 1987a), and a sizable portion of that is not obligated until the last month of the fiscal year (see below). In sum, the annual budget is the wrong place to look for short-term manipulation of defense spending. The budget process takes too long, is too complex, and has too few economic effects by itself.

PRIME CONTRACT AWARDS AS THE APPROPRIATE LEVEL OF ANALYSIS Incumbent politicians and officials are most likely to tinker with obligations, which for non-pay accounts occur when contracts are awarded. Incumbents


19

can easily control the timing and level of contract awards, and can quickly alter award patterns if political or economic circumstances warrant. Contract awards create jobs almost immediately, as defense contractors hire or retain engineering, manufacturing, and management personnel, issue sub-contracts, and gear up production facilities as soon as a contract is awarded (Greenberg 1967). In addition to their economic benefits, defense contracts create valuable credit-claiming opportunities. Every large defense contract award is accompanied by pronouncements from the local members of Congress, who try to connect themselves to the benefits the award creates. Until the practice was stopped in 1971, the Pentagon routinely allowed favored members of Congress to announce contract awards, which gave the impression that legislators were intimately involved with, even responsible for, the awards. Although DoD now announces contract awards through regularly scheduled and routine public releases, legislators still proclaim their support for, and active involvement in, local projects (even though they probably played no part). Presidents often do the same. Constituents thus see economic benefits tied ostentatiously to a particular politician or party, an image incumbents hope they will recall in the voting booth. Decision makers in the Pentagon also have broad discretion in deciding when to award contracts. Apart from some statutory limits—funds must be obligated before they ‘expire,’ and certain awards must be listed in the Commerce Business Daily for 30 days before the actual date of award— nothing prevents contracting agencies from accelerating, or holding up, contract award announcements as conditions dictate. Once money has been appropriated, the Defense Department decides when to obligate it (Fisher 1975:123). This controllability manifests itself in different ways. The best example is how awards are acclerated before the end of each fiscal year when DoD tries to obligate all of its remaining funds to avoid having to return left-over money to the Treasury.6 Since Congress views unobligated funds as a sign of mismanagement and excessive budget requests, any agencies with money left at year-end are likely to have their future budget requests slashed (Fox 1974:134). The military has no immunity from this. In 1967, Congress ‘ordered a decrease in weapons procurement funds (primarily Navy) because the military services were maintaining excessively large carryover balances’ (Fisher 1975:140). To avoid this unpleasantness, agencies routinely rush to get money ‘out the door’ during the closing days of the fiscal year, in a yearly frenzy that was once sanctioned. ‘Prior to 1971,’ Fox writes, ‘official notices were sent to all senior government personnel during April or May, reminding them to use all their funds before June 30’ (1974:134).

20


Although many agencies now try to limit year-end accelerations, they have proved impossible to stop. The primary control involves prohibiting obligations after a specific date, say 15 September, which simply moves the rush deadline back. Other laws exist to block the spending binges, but they too are ineffective. Since 1953, language in the defense authorization bill has prohibited the Defense Department from obligating more than 20 percent of the available funds in the last two months of the fiscal year. However, the limitation applies to only about 30 percent of the defense budget, and excludes all procurement, research and development, and construction funds —and hence nearly all contract awards. The sheer size of the defense budget can propel the Pentagon spending fury to absurd heights. In 1983, the military obligated $4.5 billion on the last day of the fiscal year (US Congress 1983:181). That is an annual rate of over $1.5 trillion, more than five times the actual 1983 budget. As Figure 2.1 shows, 1983 was not an exceptional case. Between 1953 and 1986, contract award levels in the last month of the fiscal year have routinely been two to FIGURE 2.1

Contract awards: fiscal year-end acceleration, 1953–86


21

six times higher than the average award level for the other eleven months. Over the entire sample, 1953–86, last-month obligations were 2.3 times larger than other months, and were the year’s biggest in every year except 1977, when the transition to the new fiscal year was made, and 1984, when awards peaked in November. The pattern of fiscal year-end spending shows that DoD can rapidly accelerate awards to meet an artificial deadline. Nothing inherent to the procurement process causes the fiscal year-end rush; it is the Pentagon’s response to an external constraint imposed upon the process. If awards can be accelerated for one such purpose, it is likely that they can be similarly accelerated for others—such as elections. We need not assume that the overall level of contract awards rises during any particular year for political reasons, but rather that those in power manipulate the timing of contracts that would have eventually been awarded in any case. Other government agencies have used this tactic. Government grants in the Economic Development Administration, and Housing and Urban Development’s sewer and water program, were heaped on key congressional districts during election years ‘among projects that would have been announced anyway’ (Anagnoson 1982:560)—a bureaucratic strategy designed to protect budget levels and ward off congressional interference (ibid.: 549). Similarly, a 1980 General Accounting Office investigation found the same pattern, and concluded ‘grants that would have been awarded in the normal course of events were being timed and orchestrated to gain maximum political effect’ (US General Accounting Office 1980:3). A similar process might operate within the defense establishment. The Defense Department might anticipate the electoral needs of the President or sympathetic legislators, and time announcements to generate maximum political advantages for them. Alternatively, the government could speed up the contract award process during times of economic hardship, in an attempt to lower unemployment levels and insulate the defense industry from recessions.

THE POLITICAL-ECONOMIC MODEL In order to generate political and economic effects, contract awards would have to be timed to respond to specific events. The most important political events are of course national elections. Specifying the appropriate economic trigger is more difficult, particularly since the defense budget creates substantial economic effects on its own, but also because the level of spending appears, at least, to respond to a large number of economic variables— corporate profits, unemployment, and inflation, according to the

22


neo-Marxist model, and industrial productivity according to others. However, when political leaders speak of the economic benefits of defense spending, they almost always mean jobs; jobs in the defense industry, jobs created by large military installations, and the like. A reasonable hypothesis is that leaders will pay attention to the level of unemployment, which is clearly related to public attitudes towards the economy and the popularity of incumbents. A political-economic model of defense spending predicts that contract awards should rise before elections, and also accelerate when unemployment is high. Since the economic effects of contract awards kick in almost immediately, the accelerations should closely match the timing of these events. To provide electoral benefits, contract awards would have to be timed to fall into a narrow window prior to election day, far enough in advance to maximize the pre-election effects, but close enough to election day that incumbent credit-claiming is fresh in voters’ minds. In order to time award peaks with elections, which occur in early November, one hypothesis is that awards should jump in September and October, when campaigns are in full swing and voters have time to notice economic stimulation and connect them with the candidates. In response to high unemployment levels, contract awards should go up almost concurrently, especially if the economy is mired in a recession. So, if there are economic and electoral cycles in defense contract awards, the following is one set of plausible expectations: (1)

(2) (3)

Contract awards in September and October of election years will be higher than award levels in the other months of election years, and higher than award levels in September and October of non-election years. Contract awards in September and October of non-election years will be no higher than awards in the other months of those years. Contract awards will rise in response to high unemployment, and should vary with the unemployment rate.

The data used to test these hypotheses are monthly Department of Defense prime contract awards to US firms between January 1951 and October 1986, with no seasonal adjustment. To simplify across-year comparisons and reduce the problem of autocorrelation, the series was converted to constant 1987 dollars using a deflator calculated by DoD (US Department of Defense 1987b:53). The seasonally unadjusted form is used because we are interested in the very types of seasonal variations that the adjustment process removes. Specification of the statistical model is straightforward. The equation to be estimated is as follows:


23

24


The awardt–12 variable takes into account both seasonal variation and longterm trends. The dummy variables for the beginning and end of the fiscal year control for the spike during the last month of the year, as well as an expected trough during the first month of the year. Non-contract obligations are included as an additional control.8 The variables in the ‘Reagan’ portion of the model estimate the impact of the post-1980 defense buildup; the awards data show that both the overall level and the fiscal year effect swings rise after Reagan’s inauguration. Since obligations lag annual budget increases, the effects become more noticeable as Reagan’s tenure lengthened (hence the ‘time in office variable’). The final control variable, the end of calendar year dummy, accounts for the rise in awards each December; since many contractors operate on a January–December fiscal year, they push for December obligations to improve their year-end financial position. The last three variables are designed to detect political and economic cycles. The variable ‘election’ should be positive and significant, indicating that contract awards jump in the two months preceding both presidential and mid-term congressional elections. The variable ‘non-election,’ which estimates the rise in the same months of non-election years, should be small, indicating that no such acceleration occurs in non-election years. The unemployment rate coefficient will be positive if contracts are awarded in response to high unemployment levels. The results for the entire series are shown in column 1 of Table 2.1. They strongly confirm the model’s hypothesis that contract awards will be accelerated in September and October of election years. Over the 1954–86 period, $3.5 billion in contracts are heaped into the two months preceding elections, roughly twice the increase in non-election years.9 There is some evidence that defense contract awards go up in response to unemployment; each 1 percent increase in the unemployment rate increases contract award levels by $297 million. The other coefficients show that contract awards rise by $6.6 billion at the end of the fiscal year, and $3.1 billion during wartime months. Perhaps the most unexpected result is the strong negative relationship between noncontract obligations and contract awards. One explanation is that the Pentagon faces a stark tradeoff between spending money in investment accounts (procurement, research and development) and day-to-day operations (personnel, operations and maintenance, etc.). The military’s reluctance to cut procurement spending is well known; as a result readiness accounts are the first to be cut when budgets decline. To eliminate the possibility that the September/October election-year acceleration is an artifact of the post-1977 fiscal year (which ends in September), the model was re-estimated for the 1954–76 period, when the fiscal year ended in June. The results, shown in column 3, show clearly that


25

TABLE 2.1 Regression results

Note: Prime contract awards in 1987 dollars; figures in parentheses are t-ratios.

the election-year acceleration is real. In fact, the heaping is more pronounced— nearly $4.4 billion additional dollars, with no indication of a similar acceleration in non-election years.10 This translates into a maximum of about 110,000 direct and 132,000 indirect jobs. Unemployment has less effect during this period, with the coefficient, from a probabilistic stand-point, indistinguishable from 0. The macroeconomic consequences of electoral and economic contract accelerations are certainly detectable, even if relatively small. An additional

26


240,000 jobs will not significantly effect unemployment or national income accounts. At the November peak of the 1982 recession, unemployment stood at 10.8 percent out of a total civilian labor force of 111 million. If all 175,000 jobs produced by electorally timed contracts were new (which they probably are not), they would comprise only 0.22 percent of the labor force, and would have reduced unemployment by less than 0.25 percent. Similarly, a 1 percent rise in unemployment raises contract awards by $296 million, which works out to about 16,000 jobs—hardly significant given the size of the US labor force. Moreover, the extra few billions in contracts produced by either elections or recession would scarcely nick a Gross National Product measured in the trillions. This suggests that perhaps well-timed creditclaiming, along with concern about economic conditions at the local level, is a major motivation for the electoral cycle in defense contracting. Even though the political-economic accelerations are relatively small, they are still significant when put into the context of overall national security policy. Since most studies of the defense budget find that defense spending responds most strongly to international events, we can, realistically, expect domestic factors to come into play only at the margins. Nevertheless, the fact that contract award timing does respond to domestic economic, political, and structural variables shows that defense spending has some important domestic functions unrelated to national security. One way of distinguishing between the credit-claiming and economic explanations for the accelerations is to see if award increases for congressional and presidential elections differ. Members of Congress are probably more concerned with credit-claiming than with national economic conditions, and presidents concerned more with economic stimulation. A major defense contract will have more impact on a congressional race than on the national election; 5,000 jobs can have a decisive impact on an incumbent legislator’s re-election prospects, but cannot realistically influence national outcomes. Presidents also have more incentive than legislators to pump up the economy, because their re-election success depends more heavily on national economic conditions. Tufte found that a 1 percent increase in election year per capita disposable income caused a 1.3 percent increase in the popular vote for incumbent presidents (1978:121), but only a 0.6 percent increase in the national ‘midterm vote for the congressional candidates of the president’s party’ (ibid.: 112). A sitting President thus has more at stake in the economy than members of Congress. If economic stimulation was the main motivation for pre-election award increases, the jumps should be larger in presidential election years than at mid-term. To test this proposition, separate September/October effects were estimated for the two types of elections. The results, shown in columns 2 and 4 of Table


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2.1, indicate that the increases are about the same. Before 1977, awards rose by $4.6 billion during mid-term years, and $4.04 billion during presidential election years. Given the variance of the estimates, the coefficients are in fact indistinguishable, which means that the accelerations can be considered equal. This suggests election-year accelerations serve mainly to give legislators the pleasant—and aptly timed —job of reminding constituents that they have a friend in Washington. The military need not engage in ‘conspiracies’ or violate contracting regulations to produce this effect. It need only speed up, or delay, the contract process to time awards appropriately. Legislators who support the military will presumably get this kind of favorable treatment (although there is no way to prove this with the available data). A former chief-of-staff to a prominent pro-military Senator indicated that his office routinely requested that contract award announcements be timed to coincide as closely as possible to the Senator’s campaign schedule (Mayer 1988:296). This practice, judging from the results here, may be widespread. The importance of the credit-claiming function of award accelerations makes their countercyclical use less significant. The government can fight unemployment with more direct instruments, without relying on defense contracts. Monetary policy and budget-wide fiscal policy (including tax policy) can do more for the economy than defense contract accelerations, and a wide array of social programs insulate the public from the worst effects of recessions. The relative contribution defense contracts can make in this effort has thus declined, particularly since the mid-1960s and the advent of widespread social welfare policies. Support for this argument is found in column 5 of Table 2.1, which estimates the model’s parameters for the pre-1964 period. Then, defense contracts played a more important countercyclical role, with monthly contract award levels increasing $811 million for each 1 percent rise in unemployment. The coincidence between the timing of contract award accelerations and unemployment is shown in Figure 2.2, which plots seasonally adjusted contract awards and the unemployment rate by quarter.11 During the 1954, 1958, and 1961 recessions, contract awards increased along with unemployment, increasing by a total of about $10–15 billion during the worst periods. When unemployment dropped, contract awards slowed. Tinkering with the timing of contract awards was a powerful tool for affecting macroeconomic conditions.


28 FIGURE 2.2

Contract awards and unemployment (quarterly, seasonally adjusted), 1951–64

CONCLUSION Defense contracting activity increases immediately before elections, both to stimulate the economy and to advance the interests of incumbent legislators. Before major social programs were enacted, defense contracts were also used to combat unemployment. The use of defense contracts to gain domestic political and economic advantages is not surprising, except for the fact that DoD claims, at least publicly, to be above all that. The patterns observed here show that in fact DoD is no different from any other agency, in that it has developed strategies designed to protect budgets, attend to friends on Capitol Hill, and advance the political interests of the administration. Without more data on where strategically timed contracts go, it is not possible to say whether Democrats benefit more than Republicans, or Armed Services Committee members more than non-members, or whether pro-defense legislators get more cooperation from procurement agencies than military critics (although all three are reasonable presumptions). Nor is it possible to say what impact accelerating or delaying awards has on the quality of contracting decisions. Politically astute timing of


29

announcements, by itself, will have little impact, since nearly all of the awards would have been made eventually. Procurement officers could conceivably be pressured to award a contract prematurely, perhaps bypassing necessary management or engineering controls, but this is speculation. Electorally and economically motivated contract awards probably do distort the level of defense activity, though. Defense budgets are sold to the public as being necessary to insure US security, mainly from an often exaggerated Soviet menace. But when defense expenditures produce benefits (real or imagined) having little to do with national security interests, budgets will remain high even if the threat goes away, because of domestic political imperatives. Here we can distinguish between unavoidable political sidebenefits (the fact that defense spending creates jobs) and unnecessary ones (timing contract awards to provide political advantage). As long as legislators and presidents can reap political benefits from defense contracts awarded in the heat of election campaigns, they will continue to accept, or even encourage, artificially high defense budgets. Incumbents also enjoy an important side-benefit of the current fiscal year structure. In creating a 1 October–30 September fiscal year, Congress guaranteed that contracting would skyrocket before every election because of the fiscal year-end effect. Even if political considerations were completely set aside by DoD activities, members would still benefit from the annual rush to spend money. The fact that the acceleration would also occur during nonelection years is immaterial to the utility of its occurring each election year. Criticism about politicizing the awards process is neatly deflected; the fiscal year becomes the villain. The results of this analysis show how a major portion of defense spending —contract awards—fits into the broader picture of the American political economy. Far from being ‘above politics,’ defense contracts are routinely—if not perniciously—used to political ends. Members of Congress in particular gain from the biennial surge in electorally motivated contract awards, because they can routinely point to the jobs those contracts produce during election campaigns when doing so provides maximum political advantage. Moreover, the government uses defense contracts to neutralize downward economic trends, at least at the margins. In these respects defense contracts are no different than any of the other macroeconomic tools government actors manipulate to influence economic policy and assure their own political survival.


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NOTES 1 2

3

4 5

6

7

8

9

10 11

The 25,000 figure is from the US Congressional Budget Office (1983). The larger figure is from Oginibene (1975). During the 1976 presidential campaign, both Gerald Ford and Jimmy Carter took pro-B1 positions in front of various groups involved in B-1 bomber production, even though Carter was actually opposed to the plane (Kotz 1988:156–7). Gansler (1989:115). Gansler also notes that, in fiscal year 1983, Congress failed to approve 6 of the 11 categories of defense spending ‘by the end of the fiscal year’ (p. 115, emphasis in original). Rovner (1983) provides a concise summary of the budget process. This figure applies to shipbuilding accounts, which constitute a significant part of the budget—$10.8 billion in 1986 and $10.2 billion in 1987 (US Department of Defense 1987a). ‘When funds are made available for a specified period of time (either for one year or a multiple of years), any funds not obligated by that time will lapse’ (Fisher 1975:130). Identifying the endpoints of the Korean war was simple: the North Koreans invaded in June 1950, and the armistice was signed in July 1953. Doing the same for the Vietnam war is much more difficult, since US involvement grew slowly, and wound down gradually prior to complete disengagement in 1974. However, analysis of overall funding levels for the war effort shows that, as far as prime contracts go, the first jump occurred in 1965, when US ground forces were introduced. Funding dropped after 1971 as part of the ‘Vietnamization’ of the war. The variable ‘war’ takes the value 1 starting in February 1965, and reverts to 0 after June 1971. This identification process is somewhat arbitrary, but the model specification is surprisingly insensitive to war specification; several different endpoints were used, with no appreciable changes in the overall estimates. More detail can be found in Mayer (1988:300–6). This variable is calculated as the difference between total DoD obligations and DoD contract awards. Because of some retroactive adjustments made to the prime contract series during the Korean war, total obligations are recorded as less than contract awards. Thus, it is necessary to begin the analysis in January 1955, to avoid this error in both the current and lagged independent variables. The coefficient for September/October of election years is 1742.3, which means that an additional $1.74 billion is awarded in each of the two months, for an overall acceleration of $3.48 billion. There is approximately a 1 in 5 probability that no non-election year acceleration actually occurs. Seasonal adjustment eliminates periodic fluctuations that may obscure other more interesting patterns (even election-year accelerations are removed, since they occur at regular twoyear intervals). Quarterly contract figures make visual inspection easier.

REFERENCES Anagnoson, J.T. 1982. Federal grant agencies and congressional election campaigns. American Journal of Political Science 26 (3). Fisher, L. 1975. Presidential Spending Power. Princeton, NJ: Princeton University Press.


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Fox, J.R. 1975. Arming America, Boston, MA: Division of Research, Graduate School of Business Administration, Harvard University. Gansler, J.S. 1989. Affording Defense. Cambridge, MA: MIT Press. Greenberg, E. 1967. Employment impacts of defense expenditures and obligations. Review of Economics and Statistics 49 (2). Griffin, L.J., Devine, J.A. and Wallace, M. 1982a. Monopoly capital, organized labor, and military expenditures in the United States, 1949–1976. In M.Burawoy and T.Skocpol (eds), Marxist Inquiries: Studies of Labor, Class, and States. Chicago: University of Chicago Press. Griffin, L.J., Devine, J.A. and Wallace, M. 1982b. The political economy of military spending: evidence from the United States. Cambridge Journal of Economics 6 (1). Kernell, S. 1978. Explaining presidential popularity. American Political Science Review 72 (2). Kotz, N. 1988. Wild Blue Yonder: Money, Politics, and the B-1 Bomber. New York: Pantheon Press. Kramer, G. 1971. Short term fluctuations in American voting behavior, 1896–1964. American Political Science Review 72 (1). Krell, G. 1981. Capitalism and armaments: business cycles and defense spending in the United States, 1945–1979. Journal of Peace Research 18 (3). Mayer, K.R. 1988. The politics and economics of defense contracting. PhD dissertation, Yale University. Maw, L.L. 1970. Impact, pattern and duration of new orders for defense products. Econometrica 38(1). Mintz, A. and Hicks, A. 1984. Military Keynesianism in the United States, 1949–1976; disaggregating military expenditures and their determination. American Journal of Sociology 90(2). Nincic, M. and Cusack, T.R. 1979. The political economy of US military spending. Journal of Peace Research 16 (2). Oginibene, P. 1975. The Air Force’s secret war on unemployment. Washington Monthly, July– August. Ostrom, C.W. 1978. A reactive linkage model of the U.S. defense expenditure policymaking process. American Political Science Review 72 (3): 941–57. Rovner, M. 1983. Defense Dollars and Sense: a Common Cause Guide to the Defense Budget Process. Washington, DC: Common Cause. Stubbing, R.A. 1986. The Defense Game. New York: Harper & Row. Tufte, E.R. 1978. Political Control of the Economy. Princeton, NJ: Princeton University Press. US Congressional Budget Office. 1983. Defense Spending and the Economy. Washington, DC: US Government Printing Office. US Congress. 1983. Review of Defense Acquisition and Management. 98th Congress, 1st sess. House Committee on the Budget. US General Accounting Office. 1980. Assessment of Whether the Federal Grant Process is Being Politicized During Election Years. GCD-81–41, 30 December.

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US Department of Defense. 1987a. Financial Summary Tables: Department of Defense Budget for Fiscal Year 1988 and 1989. January. US Department of Defense. 1987b. National Budget Estimates for FY 1988/1989. Office of the Assistant Secretary of Defense (Comptroller), May.

CHAPTER 3

Do Leaders Make a Difference? Posture and Politics in the Defense Budget William K.Domke

Controversy over the defense budget is a recurrent theme of post-Second World War US political debate. Periods of increased threat perception have brought about rises in defense spending only to be followed by criticism of the costs and a period of defense reduction. Following Sam Huntington’s (1983) characterization of cycles in defense spending moods, recent debate and emphasis on budget deficit and defense spending limits places us firmly in the fourth phase of the third cycle, marked by leveling off and decline in spending. The principle elements of debate concern the overall size of defense spending. However, the components of the defense budget are generally ignored in debate as well as in scholarship. In this chapter I wish to examine patterns in the distribution of defense resources. Distinct patterns exist in these distributions since the first budget of the Eisenhower administration (fiscal year 1955) through the last Reagan budget submissions (for FY1988 and FY1989). The United States defense budget presents several special problems for the student of budgeting. No other organization consists of four so very competitive, parochial, yet overlapping services with frequently redundant tasks. In most respects, it would be difficult to identify a functionally integral agency among this constellation of organizations were it not for the annual budget cycle that unifies the civilian and military actors into a single federal department. The organizational posturing that continually takes place to divide missions and resources is the key internal characteristic of the Department of Defense (DoD). Despite infrequent efforts at reform, which seek either to remove sources of rivalry or to control it through greater civilian political direction of the services, competition between the armed services is an important aspect of defense politics (Kanter 1979). The first section of this 33

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chapter focuses on the allocation of resources within the defense budget among the service branches. Because of the largely autonomous organization among the three services (really four since the Marine Corps has protected a good deal of independence), the division of resources between their missions is the traditional and most obvious feature of each year’s budget. Moreover, service politics represent the chief source of disintegrative pressure on defense policy. A second issue relates to the volatility of defense spending. In studies of public spending, one usually finds an exponential growth of expenditure over time. This has led to faith in the incremental norm of budgeting outcomes (Wildavsky 1979). Agencies can anticipate spending at the previous year’s level plus a little more. Yet, since 1950, budget authority for the Department of Defense has decreased eight times in nominal terms and 17 times when inflation is taken into account. In over 40 percent of the annual budgets for defense, the incremental expectation of a marginal increase on last year’s base does not fit the change in defense spending. Factors other than organizational momentum seem to determine the overall size of defense spending (see, for example, Nincic and Cusack 1979; Ostrom and Marra 1986). Participation in war obviously stimulates spending and also produces sharp declines at war’s end. Spending for the Korean and Vietnam wars, therefore, explains a large part of the variation in resources. While war produces change in the defense total, perhaps the most important implication is the change in the structure of allocation towards funds for combat missions. In other words, changing from wartime to peacetime budgets creates an alternating current that make year-to-year comparisons troublesome. In no other federal government agency are responsibilities in the form of missions and operations altered so readily and so markedly. Layered upon the more direct influences of war is the degree of tension between the United States and Soviet Union. Twice since the end of the Korean war periods of ‘thaw’ or detente were followed by significant peacetime armament programs: the Kennedy missile program and the Reagan defense program. The challenge of the Soviet Union, domestic political forces, new technologies, and military doctrines all work to push military spending upwards or down wards. When the upward pressures are weakest, defense spending is more easily cut, as such large spending items seem less justified in the face of budget deficits, economic austerity, or perhaps social welfare goals. Such differences are reinforced by the autonomy of the defense budget process. Whereas the non-military portion of the federal budget is directed and coordinated by the Office of Management and Budget (OMB), the Department of Defense constructs its own budget, loosely based on OMB guidances. It is reconciled with the rest of the federal budget only late in the annual budget process. The budget agencies of the Defense Department are nearly as large as the entire OMB, and trends in the military and civilian

Do leaders make a difference?

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components of the federal budget need not match, depending on the bureaucratic skill, and relationship to the President, of the key budget actors (Mowery and Kamlet 1984). The peculiar features of the defense budget lead many scholars and analysts to exclude it from their studies of budgetary behavior. Most empirical work focuses on the defense total, but this overlooks the important question of where defense resources go and the factors to which allocation patterns respond. Other studies analyze annual defense budgets with respect to particular missions and weapon systems. Most prominent among these are the reviews published by the Congressional Budget Office and the Brookings Institution. Yet, while informative as to the issues going into the contemporary defense program, they do not permit ready comparison to past trends in allocation. The second section of this chapter deals with questions of the distribution of defense resources. First, to what extent are budgetary ‘winners’ in one year the ‘winners’ in the next. This is a question of continuity in defense program, which should reveal a peacetime and Vietnam wartime pattern. Further, since each administration sets fairly explicit programs and doctrines to meet security goals, it should be possible to observe patterns of continuity within each administration. In addition, changing priorities across administrations would indicate the primacy of political factors over the organizational interests of the services. The third section of this chapter puts these aspects of changing allocation into the broader context of fiscal requirements and political forces. Does the ‘shape’ of defense allocation respond to the size of the increase in defense spending? Are there different allocation patterns in time of presidential elections? Such analyses permit defense decisions to be analyzed in a more general context. The data used for this study are the percentage changes in appropriation requests announced in the President’s January budget message. There are many stages in each year’s budget process: Spring reviews, service requests, DoD submissions to OMB, and lastly the President’s request to Congress, which is sometimes much altered before enacted into an appropriations bill. The January submission is the most important stage for viewing choices within defense. First, it summarizes the activities of all of the relevant actors in the previous stages. Second, as the budget approved by the President as the final arbiter, it concludes the executive budget cycle for a given fiscal year. From then on, attention focuses on congressional actions and the ability of the administration to persuade Congress to follow its planned expenditure. The Defense Department budget can be categorized in several ways, but the most useful breakdown is to the allocation categories used in the congressional budget process. Since the Eisenhower years, the number of

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categories has grown to 61. Table 3.1 displays the 46 categories used in the analyses here; 15 categories are excluded because requested funds were small or appear on an irregular basis (these omissions were less than 1 percent of the FYl989 budget request). TABLE 3.1 Major appropriation categories of the Department of Defense


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The measure of change for each category is the percentage change from the ‘estimate’ of final spending for the previous year to the President’s January budget request. This represents the marginal change in allocation based on last year’s results rather than last year’s request. In this way, budgetary ‘winners’ and ‘losers’ are defined on a year-to-year basis. There is no control for inflation, since it is an important empirical question whether periods of higher inflation affect the distribution within the defense budget. The focus of analysis is Total Obligational Authority, which is congressional authorization to enter into contracts. Outlays (cash payments, much of which has been authorized in previous years) are important, but Congress acts on budget authority and the categories that comprise this legislation are used here.

INTER-SERVICE COMPETITION The Pentagon’s budget is built up from service requests, and the most visible accounting of ‘winners’ and ‘losers’ comes from the competition for funds between the service branches. In the Fall of each year, each service submits its requests to the Office of the Secretary of Defense. It is then up to the Secretary of Defense to resolve the spending conflicts and bring the budget into line with a pre-set budget target or to attempt to modify the defense total. The degree of service autonomy has varied over time, as has the role of budget ceilings in defense. The Eisenhower administration set firm upper limits for spending by each service, but then let the services work out their own spending programs with little oversight (Huntington 1961). The independent services, which made separate budget requests until FY1959, battled among themselves in this limited resource environment. In this period of uncertain service roles and organizational futures, the contest for budget shares was at its most intense. The McNamara Defense Department did not set service totals in advance of the budget cycle. Instead, each service was to carefully justify each program of expenditure in order to provide both greater flexibility from year to year, but also far greater control from the Office of the Secretary of Defense (see Enthoven and Smith 1971; Kanter 1979; Mintz 1988). In this period, interservice rivalry waned as the military struggled against civilian management and the new rules of the game called the Planning, Programming and Budgeting System (PPBS). During the Nixon/Ford years, civilian control was irregular, emphasizing the restoration of service morale in the wake of McNamara and Vietnam. Laird seemed less interested in oversight of the services (partly to boost morale) and concentrated on fending off outside influence over defense 6 matters (see

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Korb 1979; Stubbing and Mendel 1986). First, the National Security Council, under Kissinger’s direction, sought to intervene in the budget process and exert White House priorities. Second, and certainly more successful, was the important rise of congressional influence over the federal budget and defense spending in particular. Scrutiny of defense spending was at its height and demand for justification of appropriations was extreme. The revolving door at the top of the Defense Department after Nixon’s reelection —Richardson, Schlesinger, and Rumsfeld—may also have contributed to growing service autonomy and a decrease in service conflict. The record of the Carter administration and the direction of the Defense Department under Harold Brown is still unclear. Although Brown set out to maintain the upward growth of the defense budget achieved in the last two Ford budgets, a consistent or well-articulated management style or organizational plan does not seem to have existed, except in the form of a somewhat nostalgic attempt to reassert McNamara-style management from the center. Despite responsibility for service requests, the military voice in the planning process was much reduced and seems to have been replaced by rather inconsistent interventions by President Carter himself (Stubbing and Mendel 1986: Ch. 18). The direction of Reagan era leadership by Caspar Weinberger and Frank Carlucci favored the independent judgments of the services, which re-acquired considerable authority over their budgets and programs. The remnants of McNamara’s civilian directorate were visible only as shadows of the past. To most, it was reminiscent of the Eisenhower years, although new service authority did not generate conflict in an era of rising defense spending. Instead, highly political decisions on major weapon programs, with considerable congressional involvement, dominated debates on defense spending. The focus of defense policy was on persuading outsiders to grant spending authority, since services had been able to develop their own priorities without much outside review or restriction. If there are differences in the relative authority of the services and the rivalry and competition between them, how does one detect and relate them to political and organizational developments within the Department of Defense? A budgetary perspective provides some insight, as changes in budget shares identify the ‘winners’ and ‘losers.’ But this is only an indirect view of competition, since budget allocations can be as much a result of programmatic choices as they are evidence of service power. Still, budget outcomes are the most useful benchmark. The three services have sufficiently vast and overlapping missions that changes in budget allocation are the focus of great attention and conflict. Budgets which show the greatest changes in allocation shares would seem to indicate greatest rivalry: one service gaining resources at the expense of others. Likewise, smaller


39

changes in allocation across the services suggest that a harmony or balance of service responsibilities exists. Table 3.2 displays changes in service shares since the beginning of the Eisenhower administration. The figures for each service are the differences in the percentage share of the President’s January budget request from the share estimated as the result for the preceding or ‘base’ year. The ‘shift’ index of TABLE 3.2 Changing service shares of the defense budget, 1955–89

Note: aThe FY1989 submission accompanied the FY1988 request.

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TABLE 3.3 Service shifts in the first two years of an administration

inter-service rivalry is the sum of absolute changes. If the services are receiving roughly the same shares as the year before, the index value is small. If one service does far better or worse than the others, the index value is large. The steadily increasing share of resources going to defense agencies and defensewide activities is excluded from the index. Only a few patterns can be discerned. To begin, the biggest shifts typically occur in the first few years of a presidential administration. Table 3.3 shows that such a pattern exists for all but the Carter administration. This is consistent with programmatic realignments, perhaps more than with inter-service rivalries. Eisenhower’s post-Korean war budgets show the result of drastic drops in Army personnel and the large expansion of the Air Force share of the budget (an increase of almost 12 percent). Since this early rise of the Air Force share of the defense budget, the Air Force share of the budget has steadily declined. With an early Eisenhower share of over 46 percent of the budget request, a long Air Force decline was to be expected. The only significant annual spending increase in Air Force since the mid-1950s came in the second Reagan budget submission. In the 1950s, the large gains by the Air Force generated considerable competition from the other services, which saw their futures jeopardized by the potential domination of the Air Force, especially in the area of strategic nuclear missions. A clear assessment of the degree of inter-service rivalry can be found for the Eisenhower and McNamara years (see Kanter 1979). Owing to the strict budget limitations imposed during the Eisenhower years, inter-service competition was seen to be greater than in the McNamara period, when civilian-military rivalries led to more cooperation between the services. This impression is born out in the index of inter-service rivalry—an average Eisenhower score of 6.93 versus 2.36 for the McNamara years. A marked difference exists even when the first two years of each administration are omitted. This finding is consistent with the record of defense posture in these years. Throughout the 1950s, the military services sought to ensure their


41

organizational survival in an era which emphasized new technologies, especially nuclear weapons. Early Air Force gains can be seen as the result of being the first service to develop the means to deliver nuclear devices. The result was an emphasis on prestigious but often redundant or ineffective weapons systems, cutbacks in less glamorous but necessary support facilities, and open inter-service disputes over roles and missions that the White House was never really able to stop’ (Gaddis 1982:225). McNamara’s emphasis on civilian control through the PPB System came after each service had secured a role in US defense. In particular, by the early 1960s, each service had developed an ensemble of weapons that carried nuclear warheads. Each had created missions and programs within budget ceilings. The Kennedy administration’s shift to a strategy of ‘flexible response’ and somewhat greater defense spending let each service compete for a wider spectrum of missions to fulfill the hypothetical goal of concurrently waging two and one-half wars. The overall strategy created more opportunities to acquire missions of any sort. One would expect less rivalry if each service could succeed in developing many new missions. The important illustration of this tendency is the Vietnam war, where each service was able to share in the fighting to a remarkably independent extent. ‘Each service, instead of integrating efforts with the others, considered Vietnam its own war and sought to carve out a large mission for itself. For example, each fought its own air war, agreeing to limited measures for a coordinated effort’ (Jones 1982). Though PPBS transferred more control to the Office of the Secretary of Defense (OSD), it did not necessarily lead to hard choices between service responsibilities. Much less has been written about the handling of the Defense Department by the successors of McNamara. Subsequent administrations continued to preserve some measure of OSD control, though it seems to have declined since McNamara’s departure. Curiously, the reduced authority of the Secretary is not consistent with budget trends, which show a more general tendency of resources to flow away from the services towards the defense agencies and defense-wide activities, although a large share of this money is in the form of retired pay for armed service personnel. The budgetary basis of inter-service rivalry, as measured by the ‘shift’ index, suggests an underlying dynamic that represents increasing inter-service balance and decreasing changes in service shares of the budget. If one compares the average ‘shift’ scores for each administration, one finds a decline from 3.66 (the last six Eisenhower budgets) to 2.36 (JFK/LBJ), 1.96 (Nixon/Ford), 1.85 (Carter) and 1.88 (Reagan’s first six budgets). By the time of the Carter administration, well-defined service responsibilities and ‘power’ seemed to have evolved into a steady-state wherein change in budget shares is quite small.

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This was not true of the first two Reagan budgets, which showed large shifts in service shares based almost entirely on new procurement programs. The first Reagan budget favored the Navy, which could easily and quickly commit resources to expand the size of the fleet through a variety of expensive shipbuilding programs. The second Reagan budget favored the Air Force, whose MX and B-l programs are very expensive. Whereas the Navy had shipbuilding plans ready for contracts, the Air Force required more time to develop and justify new weapon programs. Since the first two Reagan budget requests for defense, there has been a surprisingly small change in the share of resources going to each service. Except for the FY1978 budget submitted by the outgoing Ford administration, the last four Reagan budgets have shown the smallest changes in service shares. In the last three budgets, they are almost non existent, with the Navy and Air Force each receiving 33 percent of the budget request and the Army 26 percent. The FY1989 budget likewise showed no change in service allocations. The absence of change in the last four Reagan administration budgets is remarkable, when contrasted with the earlier administrations. It does reveal, however, that a steady-state exists within defense budget. Inter-service rivalry does appear to be at an all time low as few inter-service disputes have emerged in the popular press. On the other hand, the key spending choices have returned to the services, and civilian direction of the defense program seems to have returned to the level of the Eisenhower administration, where procurement spending is favored over support programs.

CONTINUITY IN THE DISTRIBUTION OF DEFENSE RESOURCES The previous analysis shows that there is some consistency in the year-toyear competition between the services. Such continuity suggests programmatic choices in selecting ‘winners’ and ‘losers’ in each budget. Two factors support a pattern of one year’s changes predicting the next. First, each presidential administration generates a doctrine that specifies preferred missions and programs. During the Eisenhower ‘New Look,’ the desire to limit defense spending led to the decision to rely on nuclear weapons. The ‘flexible response’ strategies of the Kennedy administration opened competition a bit by expanding missions and increasing expenditure, especially for the new missile programs. The war in Vietnam restructured spending priorities to accommodate the buildup of manpower and weapons for the conflict. Nixon’s program was to cut spending on the war and modernize weapons within the confines of the arms control process. Carter sought to improve readiness


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(operations and maintenance) and capabilities in remote areas. Lastly, the Reagan administration strongly favored modernization of US forces across the board. A second factor supporting continuity is the distribution of authority within the Department of Defense. As time goes on, the emergence of a configuration of actors that dominates budgetary battles can occur. This seems particularly important for the Secretary of Defense who, as an outsider, must first master the intricacies of the budget process (or create them, as in the case of PPB). His ability to override service interests can be modified through replacement of the service chiefs, but this can take several years. McNamara’s tenure illustrates this tendency, when the support of the Joint Chiefs of Staff was created by replacing three service chiefs in 1963. To test the degree of continuity between budgets, a simple model can be estimated to predict changes in each year’s budget by changes in the previous year. ‘Winners’ in one year should be ‘winners’ in the next. The size of the program is an important factor, as larger categories tend to vary less than the smaller ones. The expectation is that changing priorities will occur in the early budget submissions of each administration and that programmatic continuity will settle in only after several budget cycles. Table 3.4 displays the results of ordinary least squares estimates of the coefficients for this model. In 20 of the 32 budgets (excluding FY1989), a significant relationship emerges between the changes in allocation and the prior year’s changes, but it is not always a positive relationship. However, the expectations are borne out: there was no continuity in early administration budgets and continuity emerged thereafter. The budget reforms of the 1950s and the Vietnam war confounded this pattern. Eisenhower’s initial objective was to transform the defense budget from a high-spending Korean war level to more modest peacetime levels. The Army was particularly hard hit by the ‘New Look.’ The negative relationship to the previous year’s ‘winners’ in the first three Eisenhower budgets (including FY1955) shows the result of reorienting the defense budget from a wartime to a peacetime establishment. However, the rest of the Eisenhower budgets do not show strong continuity, perhaps as a result of the ‘ceilings’ practice and the more passive civilian oversight of the services. With the Secretary of Defense not exercising authority, there was little control over the budget process to enforce program goals over several budget cycles. However, one should be cautious in interpreting these findings owing to the reform of the Defense Department in 1958 and the restructuring of the budget for FY1960. The budgets of the McNamara era show a more reliable and interesting pattern. First, the initial two budgets show a negative, though very weak, relationship to earlier allocations. In short, Eisenhower priorities were being reordered. The third and fourth budgets established year-to-year continuity.


44 TABLE 3.4 Continuity in the defense budget, 1956–89

Notes: Coefficients in bold are statistically significant. The rearrangement of categories in the FY 1960 budget makes it impossible to compare with the previous year. b The FY1989 submission accompanied the FY1988 request. a


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For these two years, the prior year’s ‘winners’ won again. As would be expected, whatever continuity was established by the McNamara program was reversed by the Vietnam war. There were two transition budgets (FY1967 and FY1968) where priorities were reversed to support the war and, then, a measure of wartime continuity emerged and persisted into the Nixon era. Clearly, the war in Vietnam delineated allocation patterns more than could be changed by the new Nixon administration. Despite inheriting the war in Vietnam, Secretary of Defense Laird actively sought to disengage US forces from the conflict. During the first year of the Nixon administration, Laird managed to persuade the White House to embark on the ‘Vietnamization’ of the war (Stubbing and Mendel 1986:294–7). After submitting a war budget for FY1971, the next two budgets recorded priorities and can be labeled withdrawal or ‘Victimization’ budgets. The period from FY1974 to FY1978 shows a vary stable allocation pattern, the ‘winners’ from one year being carried over to the next. It is interesting to note that this period also experienced the greatest turnover in Secretaries of Defense: Laird left in early 1973, Richardson in 1973, Schlesinger in 1975, and Rumsfeld in 1977. This suggests that the configuration of stable service actors can protect allocation patterns (‘winners’ keep winning) if there is a revolving door at the top. Inter-service changes were also smaller in this period. The Carter administration pattern is simple and consistent with expectations. First, the initial budget reversed the pattern of allocation in the last Ford budget. Ford ‘winners’ were Carter ‘losers.’ The FY1979 budget omitted funds for the Bradley armored personnel carrier, submarine-launched cruise missile, nuclear cruiser, a new conventional carrier, FB-111 strategic bomber, and MX (Stubbing and Mendel 1986:350). It was only in the last Carter budget that continuity existed, and to a remarkable extent. The budgets of the Reagan administration echoed this pattern. There was no year-to-year continuity in the first two budgets, again showing a reordering of priorities in allocation. Carter budgets favored readiness and Reagan emphasized modernization. As was seen in the extremely stable service budget shares, the last four Reagan budgets show a high degree of continuity. Table 3.4 also has an entry for the FY1989 budget submitted to Congress along with the FY1988 budget. It had no real bearing on the eventual outcomes and shows a reversal in spending priorities. Since the FY1988 budget request showed the smallest increase of all Reagan budgets (6.2 percent versus an average of 14.4 percent in the first five budgets), relative ‘losers’ in the FY1988 budget were compensated with larger increases in the accompanying FY1989 budget. Throughout this entire period, with the exception of the reform-oriented Eisenhower years, the pattern was consistent. Changes in priorities are made

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in the first two fiscal years, sometimes reversing the priorities of the previous administration. Thereafter, a period of stability emerges when ‘winners’ and ‘losers’ are consistent over several years. The Vietnam war, as would be expected, disturbed this pattern, but, in doing so, supported the general pattern of distribution of resources in the defense budget.

VARIATION IN ALLOCATION The appearance and disappearance of continuity in allocation patterns reveals that ‘defense posturing’ occurs constantly, especially in new administrations. Much research has been conducted to support the notion that ‘incrementalism’ and ‘organizational momentum’ guide allocation decision making. According to these ideas, budget formulation is too complicated for decision makers to be able to significantly alter spending trends buttressed by organizational vested interest. Other research, however, indicates that budget decisions are not based on principles of incremental additions to existing spending levels, but derive from a process that produces budget outcomes sensitive to (1) the merit of competing programs and (2) fiscal constraints in available funding (Padgett 1980). One might, however, substitute the political skill of budget actors for the ambiguous notion of merit (Mowery et al. 1980). In the case of the US defense budget, these ‘serial judgments’ serve to allocate resources deemed necessary to meet both defense and budget objectives. On the basis of the above analyses alone, such notions seem more appropriate given the absence of standard increments in US defense allocation patterns. In the absence of program merit and fiscal constraint, incremental decision making would prevail, as there would be no basis for discriminating among competing claims for resources. The pattern of allocations would be grouped around an average increase with very few appropriation categories far off the overall budget increase. The degree of variation in each year’s budget is shown in Table 3.5. Although several measures of variation are possible, the most general summary statistic is kurtosis, or the degree of concentration around the mean or ‘peakedness’ (Bickel and Doksum 1977). Small values of this statistic show that most changes are very near to the average increment across all of the appropriation categories. Large values result from a wide dispersion of changes—some very large ‘winners’ and/or some large ‘losers.’ The obvious conclusion drawn from Table 3.5 is that there is a great variation in kurtosis. There are several years when changes in allocation are concentrated around the average changes and some years in which allocations are skewed towards a few ‘winners’ and ‘losers.’

Do leaders make a difference? TABLE 3.5 Variation in the defense budget, 1955–89

Note: a The FY1989 submission accompanied the FY1988 request.

47

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No obvious patterns can be discerned, although there was more variation in the Eisenhower (an average of 12.4) and Nixon/Ford (11.2) administrations than in the other three (JFK/LBJ 7.9, Carter 5.2, and Reagan 2.3). While there are years of great variation in changing allocations in these periods, there are also years of stability or more ‘incremental’ changes. Unlike changes in service shares and reverses in continuity, the early years of each administration do not show a tendency for greater variation in allocation. The most important finding relates to the relationship between growth in the total defense budget request and the distribution of allocations. A strong negative relationship exists (r=-.45), indicating that large increases in defense requests are distributed much more evenly than small increases or decreases. This supports the reasoning that fiscal constraint creates hard choices. When there are large increases in the budget request, there is a tendency to distribute it evenly across the appropriation categories. The tendency to distribute large increases evenly across the range of defense programs is remarkably characteristic of the Reagan defense budgets. The growth of the defense budget in the Reagan administration was across the board, with few programs delineated as large ‘winners’ or ‘losers.’ With abundant resources for defense, fiscal constraint was not present and incrementalism seemed to dominate. Interestingly, however, the FY1988 budget was the smallest Reagan growth in total request for defense, but showed almost no variation across categories. Table 3.5 also reports the largest ‘winner’ and ‘loser’ in each year. Only a few findings can be noted. First, and not surprisingly, personnel categories are not often big ‘winners’ or ‘losers.’ They represent fairly stable allocations based on small changes in manpower levels. One interesting example stands out as a curious illustration of defense politics. From FY1976 to FY1980, the budget specified large reductions in the size of the US Navy Reserve. When summed, these reductions would have amounted to an 80 percent reduction! But these were only budget requests and, in each of these years, the Navy lobby in Congress reinstated funds for the Navy Reserve. The five-year run on the Navy Reserve was interrupted only for FY1978, when the Secretary of Defense was Captain Donald Rumsfeld, US Navy Reserve. The Navy Reserve was partly protected in Congress by Senator John Tower, US Navy Reserve (retired), who no doubt approved of the 85 percent increase contained in the first Reagan budget submission. Procurement and construction are the most volatile. Of these, Navy shipbuilding and conversion is a frequent large ‘winner’ or ‘loser.’ Even a modest shipbuilding program is very expensive, especially in Total Obligational Authority. These short-term appropriations for future deliveries are usually followed by the appearance of shipbuilding as a large


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‘loser,’ but this is merely the down-side of a naval buildup. Further, Navy shipbuilding is usually accompanied by a reduction in naval base construction. When the Navy launches a new shipbuilding program, increased spending for ships is offset by cuts in construction, which presumably can be recouped later as the new ships are commissioned. On this basis, construction is the most flexible kind of appropriation, in the sense that it is more easily deferred.

CONCLUSIONS Since the creation of the National Military Establishment in 1947 as a loose alliance between the services, the rapid evolution of defense politics has encumbered investigations of budget behavior. The results of the analyses reported here show that (1) changes in presidential administrations have resulted in meaningful shifts in allocation, (2) continuity in programs has grown, and (3) large increases in defense spending are distributed more evenly than is spending in periods of fiscal constraint. These conclusions are based on findings that show political change is related to changing patterns of allocation in the defense budget. First, allocation between the services changes most in the early years of an administration (although this was not true of the Carter administration, when changes in service shares were slight). This is consistent with the desire of each President to tailor his own defense programs and perhaps also to meet campaign commitments. Second, when appropriation categories are examined for year-to-year continuity, program reversals occur in the first years of a new administration. This is true of all but the Nixon administration, whose priorities can be understood to have been established by the ongoing war. Third, the pattern of ‘peakedness’ shows that shifting priorities among appropriation categories is very common. A recurring incremental pattern would be more consistent with organizational parochialism, in this case the services, and more marginal changes. It seems more likely that politicians can and often do alter resource distributions. Fourth, the relationship between the size of defense increase and the distribution of allocation shows that, in the absence of fiscal constraint, far less discrimination is made between appropriation categories. Smaller budget increases are marked by greater separation of ‘winners’ and ‘losers.’ Several findings support the importance of defense politics, isolated from outside influences. Over time, the share of the budget devoted to each service seems to have stabilized. From Eisenhower through Reagan, the tendency was for smaller shifts between the three services. This might suggest that an

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inter-service balance of power has arisen, leading to well-marked divisions and resources. Similarly, it appears that continuity in spending priorities—programs in one year receiving the same treatment in the next—takes place after two or three years of each administration. This may be the result of organizational power configurations. Such a finding, however, is equally consistent with the ability of a presidential administration to carry through original intentions. On balance, political factors like the changing of presidential administrations seem to have the greatest impact on the distribution of defense resources. In assessing the current direction of defense politics, it appears that the disintegrative aspects of inter-service rivalry has been muted by the development of clearly delineated service ‘turf and civilian coordination of mission planning and force posture. Discussions of future budgets are bound to be inaccurate, but they can reflect the trends exhibited since the Eisenhower administration. Regardless of future developments, trends in US budgeting for defense are now becoming discernible and the search for patterns can enlighten the dynamics of budgeting.

REFERENCES Bickel, J. and Doksum, K. 1977. Mathematical Statistics. San Francisco: Holden-Day. Enthoven, A.C. and Smith, K.W. 1971. How Much Is Enough? New York: Harper & Row. Gaddis, J.L. 1982. Strategies of Containment. Oxford: Oxford University Press. Huntington, S.P. 1961. The Common Defense. New York: Columbia University Press. Huntington, S.P. 1983. The defense policy of the Reagan administration. In F.I.Greenstein (ed.), The Reagan Presidency: An Early Assessment, pp. 82–116. Baltimore, MD: Johns Hopkins University Press. Jones, D.C. 1982. What’s wrong with our defense establishment? New York Times Magazine, 7 November. Kanter, A. 1979. Defense Politics: A Budgetary Perspective. Chicago: University of Chicago Press. Korb, L.J. 1979. The Rise and Fall of the Pentagon. Westport, CT: Greenwood Press. Mintz, A. 1988. The Politics of Resource Allocation in the US Department of Defense: International Crises and Domestic Constraints. Boulder, CO: Westview Press. Mowery, D. and Kamlet, M. 1984. Games presidents do and do not play. Policy Sciences 16: 301–35.


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Mowery, D.C., Kamlet, M.S. and Crecine, J.C. 1980. Presidential management of budgetary and fiscal policy making. Political Science Quarterly 95:395–425. Nincic, M. and Cusack, T. 1979. The political economy of US military spending. Journal of Peace Research 15:101–15. Ostrom, C.W. and Marra, R.F. 1986. U.S. defense spending and the Soviet estimate. American Political Science Review 80 (September): 819–42. Padgett, J.F.1980. Bounded rationality in budgetary research. American Political Science Review 74 (June): 354–72. Stubbing, R.A. with Mendel, R.A. 1986. The Defense Game. New York: Harper & Row. Wildavsky, A.1979. The Politics of the Budgetary Process, 3rd edn. Boston, MA: Little Brown.

CHAPTER 4

‘Too Little,’ but Not For Too Long: Public Attitudes on Defense Spending Richard J.Stoll

Making foreign and defense policy in a democracy is a mixed blessing. On the one hand, some feel that there is no more powerful a force than a democracy with the ire of its people aroused. On the other hand, a foreign and defense policy heavily influenced by the will of the people is seen by many as a source of weakness and vacillation in an unfriendly world. This chapter is concerned with one question related to the making of foreign and defense policy in the United States: What accounts for the attitude of the American public toward US defense spending? The question is an important one for several reasons. First, the presumption of some that public opinion is fickle, changeable, and susceptible to wide fluctuations without any underlying rationale can be examined. If it can be shown that public opinion on defense spending is systematically related to a set of factors, this presumption is called into question (for recent work which asserts that US public opinion is systematically structured, see Nincic 1988 and Shapiro and Page 1988). Second, work by Ostrom and Marra (1986) demonstrates that, when a strong consensus exists in the public on desired changes in defense spending, it can have a discernible impact on the budget process. Understanding what could produce this consensus is important for forecasting future budgets. Finally, if we know what factors are associated with public opinion on this issue, we could come to some understanding about how public opinion can be influenced on this issue. This is a matter of particular importance for President Bush, since recent events in Eastern Europe and the Soviet Union have produced an atmosphere that would appear to make it difficult, if not impossible, for him to sustain his desired defense program. To explore the basis of public opinion on defense spending, we will analyze a set of factors accounting for the proportion of the public which believed 52

Public attitudes on defense spending

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the United States was spending too little on defense during the time period 1947–87.

THEORETICAL BACKGROUND Before we begin, two points should be noted. First, what we call ‘public opinion’ on an issue is actually a composite of the opinions (or lack of opinions) of different groups in a society with very different orientations. Second, if the general public does consist of these different groups, then any measure of aggregate public opinion contains a random component that will undoubtedly defy all efforts to account for the total figure in a systematic fashion. Perhaps because of these problems, very little empirical work has been done trying to account for public opinion on defense spending. The most prominent work is that of Russett (1972; see also Russett and DeLuca 1981). His pieces were mainly descriptive, charting the level of support for military spending from the late 1930s to 1981. He also offered several explanations for the predominantly permissive attitudes of the American public. But he conducted little actual analysis, beyond comparing this variable with actual levels of defense spending, with support for defense budget cuts in Congress, and with the willingness of the American public to defend other countries. His major conclusion was that the late 1960s and early 1970s were the only time since the start of public opinion polling that a substantial portion of the American public felt defense spending was too large. Another study by Abolfathi (1980) considered the links between the international situation, public opinion, and defense spending in the United States from 1930 to 1978. He used two variables to account for public support for increased defense spending: defense as a percentage of the Gross National Product, and the proportion of the public which named an international or defense problem as their primary concern. Although both variables were statistically significant, they accounted for only about 20 percent of the variance in support for an increase in defense spending. Factors influencing public opinion on defense spending When considering what factors should be related to public support for increases in the defense budget, we must bear in mind that, with the exception of the opinion leaders, members of the public are likely to ignore all but the most dramatic events and largest elements in forming their opinions on the

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defense budget. Nevertheless, a strong case can be made that public attitudes on defense spending will be affected by a small number of factors. The factors selected for analysis represent both the most obvious external and internal manifestations of US defense policy (which should be known— albeit vaguely—to the public), and the tendency for some stability to persist in public evaluation of public policy problems. Finally, the uniqueness of the Reagan era, and that President’s stalwart commitment to a strong defense, deserve inclusion as separate factors. Let us turn to a discussion of each of the predictor variables. VISIBLE USES OF FORCE

In the international arena, dramatic and visible actions which involve the US military against the Soviet Union should lead to high levels of support for an increased defense budget. During peacetime, incidents involving US forces in brief combat or potentially dangerous situations cause the public to rally around the President (Mueller 1973), and can be expected to generate support for the military. This will also be reflected in a desire to expand the military, hence to increase defense expenditures. This should be particularly true about military actions directed against the Soviet Union, the largest and most dangerous adversary of the United States. During the US war involvements in Korea and Vietnam, this positive effect will be smaller for two reasons. First, at the beginning of a war, the war involvement will overshadow other uses of the US military; due to its sheer size, events that would otherwise be front-page news are given little or no attention. Second, as the war involvement wears on, its uniqueness declines, and (as a separate process) support for the war will drop off. In these circumstances, uses of the US military outside the war zone will become more noticeable, but will be interpreted by many in the context of a long and unsuccessful military involvement. PREVIOUS DEFENSE SPENDING

The size of the defense budget itself will also have an impact on public attitudes towards the defense budget. If the recent defense budget is large, the public is likely to feel that it should be reduced. Aside from those in the public who favor other spending priorities, a large recent defense budget may convince many who favor a strong defense that the US posture is in good shape, and the budget can now be cut. CONSISTENCY OF ATTITUDES

We also expect that some portion of the public will persist in its belief about the adequacy of the defense budget from year to year. In many cases, whatever led individuals in the public to form an opinion on the defense budget in the


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previous year will not change dramatically. Consequently, their opinion will stay constant from year to year. When aggregated across all the individuals in the general public, we expect that there will be a positive relationship between the proportion of individuals who favored an increase in defense spending last year, and the proportion who favor an increase this year. THE IMPACT OF REAGAN

Finally, the Reagan presidency was associated with a renewed emphasis on military power. This attitude was represented in the rhetoric of its spokespersons (including the President himself), its defense budget submissions, and the use of US military forces abroad. The impact of this set of interlocking policy initiatives should be an increase in the level of support for defense spending in the general public. And, for President Bush, the size of the Reagan effect represents a base of support that he may be unable to mobilize inspite of his best efforts.

OPERATIONALIZATION AND RESEARCH DESIGN Turning each of the concepts mentioned above into something that can be measured is by no means a simple task. Slippage between the factors as we describe them, and the available means to measure them, is one of the regrettable in-evitabilities of social science research. It is ironic that some of the greatest problems occur in public opinion sampling. A well-designed survey is one of the most powerful tools in the social scientist’s arsenal. But secondary analysis of these data are completely at the mercy of the original researchers. Once the questions are set and administered, there is no going back in time to correct any deficiencies or to alter anything so that it will be more useful for a particular study. Some of these problems arise in this study. However, these problems are not severe enough to prevent this investigation from acquiring useful information. The dependent variable One of the very few questions on foreign and defense policy which has been asked consistently through the 1947–87 time period concerns the respondent’s opinion on the size of the defense budget. The lead-in to the question has varied, and this can have an impact on the response of an individual. But the wording of the question itself has been fairly consistent: Do you think we are spending too little, too much, or about the right amount? (Abolfathi 1980:97)

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The proportion of the respondents responding ‘too little’ will be taken as an indicator of the amount of support in the general public for an increase in defense spending. The studies discussed earlier have relied on this question as well, but that should not blind us to the theoretical and empirical problems associated with it. At the theoretical level, it is clear that not everyone who feels the US is spending too little on defense would also agree that the budget should be increased. A simple example of this lack of congruence is any person who favors a strong defense, but also favors a balanced budget. Such an individual may wish to increase defense spending, but believes that any increment would cost more in damage to the US economy than would be gained in terms of the military security of the US. Nevertheless, we should expect that it is highly probable that an individual who feels that the US is currently spending too little on defense will favor an increase in defense spending. The empirical problem with the question is that it was not asked in all of the years under study. In fact, the question was not asked in 14 of the 36 years (39 percent). In order to reduce the amount of missing data, the following procedures are adopted for estimating the proportion of ‘too little’ responses. First, if a survey was conducted in the December of the previous year, this figure is used. Second, if there was no December survey but data are present for the year before and the year after, the average of these two years is used. This still leaves missing data for the years 1962–68. The failure to ask the question during this time period is especially unfortunate since the post-1968 time period has a much smaller proportion of ‘too little’ responses than the 1947–61 time period (see Figure 4.1 below).1 The predictor variables Five variables are used to operationalize the factors influencing public opinion discussed above. Two variables are necessary to operationalize the first factor, the impact of dramatic and visible actions which involve the US military against the Soviet Union. Each of the remaining factors needs only a single variable for its operationalization. Data used in the analysis (other than the dummy variables) are displayed in the Appendix to this chapter. VISIBLE USE OF FORCE

A visible use of military force is defined as a situation in which components of a nation’s uniformed military are deployed in such a manner that sporadic combat occurs, or is a distinct possibility. The definition excludes uses that occur as part of an ongoing war involvement. Data for this indicator are constructed from Blechman and Kaplan’s (1978) study of the political use of


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the US military for the 1946–76 time period, as updated by Zelikow (1987) for the years 1977–86, and by the author for 1987 (Stoll 1987). As defined by Blechman and Kaplan (1978:12–16), a political use of the armed forces occurs when a physical change in the disposition of some elements of the military is used to influence a foreign actor.2 Not all of the types of actions coded in this data set involve combat or a reasonable chance of it. Based on a scaling of these actions done by Stoll (1984), five types of military activity from the data set are taken as indicators of visible use of military force: (1) (2) (3) (4) (5)

establishment of a selective or complete blockade; interposition of military forces between two foreign actors; emplacement of ground forces; patrol, reconnaissance, or surveillance; use of firepower or other violent action.

The total number of US visible uses of force in a year in which the Soviet Union is a target of US influence is the variable used in this study. However, a separate variable is needed to account for the changing relationship during wartime. This variable is created by multiplying the number of visible uses of force involving the Soviet Union by a dummy variable coded 1 if the US is involved in the Korean or Vietnam war, and 0 otherwise. PREVIOUS DEFENSE SPENDING

The size of the defense budget is operationalized as the budget outlay for national defense expressed in constant 1982 dollars. The outlay figures are taken from the Statistical Abstract of the United States (US Department of Commerce). The Implicit Price Deflator for GNP is used to convert the outlays into constant dollars. The deflator is reported in the Survey of Current Business (US Department of Commerce). Since this variable is lagged, data for the years 1946–86 are used in the analysis. PREVIOUS LEVEL OF SUPPORT FOR INCREASED DEFENSE SPENDING

Another predictor variable is the previous level of public support for increased defense spending. This is operationalized as the proportion of the public who felt that defense spending was too little in the previous year. THE IMPACT OF THE REAGAN ADMINISTRATION

The impact of the Reagan administration on support for defense spending is measured in a very straightforward manner. A dummy variable is coded, with a value of 1 for the years in which Reagan was in office, and 0 otherwise.


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Research design The research design is a simple one. After all cases with missing data on the ‘too little’ question—either the dependent variable or the lagged version which is used as a predictor variable—are deleted, 32 cases remain. These cases are analyzed using ordinary least squares. Since the data are a time series, including the use of a lagged dependent variable, the residuals are examined for the presence of autocorrelation.

RESULTS The results of the regression analysis are displayed in Table 4.1. The overall fit is good, and most of the variables are significant (t-values over 2.00) and in the predicted direction. Further, when the residuals are subjected to autocorrelation, no significant levels are found (up to 15 lags were tested).3 Clearly, public support for increasing the defense budget is systematically related to a small set of factors. The notion that the public is fickle and transient in its attitude towards defense spending is not supported. TABLE 4.1 Regression analysis: predicting proportion of public who feel current spending is too little

Note: No significant autocorrelation of residuals.


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The two variables with the strongest impact on support for increased defense spending (see the standardized coefficients in Table 4.1) are the number of visible uses offeree involving the Soviet Union, and last year’s defense budget. Visible uses offeree have a strong positive impact on support for the defense budget (producing almost a 9 point increase in the proportion who feel that the defense budget is too little for each use of force in a year). But during a US war involvement, this impact is almost completely negated; for each visible use offeree during war, there is only about a 1 1/2 percent increase in those favoring a boost in the defense budget. The lagged defense budget has a negative impact on current levels of support for a spending increase, raising the possibility that support for an increase is self-liquidating in the near future. This could happen if (a) the public presses for an increase, (b) this leads to a larger budget, and (c) in the next year, this larger budget produces a decrease in support for further increases. Two of the variables have large, but not significant, t-values. There is a positive link between the proportion of the public who feel that the defense budget is too small from one year to the next, although since the coefficient is less than 1.0, there is a drop-off from year to year. Finally, during the

FIGURE 4.1

Proportion of public feeling too little spent on defense (observed versus predicted), 1947–87

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Reagan administration, there is a higher level of support for increased defense spending than in the earlier years. Figure 4.1 displays the observed and predicted values through time. The predicted values track the ups and downs of the observed values reasonably well, but there are two caveats to this conclusion. First, there is a tendency to underestimate the peaks of support for spending increases; note the difference between predicted and observed values in 1951, 1958, 1980, and 1981. It would appear that some factor which produces extremely high levels of support for budget increases has been left out of the model. Second, the model predicts a total absence of support for defense increases in 1986 and 1987.4 This pattern suggests that there may well be a floor of support for increased defense spending that is always present. This effect is not captured in the model.

DISCUSSION Given the predictions of the model, combined with recent events in Eastern Europe, a downward slide in public support for defense spending seems inevitable. Is there anything that can be done to stop it? The model offers one clue as to how a President may be able to keep public support at levels high enough to sustain a period of growth—or, in current circumstances, stability —in the defense budget. Recall the argument for visible uses of force. The argument was that, in situations in which the national security interests of the United States were clearly at stake, the public would stand with the President and support increased defense expenditures. Visible uses offeree involving the Soviet Union fall clearly into this category, and, although these appear less likely, military events involving other countries will stir up the same reaction. But it may be possible for a President to ‘go to the people,’ and, through a well-orchestrated campaign, lift the level of public support for an increased defense budget. This is precisely what presidents tend to do in these situations. But there are dangers. Increases in support are short lived, which forces a President to mount an ‘education’ campaign for each year’s defense budget. But continual assertions that the national security of the United States is gravely threatened will tend to reduce their impact. In effect, they become ‘old news,’ lose their uniqueness, and hence their ability to stir the American people. Of course, a President could wait for the occurrence of a threatening situation, involve US military forces, and use this to increase public support. But this leaves the initiative for spending increases in the hands of other, presumably hostile actors. Furthermore, one would wish that US


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defense policy would prevent such occurrences, rather than encourage them.5 The short-lived nature of public support for defense increases suggests that a President wishing to increase defense spending must move quickly. From the point of view of efficiency, a long series of small steady increases would be best. But if a President believes that such a set of increases cannot be sustained, he may feel compelled to submit a smaller number of very large requests to have them enacted before popular support evaporates. This strategy produces a higher amount of waste.

CONCLUSION Public opinion in democracies is cursed or praised, depending on the inclinations of the observer. This chapter investigated some of the sources of public support for increases in defense spending during the 1947–87 time period. The results indicate that a small number of factors exercise a significant influence on public attitudes. This refutes the argument that public opinion is fickle, and often random, on defense matters. The results also indicate that it is extremely difficult to sustain continual growth in defense spending. This chapter represents only a first step. More work needs to be done to integrate the role of public opinion into the national security policy-making process. But these results indicate that we can achieve a better understanding of the overall policy-making process through the use of simple empirical analysis.

NOTES 1

2

Data for 1947–78 are taken from Abolfathi (1980, Table 3.3), and data for 1979-S7 are taken from the Gallup Opinion Index. No Gallup surveys were conducted using this question in the following years: 1954, 1956, 1959, 1976, and 1984. If the question was asked more than once in a year, the average proportion of ‘too little’ responses is used. Abolfathi uses the average proportion for the 1955–61 time period to replace the missing data for 1962–68. This is a very questionable procedure, and may have dramatic consequences for his results. Additional data were collected by General Electric for the years 1965–67, but the question wording is different from that used by Gallup, so they are not included in this analysis. More particularly, [a] political use of the armed forces occurs when physical actions are taken by one or more components of the uniformed military services as part of a deliberate attempt by

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I: CYCLES IN MILITARY SPENDING the national authorities to influence, or to be prepared to influence, specific behavior of individuals in another nation without engaging in a continuous contest of violence…. a political use of the armed forces was inferred to have taken place if five elements were present in the situation. 1. A physical change in the disposition…of at least a part of the armed forces had to occur… 2. Behind this activity there had to have been a certain consciousness of purpose… 3. Decision makers must have sought to attain their objectives by gaining influence in the target state, not by physically imposing the US will… 4. Decision makers must have sought to avoid a significant contest of violence… 5. Some specific behavior had to have been desired of the target actors. (Blechman and Kaplan 1978:12–16)

3

4

5

The missing data in the series render this sort of test less useful than if the data are complete. Mindful that the small number of cases do not allow for extensive additional analyses, three additional variables were introduced to check the validity of the results. A dummy variable for US war involvement, a dummy variable for cases in which the lagged defense spending support variable was interpolated, and a dummy variable for years following Soviet invasions (Hungary, Czechoslovakia, and Afghanistan) were used. Individually no variable had an impact on the dependent variable. Collectively they did not produce changes in the other coefficients in the estimated equation or the overall fit. The data for 1987 are problematic. The figure for opinion favoring a spending increase is based on a single survey conducted on 10–13 April. The defense spending question is usually asked three or four times a year, so this datum may not be equivalent to that of previous years. Recent research has shown that the Congress, like the general public, will rally around the President in the wake of serious military involvements (Stoll 1987). If a President can time his budget request to arrive soon after such an event, he has an increased chance of gaining congressional support.


APPENDIX: DATA USED IN THE ANALYSIS

Key: INCDEF=proportion of public: defense budget it too small; LDEFBUD=last year’s defense budget; LINCDEF=last year’s proportion of public: defense budget is too small; USSUVIS=number of US visible uses offeree involving the USSR; VISARWAR=during US war involvements, the value of USSUVIS; 0 otherwise; REAGAN=dummy variable: Reagan presidency; -99.000=missing data.

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REFERENCES Abolfathi, F. 1980. Threat, public opinion, and military spending in the United States, 1930– 1990 in McGowan and C.W.Kegley (eds), Threats, Weapons, and Foreign Policy, pp. 83– 136. Beverly Hills, CA: Sage. Blechman, B. and Kaplan, S. 1978. Force Without War: U.S. Armed Forces as a Political Instrument. Washington, DC: The Brookings Institution. Gallup Opinion Index. Various years. Princeton, NJ: American Institute of Public Opinion. Mueller, J. 1973. War, Presidents, and Public Opinion. New York: John Wiley. Nincic, M. 1988. The United States, the Soviet Union, and the politics of opposites. World Politics 40:452–75. Ostrom, C. and Marra, R.F. 1986. U.S. defense spending and the Soviet estimate. American Political Science Review 80 (3): 819–42. Russett, B. 1972. The revolt of the masses: public opinion on military expenditures. In B. Russett (ed.), Peace, War, and Numbers, pp. 299–319. Beverly Hills, CA: Sage. Russett, B. and DeLuca, D.R. 1981. ‘Don’t tread on me’: Public opinion and foreign policy in the eighties. Political Science Quarterly 93 (3): 381–99. Shapiro, R.Y. and Page, B.I. 1988. Foreign policy and the rational public. Journal of Conflict Resolution 32:211–47. Stoll, R. 1984. The guns of November: presidential reelections and the use offeree, 1947–1982. Journal of Conflict Resolution 28 (2): 231–46. Stoll, R. 1987. The sound of the guns: is there a congressional rally effect after U.S. militaryaction? American Politics Quarterly 15 (2): 223–37. US Department of Commerce. Various years. Statistical Abstract of the United States. Washington, DC: US Government Printing Office. US Department of Commerce. Various months. Survey of Current Business. Washington, DC: US Government Printing Office. Zelikow, P.D. 1987. The United States and the use of force: a historical summary. In G.K. Osborn, Clark, Kaufman, and Lute (eds), Democracy, Strategy, and Vietnam, pp. 31–82. Lexington, MA: Lexington Books.

CHAPTER 5

Risky Business: US–Soviet Competition and Corporate Profits Michael D.Ward and David R.Davis

In an earlier article about US–Soviet strategic competition, based on data through the end of 1978, Ward (1984) argued that superpower competition focused not on military budgets but rather on military stockpiles. Decision makers in deciding upon the budget look carefully at competitive weapon stockpiles rather than focusing exclusively on competitive spending levels, a point made convincingly in McCubbins (1983). In finding empirical support for this argument it was argued that the ‘USSR is racing to catch up to the United States’ and that ‘the dynamics governing arms competition between the United States and the USSR appear to be undergoing marked change’ (Ward 1984:297). In concluding that earlier study it was noted: Having followed different paths, the United States and the USSR have arrived at a position of relative parity. The irony is that reaching that goal may well bring about an increase rather than a decrease in the perceived threat. New paths must be chosen; the old paths are unlikely to serve well in the terrain of the future. (Ward 1984:311)

With the benefit of some hindsight, the above conclusion seems in some respects to be especially informative. The decade of the 1980s ended with a ‘geo-political’ earthquake of enormous proportions, the epicenter of which appears to be in Central Europe. If the first one-half of the 1980s was characterized by increasing US–Soviet tension as the Federation of Atomic Scientists moved the hands of their hypothetical doomsday clock ever closer to midnight—the second half was marked by an enormous relaxation in US-Soviet military and strategic tension. So much so that during the last months of 1988, the Soviet Union 65

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began withdrawing military forces in sizable numbers from Eastern Europe as part of unilateral disarmament moves aimed at adopting a ‘more defensive’ Soviet military posture in Europe. Soviet forward nuclear war fighting capabilities were withdrawn at the end of the 1980s from the coasts of the US. Indeed, by one estimate Soviet military power was assessed to have been reduced by about 20 percent by the end of the decade (E.L.Warner testifying at the House Armed Services Committee in September 1989). After a period of some reticence, the United States also began responding to these Soviet initiatives. Quite astonishingly in the same decade as President Ronald Reagan’s ‘evil empire’ speech, the Pentagon would ‘leak’ initial plans of a 1992–94 defense budget reduced by about $200 billion over previous defense plans for the same period. US intelligence experts also concluded in 1989 that a Soviet attack could not be mounted in less than about 30 days. Further, the US Defense Secretary proposed a cessation of round-the-clock flights of the US airborne command post on the grounds that the threat of surprise attack was minimal (Bush vetoed this proposal on ‘symbolic’ grounds). Clearly, change is afoot. The purpose of this chapter is to update earlier work on US-Soviet strategic competition, and to evaluate the impact of the current diplomatic climate on the interplay between the strategic concerns of the US and Soviet Union on the one hand and the corporate concerns of the US defense industry on the other. This effort examines five separate, but interrelated aspects of US defense policy making: •

•

•

•

First, we elaborate several of the myriad ways of assessing the relative nuclear military strength of the US and the Soviet Union, ranging from numbers of warheads, through delivery vehicles, and on to deliverable megatonnage. We show that different trends are evident in each approach, but that the ‘parity’ reached during the 1980s was transitory, and that the US now far outstrips Soviet nuclear capabilities. Second, we briefly examine the conventional balance offerees as it stands in relief to the nuclear competition between the United States and the Soviet Union. Third, we examine the domestic political economy of the US defense sector, a sector accounting for approximately 5 percent of GNP during the last four decades, during which time there has been enormous growth of profits in the defense sector. Fluctuations in these corporate profits appear to be contemporaneous with many of the fluctuations in US defense spending. Fourth, we briefly examine the economies of the US and the Soviet Union as they relate to the pressures and opportunities brought forth by the arms races of the last four decades.

US–Soviet competition and corporate profits

•

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Lastly, we illustrate the decline in the uncertainty of US–Soviet relations, both in terms of absolute tension and in terms of degree of fluctuations.

MILITARY CAPABILITIES Strategic capabilities indicators One contribution of this chapter is the creation of a strategic capabilities indicator for both the Soviet Union and the United States. This section documents that effort. Information was collected which measures the nuclear capabilities of both actors within the so-called strategic triad—long-range bombers, intercontinental ballistic missiles (ICBMs), and submarine-launched ballistic missiles (SLBMs). The capabilities indicator incorporates information about two central aspects of the nuclear arsenals of the superpowers: the types and characteristics of the available delivery vehicles, and the numbers and characteristics of nuclear warheads carried by each vehicle. This information is then combined to create a measure of the total deliverable nuclear firepower, which we then use as an indicator of strategic capabilities. In order to develop a satisfactory way of comparing the strategic capabilities of the US and Soviet nuclear forces a number of issues need to be considered. Previously a number of studies chose very simple measures of nuclear capabilities such as counts of the number of nuclear weapons or the number of delivery vehicles (e.g. Ostrom 1978). Obvious problems exist for both of these measures. Simply counting nuclear weapons does not take into account the wide variety of different warhead destructive capacities. In the same manner, counts of delivery vehicles do not reflect the number of warheads carried or the range of reachable targets, nor do they consider the range within which they may be delivered. For such reasons we chose to create an indicator that would address as many of these issues as possible; including, the number of delivery vehicles, the number of warheads, the yield of warheads, and the range and accuracy of delivery vehicles. We provide all of our data and assumptions so that others may use or modify our approach. These factors were combined to create our strategic capabilities indicator in the following manner. (5.1) where s is the indicator of strategic capabilities, m represents equivalent megatonnage, c stands for circular error probable (CEP) in meters, r is the

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range of the delivery vehicle in kilometers, w is the number of war-heads per delivery vehicle, and v is the number of operational delivery vehicles. The equivalent megatonnage of each weapon, which is calculated by raising the weapon’s yield to the 2/3 power, accounts for the fact that destructive power does not grow proportionately with a simple increase in yield. The CEP of the warhead measures the radiums of a circle within which half of the warheads are expected to fall, thus gauging the accuracy of each weapon. Dividing equivalent megatonnage (destructive power) by CEP (accuracy) results in a measure of the lethality of a particular warhead. This measure is then multiplied by the range of the delivery vehicle, the number of warheads per vehicle, and the number of operational delivery vehicles. This creates a measure of the deliverable firepower for a specific weapon system. The deliverable firepower for both the US and Soviet weapons systems is aggregated yearly to create strategic capabilities indicators for each nation. Data sources The task of collecting much of the above information proved to be difficult for the early years of nuclear weapons deployment and it was necessary to make several assumptions about the numbers and sizes of weapons deployed. The extreme lengths to which the US and Soviets went to prevent the spread of official secrets about their nuclear arsenals during the early years of the cold war and poor organizational record-keeping resulted in a situation in which the exact numbers and types of nuclear weapons deployed in the late 1940s and early 1950s may never be known with certainty (Rosenberg 1982). However, by the mid-1960s the quality of official and unofficial data collection efforts had improved greatly and the number of sources also increased. Most important were the collection efforts of the Stockholm International Peace Research Institute (SIPRI) and the International Institute for Strategic Studies (IISS). Beginning in the late 1970s and early 1980s, a number of detailed compilations were assembled which combined information from a wide variety of sources into somewhat complete studies, foremost among which are Cochran et al (1989), Collins (1980, 1985), Crawford (1986), Gervasi (1986), and Wright (1986). These constitute the main sources on which we relied. The specific data taken from each one will be detailed below along with other secondary sources. We also enumerate the specific assumptions we made in estimating nuclear capabilities by leg of each nation’s triad.


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The United States INTERCONTINENTAL BALLISTIC MISSILES

The numbers and capabilities of US ICBMs have not yet been assembled in a single volume. The data employed herein came from SIPRI for the period 1960–69, Collins (1980, 1985) for the period 1970–84, and lastly the Annual Report of the Secretary of Defense (US Department of Defense 1987, 1988) updated the series to the present. There is general agreement about the capabilities of US ICBMs. Missile characteristics were taken from Collins. The only major disagreement in the various sources centers around the original and operational deployment dates of the Atlas, Titan, and Minuteman I missiles. We use the estimates of the IISS (various years) for this information. SUBMARINE-LAUNCHED BALLISTIC MISSILES

Calculating the deliverable yield of US SLBMs was straightforward. Data were taken from Collins (1980, 1985) for the period 1970–85 and from SIPRI and IISS before and after. The only point of uncertainty is the yield of the warheads on the original Al Polaris missiles, where estimates range from 500kt to 1Mt. We chose the more conservative 500kt figure. It should also be noted that submarine-launched cruise missiles (SLCM) are not included in our analysis of the US strategic capabilities because in the first instance these weapons are considered to be tactical rather than strategic weapons and in the second instance their limited range makes them incapable of reaching the Soviet Union when fired from traditional ballistic missile submarine patrol areas. LONG-RANGE BOMBERS

The most difficult data to collect for the US proved to be the long-range bomber force. This is the case for a number of reasons. Specifically, in the first few years of nuclear weapons deployment medium-range nuclear bombers (B-29s) based overseas were modified to carry nuclear weapons, which resulted in a considerably larger number of delivery vehicles than of warheads. In addition, new delivery systems (B-36, B-50) were developed as both strategic and conventional weapon systems. This compounds the difficulty of determining the payload characteristics of the delivery vehicles. Thirdly, the above-mentioned delivery vehicles were capable of carrying a large number of different nuclear bombs with different characteristics, making it impossible to determine the exact mix of deployed nuclear bombs. Therefore, we estimated the US strategic indicator by taking the number of warheads from Gervasi (1986), confirmed by Cochran et al. (1984), and inferred the number of delivery vehicles based on this information. The yield was estimated by averaging the yields of the different


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TABLE 5.1 US yield and range estimates for long-range bombers, 1948–54

Source: Authors’ calculations.

bombs deployed in the early years, a figure reported in Cochran et al. (1984). The range and payloads of the delivery vehicles were taken from Jones (1962), and then averaged to create a ‘typical’ delivery vehicle. Data estimated for the period 1948–54 are displayed in Table 5.1. From 1955 on it is assumed that the production of nuclear warheads, in combination with the retiring of the forward-based medium-range bombers, resulted in a situation where the numbers of delivery vehicles and warheads were at least equal or where the numbers of warheads exceeded the number of vehicles. Following this date, the deliverable yield of the strategic bomber leg of the US triad was estimated in accordance with the formula mentioned above, using data from Collins (1980, 1985), Cochran et al. (1984), the Annual Report of the Secretary of Defense (various years), SIPRI (various years), and IISS (various years). Yet, it was still necessary to make a number of relatively minor assumptions to reflect changes in the mix of nuclear weapons. For instance, while the number of B-52s remained relatively constant over time, the number of warheads each plane could carry greatly increased. In addition, the conversion of a number of B-52s (approximately 100) into airlaunched cruise missile (ALCM) carriers greatly increased their effective range and lowered their CEP. The following assumptions were made about the payloads of the B-52: • • • •

before 1972, B-52c and B-52g/h carried 4 X 1Mt bombs each; between 1972 and 1989, B-52c still carried 4 X 1Mt bombs; between 1972 and 1982 B-52g/h carried 4 X 400kt Short Range Attack Missiles (SRAMs) and 4 X 300kt bombs; after 1982, B-52g/h carried either - 8 X 400kt SRAMs and 4 X 300kt bombs, or - 12 X 300kt cruise missiles.

US–Soviet competition and corporate profits TABLE 5.2 US nuclear delivery vehicles, 1948–89

Source: see text.

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72 TABLE 5.3 US deliverable nuclear warheads, 1948–89

Source: see text.

US–Soviet competition and corporate profits TABLE 5.4 US total deliverable nuclear yields by triad, 1948–89

Source: see text.

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US DATA

The results for the United States are displayed in Tables 5.2, 5.3, and 5.4 for the period between 1948 and 1989. Table 5.2 presents the numbers of US nuclear capable delivery vehicles by leg of the triad and the total number of delivery vehicles. Table 5.3 displays the numbers of warheads by triad as well as the total number of warheads. Table 5.4 contains the data on the total deliverable nuclear yield of the United States, broken down by leg of the triad. Total deliverable yield was calculated according to the formula discussed above.

The Soviet Union INTERCONTINENTAL BALLISTIC MISSILES

Data for Soviet ICBMs were taken principally from Wright (1986) along with Cochran et al (1989), and updated through 1989 using SIPRI Yearbooks (various years). Data for this leg of the Soviet nuclear triad is the least controversial and there is general agreement within the literature about the capabilities of Soviet ICBMs. There is, however, some disagreement about how many of their ICBMs have been equipped with multiple reentry vehicles (MIRVs). In cases of disagreement between SIPRI and Wright, additional sources such as Collins (1980, 1985), Cochran et al (1989) or Gervasi (1986) were consulted to help resolve differences. SUBMARINE-LAUNCHED BALLISTIC MISSILES

Data for Soviet SLBMs are more difficult to collect because they have not been compiled in a single source. Data for the period 1960–69 and 1985 to the present were taken from SIPRI; data for 1970–85 came from Collins (1980, 1985). It was impossible to determine the mix of SS4N and SS5N missiles deployed; we interpolated this information based on the data in Gervasi (1986:411). It is also important to note that both SS4N and SS5N missiles are considered to be short-range nuclear missiles and are not included in many discussions of Soviet nuclear capabilities. However, they were capable of reaching the US mainland and were therefore included in our indicator. While it was possible to locate the characteristics of the three different types of SS6N missiles (Collins 1980), we could not locate the deployment mix of the three types. Therefore, we ‘simply’ took the averages of the characteristics of the three types. The same holds true for the mix of SS18N missiles. Other than these three problems, calculating the deliverable yield from Soviet SLBMs was straightforward.


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LONG-RANGE BOMBERS

The long-range bomber portion of the Soviet strategic triad presented significant problems for estimation. Prior to the early 1960s, there is very little reliable information concerning the yield, size, or accuracy of Soviet nuclear gravity bombs. This uncertainty is compounded by the fact that there was a considerably greater number of available delivery vehicles than warheads for the first ten years of the Soviet nuclear weapons program. The most consistent estimation of the numbers of Soviet long-range nuclear-capable bombers came from Cochran et al. (1989). We employed their estimates for the numbers of nuclear-capable bomber delivery vehicles, although care was taken to check his estimates against those of Gervasi (1986), Collins (1980), and both SIPRI and IISS whenever possible. The payload estimates were based on Cochran estimates as well; however, rather than assume that each bomber was equipped only with nuclear gravity bombs (an assumption that substantially increases the number of bomber-based nuclear warheads), we assumed that the types of nuclear weapons deployed in the Soviet bomber force were equally split between gravity bombs and air-surface cruise missiles. This assumption decreases the total number of bomber-based warheads, but does not dramatically affect total deliverable fire power, since planes equipped with cruise missiles have a greater range. The yields of the nuclear gravity bombs were estimated to be 200kt and the CEPs of bomber-based nuclear gravity bombs were estimated to be 500 meters. For the years after 1960, data on delivery vehicle and warhead characteristics were taken primarily from Crawford (1986), and secondarily from Collins (1980, 1985) and Gervasi (1986). Delivery vehicle and warhead data for the period from 1985 to the present came from IISS and SIPRI. SOVIET DATA

The data collected for the Soviet Union are displayed in Tables 5.5, 5.6, and 5.7. Table 5.5 contains the total number of Soviet delivery vehicles, along with the breakdown by sections of the triad. Table 5.6 contains information about the numbers of Soviet warheads broken down in the same manner. The total deliverable nuclear yield of the Soviet Union is displayed in Table 5.7. This yield information was calculated using the formula described above.


76 TABLE 5.5 Soviet nuclear delivery vehicles, 1948–89

Source: see text.

US–Soviet competition and corporate profits TABLE 5.6 Soviet deliverable nuclear warheads, 1948–89

Source: see text.

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TABLE 5.7 Soviet total deliverable nuclear yields by triad, 1948–89

Source: see text.


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Comparison of US and Soviet nuclear capabilities Since the data were collected in a contextually comparable fashion we believe that the US and the Soviet data are directly comparable, even though we recognize that these data are not perfect. Figure 5.1 directly compares the total numbers of US and Soviet delivery vehicles since 1948. The figure clearly shows how the US first developed and deployed nuclear weapons in large numbers, typically about a decade before the Soviets could match these efforts. By the mid-1970s, however, the Soviets ‘caught up’ with the US and went on to deploy about 20 percent more total delivery vehicles than the US. However, comparing only delivery vehicles may be somewhat misleading. Figure 5.2 shows that, when warheads instead of delivery vehicles are compared, the Soviets have yet to catch up with the United States, although they have managed to dramatically close on the United States, and to maintain a small gap between the two for about a decade. Figure 5.3 displays additional information about the strategic competition between the United States and the Soviet Union by comparing the deliverable yield between the two. This figure clearly shows that US has always retained a lead in nuclear destructive capabilities, although the Soviets did come close

FIGURE 5.1

US and Soviet strategic delivery vehicles, 1948–88

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FIGURE 5.2

US and Soviet strategic nuclear warheads, 1948–88

FIGURE 5.3

US and Soviet deliverable nuclear firepower, 1948–88


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to parity in the late 1970s before the Reagan nuclear weapons build up. This observation supports Ward’s (1984) contention about parity at that time. The strategic arms race over the last four decades becomes even more evident in its development and its outcome if we look at Figure 5.4, which presents a logarithmic version of Figure 5.3. Not only is the rapid growth of destructive power evident for both the US and USSR, but the ‘closing of the gap’ by the Soviet Union clear stands out, as does the permanent, though diminishing, ‘lead’ of the US. Clearly the ‘numbers game’ is important, for different conclusions are evident in the different data, though these conclusions do not necessarily contradict, but rather may complement, one another. However, it is important to recognize that the goals of both Soviet and US strategic planning have changed markedly over the past four decades, and may change more in the near future. Obvious changes have involved targeting strategies, which have tended to undergird the importance of accuracy and lower megatonnage. Beyond that, readers should recognize that we have sidestepped entirely an important arena of nuclear firepower: battlefield weapons. This aspect of war fighting technology has a very thin line separating nuclear with nonnuclear options and it too has grown in importance over time. Finally, we have ignored two other important aspects of strategic competition. The first FIGURE 5.4

Log of US and Soviet deliverable nuclear firepower, 11948–88

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of these is the area of readiness. We do not have readiness estimates for weapon systems, even though we know that these have been recently revised by US intelligence experts for the Soviet Union, for example. This revision tells us two things: first, that it is fairly problematic to gain entirely credible information about the readiness of weapon systems in hypothetical situations; second, that this is adjudged to be a fairly important aspect of strategic competition. The second area we ignored is that of chemical weaponry. In the next section, however, we do turn to an evaluation of conventional military capabilities.

CONVENTIONAL CAPABILITIES Lambelet (1973) was the first social scientist to develop and apply a systematic approach to measuring conventional military capabilities, though many have followed in his footsteps and those of Dupuy (1980). His approach was an elegant one that combines firepower with manpower and mobility. He developed data for the US–Soviet competition from 1948 through 1970, and his data were replicated forward to 1978 by Ward. In this effort we bring those conventional data forward to the present, resolving a few issues on the way. Once again, because of the tensions associated with the cold war, it was not possible to collect information on Soviet conventional weapons stocks much before 1970. Therefore we chose to combine current data on conventional capabilities with Lambelet’s previous index of capabilities. Accordingly, we collected information on three different types of conventional weapons: heavy and medium tanks, attack helicopters and combat aircraft. The information collected is shown in Table 5.8 and was taken from Collins (1980, 1985) and the IISS. As displayed in Figure 5.5, the Soviet Union has developed and maintained to the present an impressive array of conventional warfighting capabilities far in excess of US capabilities. If we analyze this in terms of market endowments, wherein the US has been relatively efficient at producing nuclear capabilities, the Soviet Union has exploited its own endowments to produce conventional capabilities. Thus, overall assessments of the ‘total’ military capabilities will be influenced by the weight associated with conventional versus nuclear firepower.

US–Soviet competition and corporate profits TABLE 5.8 US and Soviet conventional capabilities, i970–88

Note: Estimated via linear interpolation. Sources: 1970–75, Collins 1980; 1975–84, Collins 1985; 1985–88, IISS 1985–89.

FIGURE 5.5

US and Soviet conventional capabilities index, 1948–88

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PAYING THE BILL While the above descriptions give important consideration to military stockpiles, following the earlier efforts of McCubbins (1983), Baugh (1984), and Ward (1984), it is clear that most of the scholarly writing on the military competition between the superpowers has focused on spending patterns. McGinnis and Williams (1989) provide a good example of this. It may be that the bottom line of paying for the military is the paramount consideration in maintaining the competition. Toward that end we briefly look at how all that destructive power, both conventional and nuclear, is purchased. US military expenditures The data on US military spending are displayed in Table A3 in the Appendix to this volume. The total defense budget is portrayed in its four component parts: personnel costs, operations and maintenance, procurement, and research and development. Table 5.9 presents both total defense spending and the strategic component of the military budget. Figure 5.6 graphs the data displayed in Table 5.9, which were taken primarily from the Historian of the Department of Defense. It is important to note that the manner in which the Department of Defense categorizes defense spending has undergone some FIGURE 5.6

US total and strategic defense spending, 1950–88


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TABLE 5.9 US strategic military spending, 1950–89 (current US$ bn)

Sources: Historian of the Department of Defense (unpublished report) and Annual Report of the Secretary of Defense (US Department of Defense, various years).

fundamental changes over time and the data for strategic spending may reflect some bias which results from the modification of accounting procedures. Figure 5.6 makes it easier to note how the strategic budget has remained relatively constant over time while the defense budget as a whole has grown rather dramatically (although the figures shown here have not been adjusted for inflation). Despite this fact, US strategic forces have shown the greatest growth, both in destructiveness and in impact on strategic thinking, when compared with conventional forces. Soviet military expenditures The level of military spending by the Soviet Union for the time period in question is the subject of considerable controversy, which the reader will be spared here. There are a wide variety of sources and conflicting estimates about the amount of money the Soviets spend on national defense. Jacobsen (1987) provides a good discussion of the associated issues. We have chosen to adopt both the estimates presented by the United States Arms Control and Disarmament Agency (ACDA) and the estimates of SIPRI. Table 5.10 contains

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TABLE 5.10 Estimates of Soviet military expenditures, 1948–87 (constant 1980 US$ millions)

Sources: SIPRI World Armaments and Disarmaments Yearbook, various years, and the US Arms Control and Disarmament Agency’s World Military Expenditures and Arms Transfers, various years.

FIGURE 5.7

Estimates of Soviet military expenditures, 1949–87


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both ACDA and SIPRI estimates of Soviet military expenditures over time in constant 1980 US dollars. Figure 5.7 graphs these data. It is clear that the ACDA estimate is 10–30 percent higher than the SIPRI estimate. We chose to present both data sources because the ACDA estimates are based on information provided by the CIA and it is these data that decision makers are most likely to rely upon when assessing the relative threat posed by the Soviet Union. We present the SIPRI series because it is generally regarded as being free from many of the political biases and considerations which may be reflected in the CIA (and thus ACDA) estimates. Both series show the rather constant growth in Soviet spending over the last two decades, a fact which may ‘explain’ their growth in nuclear firepower as well as the continued preponderance of conventional firepower. Bang for the buck The previous sections have shown how, on the one hand, both conventional and nuclear firepower have grown dramatically during the last four decades and how, on the other, military expenditures have also accelerated. However, it is not the case that there is a simple linear relationship between what is paid and what is purchased. Figure 5.8 portrays the nuclear firepower of the US and the Soviet Union as a proportion of the cumulative military spending FIGURE 5.8

Cost of nuclear firepower, 1951–88


88 FIGURE 5.9

Cost of conventional firepower, 1950–87

to that point in time. Thus, we address the question: ‘How much nuclear firepower has been purchased for a given investment?’ It is noteworthy that nuclear firepower first became relatively cheap during the 1950s for the United States, but it has become relatively more expensive to produce ever since. Soviet nuclear firepower, has, in an opposite way, become less expensive over time in a fairly steady way. During the 1980s, however, both US and Soviet ‘bang per buck’ ratios were approximately equal. Conventional ‘bang per buck’ ratios for the US and Soviet Union, as shown in Figure 5.9, contrast sharply with the nuclear picture, though our conventional indices are not ‘pure’ firepower measures. The price of conventional ‘firepower’ has shown an exponential growth, as the firepower purchased for each subsequent investment mirrors quite nicely a decline along the path of the negative exponential. This makes good sense since technology for conventional weaponry has become increasingly more sophisticated and more expensive at the same time. US economy Table 5.11 presents some data on the US economy for the time period in question, all of the data were taken from the Economic Report of the President (US President 1989), except for contract awards which were taken from the


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TABLE 5.11 Selected corporate indicators for the United States, 1948–88 (current US$ bn)

Note: The Dow-Jones Industrial Average reflects 30 common stock prices; Moody’s reflects average bond yields; Total Industrial Production Index, 1977=100. Sources: Economic Report of the President 1989; contract awards taken from the Statistical Abstract of the United States (US D Department of Commerce, various years).


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Statistical Abstract of the United States (US Department of Commerce, various years). These data focus on the defense sector and the overall economic health of the corporate sector in the United States. A wider variety of economic data are presented in Table A. 1 in the Appendix to this volume. We do not quite have the hubris to attempt a quick summary of 40 years of US economic history here. The relationship between military spending and economic growth, however, has continued to be a topic of considerable debate, with much effort focused on uncovering the relationship between military spending and investment on the one hand and investment and growth on the other. Bootleg translations of Sony’s Morita’s evaluation of the United States suggest that he feels that ‘long-term’ (by which is meant a decade) investment goes up in the United States only when defense spending is climbing, because it is only under the guarantee of long-term (military) procurement that US entrepreneurs were willing/able to make long-term (as opposed to short-term) investments in the product cycle. More systematic evidence (e.g. Mintz and Huang 1989) convincingly demonstrates that long-term investment is driven down by military spending; it is clear that in the US the policy makers use the deficit to ‘refinance’ a sizable portion of the military spending/ investment tradeoff. That refinancing has significant implications for the profitability of defense contracting. CORPORATE PROFITS FOR MAJOR DEFENSE CONTRACTORS

Annual net income data were collected for ten major defense contractors from Moody’s Industrial Manual and then summed together to create an index of defense industry corporate profits. The ten defense contractors that were chosen to make up this index were selected on the basis of their position among the top 200 defense contractors in fiscal year 1985 according to Kitfield (1986). We chose the ten largest defense contractors on the basis of sales. General Electric and Western Electric were not included because defense contracts make up a small portion of their total sales and Hughes Aircraft was not included because it did not file a copy of its annual report with the Securities and Exchange Commission. Therefore Grumman, Textron, and Northrop were added to the original list often, provided here with 1985 total Department of Defense sales1: 1 2 3 4 5 6 7

McDonnell Douglas ($8.95 bn) General Dynamics ($7.57 bn) Rockwell International ($6.26 bn) Boeing ($5.42 bn) Lockheed ($5.06 bn) United Technologies ($3.92 bn) Raytheon ($2.99 bn)


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8 Martin Marietta ($2.74 bn) 9 Grumman ($2.74 bn) 10 Textron ($1.95 bn) Table 5.12 displays the annual net income for five of the ten companies plus the total annual sum of the ten companies. The yearly totals for the profits of these ten defense contractors are displayed in Figure 5.10, which shows that corporate profits increased dramatically from the mid-1970s through 1988. Figure 5.11 displays the percentage change in the index over time, excluding the data for a major loss reported by Lockheed in 1961. The average percentage change in the defense industry index is 20.61 percent, and 11.02 percent if 1962 is not included. Figure 5.12 displays the cumulative sum of the index over the entire time period. The high profitability of the defense industry is obvious in the United States at least; Mintz (1988:14) reports that a survey of US business in the 1970s indicated that defense industries were about 35 percent more profitable (compared to assets) than non-defense industries. It is often argued that, since defense is a risky business, the greater risk ‘ought’ to be balanced out by higher profits. A look at the overall profitability suggests that even risk-averse corporations have done very well by investing in

FIGURE 5.10

Annual corporate profits for ten major defense contractors, 1948–88


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TABLE 5.12 Annual net income for major defense contractors, 1948–89 (current US$ m.)

Source: Moody’s Industrial Manual, various years.

US–Soviet competition and corporate profits FIGURE 5.11

Percentage change in corporate profits for defense contractors, 1949–88

FIGURE 5.12

Cumulative sum of corporate profits for defense contractors, 1948–88

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defense. Whether the clarion call for spending the so-called ‘peace dividend’ in non-defense areas will change all of this is very much an open question. Melman (1985, 1988), Ridell (1988), and Smith (1977) have all written about the links between capitalism and the military and have provided guidance to much of the debate about ‘conversion.’ The Soviet economy Despite considerable recent criticism of its inefficiency and predictions of its imminent demise, the centrally planned economy of the Soviet Union has until recently been generally effective in insuring a modicum of economic growth, almost full employment, a standard of living that is rising slowly, but rising nonetheless, and an artificially low rate of price inflation. It has after all managed to support the expansion and growth of the world’s largest conventional military and the development of strategic nuclear capabilities which have reached a relative parity with the US. Table 5.13 presents average annual growth rates for Soviet GNP by sector. Whether one accepts the official Soviet or the CIA estimates, Soviet economic performance has been much stronger over the period 1950–80 than often portrayed. However, this does not imply that the Soviet economic system is competing effectively with the OECD nations. Consider that, between 1960 and 1973, Japan’s labor productivity increased an average of 9.9 percent per annum, while the Soviet Union’s labor productivity increased only 3.7 percent. The trends in labor and capital productivity are compared in Table 5.14. Assessing the current economic performance of the Soviet Union is complex and there are quite a number of measurement problems when attempting to compare the Soviet economy with that of other contemporary societies. For instance, the Soviet Union has a fairly large shadow or alternative economy that is not subject to formal control or legislation, making accurate statistics

TABLE 5.13 Average annual percentage growth rate of Soviet GNP, 1951–80

Source: US Congress, Joint Economic Committee 1982: viii, 15, 26.


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TABLE 5.14 Comparative trends in labor and capital productivity 1960–78

Source: Cohen 1983:173.

impossible to obtain. Compounding such problems are difficulties associated with converting values from the official exchange rates to free, fluctuating hard currencies. Thus, evaluating the impact of the defense burden on the Soviet economy is difficult, although economists generally acknowledge that the effects of the Soviet defense burden have been deleterious to the rest of the economy (see Lane 1985; or Bond and Levine 1983). Several possible effects of the defense burden on the Soviet economy have been put forth: (1) the allocation of resources to defense comes at the expense of investment and hastened the decline in capital productivity; (2) military procurement is also given priority for supplies, exacerbating material shortages and bottlenecks for the rest of the economy; and (3) the military burden may also have reduced investment levels and diverted machinery output from consumer to military production. These negative effects of the defense burden on the Soviet economy are compounded by the fact that the economic base of the Soviet Union is considerably smaller than that of the United States, yet the Soviet Union’s level of military spending is similar in scope to or even exceeds that of the United States. One interpretation of recent Soviet arms control and conventional force reduction initiatives rests on the premise that the negative tradeoff of the defense burden on the economy is great. Accordingly, this idea posits that the Soviets have accepted relative nuclear parity and conventional superiority in order to redirect productive capacity from defense sectors to consumption-oriented sectors. This has certain plausibility but ignores the long-term structural goals made by Soviet defense planners in the Soviet (as well as the US) system. We have a clear picture neither of the long-term changes of the arms race nor of the resilience of defense interests in the Soviet Union.


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ASSESSING DETENTE Measures of the dyadic interactions between the US and the Soviet Union over the time period in question were also included in order to provide additional information about the state of relations among the superpowers. Data for both conflict and cooperation variables were created by summing the scaled values of Azar’s (1980) Conflict and Peace Data Bank (COPDAB) data set and supplemented by Dieter Ruloff. The aggregated data are displayed in Table 5.15. A measure of net tension was created for each nation by subtracting the amount of cooperation sent to the other from the amount of conflict sent to the other. These raw measures of tension between the two nations are displayed in Figure 5.13. It shows that there has been a considerable relaxation of tension among the two over time, although there have been mutual increases in tension occasionally, most recently during the late 1970s and early 1980s. A display of the first differences of the tension indicators for the two nations (not shown) reveals that there is clearly a decline in the fluctuations over time. FIGURE 5.13

US–Soviet tension levels, 1948–86

US–Soviet competition and corporate profits TABLE 5.15 Conflict and cooperation among the superpowers, 1948–86

Source: Azar’s (1980) Conflict and Peace Data Bank, as updated by Dieter Ruloff.

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SUMMARY AND RECAPITULATION •

•

There has been enormous growth in the risky business of producing military might over the last four decades, as seen in the capabilities of both the US and the Soviet Union. There is clear evidence of a nuclear arms race that has been in place for four decades, although the current climate (1990) may call into question its subsequent longevity. In particular, — the Soviet Union has caught up with and surpassed the US in the area of delivery vehicles, after a fairly slow start; — the US has maintained a lead in warheads, although the Soviet Union now has approximately the same trajectory for production of nuclear warheads as does the US; and, importantly, — there is evidence that, in terms of deliverable, nuclear firepower, the US has maintained a clear lead over the Soviet Union over the past 40 years, with the exception of a short period at the end of the 1970s during which the gap was substantially reduced prior to the rapid military buildup in the United States during the 1980s.

•

•

•

•

•

•

On the conventional side of the equation, the Soviet Union has maintained a substantial advantage over the United States over the last four decades, an advantage couched primarily in terms of both tanks and manpower. In order to accomplish the acceleration of nuclear and conventional capabilities, the Soviet Union has been active in promoting higher defense spending each year during most of the past 40 years. This level of spending on the military has had important impacts in reducing long-term investment in the United States and, more critically, in the Soviet Union. US defense spending shows marked ebbs and flows, but the decade of the 1980s has seen a rapid acceleration in spending that only now is beginning to recede in direct response to Soviet ‘disengagement.’ Nuclear firepower has become cheaper for the Soviet Union and more expensive for the US, while conventional firepower has become more expensive for both. The profitability of the defense sector of the US economy has been maintained at substantial levels over the past four decades; it now accounts for about a twentieth of the US GNP. Doubtless, a similar commandeering of productive economic resources has occurred in the Soviet Union.

One conclusion that many have drawn is that the system of nuclear terror and deterrence has succeeded in preventing a military conflict between two


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long-term rivals, the United States and the Soviet Union. Brzezinski’s Game Plan (1986) provides one such ready conclusion. While, if we ignore the personal impact of Gorbachev, we may agree with Brzezinski that the Soviet Union is a one-dimensional (i.e. military) rival of the United States, and while we may also agree with McGinnis and Williams (1989) that the superpower rivalry is fairly impervious to changes in the existing level of threat, our descriptive survey of the military, political, and economic evidence leads us to another set of ‘ready’ conclusions. In particular, we believe that there was an arms race between the US and the Soviet Union between the early 1950s and the late 1970s. At that time, the Soviet Union’s mounting investment had succeeded in bringing it to a position of relative nuclear parity with the United States, ranging from warhead, to delivery systems, to nuclear firepower. Much like the so-called ‘power transition’ theories of Organski and Kugler (1980) suggest, the approach of the so-called challenger energized the US to devote greater resources to this nuclear race. The Reagan military buildup began yet another round of the arms race. The trajectories of military stockpiles in the 1980s retrace, albeit at substantially higher levels, the trajectories of the 1950s. By the end of the 1980s it was apparent that the US was again in a superordinate position militarily. Gorbachev’s broad initiatives may be seen as a partial response to that reality. To the risky business of deterrence has been added the risky business of recalibrating one large and one sizable economy that have both been partially dominated by a defense sector that is increasingly dysfunctional, if the arguments of Kennedy (1987) and Goldstein (1988) are to be given substantial weight. Further, we note that, if we are in an era in which dramatic reductions are being made by the Soviet Union, it presents an interesting opportunity for the United States to respond in kind. However, are there any reasons to suspect that the so-called ‘peace dividend’ might not be delivered? Utilizing the data collated and described above we probed this question using a heuristic methodology known as vector autoregression.2 In the first instance we find heuristic, statistical evidence to support the claim that the corporate profits of the defense industry are largely driven by military spending in the United States.3 This does not occur at the aggregate level, but rather turns up when military expenditures are broken down into their component parts. In particular, we find strong evidence that operation and maintenance expenditures are unrelated to corporate profits, but that there is a clear link between research and development, personnel expenditures, and procurement expenditures and the level of corporate profits over a period of about four years. In the second instance, we find that in the short run (lags of a couple of years) and the medium term (lags of six or more years) corporate


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profits actually tend to drive US military spending at the aggregate level. Thus, there is evidence of a feedback process that links corporate profits to defense spending through the component expenditures, a process that appears to put overall pressure back on the defense budget at the aggregate level. Further analysis suggested that, in addition to these two aspects of the feedback between defense spending and corporate defense profits, further linkages were visible. In particular, Soviet conflict with the United States tends to drive up Soviet military expenditures as well as stimulate US research and development budgets, which along with US defense spending tends to stimulate procurement budgets. This set of linkages also suggests a nexus of security interrelationships which promote military spending in the presence of conflict. This may be seen to further accelerate research and development programs which are directly tied to corporate profits, which in turn place pressure on the overall defense budget. While the positive feedback between the military research and procurement programs and the profitability of defense contracting appears to have ineluctably fueled the rapid accumulation of military hardware (at increasing costs) during the 1960s, 1970s, and 1980s, the 1990s may prove to be an entirely new decade, if its beginning is a guide. It may be possible to find the ‘peace dividend’ in current US—Soviet relations, but it is clear that the financial stakes are quite salient and cannot afford to be overlooked. The process of producing ‘national security’ is a risky business, not only for the lethality of the instruments with which it is supported and extended, but also for the risk attendant on the huge investments already sunk into this industry by some of the largest corporations in the world, investments which heretofore have proven quite profitable.

NOTES This material is partially based upon work supported by the National Science Foundation under Grant No. SES-8910820. The government has certain rights in this material. This research was conducted at the Program on Political and Economic Change, Institute of Behavioral Science and the Center for International Relations, Department of Political Science, University of Colorado, Boulder, Colorado, USA, 80309–0487. Todd Sandier made helpful comments on an earlier version of this manuscript. 1 2 3

Typically about 90 percent of sales come from procurement for most defense concerns. Details on this technique may be found in Freeman, Williams, and Lin (1989). We only summarize these findings here. Interested readers may request the full statistical results from the authors.


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REFERENCES Azar, E.E. 1980. The Conflict and Peace Data Bank (COPDAB) Project. Journal of Conflict Resolution 24:142–52. Baugh, W.H. 1984. The Politics of Nuclear Balance. New York: Longman. Bond, D.L., and Levine, H.S. 1983. An overview. In A. Bergson and H.S.Levine (eds), The Soviet Economy: Toward the Year 2000. London: Allen & Unwin. Brzezinski, Z. 1986. Game Plan: A Geo-strategic Framework for the Conduct of the U.S.– Soviet Contest. Boston, MA: Atlantic Monthly Press. Cochran, T.B., Arkin, W.M., and Hoenig, M.M. 1984. Nuclear Weapons Databook: Vol IU.S. Nuclear Forces and Capabilities. Cambridge, MA: Ballinger. Cochran, T.B., Arkin, W.M., Norris, R.S., and Sands, J.I. 1989. Nuclear Weapons Databook: Vol IV–Soviet Nuclear Weapons. Cambridge, MA: Ballinger. Cohen, S.H. 1983. Sources of low productivity in Soviet capital investment. In Soviet Economy in the 1980s: Problems and Prospects. US Congress Joint Economic Committee. Washington, DC: US Government Printing Office. Collins, J.M. 1980. U.S–Soviet Military Balance: 1960–1980. New York: McGraw-Hill. Collins, J.M. 1985. US–Soviet Military Balance: 1980–1985. Washington, DC: PergamonBassey’s. Crawford, N. 1986. World Weapons Database: Vol. II—Soviet Aircraft. Lexington, MA: Lexington Books. Dupuy, T.N. 1980. The Almanac of World Military Power. San Rafael, CA: Presidio Press. Freeman, J.R., Williams, J.T., and Lin, Tse-min. 1989. Vector autoregression and the study of politics. American Journal of Political Science 33:842–77. Gervasi, T. 1986. The Myth of Soviet Military Supremacy. New York: Harper & Row. Goldstein, J.S. 1988. Long Cycles: Prosperity and War in the Modern Age. New Haven, CT: Yale University Press. International Institute for Strategic Studies. Various years. The Military Balance. London. Jacobsen, C.G. 1987. The Soviet Defense Enigma: Estimating Costs and Burden. Stockholm: Stockholm International Peace Research Institute. Jones, L.S. 1970. U.S. Bombers: B1-B70. Los Angeles, CA: Aero Publishers, Inc. Kennedy, P. 1987. The Rise and Fall of the Great Powers. New York: Random House. Kitfield, J. 1986. The best of times, worst of times. Military Logistics Forum 3:6–13. Lambelet, J.C. 1973. Toward a dynamic two-theater model of the East—West arms race. Journal of Peace Science 1:1–37. Lane, D. 1985. Soviet Economy and Society. New York: New York University Press. McCubbins, M. 1983. The policy components of arms competition. American Journal of Political Science 27:485–514. McGinnis, M.D. and Williams, J.T. 1989. Change and stability in superpower rivalry. American Political Science Review 83:1101–23.

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Melman, S. 1985. The Permanent War Economy. New York: Simon & Schuster. Melman, S. 1988. Economic consequences of the arms race: the second-rate economy. American Economic Review: Papers and Proceedings of the One-Hundredth Annual Meetings 78: 55–9. Mintz, A. 1988. The Politics of Resource Allocation in the U.S. Department of Defense: International Crises and Domestic Constraints. Boulder, CO: Westview. Mintz, A. and Huang, C. 1989. Guns versus butter: the indirect link. Unpublished manuscript. College Station: Texas A&M University. Moody’s Industrial Manual. Various years. New York: Moody’s Investor Service. Organski, A.F.K. and Kugler, J. 1980. The War Ledger. Chicago: University of Chicago Press. Ostrom, C.W. Jr. 1978. A reactive linkage model of the U.S. defense expenditure policymaking process. American Political Science Review 72:941–57. Ridel, T. 1988. U.S. military power, the terms of trade, and the profit rate. American Economic Review: Papers and Proceedings of the One-Hundredth Annual Meetings 78:61–5. Rosenberg, D.A. 1982. US Nuclear Stockpile, 1945 to 1950. The Bulletin of Atomic Scientists 38: 25–30. Smith, R. 1977. Military expenditure and capitalism. Cambridge Journal of Economics 1:61– 76. Stockholm International Peace Research Institute. Various years. World Armaments and Disarmament Yearbook. Stockholm. US Congress, Joint Economic Committee. 1982. USSR: Measures of Economic Growth and Development, 1950–1980. Washington, DC: US Congress. US Department of Commerce. Various years. Statistical Abstract of the United States. Washington, DC: US Government Printing Office. US Department of Defense. Various years. The Annual Report of the Secretary of Defense. Washington, DC: US Government Printing Office. US Department of Defense. Unpublished report of the Historian of the Department of Defense. Washington, DC: Department of Defense. US President and the Council of Economic Advisers. 1989. Economic Report of the President, together with The Annual Report of the Council of Economic Advisers. Washington, DC: US Government Printing Office. Ward, M.D. 1984. Differential paths to parity: a study of the contemporary arms race. American Political Science Review 78:297–317. Wright, B. 1986. World Weapons Database: Vol. I— Soviet Missiles. Lexington, MA: Lexington Books.

CHAPTER 6

On the Domestic Political-Economic Sources of American Military Spending Thomas R.Cusack

Many commentators agree that Ronald Reagan’s tenure in the White House was marked by some major shifts in American domestic and foreign policies and governmental priorities. Such courses of action as the cutback in tax rates, substantial restraint on domestic programs and spending, and vast infusion of funds into the military sector, were some of the principal policy initiatives we associate with the Reagan administration. It is my contention that, at least with respect to the last-named example, the Reagan policy represents nothing more than ‘politics as usual.’ That is to say, while dramatic in terms of the quantities of money involved in the ‘Reagan defense buildup,’ the policy was simply a continuation of past practice, one which reflected certain typical responses to a set of conditions that has come to play a major role in shaping American military spending practices. The first section of the chapter provides some background. Here the development of the American military effort in the post-World War II era is presented. Included as well are some details on the scope of the changes in the structure of the federal budget brought about by Reagan’s practice of military Keynesianism. In the second section the American experience is examined from the perspective of whether it must be viewed as an exceptional case in terms of the defense burden that it has carried relative to other industrialized democracies. An argument is made and empirical evidence provided which suggest that this exceptionalism exists only in that the US is singular in terms of the scope of the military effort; on a theoretical level it conforms with a general pattern that arises from a state’s position in international hierarchy and its domestic political-economic arrangements. 103

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The third section briefly surveys some of the many schools of thought on the dynamic forces driving the American military effort. This area has been the subject of extensive theoretical and empirical effort over the last decades. A number of fundamentally different positions can be discerned here and the purpose of this discussion is not to extensively review the strengths and weaknesses of each, but rather to place in context the argument that follows in the succeeding section. The fourth section focuses on one of these schools and a particular model therein; it examines the debate that has developed around this model, and provides a further empirical evaluation of the model’s performance. The general argument is that domestic political and economic factors are critical in the determination of the US defense effort. The model outlined and tested here derives from some early work with which I have been involved (Nincic and Cusack 1979), and represents an effort at shoring up some of the weaknesses of that earlier effort as well as demonstrating the robustness of the argument. The last section of this chapter draws together some of the principal arguments and findings and attempts to point out some of the theoretical and practical implications that derive therefrom.

THE PATTERN OF AMERICAN MILITARY EFFORT IN THE POST-WORLD WAR II ERA At no time during the post-World War II period can it be said that the United States has been particularly hesitant to allocate significant sums of money to the defense sector. Nonetheless, there have been major swings in the total amounts of money spent and the significance of these outlays relative to the income at the disposal of the American government and people. Figures 6.1a and 6.1b chart the evolution of the US defense effort using two different indicators. In Figure 6.1a, the total spent in real (base year 1982) dollars is plotted on a calendar year basis from 1948 through 1986. Parallelling this, in Figure 6.1b, the defense burden, representing military spending as a percentage of gross domestic product, is plotted. An early surge in both the level of spending and the burden it imposed on the economy is evident with the onset of the Korean war. While both values dropped with the winding down of that war, quite high levels, relative to previous peacetime periods, were sustained through the 1950s, the height of the cold war. The mobilization for the Vietnam war in the mid-1960s propelled spending upwards in real terms, but, as a percentage of gross domestic product, the strain it put on the economy represented a smaller relative cost than anything sustained during all but the last year of the Eisenhower administration. Withdrawal from Vietnam, with the concomitant disinclination to finance further adventures of that sort, brought about a return to spending levels

Political-economic sources of military spending FIGURE 6.1b

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US defense burden, 1948–86

Sources: Data on defense spending derive from the Economic Report of the President, 1987. Data on the GDP price index, used to deflate the expenditure term, derive from IMF, International Financial Statistics Yearbook, various issues.

FIGURE 6.1a

US military spending, 194128–86

Source: Data on gross domestic product are taken from IMF, International Financial Statistics Yearbook, various issues.

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that in real terms, through most of the 1970s, were quite on a par with the outlays sustained during the peak of the cold war in the 1950s. Yet, and despite the sluggish overall economic growth of this period, the defense burden declined significantly until the middle of the Carter administration. Then one detects the seeds of a reversal in the pattern for both variables by this time. Real outlays began to move up significantly, and indeed by 1986 stood well above any year in the post-World War II period. The drain this represented on the economy began to grow as well, though not at such a rapid rate. By 1986, however, the share of gross domestic product going to the military had advanced to levels matching those of the last years of the Vietnam war. What sort of impact did the Reagan administration have on the budgetary situation of the federal government and what did this mean for the economy as a whole? Figures 6.2a and 6.2b provide a graphic portrayal of the consequences of the Reagan administration’s policies. Entering office, the administration inherited a situation where less than one-fourth of the federal budget was given over to national defense. The Carter administration had laid the groundwork for increasing the level of defense spending at a significant rate, but this was revised radically upward in the Reagan budgets and culminated in fiscal year 1988 with nearly 29 percent of the budget allocated to defense. All this took place against a backdrop of major changes in the revenue-raising activities of the federal government where, particularly in terms of personal and corporate taxes, rates were significantly lowered. As Figure 6.3 demonstrates, the impact was to drive the fiscal imbalance into a continuous deficit of large proportions and significantly raise both the federal debt and the burden of interest payments (the latter rose from less than 9 percent of the budget to 14 percent during these eight years). Bonds and rockets would seem to have been the legacy of the Reagan administration, with the combined burden of defense and interest payments rising from 31.6 to 42.8 percent of the budget. When viewed from a long-term perspective, however, the Reagan changes do not seem sui generis. Thus, while total federal debt in nominal terms has reached a historically high level, the burden it represents on the economy, as reflected in the debt relative to GNP, has not even reached the levels of the 1950s (see Figure 6.4). And the composition of the budget by the end of Reagan’s two terms is more in keeping with the distribution of federal outlays that held in the late 1950s and early 1960s than the budget it inherited from the Carter administration. By 1988 (see Figure 6.5), national defense, international affairs, and veterans administration outlays, along with interest payments (due mainly to the debt incurred in order to finance earlier military outlays) accounted for well over 40 percent of the federal budget. This figure is about equal to that which obtained in the last years of the Vietnam war. In

Political-economic sources of military spending FIGURE 6.2a

Federal budget shares: pre-Reagan (fiscal year 1980)

FIGURE 6.2b

Federal budget shares: end of Reagan administration (fiscal year 1988)

Source: Tax Foundation 1988.

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108 FIGURE 6.3

US federal surplus (+)/deficit (-), 1950–86

FIGURE 6.4

Federal debt and the economy, 1950–88 (end of fiscal years)

Source: Tax Foundation 1988.

Political-economic sources of military spending FIGURE 6.5

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The evolution of federal budget shares, 1950–88 (fiscal years)

Source: Time series data derived from Tax Foundation 1988

some significant ways, then, the Reagan administration’s general priorities represented a return to past practices and not a major new direction in American public policy. Moreover, the way in which the DoD (Department of Defense) budget was allocated across functional areas during the Reagan administrations began to take on old forms (see Figure 6.6). Significantly, in terms of its impact on industry and the capital goods sector of the economy, defense spending was more and more shifted toward the procurement of goods and the financing of research and development.1 During the Cold war era, more than 40 percent of DoD funds were spent in these two categories. Withdrawal from Vietnam and the restraint that this placed on defense spending as well as the higher costs associated with the new all-volunteer personnel policies (along with the continuously growing burden of financing pensions for retired long-term service members) placed significant strains on the budget. Thus, the share of the budget allocated to procurement and R&D had diminished to less than 30 percent by the mid-1970s. This had risen slightly to close to 32 percent by 1980. By 1986, the two items combined once again took up more than 40 percent of the DoD budget. In terms of both its general priorities and the emphasis it gave to particular elements of the defense budget, the Reagan administration represented no major evolutionary deviation from the traditions established through much of the post-World War II era. In the next section the bases of this tradition are examined from a cross-national perspective.

110 FIGURE 6.6

I: CYCLES IN MILITARY SPENDING Distribution of Defense Department budget across major functional categories, 1953–86 (fiscal year basis)

Source: Time series data derived from Tax Foundation 1988.

THE AMERICAN PATTERN IN INTERNATIONAL CONTEXT How different is the American pattern from that of countries most similar to it in terms of political and economic structures? As Table 6.1 demonstrates, the military burden sustained by the Americans has been very different from that of other industrialized democracies. While the trends in this burden have generally moved along parallel paths, the levels have been far from one another. While a general increase took place in the defense burdens borne by the industrialized democracies during the 1950s, the overall pattern from 1960 through 1980 was one of general decline. Countries within NATO have carried, on average, larger burdens (between one and a half and two times as large as non-NATO industrialized democracies), but amongst these states there also has been a downward trend which only halted in the 1980s. The military burden the Americans have shouldered has always been far heavier than that of their NATO allies and other industrialized democracies. Since the Korean war, the Americans have shouldered a military burden approximately twice as large as their NATO allies and from three to four times the burden sustained by the non-NATO industrialized democracies. However, it too has waxed through the Cold war and waned in the immediate post-Vietnam war era. The general acceleration in defense effort amongst the

Political-economic sources of military spending

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TABLE 6.1 Defense burdens amongst the Western industrialized countries, 1950–85

Note: The figures for the US are slightly different from values deriving from American sources. Source: Derived from Stockholm International Peace Research Institute, World Armaments and Disarmament Yearbook, various issues.

NATO allies was most pronounced in the American case, with the defense burden growing from 5.4 percent to 7.0 percent by 1985. It is often argued that the large defense effort by America, relative to its formal and informal allies, represents a form of free-riding by the latter or exploitation by the latter of the former (see Olson and Zeckhauser 1966). Indeed, a recent assertion on the part of the Pentagon suggests that more than half of the American defense effort represents a direct subsidy to the West European states for military burdens they are unwilling and yet able to sustain (Calleo 1987). Such arguments seem particularly self-serving and downright misleading. America has played the role of hegemon within the world system for the decades since World War II. Its military apparatus plays a significant role in retaining American domination. That it does more in this sphere than those linked to it by political and economic ties does not need an explanation based on misplaced economistic reasoning; the benefits it derives are proportionate to its efforts, and those efforts, absent domestic constraints

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and stimuli, are likely to be proportionate to its relative strength in the international political economic system. But domestic political-economic constraints and stimuli are not unimportant. Indeed, they have a powerful influence on how much the United States and its allies are willing to sustain in the way of military burdens. The argument here draws heavily on Michael Kalecki’s (1943) classic paper on the problems of government demand management policies in market economies. As Kalecki has pointed out, there are three strong grounds on which capitalists object to the use of fiscal policy as an instrument to secure full employment and stable growth. These include a general dislike of government interference in markets—particularly labor markets—because this undermines the basic strength of capitalist classes vis-à-vis labor. Second, public investment outside traditional spheres of the ‘nightwatchman’ state or for purposes that might directly compete with the capitalist classes represents a threat to their societal position. Third, the social and political consequences that arise from the maintenance of full employment challenge the power of the capitalists by removing one of their major weapons: the disciplinary regimen of unfettered labor markets. Weakened vis-à-vis the working class, the capacity of the capitalists to withstand the demands of labor would have untoward effects on them personally and would, from their perspective, undermine the normal and, to them, beneficial workings of the capitalist system. Nonetheless, Kalecki argued capital is not so short-sighted as to fail to eventually appreciate the benefits to the capitalist system that government intervention can produce. So long as this intervention does not undermine the political and economic position of the class, then that class will not lose its confidence and threaten the political-economic stability of state and society. If the direction of government policy is not to achieve permanent full employment but simply to alleviate slumps, and if the instruments used neither compete with nor threaten the interests of capital, then it will support governmental stabilization policies. This rather restricts the latitude of government and, according to Kalecki, the obvious focus of such policy is spending on the military. Such a solution is clearly not only limited to such an extreme form of capitalist society wherein labor is rendered completely powerless. Indeed, one would expect that the degree to which labor plays a central role in the bargaining processes whereby the overall shape of the political economy takes form and is reproduced would act to constrain government and business and thus militate against military Keynesianism. Capitalist societies in the post-war period have been marked by a broad range of power-sharing structures amongst capital, labor, and government. The differences in these structures are likely to have had an influence on the form of stabilization and employment policies and this is likely to be revealed in


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the scope of military Keynesianism. Certainly, the United States stands within a subgrouping of such states where labor has been relatively weak, disorganized, and possessing very limited access to the centers of politicaleconomic power. This factor ought to explain part of the variance in the cross-national distribution of military burdens and would thus partially account for America’s extraordinarily high military expenditure burden. At least one other facet of the domestic political-economic situation might also play a significant role in accounting for the weight of military burdens taken on by states. This is the extent to which labor has managed to capture the control of government—at least in formal parliamentary terms. The efforts by labor as manifested in leftist parties to obtain a voice in the running of the political system has led it through a difficult if not tortuous path during the twentieth century. For a variety of reasons it is not the obvious majority within bourgeois democratic systems (Przeworski and Sprague 1986). The success it has achieved should, given the general anti-militaristic stance of the left in capitalist societies, act as a constraint on the military burden that governments would impose on the economy. However, as Keman (1982) has pointed out, it is possible to entertain a set of diverse hypotheses with respect to the influence that party preferences and dominance have on military spending. Thus he argues that there are sufficient reasons to suspect the validity of the ‘traditional’ view that rightist parties are heavily oriented toward security concerns while leftists are anti-militaristic, and that such stances may not work their way through to defense policy outcomes. There is, for example, the argument that the ‘decline of ideology’ has led to a convergence between parties at different ends of the left-right continuum even in security matters. Just as plausible is the ‘strategic’ hypothesis that leftist parties when in power would view it as in their interest to support the military establishment in an effort to be perceived as sound and legitimate in the eyes of the middleclass electorate. Relative to rightist parties, then, leftist parties in government would tend to opt for higher military burdens, other things being equal. An assessment of the role these three factors—international economic strength, the extent to which labor participates in power-sharing arrangements for the direction of the economy, and the scope of labor’s dominance in the political system—is provided below. Here the results from a regression analysis based on cross-sectional data using military burden in 1980 as the dependent variable are reported upon. Within the equation, economic strength is captured by the relative volume of GDP.2 Labor’s strength in the political-economic sphere is tapped by an index of corporatism, provided by Pryor (1988).3 Left control of government is captured by Cameron’s (1984) index for the control of government by leftist parties. Based on a very limited sample of 16 cases, these results, though obviously tentative, clearly reveal an interesting pattern. The relative international economic strength variable takes on the predicted

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sign and is statistically significant. Per the military Keynesianism argument, corporatism appears to act as a restraint on the military burden governments are willing to sustain; the statistical effect estimated is negative and significant. Finally, left dominance of government would appear to invoke a ‘strategic’ response to the problem of allocating resources to the military. The estimated effect of left dominance is to increase the overall defense burden; the estimated coefficient is also significant.

Relative to other industrialized democracies, the United States carries a heavy military burden. In part this reflects the dominant position of the United States inside the international system. But it also reflects the domestic political-economic character of the American system. The weakness of Labor in the bargaining needed to regulate and reproduce the workings of the capitalist system has the effect of channelling significant government intervention for stabilization purposes along lines that favor the militaryindustrial sector. Apparently, though, the fact that labor has also been incapable of generating strong political party organization and consequent governmental presence has had the effect of lowering the relative military burden that the US sustains.

THE DYNAMICS OF AMERICAN MILITARY SPENDING: INTERNAL VS EXTERNAL SOURCES In the effort to understand the forces shaping the dynamics of American military spending, analysts have been prone to rely mainly on one or another general approach. The approach with the lengthiest history focuses on external conditions and generally is cast within an ‘arms race’ framework. Richardson’s


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(1960) system of equations is the basis of most of the models employed within this tradition. On the other hand, a fair number of analysts have argued that the roots of arms spending reside in internal factors. Early on the dominant tendency here was to focus on bureaucratic and organizational politics schemes as frameworks for accounting for the movement in defense spending. This emphasis on internal factors began to shift focus later as developments within other areas of public policy analysis began to demonstrate the utility of political-economic theoretical structures. As one important review (Russett 1983) of this literature has noted, the purely external model of the Richardson sort has not met with a tremendous amount of success in accounting for the dynamics of US military spending. There have been efforts to further elaborate on this approach over the last decade and some measure of success has been achieved, particularly when the model has incorporated within it a richer set of constituent elements and more plausibly based theoretical justification in terms of the putative decision-making processes that are argued to produce the outcomes of interest. One of the first attempts at placing the defense spending question within a framework where the entire budgetary decision-making process is represented was that by Fischer and Crecine (1979). Using a ‘top-down’ approach to the budgetary process that allowed the constraints implied in fiscal authorities’ own preferences and the pressures from competing spending authorities to come into play, they found that there was little evidence to suggest that US defense spending responded in a ‘fine-tuned fashion to marginal changes in Soviet activities’ (1979:36). Later work by Fischer and Kamlet (1984), however, modified this conclusion. Using the ‘Competing Aspiration Levels Model’ (CALM), which allows for both ‘top-down’ and ‘bottom-up’ influences within the overall budgetary process to manifest themselves, they found evidence to the effect that marginal changes in Soviet defense spending did work themselves through to influence American military spending decisions in a way consistent with the Richardson action-reaction model (1984:366). Still later efforts have provided some supportive and some contradictory evidence. Further support within a structurally rich modelling framework (Ostrom and Marra 1986), wherein contemporaneous estimates of the great undefinable, Soviet military spending levels, were employed, demonstrated American decision makers’ sensitivity to Soviet efforts when finalizing US military spending levels. Kiefer’s (1988) long-term analysis of American federal budgetary behavior, however, found little support for the actionreaction perspective. Furthermore, an effort to employ a sophisticated representation of the weapons-stock and budgetary interactions inherent to a competitive arms process between the United States and Soviet Union

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once again brought forward the counter-intuitive result that suggests the US may be responsive to Soviet efforts but in a disarming sort of way (Ward 1984). Some of my own work (Cusack 1981, 1985, 1988) has attempted to combine these two innovations in the area of defense budget analysis. This work has relied on the CALM framework, deriving from the Carnegie-Mellon analysts, and used a combination of physical capability indices and budgetary concepts. It has also attempted to integrate a representation of the changing structure of international threats that confront policy makers (Deutsch and Singer 1964; Russett 1983) as well as some of the concerns for domestic political-economic problems that constrain budgetary decision makers (Frey 1978; Nincic and Cusack 1979). This model has been applied successfully to an extensive number of Western industrialized democracies, including the United States (1988), as well as to a very mixed sample of states that included not only Western industrialized democracies, but Third World and communist states (Cusack 1985). One of the central findings that emerged from both studies was that the potential threat to a state’s security manifested in the conjunction of the behavior and capabilities of other states appears to be a significant stimulative factor for many states in the determination of budgetary outcomes. At least as critical, if not more so, however, was the apparently strong and controlling influence that fiscal authorities’ and their concerns for demand management have on shaping both the overall budget as well as defense spending.

A POLITICAL-ECONOMIC MODEL OF AMERICAN MILITARY SPENDING Background Some time ago, Miroslav Nincic and I (Nincic and Cusack 1979) advanced the idea that some of the primary forces shaping the size of the American military establishment stand outside of the usually cited factors of (1) external conditions (e.g. the Soviet ‘threat,’ engagement in ‘hot’ wars, etc.) and (2) bureaucratic inertia, the two dominant models in use. We suggested that a significant element in shaping the defense budget derived from domestic political-economic problems confronting governing elites. There were two central points to our argument. On the one hand, it was hypothesized that, in advanced capitalistic societies, an active fiscal policy was necessary but would be tightly constrained and channelled. If it were to preserve the interests of the entrenched and powerful, and not undermine itself by using the Keynesian weapon of demand management by


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government in system destructive ways (i.e. social spending and entitlements which would loosen the ties that bind the great majority of people to the discipline of the labor market), then government would have to rely heavily on military spending as a fiscal policy instrument. This instrument has the ‘appealing’ qualities of being neither redistributive in an egalitarian way nor capable of enhancing the level of social citizenship. On the other hand, we argued, extending the Zurich public choice school thesis, that military spending would also be subject to the kinds of manipulations favored by politicians through the course of the ‘electoral cycle.’ That is, we conjectured that ‘critical moments’ in the electoral calendar would prompt ‘pumppriming’ or greater military spending as an election approached and the reigning party sought to assure its future tenure in office. Our effort was innovative to the extent that we brought together these two strands of political-economic reasoning and that we attempted to loosely formalize and test them against empirical data. On the whole we were sufficiently impressed with the results of the latter, which suggested that, by prevailing standards, they had not been disconfirmed. Since that time a number of other studies have examined this question from a variety of perspectives. On the whole, the conclusions that have been drawn represent a fairly mixed picture. On the negative side, Ted Goertzel (1985) reports but does not provide very persuasive proof to substantiate his conclusion that the ‘evidence shows…that fluctuations designed to influence the business cycle have only a minor effect on military spending patterns’ in the United States. His analysis focuses on revenues and competing expenditure items and seeks to show that defense is (a) a weak contender in the competition for scarce federal resources, and (b) one that can acquire, for a limited period, greater resources when international events appear (in the public imagination) to threaten the security of the United States.4 Gert Krell (1981), in a long and detailed recounting of post-World War II economic tendencies within the US, has attempted to evaluate the plausibility of what he describes as three ‘economistic’ models of American military spending. These included (1) the military-industrial complex notion, (2) the capitalist growth imperative idea, and (3) our argument with respect to the impact of economic stabilization and the electoral cycle. Eschewing any econometric techniques and employing a variety of graphic and verbal illustrations, he concludes that each of these arguments is ‘inadequate.’ Michael Wallace (1980) also examined the question in an attempt to evaluate directly the relative impact of exogenous and endogenous influences on defense spending and concluded that ‘[n]either presidential elections nor unemployment appear to have any significant impact at all’ on US military spending. Harold Jacobson’s (1985) interesting paper on public opinion and American military force structure does not

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directly examine the question but provides a succinct statement to a contrary view: ‘There is no evidence to support a claim that the federal government increases military spending so as to improve economic conditions in election years’ (1985:12). Perhaps the most exhaustive critical examination of the thesis can be found in Gary Zuk and Nancy Woodbury’s Journal of Conflict Resolution article in 1986. From other work, by Thompson and Zuk, they suggest that the notion of politically manipulated business cycles is not supported.5 More relevant to the present concerns they focus on the determinants of American military spending. Here they adopted a different methodology than our own and employed different operationalizations of a number of variables. Sub-stantively, they argue that the use of the aggregate demand term in the original model is problematic. Therefore, they use unemployment as a measure of the need for stabilization activity. They also argue that the relationship between presidential electoral cycle and defense spending is spurious because both are associated with serious international dispute involvement on the part of the United States. Finally they suggest that electoral cycle effects should only show up during an election year. On the methodological side, they point out that the technique we employed may be inappropriate and they themselves employ an alternative, namely Box-Jenkins time series analysis. As a result they found little if no evidence to suggest that military spending is ‘used on a systematic basis by the president or Congress as a macroeconomic policy instrument and, by extension, not used for the purpose of winning elections,’ On the other side, there have been a number of studies with findings generally supportive of our position. Michael Ward and I (Cusack and Ward 1981), in examining alternative models of defense spending, replicated the results of the original analysis for a slightly longer period (originally Nincic and I looked at the period from 1948 to 1976; Ward and I extended it to 1978 and found that the original results held). Griffin et al. (1982:8, 10-11) came to generally similar conclusions as to the effects of stabilization concerns (‘in the U.S., military outlays (as a percentage of GNP) do appear to be employed as a counter-cyclical instrument by the state…’) and the electoral cycle (elections increase defense as a share of GNP). A similar conclusion was reached by Alex Mintz and Alexander Hicks (1984): first with respect to the electoral cycle (‘elected state officials apparently use defense spending on the remuneration of military and civilian personnel of the U.S. Department of Defense to insure their reelection’) and second with respect to stabilization concerns (unemployment shown to stimulate defense expenditures). Mintz’s (1988) detailed analysis of DoD resource allocation patterns is also generally supportive of the importance of electoral cycle and stabilization policy concerns on defense outlays.


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A reformulation and test In the main, I am still confident that the thesis Miroslav Nincic and I advanced earlier has more than a modicum of validity. My later work in this area (Cusack 1985, 1988) has depended in part on it, and has attempted to fashion a synthesis of it and some other important elements, particularly with respect to the budgetary decision-making process and the way in which international forces impinge on that process. I think, however, it is worthwhile going back to examine the ideas once more and particularly with an eye to attempting to rectify some of the problems others have raised (Zuk and Woodbury 1986) and also to attempt to bring into the model an important element, public opinion, that was not explicitly incorporated originally. The original model postulated that changes in American military spending were significantly contingent on three domestic political-economic factors: the presidential electoral cycle, stabilization policy concerns, and bureaucratic momentum. In addition, the mobilization for active involvement in largescale international conflict (viz. the Korean and Vietnam wars) was also held to play an important role in shaping changes in American military outlays. Estimating the model for the period 1948 through 1976, using total military outlays, and then disaggregating these and using outlays on personnel and on procurement, respectively, it was found that the overall fit of the model was quite good and that the estimated parameters of the model took on the predicted signs and were generally significant. As noted above, replicating this for a slightly longer period (1948–78) proved an equally successful undertaking. A reexamination is in order. Three reasons substantiate this claim. First, another eight years of data are available and it is a reasonable expectation to have of any model that it can deal adequately with a broader sample of observations than that on which it was originally estimated. Second, five of these new data points fall within a period of time during which the Reagan administration can be said to have had effective control of the determination of the defense budget. If, as argued above, this administration’s policies in the military area really conform to the post-World War II American tradition, then the model ought to continue to perform adequately for these years. Third, this undertaking permits the introduction of some improvements to the model, improvements which are consistent with the basic theoretical thrust of the argument and improvements which rectify some of the methodological weaknesses endemic to earlier efforts at estimation. Instead of formulating the model in terms of first differences, it is specified in the form of a lagged adjustment process. Thus, a set of exogenous variables are postulated as determining a target level of defense expenditures:

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As with most social systems, adjustment between actual and desired levels is not likely to be instantaneous. Therefore, the relationship that should hold between these two variables should take on the following form:

with the parameter, a, representing the rate at which existing levels of defense outlays adjust to the desired value over the period. The advantage of this form is that it leads to more readily interpretable coefficients than the form used previously and implicitly incorporates in a substantively meaningful way the workings of bureaucratic and other forms of inertia that we awkwardly attempted to include in our previous specification. With this type of specification, then, the bureaucratic inertia term is implicitly included. Turning to the electoral cycle variable, one of the putative determinants of the desired and actual level of defense outlays, it seemed appropriate, given the availability of public opinion data tapping voter support, to go beyond the simple type of dummy variable formulation previously used by us and others. Work by Frey and others also suggested that an electoral cycle term wherein not only time but also the majority or minority position of the administration in terms of popular support would be a superior indicator. Thus, included in the specification of the desired level of defense expenditures is a term that captures the influence of presidential electoral concerns (ELECP) in the following way: the distance between a desired (better yet, required) level of public support and the actual level of support is weighted by the time to the next presidential election. The notion here is that the administration knows that it needs to achieve a majority of public support but that its concern for the level of performance it has with respect to public support will increase the closer it comes to an election. In operational terms this was captured by taking the ratio of two terms, the constant of 50 percent to the base of the present level of public support for the President as measured in the Gallup polls, and then raising this ratio to the power of another ratio, the constant 1 divided by the integer representing the number of years to the next presidential election. In terms of economic stabilization concerns, the original model used the change in aggregate demand. Though Zuk and Woodbury’s suggestion that this term is inappropriate seems unfounded, there is a lot to be said for relying on the unemployment term that most other analysts have tended to use. It has a relatively straightforward interpretation and is perhaps of more salience to public officials. Therefore, the present specification substitutes the percentage unemployment (UNEMP) variable in the place of the change in aggregate demand term. The final term in the original model was meant to


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represent the influence of wartime mobilization (WARIND, decribed below). Zuk and Woodbury cricitize the use of a generic variable to capture the effects of two different wars, but on the face of it this is not a terribly compelling argument. That aside, given data limitations it will be possible to estimate the model for the period 1953 through 1986. In effect, this means that only one year of the Korean experience, 1953, is included in the sample. This ought to limit any putatively deleterious effects from such a specification. Plots of the electoral pressure term, ELECP, and the unemployment term, UNEMP, are presented in Figures 6.7 and 6.8, respectively. Finally, two terms representing manifestations of public concern for areas of national life have been added to the model. The first term, EMIP, measures the extent to which the public expresses concern with economic affairs. To the extent that our thesis is correct that American public officials see a public acceptance in the use of military spending as a palliative for economic problems, one would expect that they would be prone to increase defense expenditures as the public manifests increasing concern with economic questions. A second public opinion variable, FMIP, capturing the extent to which the public is concerned with foreign affairs, ought to capture a number of influences that analysts have argued to exist within the American framework. The post-World War II trends in public opinion’s sense of the important problems confronting the nation are charted in Figure 6.9. Harold Jacobson (1985), for example sees defense spending decisions as FIGURE 6.7

Electoral pressure (function of time to election and electoral support), 1950–86

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FIGURE 6.8

US unemployment rate, 1950–86 (annual averages)

FIGURE 6.9

American public opinion: country’s most important problem, 1948–86


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very sensitive to public opinion. In another analysis of US defense spending decisions, Ostrom and Marra (1986) have also demonstrated its centrality. Through this factor, some of the exogenous influences of the external environment may also be captured. Taking these terms together, then, the desired level of defense expenditures can be specified as follows:

Using a double log transformation, the equation was estimated for the period 1953 through 1986. Given the presence of a lagged endogenous variable in the equation, a series of steps needs to be followed. Hibbs (1974) has

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demonstrated that a dynamic model such as the one above, which incorporates a lagged endogenous variable, cannot be estimated with OLS since the combination of the lagged variable and autocorrelated disturbances produces biased and inconsistent estimates of the parameters. Nor is a direct application of pseudo generalized least squares warranted either. Hibbs has shown that the use of an extended form of instrumental variables procedure can secure consistent and efficient pseudo GLS estimates with an equation similar to that above, i.e. one of the following form:

The technique involves four stages. First, the systematic component of the lagged endogenous variable must be created. This is done by using OLS on a model with the lagged endogenous variable set as a function of exogenous instrumental variables, viz.

The results of this provide an estimate of the systematic component of the lagged endogenous variable,

This systematic element is employed in the second stage to generate consistent estimates of the original model’s parameters, which is done by substituting for the lagged endogenous variable its ‘purified counterpart’ in another OLS regression:

The third stage combines the original data and model specification with the consistent estimates of the parameters for the purified counterpart of the lagged endogenous variable and the exogenous variables developed in the second stage to generate estimates of the original disturbance term, ut:

These can be used to determine the structure of any autoregressive–moving average process peculiar to the error term and allow the estimation of the coefficients of that process. In the fourth stage the variables in the original model are transformed in light of the estimated structure and coefficients of the time dependence in the


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disturbances, and the pseudo GLS estimates of the model’s parameters estimated. In the case of the present model, evidence of a second-order autoregressive process was detected. This entailed the need for the following general transformation to the data:

The final estimation results for the equation are reported below. With respect to the estimated parameter values related to variables from the original model, all take on signs that were expected and are generally significant, although the value for the electoral pressure term is significant at only the .10 level. Both of the public opinion concern variables have estimated parameters that are positive and significant, suggesting that public worries not only about foreign affairs but also about domestic economic problems are seen as signals to the administration to stimulate defense spending.

By themselves, the estimated parameters do not directly convey information on the nature of the relationships between the independent and dependent variables. They can best be evaluated by transforming them back to the elasticities and constant specified in the desired defense equation and into the adjustment term specified in adjustment process equation. The values of these parameters, after the appropriate transformations, are detailed below:

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In terms of desired military spending, then, the expectations regarding the influence of the electoral cycle and stabilization policy concerns are substantiated to a fair degree. The elasticity on the electoral cycle term, ß1, is greater than unity and thereby suggests a strong sensitivity to electoral pressures with a tendency for the administration to seek greater military outlays during periods when its support is below a majority level and a presidential election is approaching. Stabilization policy concerns are also evident. The elasticity on the unemployment term, P2, is approximately one and indicative of a desire on the part of administrations to match any increase in unemployment with a corresponding increase in defense outlays. As noted above, the parameters, P3 and P4, both of public opinion concern variables take on positive values. However, both are less than unity and indicative of a somewhat less sensitive response to these stimuli on the part of decision makers. Nonetheless, they indicate that decision makers see not only public concern for foreign affairs but also public worries about domestic economic problems as signalling the need for a response on their part by increasing the targeted defense spending levels. As expected, the elasticity on the war mobilization term, ß5, takes on the correct sign and suggests a highly sensitive response to war involvement in decision makers’ objectives with respect to military outlays. The estimated adjustment term, ␭, takes on a value of 0.092. This indicates that the authorities’ target with respect to defense outlays is met with a response that accords with the direction that they wish military spending to move but that the rate of adjustment is quite slow. Thus, by way of example, if spending at t–1 were $100 billion, and the target that arose was $110 billion for year t, then the change between t–1 and t would equal 1.009 billion, i.e. spending in year t would equal slightly more than $101 billion. In effect, the bureaucratic and other forms of political inertia within the system would appear to be fairly strong. Not only have the estimated parameter values generally proven significant and in conformity with expectations, but the entire equation appears to do very well in tracking actual defense spending over the last three decades. The adjusted R2 is quite high: 90 per cent. The actual and predicted values are charted in Figure 6.10. In sum, the evidence would once again seem to suggest that there is indeed support for the idea that domestic political-economic factors play a not

Political-economic sources of military spending FIGURE 6.10

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Predicted and actual defense expenditures, 1953–86

unimportant role in the determination of American military spending patterns. While some other analysts have been quick, perhaps too quick, to reject this hypothesis, there still seems ample reason to entertain the notion that American national security policy is not being driven exclusively by threats from a hostile environment and is indeed tightly constrained by developments and structures that are quite domestic in content.

CONCLUSION There were many facets to the Reagan Revolution. One of the most salient has been the tremendous upsurge in resources devoted to the military sector. Was this policy a break with traditional patterns (one interpretation of the term revolution), or was it simply a continuation of (or return to) past practice? Examining resource allocation patterns, both from the perspective of the federal budget as a whole as well as from the perspective of the functional distribution of military outlays, the Reagan administration seems to have stayed within the mold or, better yet, returned to the traditional ways other administrations have carried on their business in the Cold War era. Why does America spend so much, relative to others, on the military? An increasingly popular argument is that it is being exploited by its formal and


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informal allies who have gotten into the habit of shirking their rightful burdens. An alternative interpretation would suggest that, given America’s hegemony and the domestic political-economic constraints that operate on such an advanced capitalist system, the burden that it shoulders is perfectly understandable. In particular, the need for government to act in some way to stabilize the economy, when combined with the relatively weak position of American labor, makes defense one of the main props of any demand management policy and therefore enlarges the share of societal resources public authorities will allocate to it. There are more than a few competing claims about the nature of the forces shaping the dynamics of American military spending. Conventional wisdom sees the US as responding directly to a growing Soviet threat. But most analyses based on this vision have produced null or contrary results. This chapter has examined an alternative argument that has probably many more opponents than proponents. The argument suggests that there are powerful domestic political-economic forces shaping the defense budget, in particular the tendency to rely on it as a tool of fiscal policy and to exploit it for electoral purposes. The analysis conducted here lends a measure of support to that argument. Given that this argument was originally formulated and tested for a period prior to the Reagan administration, its successful performance for the Reagan era suggests once more that the latter has not broken the mold of post-World War II American policy but simply continued the practices of the past.

NOTES 1

Although defense spending rose very significantly between 1977 and 1985, its employment effects were not nearly as dramatic overall and only had a significant impact in particular sectors. According to a Bureau of Labor Statistics report (Henry and Oliver 1987), defense-related employment modestly increased from 5.309 million to 5.498 million between 1977 and 1980, and then rose by more than 20 percent to 6.680 million by 1985. There was barely any change in defense-related public employment during this period—amongst either civilians or the armed forces. In the private sector, defense-related employment increased by about 300,000 between 1977 and 1980 (1.913 to 2.214 million) and then increased by nearly 50 percent between 1980 and 1985 (2.214 to 3.207 million). Despite this private sector gain, one needs to recognize that during the period from 1977 to 1985, when defense spending as a share of GDP rose fairly steadily from 5.07 to 6.48 percent, defense-related employment as a percentage of the total labor force moved from 5.24 percent to only 5.68 percent (labor force data taken from OECD 1989). While the spending burden thus increased by nearly 28 percent, the return in terms of employment of those active in the labor market was significantly lower (the increase represented only 8 percent). Outside of the public sector, the military-related employment effects were marginal in some areas and significant in others. Between 1977 and 1985 there were slight decreases


2 3

4

5

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in both the agricultural sector and construction, -7 percent and -11 percent, respectively. Transportation, communications, and utilities as well as finance and insurance increased by 29 and 35 percent. Major increases occurred in the services (75 percent), manufacturing (75 percent) and mining (94 percent) sectors. For manufacturing, a stagnant sector of the economy, this implied that defense-related employment within the sector rose from 4.97 percent to 8.68 percent during the period. The data derive from the International Monetary Fund’s International Financial Statistics Yearbook. This index is the average value of six corporatism indices available in the literature. They derive from the work of such scholars as Schmitter, Cameron, Schmidt, Czada, Lehmbruch and Wilensky. The statistical techniques that Goertzel employed are fraught with problems. He estimated four equations singly. Together, however, they clearly compose a system of equations and ought to be estimated as such. Additionally, despite using time series, he apparently failed to check for and deal with any autocorrelated errors. Even with inappropriate techniques, he failed to substantiate his claim. When he shifts his focus to an alternative measure for defense (using ‘burden’), the results accord with his conclusion—however, his coding of ‘WARYR’ appears somewhat inconsistent. While the research cited by the authors is certainly not supportive of the political business cycle hypothesis, it is certainly clear that other researchers have provided either very strong or moderately supportive evidence for the notion (see, especially, Frey 1978; Hibbs 1987).

REFERENCES Calleo, D.P. 1987. Beyond American Hegemony. New York: Basic Books. Cameron, D.R. 1984. Social democracy, corporatism, labour quiescence and the representation of economic interest in advanced capitalist society. In J.H.Goldthorpe (ed.), Order and Conflict in Contemporary Capitalism: Studies in the Political Economy of Western European Nations. Oxford: Clarendon Press. Cusack, T.R. 1981. The sinews of power: labor and capital in the production of national military force capability. Wissenschaftszentrum Berlin, IIVG/dp 81–126. Cusack, T.R. 1985. Contention and compromise: a comparative analysis of budgetary politics. Journal of Public Policy 5 (4): 479–519. Cusack, T.R. 1988. Public expenditure decision-making: A comparative analysis. In J.A. Lybeck and and M.Henrekson (eds), Explaining The Growth of Government. Amsterdam: NorthHolland. Cusack, T.R. and Ward, M.D. 1981. Military spending in the United States, Soviet Union and the People’s Republic of China. Journal of Conflict Resolution 25 (3): 429–69. Deutsch, K.W. and Singer, D.J. 1964. Multipolar power systems and international stability. World Politics XVI: 390–406. Fischer, G.W. and Crecine, J.P. 1979. Defense budgets, fiscal policy, domestic spending and arms races: a positive model of the great budgetary tradeoffs. Paper presented at the Annual Meeting of the American Political Science Association. Fischer, G.W. and Kamlet, M.S. 1984. Explaining presidential priorities: the competing aspiration levels model of macrobudgetary decision making. American Political Science Review 78:356– 71.

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Frey, B. 1978. Modern Political Economy. Oxford: Martin Robertson. The Gallup Report. Various issues. Princeton, NJ. Goertzel, T.G. 1985. Militarism as a sociological problem: the political sociology of U.S. military spending, 1951–1983. Research in Political Sociology 1:119–39. Griffin, L.J., Wallace, M., and Devine, J. 1982. The political economy of military spending: evidence from the United States. Cambridge Journal of Economics 6:1–14. Henry, D.K. and Oliver, R.P. 1987. The defense buildup, 1977–85: effects on production and employment. Monthly Labor Review 110 (8):3-11. Hibbs, D.A. Jr 1974. Problems of statistical estimation and causal inference in time series regression models. In H.L.Costener (ed.), Sociological Methodology, 1973–74. San Francisco: Jossey-Bass. Hibbs, D.A. Jr 1987. The American Political Economy: Macroeconomic and Electoral Politics in the United States. Cambridge, MA: Harvard University Press. International Monetary Fund. Various years, International Financial Statistics Yearbook. Washington, DC: IMF. Jacobson, H.K. 1985. The determination of the United States military force posture: political processes and policy changes. Paper presented at Annual Meetings of International Studies Association, Washington, DC. Kalecki, M. 1943. Political aspects of full employment. Political Quarterly 4:322–31. Keman, H. 1982. Securing the safety of the nation-state. In F.G.Castles (ed.), The Impact of Parties: Politics and Policies in Democratic Capitalist States. London: Sage. Kiefer, D.M. 1988. A history of the U.S. federal budget and fiscal policy. Public Finance 43 (1): 113–37. Krell, G. 1981. Capitalism and armaments: business cycles and defense spending in the United States, 1945–1979. Journal of Peace Research 18:221–40. Mintz, A. 1988. The Politics of Resource Allocation in the U.S. Department of Defense: International Crises and Domestic Constraints. Boulder, CO: Westview. Mintz, A. and Hicks, A. 1984. Military Keynesianism in the United States, 1949–1976: Disaggregating military expenditures and their determination. American Journal of Sociology 90 (2): 411–17. Nincic, M. and Cusack, T.R. 1979. The political economy of US military spending. Journal of Peace Research 16:101–15. OECD. 1989. Labor Force Statistics, 1967–1987. Olsen, M. and Zeckhauser, R. 1966. An economic theory of alliances. Review of Economics and Statistics 48 (3):26-79. Ostrom, C.W. and Marra, R.F. 1986. U.S. defense spending and the Soviet estimate. American Political Science Review 80 (3):819–42. Ostrom, C.W. and Simon, D. 1984. Managing popular support: the presidential dilemma. Policy Studies Journal 12:677–90. Pryor, F.L. 1988. Corporatism as an economic system: a review essay. Journal of Comparative Economics 12:317–44.


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Przeworski, A. and Sprague, J. 1986. Paper Stones: A History of Electoral Socialism. Chicago: University of Chicago Press. Richardson, L.F. 1960. Arms and Insecurity: A Mathematical Study of the Causes and Origins of War. Pittsburgh, PA: Boxwood Press. Russett, B. 1983. International interactions and processes: the internal vs. external debate revisited. In A.W.Finifter (ed.), Political Science: The State of the Discipline. Washington, DC: American Political Science Association. Smith, T. 1985. The polls: America’s most important problems; Part I: national and international. Public Opinion Quarterly 49:264–74. Stockholm International Peace Research Institute. Various years. World Armaments and Disarmament Yearbook. Stockholm. US Department of Commerce. Various years. Statistical Abstract of the United States. Washington, DC: US Government Printing Office. US Tax Foundation. 1988. Facts and Figures on Government Finance, 1988–1989 Edition. New York: Tax Foundation, Inc. Wallace, M.D. 1980. Accounting for superpower arms spending. In P.McGowan and C.W. Kegley Jr (eds), Threats, Weapons and Foreign Policy. London: Sage. Ward, M.D. 1984. Differential paths to parity: a study of the contemporary arms race. American Political Science Review 78:297–317. Zuk, G. and Woodbury, N.R. 1986. U.S. defense spending, electoral cycles, and SovietAmerican relations. Journal of Conflict Resolution 30 (3):445–68.

PART II

The Political Economy of Military Spending and Military Action

CHAPTER 7

Military Buildup, War Escalation, and Business Confidence: Wall Street’s Reactions to the Vietnam Conflict Steve Chan

The Vietnam war was arguably the most traumatic and expensive foreign policy adventure (or, rather, misadventure) in the recent history of the US. It carried a heavy price tag in human, moral, political, and economic costs. The bills for these costs will continue to come due well into the next century. It has been estimated that the ultimate financial expense of this war for the US would be about $676 billion (Riddell 1973). Much of this estimated expense— such as in the form of future costs for veterans’ benefits and interest payments on the national debts—have yet to be borne by the American tax payers. This chapter investigates the short-term effects of the Vietnam war on business confidence in the US. I use the stock market as a barometer of this confidence. The incremental costs of the war—that is, the additional costs incurred beyond the normal expenditures of maintaining a peacetime military—are not available for the monthly units of analysis employed in this chapter. Instead, indicators such as the number of US bombing missions and ground operations are used as independent variables that reflect both the costs and the intensity of the US war effort. My purpose is to determine whether escalations (or de-escalations) in this war effort had a bullish, bearish, or insignificant impact on Wall Street.

WHY THE STOCK MARKET? The behavior of the stock market has been routinely used as a leading economic indicator by government as well as private forecasters. The stock market 135

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aggregates the judgments of diverse investors about future business profitability. Such judgments are reflected in the current prices of equity shares. Movements in these prices indicate changes in the investment community’s expectations of future business conditions. Studies have shown that changes in stock prices consistently anticipate changes in economic conditions (e.g Moore 1975; Piccini 1980). Accordingly, the movements of stock values (as well as other hedging alternatives such as commodities, collectables, precious metals, and real estate) offer a barometer of collective confidence in the current and likely future health of a political economy. Any development that increases uncertainty about this health is apt to be reflected in declining stock prices and rising values for the hedging alternatives. Adverse foreign events—such as escalating international tension or military conflict—tend to raise major doubts about a country’s political and economic future, and could therefore exercise a negative influence on the stock market. This is especially true to the extent that these events imply or forecast a significant reallocation of a society’s resources from civilian production and consumption to military production and consumption. Equity prices are usually available on a real-time basis. The major markets (e.g. New York, London, Hong Kong, Tokyo) have become increasingly interconnected (electronically as well as institutionally) in one vast global financial network, so that trading for stocks as well as commodities can now take place on a 24-hour basis around the world. Short of very rare mechanical or human errors, the reliability of these markets’ financial data is extremely high. Moreover, these data command very high face validity. The analyst is more justified in assuming that the observed behaviors of the investors represent their true feelings and beliefs, because these investors are willing to bet money to back up their convictions. In other words, the danger of contrived behavior or phony posturing is greatly reduced. Naturally, investors are not immune from making mistakes. After all, people do lose money in the market. However, whereas instances of individual follies and errors abound, the market as a whole is remarkably efficient in seeking out and adjusting to all relevant information impinging upon the future value of equity shares. This is the central contention of the so-called efficient-market hypothesis. It claims that the prices of equity shares at any given moment capture fully all currently available information, and they respond quickly and without bias to all newly available information. There is some sort of collective intelligence at work in the market. The efficient-market hypothesis has been applied to a variety of speculative markets such as betting at racetracks (e.g. Ali 1977; Asch et al. 1984, 1986; Griffith 1949; Harville 1973; McGlothlin 1956; Snyder 1978), transactions in precious metals (e.g. Solt and Swanson 1981), and, above all,

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investment in stocks and bonds. In the case of research on racetrack betting, it has been found that experts such as the official track handicappers, the odds-makers of the Daily Racing Forum, and the reporters of newspaper racing columns do not generally and consistently outperform the betting public. In fact, the odds on the tote board—reflecting the consensus sentiments of the bettors at the track —usually offer the most accurate probabilities of different horses winning the races. This sign of collective intelligence, however, does not deny the existence of individual folly—most individual gamblers are losers. More specifically, the efficient-market hypothesis refers to the distribution and use of market-relevant information. Some recent formulations (e.g. Beaver 1981; Latham 1986) consider a market as efficient in regard to a particular information set if and only if revealing this information set to all agents would not result in changes in equilibrium prices or security portfolios. This informational efficiency has traditionally been stated in three forms (Fama 1970; Lorie et al. 1985). In the weak form, the efficient-market hypothesis submits that successive changes in the security prices are statistically independent. It denies the presence of any systematic streaks or cycles in market behavior. This behavior has been described instead as a random walk or Brownian motion. Bachelier (1964) is usually given credit for being the first one to discover this phenomenon. He argued that the prices for equities are a ‘fair game’ variable; neither the buyer nor the seller could expect to make profits. In other words, as Lorie et al. (1985:55–6) put it, ‘the current price of a commodity was an unbiased estimate of its future price. Or, if each day’s expected price were subtracted from the actual price, the sum of those differences, on the average, would be zero.’ Bachelier’s observations, however, did not receive serious scholarly attention until the 1950s and 1960s with the advent of the modern computer (Boldt and Arbit 1984:23). The random behavior of security prices was first used by economists Samuelson (1965) and Mandelbrot (1963, 1966) as proof of ‘fair markets’ where all participants had equal access to pertinent information. In one of the earliest contemporary attempts to test the weak form of the efficientmarket hypothesis, Roberts (1959) found that random numbers produced patterns that were remarkably similar to the time series of actual stock prices. In another early study, Osborne (1959) discovered that the movements of stocks were like the Brownian motion in physics, where the movements of small particles suspended in solution are independent of each other. These early studies were followed by others, almost all of which tended to support the contention that market movements are unpredictable (e.g. Alexander 1961; Fama 1965a, 1965b; Godfrey et al 1964; Granger and Morgenstern 1963; Kendall 1953; Moore 1964). For instance, Moore (1964)

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found the average serial correlation between successive changes in stock prices to be an insignificant-.06, whereas looking at different stocks and years Fama (1965a) computed this serial correlation to be on the average about .03. These coefficients show the price changes of stocks to be essentially uncorrelated or to constitute a random walk. Thus, despite the widespread practice of chart-reading on Wall Street, knowledge of the history of stock prices cannot improve investment returns. The semi-strong form of the efficient-market hypothesis argues that the current prices of stock shares reflect fully public knowledge about the earning prospects of the firms in question. This knowledge is widely distributed, and is effectively incorporated into the stock prices. If sophisticated investors notice a gap between the market value of these stocks and their intrinsic value, this discrepancy will quickly disappear due to their buying or selling behavior. Therefore, the market is extremely efficient in correcting any bias. Indeed, many studies (e.g. Ball and Brown 1968; Brenner 1979; Fama et al. 1969; Samuelson 1965; Scholes 1972; Waud 1970) have shown that the market is capable of anticipating events in the sense of making adjustments in stock prices before various public announcements (e.g. stock splits, dividend increases, buy outs, annual reports). For instance, Ball and Brown (1968) found that stock prices tended to rise during the 12 months preceding positive earnings reports and to fall for those companies reporting subsequent earnings disappointments. Similarly, Fama et al. (1969) showed that stock prices tended to rise before the announcement of splits, and that this rise was due to the reasonable expectation that stock splits would usually lead to dividend increases. As another example, Scholes (1972) discovered that large block trades tended to depress stock prices, and that this downward pressure was more due to ‘information effects’ than to ‘trading pressure.’ The relevant information effects stemmed from the knowledge that someone wanted to sell a large block of stock and the deduction from this knowledge about the (poorer) business prospects of the firm in question. Finally, in a follow-up study Dann et al. (1977) found that the market was remarkably efficient and rapid in adjusting to the implications of block trades; within 15 minutes of the sale, prices had fully reestablished their equilibrium levels. A number of recent articles have tried to distinguish anticipated from unanticipated components in news about general economic conditions or specific companies. This research considers the so-called announcement effects of a variety of information (e.g. inflation, money supply, discount rate, economic activity, or such company-specific news as dividend increases, stock splits, product sales, earnings forecasts, and new acquisitions or development plans) on stock prices and trading volumes. The results of these studies again tend to support the semi-strong form of the efficient-market


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hypothesis. For example, only unexpected changes in the discount rate, the consumer or producer price index, or money supply have an announcement effect on the market. The market also adjusts quickly to this surprise, so that virtually all the announcement effect has been incorporated in the security prices by the end of the announcement day (e.g. Morse 1982; Pearce and Roley 1985; Schwert 1981; Smirlock and Yawitz 1985; Solnik 1984; Urich and Wachtel 1981, 1984). In short, there is much evidence to support the proposition that ‘[security] prices move rapidly to reflect all that is known, anticipated, hoped, and feared about particular investment situations’ (Seligman 1978:34). The strong form of the efficient-market hypothesis argues that even specialists who may have better access to privileged information cannot consistently outperform the market. Numerous studies that compared the performance of mutual funds with that of unmanaged general stock indices such as the Standard and Poor 500 Index support this contention (e.g. Friend et al 1962, 1970; Jensen 1969; Sharpe 1965; Williamson 1972). After examining 189 mutual funds during 1952–58, Friend et al. found their performance, on the average, to be comparable to that of an unmanaged portfolio. Sharpe (1965) found that, after adjustment for risk factors and management expenses, only 11 of 34 mutual funds outperformed the Dow-Jones Industrials during 1954–63, whereas 23 did worse than this market average. This conclusion was supported by Jensen (1969), who found only 43 of 115 mutual funds did better than the market (after ‘loads’ were controlled for). Even without accounting for management ‘loads,’ the mutual funds did not statistically outperform a naive strategy of choosing a random sample of stocks for purchase and holding. Disregarding the ‘loads,’ the terminal values of these funds were, on the average, 9 percent less than a randomly selected portfolio at the end of a 10-year period. Accounting for the ‘loads,’ the mutual funds would be worse off by 15 percent. These earlier findings have received support from several more recent studies. For example, Chang and Lewellen (1984:67) remarked that ‘neither skillful market timing nor clever security selection abilities are evident in abundance in observed mutual fund return data, and the general conclusion of the prior literature that mutual funds have been unable collectively to outperform a passive investment strategy still seems valid.’ Similarly, Kon (1983) noted that ‘fund managers have no unique information regarding the formation of expectations on the returns of the market portfolio.’ Comments such as those just cited obviously are not welcome by Wall Street professionals owing to the implication that ‘prices move before their …pronouncements, which implies in turn that the pronouncements aren’t worth much’ (Seligman 1978:34). Therefore, there has been much criticism

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of the efficient-market hypothesis in periodicals such as the Financial Analysts Journal. For example, Renshaw (1984) pointed to informational inefficiencies during market panics, and argued that superior security gains could be achieved. Similarly, Groth et al. (1979) evaluated brokers’ recommendations to retail customers and found them to anticipate ‘genuine changes in investment value.’ A rather comprehensive and balanced critique of the efficient-market hypothesis was given by Boldt and Arbit (1984). They noted various inefficiencies due to the tendency of market participants to engage in groupthink, the heterogeneity of market-relevant information and the greater difficulty to assimilate the so-called slow ideas, and the selection process for portfolio managers (inclining the latter to be risk averse and to make portfolio selections with only trivial distinctions). Additionally, as noted by Lehmann and Modest (1987), the evaluation of mutual fund performances can produce rather divergent assessments depending on the benchmark chosen for comparison. Finally, there is some evidence that those with privileged or monopolistic information can profit by trading in the pertinent securities before this information becomes publicly available. Of course, the Securities and Exchange Commission has various rules that ban corporate insiders or floor specialists from such profiteering. Nevertheless, several studies have shown that it is possible for insiders and specialists to make abnormal gains (e.g. Jaffe 1974; Niederhoffer and Osborne 1966; Patell 1976). Therefore, as Lorie et al. (1985:76) have noted, ‘in its strictest sense, the strong form of the efficient market hypothesis is clearly refuted.’ The strong form of the efficient-market hypothesis is, however, less relevant to the subject of this chapter than the weak and semi-strong forms. From the weak form, we deduce that stock prices are not ‘sticky’—that is, they do not move incrementally but rather are subject to great leaps as well as free falls. Therefore, statistical attempts at trend extrapolation are not suitable for market monitoring or forecasting. Perceptions of streaks, runs, or cycles are more a figment of the chartists’ imagination than an accurate description of market behavior. Whereas these phenomena do occasionally occur, they are no less random than those experienced by gamblers at casinos. Instead, market behavior is more appropriately studied in terms of first differences. We deduce from the semi-strong form of the efficientmarket hypothesis that security prices offer a useful concurrent as well as anticipatory indicator of economic health. More accurately, they provide a barometer of the investment community’s confidence about current and future business profitability.


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MARKET SENSITIVITY TO POLITICAL EVENTS Twenty-five years ago, Holsti and North (1966:190) remarked that the financial market offers ‘readily accessible data of unquestioned authenticity reported on a daily basis, measured on an equal-interval scale, and shown to be sensitive to even minor instabilities in the international system.’ I review in this section the evidence and logic pertaining to the market’s sensitivity to domestic and foreign political events. As discussed in the last section, the efficient-market hypothesis claims that the current prices of securities reflect fully all available information. Accordingly, knowledge about the historical sequence of price changes would not enable an investor to achieve above-average gains. Even though this claim has received quite a bit of empirical support, beliefs about cycles and streaks linger among Wall Streeters. For example, Allvine and O’Neill (1980) argued that the stock market tended to follow presidential election cycles in the US. According to them, the market anticipates the pre-election stimulation of the economy by the administration, and the post-election economic contraction presided over by the winning candidate. These authors maintained that, on the average, stocks returned 21.7 percent two years prior to an election, 15 percent before an election, 3.6 percent the year after an election, and -15.2 percent the second year following. In the same vein, Herbst and Slinkman (1984) posited the existence of four-year market cycles, with peaks near the November of the presidential election year. Yet, interestingly, their results show that ‘elections in prospect seem to be more bullish than elections in retrospect’ (Herbst and Slinkman 1984:44). That is, the market gains usually take place during the period immediately before an election, whether as a result of the diminishing uncertainties about the electoral winner and his policies or as a result of optimism about the next administration. If such regularities in market behavior can withstand empirical scrutiny by other analysts, they would consistitute a major contradiction of the efficient-market hypothesis. Much less controversial and understandable has been the finding by Niederhoffer (1971) that the financial market tends to be much more volatile on days following major international developments than on randomly selected days. On specific occasions such as the Cuban Missile Crisis and the outbreak of World War I, the markets reacted adversely to the escalation of international tension (Holsti et al 1968, 1969; Holsti and North 1966). With increasing tension, the stock prices declined, and the values of the belligerents’ bonds and currencies plummeted. At the same time, commodity futures (e.g. wheat), the price of gold, and interest rates rose. On the other hand, movements toward conflict de-escalation can be accompanied by a market rebound in stock prices and a falling demand for the hedging

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alternatives (e.g. precious metals, the currencies of neutral countries). Russett and Hanson (1975) found that Wall Street seemed to welcome news of possible peace settlement during the post-1967 period of the Vietnam war. This relationship, however, was absent during the pre-1967 period of this conflict as well as for the Korean war. Finally, Chan and Bobrow (1981) found substantial evidence of the Hong Kong as well as the New York markets reacting to (as opposed to anticipating) major international events. In short, then, these studies demonstrate that the market is at least occasionally sensitive to foreign policy developments. But why should the market react to such developments? That is, what is the substantive explanation for this market sensitivity? There is, of course, a long line of Marxist or neo-Marxist arguments suggesting that somehow defense expenditures and war are bullish for an advanced capitalist society. These arguments may emphasize the need of advanced capitalist states to resort to defense or war spending as a countercyclical tool for managing economic downswings (e.g. Baran and Sweezy 1966); the existence of a power elite or cabal commonly labelled as the military-industrial complex (Melman 1970, 1974); or the imperatives of lateral pressure to expand abroad and of safeguarding overseas markets, raw materials, and investments from leftist threats. Whether belonging to the so-called instrumental Marxist school or to the structural Marxist school, the aggregate research evidence to date rather decisively rejects the validity of these propositions (Rosen 1973; Russett 1970; Russett and Hanson 1975; Sarkesian 1972; Szymanski 1973). As Krasner (1978) argued, events such as the US involvement in the Vietnam war are more suggestive of an ideological (i.e. anticommunist) motivation rather than a rational pursuit of corporate interests or even of the interests of the capitalist system as a whole. Indeed, in regard to the Vietnam war, the interviews conducted by Russett and Hanson (1975:81) ‘provide no evidence for [those] theories [suggesting] that business executives advocate heavy military spending either to prop up the economy or to provide an essential military-political insurance for overseas commercial enterprise.’ The majority of the business executives interviewed thought that US involvement in that conflict was a mistake, and only 7 percent gave ‘consequences for the U.S. economy’ as a reason for their disapproval. Among those business executives approving of the US participation in that conflict, only one gave this as a reason. Thus, Russett and Hanson (1975:88) concluded that ‘if corporate executives thought that the war benefited their economic interests, there is certainly no evidence of it here’ (emphasis in the original). If anything, there is substantial evidence suggesting that heavy defense outlays tend to have a strong negative impact on the economic performance of the advanced capitalist countries (see Chan 1985 for a review of the


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literature). The expenses of fighting a war like the one in Vietnam will drive up federal deficits and encourage inflation, thereby increasing the pressure for tax surcharges (especially if the administration is reluctant to trim its domestic spending, as Johnson was reluctant to do with respect to his ‘Great Society’ programs). Such expenses also tend to dampen investment incentives, exacerbate production bottlenecks, hurt export competitiveness, and worsen balance of payments in the long run. These tendencies are part of the public knowledge that is widely distributed within the business community. According to the efficient-market hypothesis discussed earlier, this knowledge is incorporated into its investment decisions and reflected in the security prices. It is important to distinguish between the economic impact due to the actual disbursement of war or defense expenditures on the one hand, and the economic impact of anticipatory adjustment on the part of the business community to these expenditures on the other hand. The latter impact is every bit as important as the former impact. If, for example, the business community believes that these government expenditures will hurt the economy and their respective firms’ profitability and act to prepare for this contingency (such as by withholding investments and trimming production), this collective behavior can create a momentum of its own and result in a self-fulfilling prophecy. It is partly for this reason that the security market provides a sound leading economic indicator. There is indeed evidence that US stock prices have led general economic activities in the 13 business cycles during the twentieth century (Piccini 1980). Given the importance of self-fulfilling prophecy, it is also pertinent to investigate the Vietnam war’s impact on business confidence and to treat this confidence as an important mediating variable affecting the longer-term economic costs of this war. I do not wish to imply from the above discussion that escalation of international tension will inevitably have a negative impact on the stock market. Without arguing that a foreign war will necessarily be ‘bearish’ for business, one could reasonably propose that any development that increases investment uncertainty will tend to exert a downward pressure on stock prices. Since investors are risk averse, they will demand a lower stock price (or a higher interest rate) in order to offset the increased uncertainty. Similarly, given the increased prospects of instability, investors are more willing to pay a higher price for hedging alternatives such as precious metals (e.g. gold and silver), commodities (e.g. grain futures), and the safer currencies (e.g. Swiss francs). Indeed, the balance between risk and reward provides the underlying principle that guides both empirical and prescriptive, analyses of investor behavior. The idea that the selection of security portfolios should be sensitive to the expected rate of return as well as to the risk incurred in pursuing this

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return was put forth in Markowitz’s (1952) classic article. This article provided the foundation for modern portfolio theory. According to this theory, rational risk-averse investors would choose efficient portfolios— defined to mean maximizing expected return at a given level of risk or, equivalently, minimizing expected risk at a given rate of return. Following Markowitz (1952), Sharpe (1964) developed a capital asset pricing model that again emphasizes the tradeoffs between return and risk. It shows how the prices of capital assets are determined if investors are risk averse and pursue efficient portfolios as prescribed by Markowitz’s theory. The regression beta coefficient of market movements in explaining individual stock movements was used as an indicator of the latter’s volatility, and has since then become a widely accepted measure of the risk of individual stocks or portfolios by investors as well as academicians. Later studies (e.g. Sharpe and Cooper 1972) have proved that stocks with low betas (and, therefore, low risks) tend to gain less in rising markets and lose less in falling markets. Conversely, stocks with high betas tend to exaggerate market upswings and downswings. Thus, the risk of greater value declines is offset by the potential for higher expected returns. In short, then, there is strong support for the view that risk acceptance is an important determinant of investment returns. The explanations for market sensitivity to political or economic events advanced in the last two paragraphs adopt the rather mundane perspective of people as ‘economic animals’ and ‘rational agents.’ This perspective treats investors as purposeful information processors operating under constraint (see the special October 1986 issue of the Journal of Business on this subject). It seems to me that these explanations fit with the evidence produced by the earlier studies better than those based on Marxian interpretations. Naturally, as social scientists, we cannot be satisfied with such subjective hunches. I therefore turn to an empirical evaluation of the evidence from the Vietnam war.

RESEARCH OPERATIONALIZATION Since I am interested in the general business climate rather than the profitability of individual firms, I employ the aggregate indicators of the Dow-Jones Index of 30 leading industrial companies (DJI) and the Standard and Poor Index of a larger number of 500 major companies (SP500). These indicators provide valid readings of market conditions because they constitute a large portion of the total stock value of all companies whose shares are traded on the exchanges and because they tend to move together with other stocks. Lorie et al. (1985:42) noted that the Standard and Poor Index represented about 70 percent of the value of all stocks listed on the New York Stock Exchange


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in 1980, whereas the comparable figure for the Dow-Jones Industrials was 23 percent in 1982. Moreover, these authors (1985:40) cited a study by Benjamin King, who found that over 50 percent of the price variability of individual stocks was due to market wide swings. It should be noted that the Standard and Poor Index includes 400 industrial companies, 40 utility companies, 20 transportation companies, and 40 financial companies. Whereas this broad and heterogeneous coverage is useful for monitoring overall market conditions, it is not sufficiently sensitive for investigating the differential behaviors of specific business sectors. For the latter reason, I include in my analysis not only the Dow-Jones Industrials but also the Dow-Jones Utility (DJU) and the DowJones Transportation (DJT) indices. Utility stocks are traditionally less volatile, and are thus seen as safer investments. They are also particularly sensitive to changes in the interest rate, because investors have historically held these securities for dividend yields almost in the same fashion as bonds. The transportation index used to include only railway companies. It was revised in January 1970 to encompass the airline and freight industries. Some of the companies in the airline industry (e.g. Pan American World Airways, Trans World Airlines) rely very heavily on international travel for their business revenues. As discussed previously, I use the changes in the stock indices (i.e. their first differences on a monthly basis) as my dependent variables. The size and direction of changes in the aggregate stock prices (from the last business day of each month to the last business day of the next month) reflect changes in the investment community’s expectations or assessments of the country’s economic future. The period being analyzed stretches from January 1965 to September 1970. My independent variables include the monthly readings of the number of US troops in South Vietnam (TROOP), the number of US ground operations of battalion size or larger (BATTLE), the number of US bombing missions against North Vietnam (BOMBNV), and the number of US troops killed in action (KILLED). The above independent variables are derived from Milstein (1974). It must be recognized that these independent variables not only reflect the financial and human costs of the Vietnam war (as mentioned at the beginning of this chapter, I lack the monthly figures on the incremental costs of financing the US war effort). They also capture the intensity of the war and, more indirectly, the then-unknown potential danger of further conflict escalation (perhaps to the point of involving the USSR and China). Consequently, the stock market’s reaction to changes in these independent variables should be considered to incorporate concerns with more than just the direct dollar costs of the US war effort.

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As I am interested in determining whether changes in the war effort had a tangible impact on changes in the stock market, I again take the first differences of my independent variables. However, I also employ a logarithmic transformation of these variables on the ground that the market’s reactions may not be linearly related to the war effort. As in the case of presidential popularity discussed by Mueller (1973:60), one would not expect proportionate reactions from the market in response to a rise of US battle casualties from 10 to 100 as compared to a rise of these casualties from 1010 to 1100. By adopting the log values, I am assuming that the market will initially be sensitive to relatively small increases in the war costs and efforts, but that it will be sensitive only to rather large increases in these costs and efforts as the war wears on. I do not introduce other control variables that may influence the market. My aim is to determine whether the Vietnam war tended to have a bearish, bullish, or indifferent impact on the stock prices; it is not to give a full explanation of changes in these prices. Thus, it seems quite legitimate to leave or assign the possible influence of other events and processes to the unexplained variance (or error term). This logic is similar to the argument presented by Russett and Hanson (1975:155) in an earlier analysis with the same objective. Finally, a number of studies have shown the Tet offensive in early 1968 to be a crucial watershed event in the history of the Vietnam war. The conflict dynamics were quite different before and after this event (e.g. Milstein 1974; Russett and Hanson 1975). I therefore introduce a dummy variable in the following analysis to demarcate the pre-Tet (0) and post-Tet (1) periods.

ANALYSIS RESULTS Ordinary least square (OLS) regression is used to study the relationship between changes in the US war conduct and movements in the stock market. The results are reported in Table 7.1. They include the regression slope (b), the standard error of b (SE b), the T-value and its significance, the amount of variance in the stock indices explained by the independent variables (R2), and the number of monthly cases in each equation (N). I do not report the Durbin-Watson statistic for assessing autocorrelation, because as discussed earlier, there is substantial support for the claim (of the weak form of the efficient-market hypothesis) that successive changes in stock prices are statistically independent. The results overwhelmingly support the null hypothesis that US military actions in the Vietnam war did not have a systematic influence on Wall Street.

Military buildup and business confidence TABLE 7.1 OLS regression results

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TABLE 7.1 contd.

Key: D prefix=first difference L prefix=logarithm SP500=Standard and Poor 500 DJI=Dow-Jones Industrials DJT=Dow-Jones Transportation DJU=Dow-Jones Utilities BATTLE=US ground operations of battalion size or larger BOMBNV=US bombing missions against North Vietnam KILLED=US combat deaths TROOP=US troop level in South Vietnam Note: significant at the 0.05 level.

Most equations indicate that the war variables account for extremely little variance in stock movements. Moreover, in almost all equations, the T significance tests for these variables as well as for Tet fail to meet the conventional standards of statistical confidence. The prevalence of these ‘null’ findings is the most remarkable feature of Table 7.1. In general, the first differences (D) of the war variables tend to perform slightly better than their log (L) values. There is little evidence of discrepant reactions to the Vietnam war between the more broadly based index of


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Standard and Poor 500 and the more selective ‘blue chip’ firms in industry, utility, and transportation. It is also hard to tell any differential reaction to US military actions on the part of the firms in the latter three business sectors. Among the four war variables, the D values of US bombing missions against North Vietnam seemed to have the greatest impact on Wall Street. This variable had an especially significant dampening effect on the price of the utility stocks (DJU in equation 26, which features the only instance where the T-statistic is significant at the 0.05 level). Although, as mentioned above, the regression coefficients generally fail to achieve customary levels of significance, almost all of them carry a negative sign. This pattern suggests that war escalations were much more likely to have a bearish than a bullish impact on the stock market. There is certainly little evidence to support the view that somehow the US investors were encouraged by news of conflict intensification. Relatedly, even though in no instance could the T-statistic for the dummy variable Tet meet the somewhat generous confidence level of 0.10, the b coefficient for this variable displays rather consistently a minus sign. Thus, stock prices tended to be in a down trend in the aftermath of the Viet Cong’s Tet offensive. Overall, the aggregate evidence produced in Table 7.1 offers very weak evidence of Wall Street’s sensitivity to US military actions in the Vietnam war. This pattern is congruent with the results obtained earlier by Russett and Hanson (1975), who also failed to find strong statistical relationships between stock movements on the one hand, and US battle fatalities and military escalations on the other hand. However, these authors did discover that, in the post-Tet period, Wall Street tended to react favorably to conciliatory moves (usually of a diplomatic nature) by the US as well as by the communist side. Moreover, for the Korean war, they found the market to react adversely to news of communist military escalation or victory (but not to news of US military escalation or victory). One may speculate about the possible reasons for the pattern of ‘null’ findings reported in Table 7.1. First, the exclusive focus of this study on US military actions is perhaps too narrow. The Russett and Hanson (1975) study shows that the US stock market seemed to be much more sensitive to diplomatic communications than to military escalations. Second, this same study also shows that Wall Street appeared to be more sensitive to communist actions than to US actions. Stock prices tended to rise more sharply on news of communist conciliatory moves in the post-Tet period of the Vietnam war, and to fall precipitously on news of communist military escalation or victory in the Korean war. Therefore, future research on this subject should include communist actions as an independent variable. Third, prior anticipation and knowledge might have dampened the impact

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of military actions on stock prices. For instance, the actual curtailment of US air attacks against North Vietnam would customarily follow announcements of bombing de-escalation or halt, and such announcements would be preceded by frequent news leaks and considerable expectation in the media. Accordingly, by the time the anticipated action actually came to pass, the market should already have discounted its effect. Finally, the aggregate stock indices used in this study are unable to discern the possibly discrepant reactions to the Vietnam war on the part of specific business sectors. For instance, whereas war escalation may be bullish for firms that relied heavily on sales to meet the Pentagon’s needs in Vietnam, it may be quite bearish for companies whose profitability was especially vulnerable to rising interest rates.

CONCLUSION I have sought to determine whether US military actions in the Vietnam war had any positive or negative impact on Wall Street. The results show that this impact has been rather negligible. To the extent that some limited impact can be detected, the evidence is more supportive of a negative rather than a positive influence of the war on stock prices. Among the four measures of US military actions examined, it seems that the market was most sensitive to US air attacks against North Vietnam (perhaps because this variable is most telling about the danger of further widening and intensifying the war). Nevertheless, the aggregate evidence is not sufficiently strong or consistent to sustain the proposition that the Vietnam war had an important effect on business confidence in the US during 1965–70. It is not clear whether a more refined temporal demarcation (e.g. tracking weekly and even daily price changes) or a more discriminating stock focus (e.g. analyzing the shares of those companies with a heavy dependence on defense contracts or foreign sales) could produce more evidence of the market’s sensitivity to that conflict. The efficient-market hypothesis, however, would suggest that the market’s reaction to war developments should be very rapid (perhaps in a matter of minutes), that this reaction would impound many other factors impinging on a firm’s business prospects, and that knowledge about specific war developments would probably not allow an investor to consistently achieve above-average gains. On the other hand, the currently unfolding trends of global political relaxation and military detente would likely encourage business confidence and economic productivity, and would therefore have a generally long-term positive effect on the stock market.


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NOTE I thank Alex Mintz, Rick Stoll, and Mike Ward for their comments on an earlier version of this paper. I also thank Susan McMillan who helped the collection of stock data used in this paper.

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Friend, I., Blume, M., and Crockett, J. 1970. Mutual Funds and Other Institutional Investors: A New Perspective. Washington, DC: US Government Printing Office. Friend, I., Brown, F.E., Herman, E.S., and Vickers, D. 1962. A Study of Mutual Funds. Washington, DC: US Government Printing Office. Godfrey, M.D., Granger, C.W. J., and Morgenstern, O. 1964. The random-walk hypothesis of stock market behavior. Kyklos 17:1–30. Granger, C.W.J. and Morgenstern, O. 1963. Spectral analysis of New York stock market prices. Kyklos 16:1–27. Griffith, R.M. 1949. Odds adjustments by American horse-race bettors. American Journal of Psychology 62:290–4. Groth, J.C., Lewellen, W.C., Schlarbaum, G.C., and Lease, R.C. 1979. An analysis of brokerage house securities recommendations. Financial Analysts Journal 35 (1):33–40. Harville, D.A. 1973. Assigning probabilities to the outcomes of multi-entry competitions. Journal of American Statistical Association 68:312–16. Herbst, A.F. and Slinkman, C.W. 1984. Political-economic cycles in the U.S. stock market. Financial Analysts Journal 40 (2):38–44. Holsti, O.L. and North, R.C. 1966. Comparative data from content analysis: perceptions of hostility and economic variables in the 1914 crisis. In R.L.Merritt and S.Rokkan (eds), Comparing Nations: The Use of Quantitative Data in Cross-National Research, pp. 169– 90. New Haven, CT: Yale University Press. Holsti, O.L., Brody, R.A., and North, R.C. 1969. Measuring affect and action in international re-action models: empirical materials from the 1962 Cuban crisis. In J.N.Rosenau (ed.), International Politics and Foreign Policy: A Reader in Research and Theory, pp. 679–96. New York: Free Press. Holsti, O.L., North, R.C., and Brody, R.A. 1968. Perception and action in the 1914 crisis. In J.D.Singer (ed.), Quantitative International Politics: Insights and Evidence, pp. 123–58. New York: Macmillan. Jaffe, J. 1974. The effect of regulation changes on insider trading. Bell Journal of Economics and Management Science Spring: 93–121. Jensen, M.C. 1969. Risk, the pricing of capital assets, and the evaluation of investment portfolios. Journal of Business 42:167–247. Kendall, M.G. 1953. The analysis of economic time series. Journal of Royal Statistical Society 96: 11–25. Kon, S.J. 1983. The market-timing performance of mutual fund managers. Journal of Business 56:323–47. Krasner, S.D. 1978. Defending the National Interest: Raw Materials Investments and U.S. Foreign Policy. Princeton, NJ: Princeton University Press. Latham, M. 1986. Informational efficiency and information subsets. Journal of Finance 41:39–52. Lehmann, B.N. and Modest, D.M. 1987. Mutual fund performance evaluation: a comparison of benchmarks and benchmark comparisons. Journal of Finance 42:233–65. Lorie, J.H., Dodd, P., and Kimpton, M.H. 1985. The Stock Market: Theories and Evidence. Homewood, IL: Dow Jones-Irwin. Mandelbrot, B. 1963. The variation of certain speculative prices. Journal of Business 36:394– 419.


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Mandelbrot, B. 1966. Forecasts of future prices, unbiased markets, and martingale models. Journal of Business 39:242–55. Markowitz, H.M. 1952. Portfolio selection. Journal of Finance 7:77–91. McGlothlin, W.H. 1956. Stability of choices among uncertain alternatives. American Journal of Psychology 69:605–15. Melman, S. 1970. Pentagon Capitalism: The Political Economy of War. New York: McGrawHill. Melman, S. 1974. The Permanent War Economy: American Capitalism in Decline. New York: Simon & Schuster. Milstein, J.S. 1974. Dynamics of the Vietnam War: A Quantitative Analysis and Predictive Computer Simulation. Columbus, OH: Ohio State University Press. Moore, A.B. 1964. Some characteristics of changes in common stock prices. In P.H.Cootner (ed.), The Random Character of Stock Market Prices, pp. 139–61. Cambridge, MA: MIT Press. Moore, G.H. 1975. Stock prices and the business cycle. Journal of Portfolio Management I: 59–64. Morse, D. 1982. Wall Street Journal announcements and securities markets. Financial Analysts Journal 38 (2): 69–79. Mueller,J.E. 1973. War, Presidents and Public Opinion. New York: Wiley. Niederhoffer, V. 1971. The analysis of world events and stock prices. Journal of Business 44: 193–219. Niederhoffer, V. and Osborne, M.F. 1966. Market making and reversal on the stock exchange. Journal of American Statistical Association 61:897–916. Osborne, M.E.M. 1959. Brownian motions in the stock market. Operations Research 7:145–73. Patell, J.M. 1976. Corporate forecasts of earnings per share and stock price behavior: empirical tests. Journal of Accounting Research 14:246–76. Pearce, D.K. and Roley, V.V. 1985. Stock prices and economic news. Journal of Business 58: 49–57. Piccini, R. 1980. Stock market behavior around business cycle peaks. Financial Analysts Journal 36 (4): 55–7. Renshaw, E.F. 1984. Stock market panics: a test of the efficient market hypothesis. Financial Analysts Journal 40 (3): 48–51. Riddell, T. 1973. The $676 billion quagmire. The Progressive 37:33–7. Roberts, H.V. 1959. Stock market ‘patterns’ and financial analysis: methodological suggestions. Journal of Finance 14:1–10. Rosen, S. (ed.) 1973. Testing the Theory of the Military–Industrial Complex. Lexington, MA: Heath. Russett, B.M. 1970. What Price Vigilance? The Burdens of National Defense. New Haven, CT: Yale University Press. Russett, B.M. and Hanson, E.C. 1975. Interest and Ideology: The Foreign Policy Beliefs of American Businessmen. San Francisco: Freeman. Samuelson, P.A. 1965. Proof that properly anticipated prices fluctuate randomly. Industrial Management Review 6:41–9. Sarkesian, S.C. (ed.) 1972. The Military Industrial Complex: A Reassessment. Beverly Hills, CA: Sage.

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Scholes, M.S. 1972. The market for securities: substitution versus price pressure and the effectsof information on share prices . Journal of Business 45:179–211. Schwert, G.W. 1981. The adjustment of stock prices to information about inflation. Journal of Finance 36:15–29. Sharpe, W.F. 1964. Capital asset prices: a theory of market equilibrium under conditions of risk. Journal of Finance 19:425–42. Sharpe, W.F. 1965. Risk-aversion in the stock market: some empirical evidence. Journal of Business 20:416–22. Sharpe, W.F. and Cooper, G.M. 1972. Risk-return classes of New York Exchange common stocks, 1931–1967. Financial Analysts Journal 28 (2):46–54. Seligman, D. 1978. The odds against experts. Fortune 20 November: 34. Smirlock, M. and Yawitz, J. 1985. Asset returns, discount rate changes, and market efficiency. Journal of Financed: 1141–58. Snyder, W.W. 1978. Horse racing: testing the efficient market model. Journal of Finance 33: 1109–18. Solnik, B. 1984. Stock prices and monetary variables: the international evidence. Financial Analysts Journal 40 (2): 69–73. Solt, M.E. and Swanson, P.J. 1981. On the efficiency of the markets for gold and silver. Journal of Business 54:453–78. Szymanski, A. 1973. Military spending and economic stagnation. American Journal of Sociology 79:1–14. Urich, T. and Wachtel, P. 1981. Market response to the weekly money supply announcements in the 1970s. Journal of Finance 36:1063–72. Urich, T. and Wachtel, P. 1984. The effects of inflation and money supply announcements on interest rates. Journal of Finance 39:1177–88. Waud, R.N. 1970. Public interpretation of Federal Reserve discount rate changes: evidence on the ‘announcement effect.’ Econometrica 38:231–50. Williamson, J.P. 1972. Measurement and forecasting of mutual fund performance: choosing an investment strategy. Financial Analysts Journal 28:78–84.

CHAPTER 8

The Political Economy of Military Actions: The United States and Israel Bruce Russett and Gad Barzilai

War is the health of the state. (Randolph Bourne)

Political leaders live a precarious life: the demands made always exceed the leaders’ capacity to satisfy them. They are expected to solve numerous—and contradictory—social problems, to provide employment and prosperity without inflation, and peace with strength. To prevent voters’ dissatisfaction, officials can deliver what the voters want, persuade the voters that they are delivering even if they aren’t, persuade the voters not to want what the officials cannot or do not wish to deliver, or distract the voters’ attention by creating or dealing with a new problem. Faced with high levels of popular discontent, even a democratically elected government may feel some temptation to try to divert hostility toward foreign adversaries, and may be so preoccupied with its domestic problems that it exaggerates the hostility of foreign adversaries or wishfully exaggerates its chances of cowing or defeating them.1 A variety of political-social-psychological theories assert that leaders of groups may often, and often successfully, try to divert the hostility derived from frustrations into aggressive words or acts towards outsiders (see Shaw and Wong 1988; LeVine and Campbell 1972: esp. Ch. 8). In fact, democratic governments may be more tempted to do this than would authoritarian regimes accustomed to using force or threats to repress dissent. An authoritarian government may be able to handle even serious discontent by directing its military and security forces against domestic opponents. Democratic governments, by contrast, will be loath, or unable, to suppress their citizens’ dissent harshly and vigorously. 155

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In this chapter we review theory and evidence about the short-term interactions among economic conditions, domestic politics, and the threat and use of military force internationally. This aspect of political economy has been relatively neglected in research, as compared with more familiar variants of ‘military-industrial complex’ literature. We start by reviewing theory and empirical research, chiefly on the United States but putting that work into a broader context, making possible a test of some hypotheses on conditions in Israel. We find that despite differences between the two countries, among them those regarding aspects of national security, in both the United States and Israel the proximity of elections makes a substantial contribution to explaining the frequency and timing of military actions. There is also a direct relation between the state of the economy and military action in the United States, and a more complex one in Israel. We thus are able to see how the United States experience is part of a wider phenomenon affecting democratic countries with intense security problems.

ELECTORAL POLITICS AND ECONOMIC DECLINE In a democracy the state of the economy is a major determinant of electoral success. Inflation and recession are both unpopular. Inflation might not be perceived as a political problem if all citizens’ incomes and expenses were going up at the same time—but of course they don’t. Inflation may impoverish those on fixed incomes (weak non-unionized workers, holders of fixed-rate loans or pensions), while others (unionized workers with cost-of-living contracts, debtors, or creditors with adjustable-rate loans) are enriched. It is necessary, therefore, to analyze separately the political effects of recession and inflation. For either, the recent rate of change (‘What have you done for me lately?’) matters more than some absolute state of the economy. Voters’ memories are short enough for them to look favorably on a government that has presided over a recent economic recovery even if the recovery followed a recession earlier induced by that same government. A good predictor of the governing party’s electoral fortunes is the direction and rate of change in real (that is, inflation-adjusted) national product in the year preceding the election. Moderate inflation may be tolerated so long as average money incomes go up faster. But a decline, or even only a very small improvement, in real income spells trouble. Worse yet for politicians, hard times usually have more electoral impact than do good ones. People whose living standards have declined are more likely to blame the government and society at large for their plight than those whose conditions have improved are to credit the government or society.

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In the individualistic self-perception, I can make it by myself; if I don’t, others are to blame.2 Voters of course react both to changes in their own conditions and to what they perceive as happening in the economy at large. They are not entirely self-interested, reacting also with some sense of public-spiritedness and a view of what is good for the national interest. Some analysts even conclude that ‘citizens seem to pay principal attention to the nation’s economic predicament, and comparatively little to their own’ (Kinder 1981:17). In this they react strongly to information and images in the mass media—especially television, where scenes of unemployment lines can make a powerful symbolic impact even on people who are not themselves, or their families are not, directly affected.3 Knowing voters’ sensitivity to the state of the business cycle, governments in turn try to manipulate the economy or the political calendar so as to produce the necessary popular support. In parliamentary systems, the prime minister may be able, within limits, to call an election only after the economy has been expanding. Or, in anticipation of an election date, whether fixed or discretionary, leaders can try to stimulate the economy with some combination of tax cuts, spending increases, and speed-up of government payments that might not otherwise occur until after election day. Tax increases, spending cuts, and recessions are best postponed until after election day. The business cycle affects elections, and in turn the electoral cycle produces a policy cycle of vote-oriented action. Economic conditions, however, often cannot be controlled sufficiently to insure electoral success. Fine-tuning of a complex modern economy is less than an exact science. Timing is difficult. Some policy actions, such as cutting interest rates, may work relatively quickly, but if, as in the United States, monetary policy is made by an autonomous body like the Federal Reserve Bank it may not be much affected by electoral considerations (Beck 1984). Major increases in expenditure or cuts in taxes typically require months or even years to put into effect. It may be impossible to stimulate the domestic economy without unacceptable impacts on the balance of payments. Government interventions will help some people but hurt others (for example, through creating shortages and inflation in particular sectors). Even if the chief executive knows what he wants to do, the legislature will have other ideas. Military spending may seem an especially attractive candidate for electionoriented timing, since the amounts are large and often attract support from conservatives who would not approve of additional spending for civilian purposes, and acquisitions of equipment can in some degree be hastened or delayed without much obvious security effect in peacetime. But military spending will depend heavily on the international environment, and much of

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the military budget is not subject to much short-run discretion. It may actually be easier to stretch out purchases than to hasten them for an electionyear economic boost. This seems to be the case in Israel, where funds for military expenditures tend to rise before elections, especially in the category of politically useful raises in pay for personnel in the defense establishment. In the United States, military procurement contracts have tended to rise in the months immediately preceding elections, but the actual expenditure increases are not enough to have much macroeconomic impact.4 The business cycle thus is substantially less controllable than is the policy cycle, and less predictable than the electoral cycle. Even if the economy could be reliably heated up on command, that might not provide enough support. The political pressures are great at election time: the victory of the leader or ruling party can never be certain enough, the margin of victory for the party or coalition (often reflected in the size of the parliamentary majority) never large enough. As Samuel Kernell (1986:188) says about the United States: ‘As election nears, a president will be tempted to husband even what he regards as surplus support. Accordingly, an unpopular president nearing election should come as close to resembling a single-minded popularity maximizer as one will find.’ Yet the president or prime minister needs political support all the time. In a real sense he is in a never-ending electoral campaign. Theodore Lowi (1985) talks about ‘the plebiscitary presidency,’ in which the chief executive is constantly under pressure to solve problems. Popularity with the voters is a leader’s most important resource for accomplishing any of his goals; a leader who allows that popularity to atrophy will quickly find his legislative program a casualty. In the words of an American congressional staffer, ‘When you go up to the Hill and the latest polls show Carter isn’t doing well, then there isn’t much reason for a member to go along with him’ (quoted in Jacobson 1983:179–89). A leader ‘must gain and maintain the reputation for power, in hopes that the reputation for power will produce power itself;’ he ‘must somehow mobilize the electorate in order to mobilize the elite’ (Lowi 1985:139, 165). If he can persuade others that the public is on his side (whether or not it ‘really’ is), he wins. Support for the President in the polls is fairly highly correlated over time with support for the President in Congress, especially on foreign policy (Edwards 1980: ch. 4). Popularity ratings are coin of the realm in legislativeexecutive wheeling and dealing. ‘Presidential approval ratings have created a pseudo-parliamentary situation, whereby the president faces a monthly vote of confidence…Incumbent administrations come to feel that they have no choice but to behave as if they are always in the midst of an election campaign’ (Crespi 1980:42).


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If a leader’s foreign and domestic policy is mired in immobilism and he cannot control the economy enough to quiet the political opposition, then other instruments of political management must be found. Here is where the possibility of distracting attention or diverting anger can come in—and what better target than foreigners, who don’t vote in one’s elections and may not be much liked anyway? Diversionary or scapegoating theories have a long history, with many examples that seem plausible. One instance where war was probably not expected but certainly risked, and experienced, is the Falklands/Malvinas conflict between Argentina and Britain in 1982, when economic difficulties both encouraged the Argentine junta to choose that moment to rally nationalist political support behind the regime and probably helped dissuade Margaret Thatcher from any willingness to compromise had she considered it.5 Despite plausible examples which everyone can cite, evidence for a generally operating causal connection between conflict at home and conflict abroad is still ambiguous. The reason for lack of systematic research support, however, may be less in the existence of some such phenomenon than in the lack of clear theoretical specification of the circumstances—when and how, and by whom—in which international scapegoating is likely to occur.6

RALLYING ‘ROUND THE FLAG Foreign policy is an arena in which the chief of state typically operates with the least immediate legislative constraint. ‘External constraints and conventional purposes have largely closed off the domestic scene as a field of great action. It is in foreign policy—with its inherent drama, its freedom of action, its momentous consequences—that presidential heroes are made…’ (Miroff 1976:281). Short, low-cost military actions to repel an attack are almost invariably popular, at least at their inception, as are many other kinds of assertive action or speech in foreign policy. This has come to be known as the ‘rally ’round the flag effect.’7 According to the initial formulation of the rally phenomenon, almost anything that happened in foreign affairs—whether a tough action like threatening or using force, a conciliatory action like signing a treaty, or some external shock like the Iranian seizure of hostages or the Soviet success in putting their first satellite into space—had an immediately favorable effect on the leader’s popularity. This effect is short term, typically not more than a month or two in duration, after which the leader’s popularity rating drops back to about where it was (or even below if, as in the case of the Iran hostage affair, he is unable to cope with it).

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Similar reactions have been found in Israel, where opinions about ‘government handling of the general situation’ went up very sharply for some events (the Six-Day and Yom Kippur wars, the Entebbe hostage rescue, and Sadat’s dramatic 1977 visit) and less so for other assertive or conciliatory actions, but with a very rapid fall-off subsequently (Stone 1982). The usual increase is probably the result of political and media elites’ reluctance to criticise the commander-in-chief immediately, because in national security matters there is always a substantial risk that he has access to secret information which he can selectively release so as to make a critic look foolish or even disloyal (Brody and Shapiro 1987).8 The charge of disloyalty is always a greater risk when criticizing a leader who takes forceful action against an adversary than when alleging that a leader has been too conciliatory. In one set of analyses, American presidential popularity ratings typically were boosted 4–6 percent in the short term by such manipulable elements of political drama as foreign policy speeches, conflictful behavior toward the Soviet Union, or uses of military force in Europe, the Middle East, and Central America and the Caribbean. The effect of more conciliatory acts such as diplomacy and foreign travel was less predictable, and often slightly negative (Marra, Ostrom, and Simon 1989; Ostrom and Simon 1985). The matter of a drop in popularity from seeming too conciliatory is nevertheless a controversial finding, and depends very much on the context of the action and what kind of president is taking it (see, for example, Nincic 1988). What is clear is that seeming tough rarely hurts much in the short run. Given the benefit of the doubt often accorded to a president when acting in the arcane arena of foreign affairs, manipulation of foreign crises for domestic political purposes may be less visible, and hence more legitimate, than manipulation of macroeconomic policy. Support for the use of military force against foreign adversaries nearly always becomes higher in concrete situations than it was in the abstract. When asked about hypothetical occasions to use force, most people disapprove. But their immediate reaction to an actual use of military force is almost invariably favorable. For instance, before President Johnson sent troops following the Tonkin Gulf incident, only 42 percent of the populace supported involvement in Vietnam; shortly afterward, 72 percent did so. Similarly, before it happened only 7 percent endorsed the idea of invading Cambodia; after Nixon did it, 50 percent approved (Benson 1982; Weissberg 1976:235). In Israel, 88 percent of the population say it is essential ‘to support the government in a security crisis, like war, even when one does not always agree with what it is doing’ (Arian et al. 1988:104). How does the rally effect operate in the context of elections and economic distress? Psychologists have established that American presidents’ rhetoric


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toward the Soviet Union became more simplistic (its cognitive complexity declined) in the latter half of election years (Suedfeld and Tetlock 1977; Tetlock 1985), and that a decline in cognitive complexity by leaders is in turn associated with a greater likelihood of undertaking military interventions and a reduced likelihood of concluding international agreements (Tetlock and McGuire 1985). According to Stoll (1984), post-World War II American presidents were more likely to use military force if they were seeking reelection during a developing or ongoing war—that is, when a president knew that voters would be more concerned than usual with foreign affairs, and thus more likely to hold it against him if the war went badly. A more complex study of the 1948–76 period (Ostrom and Job 1986), using data at the level of quarterly (three-month) periods, looked at presidential actions to use military force. It employed several controls for international conditions (such as international tensions, the strategic balance, and war dead); most of them were significantly related to the use offeree. But it also found that presidents were more likely to use force when the economy was experiencing inflation or unemployment and the percentage of the population considering the economy to be the ‘most important problem’ was high. Both Eisenhower and Kennedy gained popularity by taking vigorous action toward the USSR at a time when those acts diverted attention from domestic problems. The authors also found a weak (not statistically significant) tendency for use of force to be more common in the months immediately preceding a national (presidential or off-year) election. A president was especially likely to use force if his popularity rating was in the ‘critical’ 40–60 percent range rather than very high or very low—in other words, when he needed the popularity boost most. Relevant examples include Lyndon Johnson’s authorization of the bombing of Hanoi in 1966 and Jimmy Carter’s go-ahead to the botched Iran hostage rescue attempt in 1980. At high levels of public support a president has little need for a further boost; at very low levels—wounded politically, with his blood in the water— military action may call forth criticism from opponents emboldened by his vulnerability (Ostrom and Simon 1985). To be sure, these illustrations and statistical findings tell only part of the story. A national leader has only a limited amount of choice about whether and when to use military force. If an adversary acts aggressively against what would typically be considered an important national interest, the state of the domestic political economy may be only marginally relevant to decisions about how to respond. The above analyses apply only to the post-World War II era, for which the public opinion data are adequate. That era, however, does coincide with the period in which American presidents, as leaders of a global superpower, have acquired the ability as commander-in-chief to use military force quickly and without consultation.

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Selected examples must be put into the context of larger comparative analyses, such as statistical studies of several countries or over long time periods. They lose the fine-grain detail about timing, circumstances, and decision makers’ conscious calculations of advantage and motivation. But their virtue lies in illuminating broad patterns. The politically relevant timing of international events is not just a recent phenomenon. Evidence for economic and electoral incentives to use force stems from the actions of American presidents over the past century. Russett (1989) looked at American participation in new militarized disputes over the period 1873– 1976, excluding years in which the United States was already involved in a high-level dispute. This study had no direct controls for the actions of other states, and hence no control for who may have initiated the dispute. (Previous analysis with a related data set, however, did not show an improvement with a control for the reputed initiator.) But it did control for increases in military personnel—a rough measure of capabilities as well as of international tensions—and they were significantly related to military actions. It also found that presidents were more likely to threaten or use military force in years when the economy was doing badly, or when there was a national election. This was especially true when economic downturn and elections coincided. The strongest results were achieved for an interactive term of presidential election year times a dummy variable for a decline in real GDP per capita two years previously, which was statistically significant at about the .01 level. A second dummy variable for congressional election times previous decline in real GDP per capita showed the predicted sign but was not significant. Presumably a president cared more about his own re-election, or bringing in his successor, than about trying to affect a congressional election wherein presidential coattails often were not very long anyway. Another study of American politics over this century-long period also found a mild association of low-level uses of military force with recession, although full-scale wars were more likely to occur at times of prosperity. A decision to go to war requires a high level of popular consensus—perhaps more easily reached in prosperous times—but low-level and less consequential uses of force may be more common in efforts to achieve a consensus that had previously been elusive (Elder and Holmes 1988). The finding about the state of the economy also applied to Great Britain. This association for the United States and Britain—powerful states that could be successfully attacked by few if any others—argues against the possibility that countries are more likely to become the victim, rather than the perpetrator, of aggressive acts when their economies are weak or their political systems are in some disarray. But there was no relation between military conflict and British elections—not surprisingly, since the prime minister has substantial


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freedom to call elections at a favorable moment and so is under less pressure to create a good political climate for a fixed election time. Intriguingly, the association with American election times was much stronger in the years from the 1870s to 1930 than later, and the association with economic downturn was much stronger in the post-1930 period (Russett 1990). Several reasons for this shift can be suggested. Presidents have been held more accountable for hard times since the creation of modern economic theories and instruments for the control of the economy. They may therefore give primary effort—with some hope of success—to improving the economy before elections, with less need to resort to the rally effect then. Also, the polls and the electronic media have created the permanent plebiscite on the President, compelling him to produce constant proof of his popularity regardless of the timing of elections. Finally, in recent years public and journalistic awareness of the rally effect may have stimulated a certain popular cynicism about the possibility of an ‘October surprise,’ perhaps making an action too closely approaching an election actually counterproductive in domestic politics. Overall, the results fit a perspective on a rational president using foreign policy actions to maximize the changes that he or his party will retain the presidency, to maximize the number of his supporters in Congress, and to maintain his popularity ratings in between. The evidence is at least as strong as that for successful presidential manipulation of the economy in accord with the electoral cycle. Leaders of states, like ordinary people, learn. If they have succeeded, either internationally or in domestic politics, by using force they are likely to continue using it (Gurr 1988). This discussion should not be interpreted as meaning that democracies are more likely to engage in either war or lesser forms of international conflict than are states which are not democracies. They are neither more nor less likely to do so. The consensus of systematic studies is that type of political system is not related to the probability that a country will be involved in war or international conflict in general.9 We have been discussing only the timing of conflicts, a matter which is partly under the control of a government. We must also emphasize that the results associating international conflict with economic downturn apply only to engaging in relatively low-level international disputes and uses of military force, not to the large-scale exercise of international violence known as war (conventionally defined, in the scientific international relations literature, as producing more than 1,000 battle deaths). Real wars are both serious and rare. They are rare enough that we should not expect to find—and do not find—any convincing regularities between economic or political cycles and war initiation in the modern era. War is serious enough that, whereas the initiation of low-level international conflict may be influenced by considerations of domestic politics, the dynamics of

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escalation from confrontation into crisis into war typically are driven much more by the international environment and the behavior of one’s adversary (Leng 1984; Huth and Russett 1988).10 It is one thing to make verbal threats or even to launch small military strikes against relatively weak adversaries. It is quite another to make a decision for war, or a decision that may lead one’s adversary to decide for war. Unlike a non-violent quarrel with a foreign adversary or a very brief military action, war is not popular. War is costly, usually dangerous, often protracted— very different from a quick demonstrative or coercive use of military force. World War I, Korea, and Vietnam (though not World War II) are all regarded by the American public as ‘a mistake’ (Erskine 1970; Smith 1971). After a brief spurt of national unity, wars usually reduce social cohesion and popular morale, with higher rates of strikes, crime, and violent protest (Stein 1980; Stohl 1975). Governments lose popularity directly in proportion to the cost of the war in blood and money (Cotton 1986). Israeli backing for the war in Lebanon shows how drastically and rapidly popular support can be withdrawn from an unsuccessful war. Initially, in the summer of 1982, two-thirds of the population supported it. Three years later that proportion was down to about 15 percent, and the greatest drop-off occurred in the first 10 months—by May 1983. Support was especially tenuous because the public viewed this as failing to achieve its war aims, and more of a ‘war of choice’ than one forced on Israel, as in 1973 or even 1967 (Arian 1985).

A SYSTEMATIC TEST IN ISRAEL Some observers of Israeli politics believe they have found instances, appropriate to the above reasoning, of uses of military force for domestic political purposes. An early article (Aronson and Horowitz 1971) claimed that Israeli leaders were likely to authorize military actions in part because of internal political calculations. The authors suggested that limited Israeli military operations have served as a means to strengthen social consensus; to raise morale in the army and civilian society; to increase the popularity of the elite; and to strengthen the hand of those favoring an activist foreign policy, and all that without war. Barry Blechman (1971:244, 289) noted that it had often been alleged, especially in 1965, that military reprisals were ‘devices used cynically to gather support in Israel’s domestic politics.’ While rejecting that interpretation, he did conclude that ‘Israel has chosen, probably tacitly and implicitly, to accept various negative long-run consequences for the reprisals, in exchange for benefits of a psychological nature within the Israeli political system…’ For both studies, however, the number of elections held


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up to then was too few to provide anything conclusive. The raid on the Iraqi nuclear reactor at Osirak on 7 June, 1981 marked a later conjuncture of security policy and electoral politics, just three weeks before Prime Minister Menachem Begin was to face the voters in a general election. However substantial the military justification for the strike, it could have been postponed a few months with little harm to Israeli security. As it was, Begin’s party benefited greatly from an outpouring of popular approval despite severe economic difficulties (from inflation rather than recession) (Sachar 1987:127–31). Based on these intriguing but inconclusive examples, the findings for the United States, and the preceding theoretical discussion, we need to conduct a more systematic test in the Israeli context. Accordingly we specify these hypotheses: H1:

Use of Israeli military force will be negatively related to the state of the economy—that is, negatively related to the recent rate of economic growth and/or positively related to the rate of inflation. H1A: Use of Israeli military force will be unrelated to the state of the economy; national security considerations may be paramount, making the government unwilling and/or unable to use military actions as a means to boost any fall in popularity due to a failing economy. H2: Use of Israeli military force will be positively related to the proximity of parliamentary elections—that is, highest in election years, and lowest immediately afterwards. H2A: Use of Israeli military force will be unrelated to the proximity of parliamentary elections. The government may be unwilling or unable to use military actions to boost its popularity for several reasons: national security considerations may be paramount; or cynical popular anticipation of such actions may eliminate their political utility; or it may be sufficient to manipulate the economy as a means of gaining support; or the effects of the ‘permanent plebiscite’ may compensate for the particular incentives of election time. To test these hypotheses and, to a lesser degree, to try to determine the reasons for supporting or rejecting them, our principal analysis will consist of a time series multiple regression of the period 1950–88, with military operations mounted by Israel as the dependent variable.11 During most of its history Israel has been subjected to a variety of shellings, border incursions, and externally mounted terrorist attacks. In turn, Israel adopted a policy of retaliatory and sometimes pre-emptive strikes—with, however, much discretion by the government as to the nature and timing of these strikes. Data on these operations (defined as ‘Israeli attacks and infiltration’) were

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initially gathered by Blechman 1971 from the Jerusalem Post, the New York Times, and other sources. We have adapted his data set and extended it to 1988 to include nearly 500 operations. Our conflict data were compiled by day from various sources, including the Israeli Defense Forces (IDF) archives (information published in a special bulletin for the fortieth anniversary of Israel and information published by the IDF’s spokesmen) and reports in Israeli daily newspapers: Ha’a retz, Ma’ariv, Yediot-Ha-Haronot, Davar, Ma’arachot, and Skira Hodshcit. These reports were found in four archives: the public archives of the Tel Aviv public library, Ha’a retz’s archives, Yediot-Ha-Haronot’s archives, and the archives of the IDF. We also consulted books about the Arab-Israeli conflict, primarily those written by military historians of the IDF, and autobiographies and personal diaries. Of course some information remains secret, but our interest in the use of force for its possible effect on electoral conditions makes the use solely of publically known information appropriate. We used only the frequency of military operations on the grounds that other dimensions, such as their scope and intensity, were largely a function of variables which are not relevant for our purposes here. Since it is logical first to assume that Israeli actions are, as they profess to be, largely in reaction to or close anticipation of Arab attacks, as a control variable we include Arab actions, using the same coding rules as for Israeli actions. In the few cases where Blechman’s reports were inconsistent with our data for Arab operations, we used the former on the grounds that his sources were likely to be more complete for Arab activities. The control will consist of two variables, for Arab attacks in the same year as Israeli actions and—somewhat less plausibly, given the incentives for quick reactions—in the preceding year. This control is especially important because some hard-line Arab groups may mount attacks on Israeli targets just before elections so as to diminish the political prospects of Israeli doves; Arabs preferring a continuing confrontation with Israel seem to have done this in 1988, for example. Thus we want to know whether, independent of any such Arab initiatives, Israeli military actions increase. For both types of military actions we include only those in the months preceding the election date, and omit periods of major war (see below). For each year we divide the number of actions by the number of months used most often 12. These and other data are shown in the Appendix. Two kinds of military actions, for both sides, are excluded from the analysis. First, we include only actions mounted across de facto international borders beyond Israeli-occupied territory such as the West Bank, Gaza, and the Israeli security zone in Lebanon—excluding, for example, events of the intifada or


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terrorist acts originating within Israeli-occupied territory. Second, we exclude actions during the course of large-scale international war defined as a set of events resulting in 1,000 or more battle deaths. That is, we begin in 1950, following the end of the War of Independence in July 1949, and then exclude the relevant days of October-November 1956 for the Suez war, June 1967 for the Six-Day war, March 1969 to August 1970 for the War of Attrition, October 1973 for the Yom Kippur war, and June 1982 to May 1983 for the Lebanon war. A methodological reason for this second omission is to avoid having our analysis heavily skewed by the effect of these intense events. A more important reason, however, stems from our theoretical perspective above, that decisions to go to war are graver, with national security (even existence) more directly at stake, and hence less subject to considerations of advantage in domestic politics. (This decision also has the effect of weighting the evidence against our first hypothesis, as in 1969 the election came during the War of Attrition and the 1973 election occurred immediately following the end of the war.) Another control variable, related to Arab operations but also partly contained empirically in Israeli operations, is the number of Israeli casualties (dead and wounded) in military or terrorist actions, gathered from the same sources. As with military operations, we computed the monthly average, excluding those in post-election months. Yet another is a four-point ordinal variable measuring fear of war among Israelis, coded from newspapers (extended from Barzilai 1987). We initially included it, treating it as an interval variable, but not surprisingly it was highly collinear with the other variables above, and we then discarded it. In fact, all these variables (Arab operations, Israeli casualties, and fear) are fairly collinear. Not all should therefore be used in the final equation, and it is difficult to be sure which of them is statistically the most important for explaining Israeli operations. One or another of them was always highly significant in our equations; our final results report the two (current Arab operations and Israeli casualties) which, when used alone, made the most significant contributions and also are theoretically most plausible. Our economic variables are the per capita rate of change in real (inflationadjusted) gross domestic product and the rate of change in the consumer price index, from the Israel Bureau of Statistics. We employ them simultaneously (this year’s growth rate with this year’s military actions) or with a one-year or two-year lag from economy to military actions. In an attempt to specify the equation as fully as possible, we also include the value of arms imports to Israel from all countries, on the grounds that higher levels of arms imports may permit the government to be more able and confident to undertake military operations. (It may also, of course, increase Israel’s dependence on those sources.) The data are in constant dollars,

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covering both purchases and arms obtained on concessionary terms (gifts and loans), from Broszka and Ohlson (1987). Our primary political variable is proximity of national parliamentary (Knesset) elections. So that the sign of the hypothesized relationship will be positive, we code each year on a four-point scale, a 4 if the election were held in it and for preceding years the number of years elapsed since the previous election.12 Some observers may claim that politically motivated uses of force are primarily a partisan phenomenon of one or the other of the major Israeli political blocs. To test this we included a dummy variable for change in the political system—that is, for the period before 1978 when the Labour Party and its electoral allies held a majority in the Knesset, and the subsequent period when Labour was out of office or governed only as part of a ‘national unity coalition’ with Likud. We include this on the hypothesis that the later governments, with perhaps a less reliable coalition or with a somewhat different ideology, may be more ready to use military force. Two further political variables were for the number of political demonstrations within Israel, and the number of demonstrations specifically about economic conditions, in some ways preferable to data on the state of the economy alone. These data had been compiled by Sam Lehman-Wilzig (Department of Political Studies, Bar-Ilan University) from reports in the Jerusalem Post, and kindly made available to us. The results of the analysis are shown in Table 8.1 with our ‘best’ equation —that is, eliminating variables that were not statistically significant.13 The total explanatory power of the equation is quite high (adjusted R2= .67). Not surprisingly, the strongest contribution to explaining Israeli military operations is Arab military operations in the same year, and another important contributor is the number of Israeli casualties in military operations during that same year. The second is hardly surprising, in that some Israeli casualties were incurred in the course of the Israeli military operations they are being used to ‘explain,’ though probably most were due to Arab-initiated actions. TABLE 8.1 Equation for Israeli military actions, 1950–88

Note: Entries in the first row are beta coefficients; parenthetical entries in the second row are exact probabilities for statistical significance.


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As suggested above, we cannot entirely dismiss related variables such as previous Arab operations or Israeli casualties, or fear of war, but these two variables show the highest coefficients and, especially in the case of current Arab operations, seem theoretically most appropriate. If we were interested simply in maximizing the R2 we could include the others, but it is more appropriate not to dwell on that.14 More interesting, however, is the major political variable. Proximity of national elections shows a strong and significant relationship, in the expected direction: the closer an election looms, the greater the number of Israeli military operations, even controlling for Arab operations (which, incidentally, are not correlated with elections). In 6 of the 11 election years analyzed (1949 is excluded), the number of military actions well exceeded the median (0.8) per month) for the entire 39-year period. An average of one or more Israeli military actions occurred during the pre-election months of 1951, 1955, 1965, 1969, 1981, and 1988—and 1981 includes the dramatic air strike against Osirak. The high 1955 figures (more than 3 per month) came during an era of intense Arab attacks and reprisals, and for which David Ben-Gurion was subsequently criticized—including by his foreign minister—as intensifying feelings of threats to national security for partisan political purposes (Khouri 1985:189; Sharet 1978:1059–60). The two election years with fewest Israeli military actions are 1961—an unexpected election15–and 1977—a year when the delicate peace process with Egypt was beginning. Moreover, the third lowest figure for election-year Israeli actions is in 1973— low only because, as noted, we excluded events of the Yom Kippur war. Another way of analyzing this material is by construction of a truth table (Table 8.2) and a little Boolean algebra (Ragin 1987), which show that: (1) High (above median) Arab military actions or Israeli casualties are virtually necessary conditions to produce a high level of Israeli military actions (the election year of 1981 is the only exception).16 (2) An election alone is not a necessary (or of course sufficient) condition for a high level of Israeli military acts. (3) But in the absence of many Israeli casualties, an election combined with high levels of Arab military actions together are sufficient to produce a high level of Israeli military actions. In short, the equation says that Israeli military operations are provoked by high levels of Israeli casualties, or by frequent Arab military actions if those actions precede a national election. Arab military actions often are not high at election times, and they do not alone determine Israeli military operations. The Israeli mythology of national security being above or autonomous from calculation of partisan politics

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TABLE 8.2 Truth table for causes of high levels of Israeli military actions

Notes: 1=variable present, 0=absent. For continuous variables, 1=value above the median. a Plus two exceptions with 0 as result: 1982, 1983 b One year (1951) with 1 as result; one year (1984) with 0 as result, although IMA just below the median c Plus two exceptions with 0 as result: 1972, 1978 d Plus one exception with 1 as result: 1986 e Plus one exception with 1 as result: 1981 IMA=ABC+aBC+AbC+ABc+abC, reduces to IMA=ABc+C.

and personal benefits should be cast aside. Our interpretation is further strengthened by looking at the variance in military actions within the years of national elections. Within those years, in the months preceding the election the average number of military actions is 1.31; in the months following the election the average number is 0.91. Even this division probably understates the effect of elections, since some actions occurring after the elections very likely were part of a continuing action-reaction process initiated in the months before election. The pattern of military action around election times is not, however, limited purely to election years, but also applies, in lesser degree, to many of the years closely preceding elections. For example, in the regression analysis we tried substituting a simple dummy variable, election year or not, for the fouryear coding but the results were not as strong. Thus a picture of longerterm anticipation of elections, including the preceding year, seems more appropriate than one that merely picks out the election year itself as carrying incentives to military action. Our dummy variable for nature of governing coalition, however, had no significant effect on the use of force. The generalization holds over time and change in the internal balance of political forces; it is not a partisan phenomenon. Perhaps surprisingly, neither political demonstrations in general, nor demonstrations specifically about economic conditions, have any significant effect either (but an objective measure of economic conditions does matter, in a way; see below); neither do arms imports.


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In terms of our hypotheses, H2 is supported and H2A—that the use of Israeli military force is unrelated to election timing—is rejected. We suggest that governments are willing, and able, to time their military actions for their own electoral benefit. The high degree of secrecy surrounding national security affairs in Israel probably makes it especially difficult to persuasively criticize military actions as politically motivated. None of the possible reasons for the alternative hypothesis seems important. Public cynicism has so far not constrained such actions— perhaps because they are screened by the very severe threats to national security that Israel does in fact face. There is more than a suggestion that Israeli governments do stimulate the economy before elections. (The correlation between our election variable and rate of growth in the economy is .36; p=.03, and only once, in 1977, did per capita GDP actually decline in an election year; also see the literature on the Israeli political economic cycle cited above.) Sometimes also elections may be called to coincide with good economic times. Two of the three Israeli elections held markedly outside the normal four-year cycle were in years of exceptionally rapid economic growth (1951 and 1961, though not 1984). However, the electoral benefits of an expanding economy apparently are not enough to dissuade the government from also engaging in the politically relevant timing of military actions. Any ‘permanent plebiscite’ is less important than the electoral pressures of the Israeli political system: Concerns for public opinion are most pressing in the brief run-up to elections; otherwise the focus of parliamentary politics is more on intra-coalition bargaining to hold the government together (Klieman 1989: ch. 5). A decision on the relevance of domestic economic conditions and H1A is not so easily reached. In the form that we stated it, H1 should substantially be rejected, with the weight of evidence in favor of the alternative, H1A. None of the economic variables enters into the final regression model in Table 8.1. Perhaps the economically debilitating effects of military actions are to some degree understood by the public, hence the temptations to use military actions to divert attention from economic woes or to give the economy a very brief stimulus are less. A more complex understanding might, however, proceed as follows: (1)

There is a negative simple correlation (-.36; p=.03) between the economic growth rate and the frequency of Israeli military actions two years subsequently. This offers modest support for a delayed distraction or externalization of frustration hypothesis, although the effects are swamped by elections and military events (Arab acts and Israeli casualties) in the multivariate model.

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(2)

(3)


The simple correlation of current per capita GDP growth and the monthly average of Israeli military acts is strongly positive (.47; p= .01), not as we hypothesized but largely a result of the fact that both a high rate of economic growth and frequent military acts coincide with elections. Thus there may well be some connection between economic adversity and military actions by Israel, but it can be better interpreted indirectly, as a dual strategy of taking military actions, and stimulating the economy, at the crucial time before elections.

Israel is a small and beseiged state, a ‘nation in arms’ with a special and acute international vulnerability. Military/security/peace-war issues are usually the dominant ones affecting citizens’ feelings of wellbeing, even more than economic issues (Stone 1982). As a consequence, an excessively economicdeterminist version of military-industrial complex theories is erroneous; the incentives to military action are more deeply embedded in the structure of democratic elections, and theories extrapolating too readily from the experience of the United States need some revision. In the impact of domestic politics upon decisions when and how to use military force, Israel both shares important similarities with other democratic regimes and shows different mechanisms.

SOME CONCLUDING OBSERVATIONS We can compare the above results to those in two studies of the use of military force by the United States referred to in the introductory pages. Neither is entirely comparable to this study, but they can illuminate some similarities. In the first (Russett 1990), change in military personnel (roughly comparable, for the United States, to the measure of arms imports used as a control for Israeli military capability) made a difference. But most important for our purposes, presidential-year elections and the state of the economy mattered; congressional-only (off-year) elections less so.17 The other study (Ostrom and Job 1986) found that various international conditions, roughly analogous to those used in this study, had major effects. But it also found use offeree significantly related to an economic ‘misery index’ and, though not significantly, to elections.18 Despite differences in these studies and in the two states’ international situation, a basic convergence of results is impressive. First, elections matter, especially those involving control of the executive as well as the legislature. (In Israel, of course, all Knesset elections imply both.) Second, the state of the


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economy also matters, but more subtly and less directly in Israel.19 These findings apply to two states with serious and continuing security problems, and enough power vis-à-vis their chief international adversaries to have some choice about the timing and nature of the military actions they undertake. For the United States the security problems stem largely from its ultimately global commitments as a major or even hegemonic power; for Israel they stem from the intense regional threats to its existence. There may not be many other similar cases, at least for democratically governed countries where elections truly matter. (Britain and perhaps France in previous decades may share many similarities.) Yet the United States certainly is not unique. We can offer several possible interpretations—not necessarily mutually exclusive ones—for the association of military actions with elections. (1)

(2)

(3)

A rather cynical one, prominent in the early part of this chapter, is some version of conscious effort, by the government, to rally popular support and convert it into public approval and votes at the polling booths. In conjunction with the evidence that governments manipulate the economy for electoral purposes we are inclined to this interpretation. An alternative is that Israel is often confronted by Arab attacks and the government senses a predominantly hawkish mood much of the time, but it feels especially constrained to respond vigorously as elections draw near. Then, when the government is most vulnerable to the public mood, it shifts to a greater readiness to use military force. The finding that high Arab military actions or Israeli casualties were virtually necessary, and with elections sufficient, to produce a high level of Israeli military actions supports this interpretation; evidence that popular approval of military action usually is greater for the fait accompli than for hypothetical acts suggests public demands for vigorous action are not too great. Still another is that members of the government suffer from a not fully conscious form of misperception; they simplify their cognitions, exaggerating the degree and importance of external hostility at times when they themselves are most insecure politically—at election time— and hence react more vigorously than otherwise.

What is needed is a fuller political-psychological model, one which explains the conditions under which people are influenced or manipulated by symbols of war, heroism, patriotism, threat, and insecurity. At the moment we cannot really sort out the alternative explanations. Quantitative analysis has the important virtue of offering systematic controls, and of establishing general patterns that may otherwise be obscured or distorted by particularly dramatic events that an observer may recall. It needs to be supplemented by information

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on the apparent perceptions and motivations of leaders in particular circumstances; some help may come from interviews, memoirs, and the further release of classified documents about government decision making. This kind of evidence nevertheless is likely to be distorted by selective and self-serving recall, and cannot be conclusive. If leaders are sometimes tempted to seek short-term support by initiating foreign policy belligerence, it is worth remembering that threats or smallscale uses offeree may lead to an acute international crisis. Even if no more than small-scale uses offeree are intended, the crisis may sometimes get out of hand and lead to a serious military engagement; military engagements may escalate and become prolonged. Continuous national security crises, even if arising from exogenous conditions, become endogenous as they lead to manipulation by political leaders. This is an often-neglected kind of damage which repeated international crises inflict upon even a democratic political system. Even if military actions do not get out of hand to become big wars, their frequent coincidence with elections and periods of economic adversity constitutes grounds for concern that the interests of governing elites, rather than broader ‘national’ interests, may drive national security policy in pernicious ways. Political elites have a clear interest in keeping themselves in power. They must conduct foreign policy with a sharp eye to its domestic political consequences, and may confound their personal interests with the national interest—believing, for instance, that the national interest would be ill-served by allowing the domestic opposition to take power if the current government is perceived as too soft. The most important point is just that foreign policy is, in substantial degree, domestic policy. Our findings extend findings which have established that arms ‘races’ are only in part interactions between adversaries; they are also in large part ‘autistic,’ driven by bureaucratic pressures and domestic politics (Russett 1983; Ward 1984). This chapter shows the major role of domestic politics even in dangerous threats and use of lethal violence. To understand that uses of international violence may be importantly influenced by a leader’s concern for his or her domestic power base is to begin to demystify the reasons and rationalizations often offered for those actions.


APPENDIX: MEASURES USED IN THE ANALYSIS

Note: aIn election years includes only actions and months preceding the election.

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NOTES This investigation was begun while Barzilai was visiting at Yale under a Fulbright-Hays research award, and completed while Russett was visiting at Tel Aviv University under a Fulbright-Hays research award. We are grateful to our universities, to our colleagues, and for the awards, but of course only we bear responsibility for this report. 1 2

3 4

5 6

7 8

9 10

11 12 13

The principle here is one of unconsciously motivated misperception of the capabilities or intentions of other states, as developed well by jervis (1976) and subsequently. The classic study is Kramer (1971). Scores of subsequent works have elaborated the point, for the United States, Western Europe, Israel, and other countries. See, for example, BenHanan and Temkin (1986); Hibbs (1987); Kiewiet (1983); Lewis-Beck (1987); MacKuen (1983); Nordhaus (1975); and Tufte (1978), with a good review on the United States being Simonton (1987). Monroe (1984) suggests some caveats. On blame and credit for government see Abramowitz et al. (1988); Bloom and Price (1975). Also see lyengar and Kinder (1987); Kinder and Kiewiet (1979). For a methodological critique see Kramer (1983). The policy cycle in the United States was first demonstrated by Tufte (1978). Important qualifications have been noted by Alt and Chrystal (1983); Brown and Stein (1982); and Thompson and Zuk (1983). The definitive work on the electoral politics of military spending in the United States is Mayer (1992). Also see Mintz (1988a) and Mintz and Hicks (1984). On Israel, see Mintz (1988b); Mintz and Ward (1988, 1989). On the popularity accruing to Thatcher for her actions see Norpoth (1987). Sanders et al. (1987) dissent on its duration. The absence of systematic findings of a relation between internal and external conflict has been widely noted; e.g. by Stohl (1980) and Zinnes (1980), both of whom lament the lack of careful and complex theory underpinning the investigations. An excellent review and theoretical discussion is Levy (1989). First labelled and documented by Mueller (1973), revised slightly but basically confirmed by Kernell (1978), and further documented by Lee (1977); Benson (1982); Brody (1984). When widespread elite disapproval does emerge promptly, popular disapproval may be very great. After disclosure of the Iran—Contra affair (which political competitors could safely criticize as a deal with terrorist Iran), President Reagan’s popularity dropped 16 percent in two weeks. This consensus stems from many comprehensive studies and reviews. The latest, citing earlier work, is Maoz and Abdolali (1989). One author did, however, find that governments were more likely to escalate military disputes when the dispute coincided with both an increase in domestic turmoil and an opportunity for a successful use of international force (James 1987, 1988). The statistical package was SPSS (X) PV (V.2). For example, the 1961 elections were unexpected, having been preceded by a national election as recently as 1959. Thus 1961 was coded 4, but 1960 only 1. Using significance at the .10 level (one-tailed test, given directional hypotheses) as the cutoff. We give the exact probability level (p) at which one would erroneously reject the null hypothesis of no relationship. Since we have reasonably strong theory and only 39 data points, it seems appropriate to use a fairly unrestrictive criterion to avoid dismissing variables that may be important. Of course we do not have a random sample here—rather virtually the universe of years following Israel’s independence—but the significance criterion is nonetheless useful to estimate variables’ explanatory power.

Military actions: the US and Israel 14

15 16

17 18

19

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Other than here, multicollinearity was not a serious problem for most variables. Another potential difficulty in time series analysis is autocorrelation. Inspection of the residuals suggests that this also is not a serious problem here; the Durbin-Watson test is at an intermediate level. If autocorrelation were serious it would inflate the apparent significance levels of the independent variables, so we pay special attention below to phenomena not affected by autocorrelation, such as six election years well above the median for Israeli military actions, a Boolean analysis, and higher levels for pre-election months than postelection ones. Also, inspection of the residuals shows that the four years in which the equation most underestimates Israeli military actions are all election years; that is, the equation, driven mostly by Arab operations and Israeli casualties, did not give enough weight to the election in those years. In general, however, there is no discernible difference between elections within or outside of the normal four-year cycle. Formally the term C alone in the final expression says that Israeli casualties alone make a sufficient condition. This interpretation, however, ignores the two exceptions out of five with the causal pattern 0 0 1 when a high level of Israeli military action did not result, and also the fact that Israeli casualties may result from as well as cause Israeli acts. A more conservative interpretation of the entire table would be that C may also require the presence of B and/or A. Since Israeli elections almost always took place in years of economic growth, there was no point in using interactive measures like that in the American study. Their ‘misery index’ was compounded of inflation and unemployment, weighted by perception of the economy as the most important problem. Our study kept real growth in per capita GDP and the inflation rate separate. No measure of the ‘most important problem’ —or of the prime minister’s popularity, also used by Ostrom and Job—was available over a long enough time period for Israel. In the analysis of the United States during the post-World War II years the relation was between the current state of the economy and use of military force, whereas in the centurylong analysis of the United States the strongest relation was between military disputes and the state of the economy two years previously. There was also a suggestion of this in Israel.

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Beck, N. 1984. Domestic political sources of American monetary policy, 1955–82. Journal of Politics 46 (3): 786–817. Ben-Hanan, U. and Temkin, B. 1986. The overloaded juggler: the electoral economic cycle in Israel. In A.Arian and M.Shamir (eds), The Elections in Israel—1984. New Brunswick, NJ: Transaction. Benson, J.M. 1982. The polls: U.S. military intervention. Public Opinion Quarterly 46:592–8. Blechman, B. 1971. The consequences of Israeli reprisals: an assessment. PhD dissertation. Washington, DC: Georgetown University. Bloom, H.S. and Price, H.D. 1975. Voter response to short-run economic conditions: the asymmetrical effect of prosperity and recession. American Political Science Review 69 (4): 1240–54. Brody, R. 1984. International crises: a rallying point for the president? Public Opinion 6:41–3, 46. Brody, R. and Shapiro, C. 1987. Policy failure and public support: Reykjavik, Iran and public assessments of President Reagan. Paper presented at the annual meeting of the American Political Science Association, Chicago, September. Brzoska, M. and Ohlson, T. 1987. Arms Transfers to the Third World, 1971–85. Oxford: Oxford University Press. Brown, T.A. and Stein, A.A. 1982. The political economy of national elections. Comparative Politics 14 (4): 479–97. Cotton, T.Y.C. 1986. War and American democracy: voting trends in the last five American wars. Journal of Conflict Resolution 30 (4): 616–35. Crespi, I. 1980. The case of presidential popularity. In A.H.Cantril (ed.), Polling on the Issues. Washington, DC: Seven Locks Press. Edwards, G.C. III. 1980. Presidential Influence in Congress. New York: W.H.Freeman. Elder, R. and Holmes, J. 1988. Prosperity, consensus, and assertive foreign policy: a long-term analysis of historical relationships in American foreign policy. Paper presented at the annual meeting of the International Studies Association, St Louis, MO, March. Erskine, H.G. 1970. The polls: is war a mistake? Public Opinion Quarterly 34:134–50. Gurr, T.R. 1988. War, revolution, and the growth of the coercive state. Comparative Political Studies 21 (1): 45–65. Hibbs, D. 1987. The Political Economy of Industrial Democracies. Cambridge, MA: Harvard University Press. Huth, P. and Russett, B. 1988. Deterrence failure and crisis escalation. International Studies Quarterly 32(1): 29–45. lyengar, S. and Kinder, D.R. 1987. News That Matters: Television and American Opinion. Chicago: University of Chicago Press. Jacobson, G.C. 1983. The Politics of Congressional Elections. Boston, MA: Little Brown. James, P. 1987. Externalization of conflict: testing a crisis-based model. Canadian Journal ofPolitical Science 20:573–98. James, P. 1988. Crisis and War. Montreal and Kingston: McGill-Queen’s University Press. Jervis, R. 1976. Perception and Misperception in International Politics. Princeton, NJ: Princeton University Press.


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Kernell, S. 1978. Explaining presidential popularity. American Political Science Review 72:506– 22. Kernell, S. 1986. Going Public: New Strategies of Presidential Leadership. Washington, DC: Congressional Quarterly. Khouri, F.I. 1985. The Arab–Israeli Dilemma, 3rd edn. Syracuse, NY: Syracuse University Press. Kiewiet, D.R. 1983. Macroeconomics and Micropolitics. Chicago: University of Chicago Press. Kinder, D.R. 1981. Presidents, prosperity, and public opinion. Public Opinion Quarterly 45 (1): 1–21. Kinder, D.R. and Kiewiet, R.D. 1979. Economic discontent and political behavior: the role of personal grievances and collective economic judgments in congressional voting. American Journal of Political Science 23 (3): 495–527. Klieman, A. 1989. Israel and the World after Forty Years. London: Pergamon-Brassey. Kramer, G.H. 1971. Short-term fluctuations in U.S. voting behavior. American Political Science Review 65(1):131–43. Kramer, G.H. 1983. The ecological fallacy revisited: aggregate–versus individual-level findings on economics and elections and sociotropic voting. American Political Science Review 77 (1): 92–111. Lee, J.R. 1970. Rally ‘round the flag: foreign policy events and presidential popularity. Presidential Studies Quarterly 7:252–5. Leng, R. 1984. Reagan and the Russians: crisis bargaining beliefs and the historical record. American Political Science Review 78 (2): 655–84. LeVine, R.A. and Campbell, D.T. 1972. Ethnocentrism: Theories of Conflict, Ethnic Attitudes, and Group Behavior. New York: Wiley. Levy, J.S. 1989. The diversionary theory of war: a critique. In M.Midlarsky (ed.), Handbook of War Studies. London: Unwin Hyman. Lewis-Beck, M.S. 1985. Un modèle de prévision des elections legislatives franchises (avec une application pour 1986). Revue Française de Science Politique 35 (6):1080–91. Lowi, T.J. 1985. The Personal President. Ithaca, NY: Cornell University Press. MacKuen, M.B. 1983. Political drama, economic conditions, and the dynamics of presidential popularity. American Journal of Political Science 27 (2):165–92. Maoz, Z. and Abdolali, N. 1989. Regime types and international conflict, 1816–1976. Journal of Conflict Resolution 33 (1): 3–35. Marra, R., Ostrom, C., and Simon, D. 1989. Foreign policy in the perpetual election: presidential popularity, foreign policy, and windows of opportunity. Paper prepared for the annual meeting of the International Studies Association, London, March. Mayer, K.E. 1992. The Politics and Economics of Defense Contracting. New Haven, CT: Yale University Press. Mintz, A. 1988a. The Politics of Resource Allocation in the U.S. Department of Defense: International Crises and Domestic Constraints. Boulder, CO: Westview. Mintz, A. 1988b. Electoral cycles and defense spending: a comparison of Israel and the United States. Comparative Political Studies 21 (3):368–82. Mintz, A. and Hicks, A.M. 1984. Military Keynesianism in the United States, 1949–1976: disaggregating military expenditures and their determination. American Journal of Sociology 90(2) :411–17. Mintz, A. and Ward, M.D. 1988. The evolution of Israel’s military expenditures, 1960–1983. Western Political Quarterly 41 (3): 489–507. Mintz, A. and Ward, M.D. 1989. The political economy of military spending in Israel. American Political Science Review 83 (2): 521–33.

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Miroff, B. 1976. Pragmatic Illusions: The Presidential Politics of John F.Kennedy. New York: David McKay. Monroe, K. 1984. Presidential Popularity and the Economy. New York: Praeger. Mueller, J.E. 1973. War, Presidents, and Public Opinion. New York: Wiley. Nincic, M. 1988. The United States, the Soviet Union, and the politics of opposites. World Politics 40:452–75. Nordhaus, W. 1975. The political business cycle. Review of Economic Studies 42 (1):169–89. Norpoth, H. 1987. Guns and butter and government popularity in Britain. American Political Science Review 81 (3):449–60. Ostrom, C. and Job, B. 1986. The president and the political use of force. American Political Science Review 80 (2):541–66. Ostrom, C.W. and Simon, D. 1985. Promise and performance: a dynamic model of presidential popularity. American Political Science Review 79:334–58. Ragin, C. 1987. The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. Berkeley, CA: University of California Press. Russett, B. 1983. International interactions and processes: the internal-external debate revisited. In A.Finifter (ed.), Political Science: The State of the Discipline. Washington, DC: American Political Science Association. Russett, B. 1990. Economic decline, electoral pressure, and the initiation of interstate conflict. In C.Gochman and A.N.Sabrosky (eds), Prisoners of War? Nation-states in the modern era. Lexington, MA: D.C.Heath. Sachar, H.M. 1987. A History of Israel, Vol. 2: From the Aftermath of the Yom Kippur War. New York: Oxford University Press. Sanders, D., Ward, H., and Marsh, D. (with A.Fletcher). 1987 Government popularity and the Falklands war: A reassessment. British Journal of Political Science 17 (3):287–314. Sharet, Y. (ed.) 1978. Moshe Sharet: A Personal Diary. Tel Aviv: Maariv Press (in Hebrew). Shaw, R.P. and Wong, Y. 1988. Genetic Seeds of Warfare: Evolution, Nationalism, and Patriotism. Boston, MA: Unwin Hyman. Simonton, D.K. 1987. Why Presidents Succeed: A Political Psychology of Leadership. New Haven, CT: Yale University Press. Smith, R.B. 1971. Disaffection, delegitimation, and consequences: aggregate trends for World War II, Korea, and Vietnam. In C.C.Moskos, Jr (ed.), Public Opinion and the Military Establishment. Beverly Hills, CA: Sage. Stein, A. 1980. The Nation at War. Baltimore, MD: Johns Hopkins University Press. Stohl, M. 1975. War and domestic political violence: the case of the United States, 1890–1970. Journal of Conflict Resolution 19 (3):379–416. Stohl, M. 1980. The nexus of civil and international conflict. In T.R.Gurr (ed.), Handbook of Political Conflict. New York: Free Press. Stoll, R.J. 1984. The guns of November: presidential reelections and the use of force. Journal of Conflict Resolution 28 (2):231–46. Stone, R.A. 1982. Social Change in Israel: Attitudes and Events, 1967–79. New York: Praeger. Suedfeld, P. and Tetlock, P. 1977. Integrative complexity and communication in international crises. Journal of Conflict Resolution 21 (1):169–84. Tetlock, P. 1985. Integrative complexity of American and Soviet foreign policy rhetoric. Journal of Personality and Social Psychology 49 (6):1565–85.


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Tetlock, P. and McGuire, C. 1985. Integrative complexity as a predictor of Soviet foreign policy behavior. International Journal of Group Tensions 14:113–28. Military actions: the US and Israel 181 Thompson, W.R. and Zuk, G. 1983. American elections and the international electoraleconomic cycle: a test of the Tufte hypothesis. American Journal of Political Science 27:464–84. Tufte, E.R. 1978. Political Control of the Economy. Princeton, NJ: Princeton University Press. Ward, M.D. 1984. Differential paths to parity: a study of the contemporary arms race. American Political Science Review 78 (2):297–317. Weissberg, H. 1976. Public Opinion and Popular Government. Englewood Cliffs, NJ: PrenticeHall. Zinnes, D. 1980. Why war? Evidence on the outbreak of international conflict. In T.R.Gurr (ed.), Handbook of Political Conflict. New York: Free Press.

PART III

Defense Spending and Economic Performance

CHAPTER 9

‘Guns’ vs ‘Butter’: A Disaggregated Analysis Alex Mintz

Most people believe there is a tradeoff between spending on defense and spending on welfare (Russett 1982), but, as a number of scholars (e.g. Clayton 1976; Domke et al. 1983; Russett 1982) have shown,1 the existence of such a tradeoff is difficult to establish empirically. Prior analysis has centered on tradeoffs between total defense spending and specific kinds of welfare spending (e.g. health, education, housing). I examine tradeoffs between welfare spending and specific kinds of defense expenditures. Congress appropriates funds to the Department of Defense (DoD) by budgetary component. The major DoD components are military personnel, military procurement, operation and maintenance (O&M), and research and development (R&D). These components typically account for 92–97 percent of the defense budget. Appropriations for military personnel finance ‘the personnel costs of the active duty forces of the United States and the future retirement benefits of the current active forces’ (US Office of Management and Budget Budget of the US Government 1987: IG1). These appropriations roughly index armed forces strength and account for about one-third of the defense budget. Procurement expenditures finance the acquisition of military equipment, weapons, and spare parts and the modification of existing equipment. Military procurement spending typically accounts for more than a quarter of the Department of Defense budget. Operation and maintenance appropriations finance the cost of repair and maintenance of DoD plant and equipment, fuel and supply costs, and remuneration of DoD civilian employees. Operation and maintenance expenditures account for about onequarter of the budget. Research and development expenditures finance the development of strategic weapons systems, tactical programs, intelligence and communication systems, and defense-oriented research. This subcategory accounts for almost 10 percent of the budget.2 185

186 FIGURE 9.1

III: DEFENSE SPENDING AND ECONOMIC PERFORMANCE Fluctuations in US defense spending, 1948–85

Source: Derived from US Government, Budget of the United States, 1948–1985, Appendixes.

DoD data (1978; 1988) show that research and development expenditures were always the smallest of all major defense spending subcategories. Procurement spending was the largest subcategory between 1953 and 1964, between 1968 and 1969 and in the mid-1980s. Between 1948 and 1952, and between 1969 and the peak of the Reagan defense buildup in the mid-1980s, military personnel and operation and maintenance expenditures were the largest (see Figure 9.1). There is no reason to expect the impact on welfare spending of allocations to the procurement of the B-1 bomber, the B-2 Stealth bomber, the Nimitz class carrier, the Trident submarine or the MX missile to be similar to the impact of spending for operation and maintenance programs or salaries and benefits of over 2 million active uniformed personnel. The Department of Defense is the largest single purchaser of goods and services in the national economy (DeGrasse et al. 1983). It buys goods and services from about 300,000 suppliers, and signs 52,000 contract actions every working day (US Department of Defense 1986). It also supports 2.1 million uniformed personnel (a quarter of whom are stationed overseas), and employs over 1 million DoD civilians, more than 1 million military reservists, and more than 2 million in

‘Guns’ vs ‘butter’

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the defense industry (US Department of Defense 1988). DoD data show (1983) that allocations of $1 billion to military personnel programs support 49,000 individuals, while allocations of a similar amount to DoD nonpay programs create only 35,000 jobs. One may expect that military procurement and R&D programs will also have an impact on welfare spending different from that of military personnel, and vice versa. The impact of each of the major defense subcategories on the major components of welfare spending is assessed below.

RESEARCH STRATEGY AND EMPIRICAL FINDINGS Clayton (1976), Russett (1982), and Domke et al. (1983) found no evidence for a defense-welfare tradeoff in post-1945 USA. This seems to imply either that no subcategory of defense expenditure affects welfare spending or that subcategories of defense spending have positive and negative impacts essentially canceling one another out. The major hypothesis tested in this chapter is that there are variations in the impact of the different components of the defense budget on welfare spending. While allocations to DoD capital-intensive programs are hypothesized to take resources away from welfare programs, allocations to labor-intensive programs may ease the task of the government’s health and education sectors rather than lead to a tradeoff. Marfels (1978) has argued that the bulk of military expenditures for the procurement of military equipment goes to large, unionized ‘monopoly sector’ firms. Galbraith (1967:316) similarly points out that much of the military research and development budget goes to large, oligopolistic corporations that need R&D for ‘technical and scientific’ advance. Huisken (1982:8) agreed that military procurement expenditures are concentrated in the capital- and technologyintensive sectors of industry.3 Labor in the defense industry is highly skilled and relatively well paid. A very low proportion of blue-collar workers and a very high proportion of engineers and scientists are involved in the development and production of weapon systems—a workforce hardly in need of welfare programs. Peroff and Podolak-Warren (1979:24) have argued that the cost of weapons systems is therefore carried to a greater extent by lowerincome groups, who have a greater need for welfare programs and ‘could use additional income for “necessities” such as health services.’ Wildavsky (1988:380) has similarly concluded that more for weapons came to be viewed as ‘an inegalitarian taking from the worst-off elements of the population.’ Given an upper limit to the federal budget, an increase in allocations to weapons systems could come at the expense of welfare spending. Military personnel expenditures (and part of the O&M budget), in contrast, go directly to finance the pay, allowances, clothing, subsistence, insurance, and retirement

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benefits of people, i.e. they may alleviate the demand for health, education, and housing programs. Military personnel expenditures may help equalize the distribution of benefits, education, and medical care. In periods of high unemployment, increases in DoD personnel expenditures can even help middleand lower-income groups, of which the armed forces largely consists. For some, military service is one of the few ways they can not only contribute to national security but also acquire skills, job training, and technical expertise and gain experience not otherwise available, as is evident by the increasing overrepresentation of lower-income class and racial groups in the ground forces. Binkin et al. (1982) argued that the armed forces provide lower-income groups with their only chance to escape from the underclass. Military service became an extension of welfare policy for those who could not make it in the larger society.4 Since the armed forces are providing health and education services to many who might otherwise be in need of government support, there may be a lesser need for the government to spend additional amounts of money on these programs. An increase in military personnel expenditures may therefore not necessarily come at the expense of welfare. Furthermore, personnel expenditures of the Department of Defense are largely ‘uncontrollable.’ Procurement and R&D spending are more ‘controllable’ and much more volatile, however. Procurement spending, in particular, fluctuates considerably over time. It is expected that during periods of modernization of weapon systems, launching of new systems, and so on,5 sharp increases in R&D and procurement expenditures will come at the expense of welfare spending. To test for the accuracy or inaccuracy of this hypothesis, I replicated Russett’s study (1982) of the guns versus butter tradeoff while substituting total military expenditures by each of the four major subcomponents of the DoD budget. Operational definitions and data on all variables (except the four components of the defense budget) were taken from Russett (1982). Data on military personnel expenditures, procurement spending, operation and maintenance expenditures, and research and development expenditures were taken from The Budget of the US Government (1947–1987). The first year for which data are available on all variables is 1948 (1949 for the operation and maintenance subcategory). As Russett (1982:776) pointed out, the Reagan presidency was different in its budgetary priorities. Since tradeoffs during the Reagan years are evident (Kamlet et al. 1988; Wildavsky 1988), the inclusion of the Reagan years in my analysis would have undoubtedly distorted the findings. Following Russett, the Reagan buildup is analyzed separately in this study. Russett’s equations are:


189

Russett has also estimated two reduced equations, excluding % ⌬ housing and %⌬ health from the education equation and %⌬ housing and %⌬ education from the health equation. Data are in constant prices and represent final outlays (see Russett 1982:772, Table 2, and 775 Table 3). As Domke et al. (1983:21) explained, it is indeed ‘best to investigate final outlays—the bottom line of the ledger comprising the many alterations of the budget and its final implementation.’ In any case data on the components of the defense budget in all other stages of the budgeting process were not found for the entire time period. The results of the disaggregated analysis are shown in Table 9.1. Column 1 in this table reproduces the results of Russett (1982). Column 2 reports my replication. Columns 3–6 show estimates of Russett’s equation, but each time with a different component of the defense budget serving as an independent variable. The analysis of total military spending produced results very similar to those of Russett and consistent with those of Domke et al. (1983). More importantly, the results of the disaggregated analysis have likewise shown a lack of defense-welfare tradeoffs. The coefficients for military personnel, procurement, operation and maintenance, and research and development in the education equation are all non-significant at the .05 level (see Table 9.1). Estimates of the reduced equations, GLS corrections for autocorrelation, SUR estimates, and the inclusion of additional controls such as battle deaths and population under 18, have produced insignificant results for all four components. Zero order correlations between education and procurement (.22) and education and R&D expenditures (.09) are likewise non-significant. The correlations between personnel and education expenditures and operation and maintenance and education spending are a bit higher (.34 and .35, respectively), but still non-significant at the .01 level. Furthermore, estimates of Russett’s health equations (not shown here6) produced results very similar to the education equations, indicating (again) a lack of defensewelfare tradeoffs. Zero order correlations of health and personnel, procurement, O&M, and R&D range from -.05 to . 14 and are likewise non-significant. It appears, therefore, that the growth in military personnel expenditures in 1947–80 has not been large enough to substitute for, or reduce the demand

190


TABLE 9.1 The impact of defense spending on education expenditures, 1947–80

Notes: statistically significant at the .01 level. † statistically significant at the .05 level. Sources: Based on data obtained from Russett 1982; US Department of Defense, annually.

for, welfare programs and create a defense—welfare tradeoff. On the other hand the rise in procurement expenditures has not ‘solved’ or alleviated the demand for health and education programs, which have continued to grow independently of the growth in procurement spending. And the magnitude of the increases in procurement and R&D spending has not been large enough to shift resources from one budgetary component to the other in an expanding budget. The purpose of Russett’s studies (1969, 1982) was to test for systematic tradeoffs between military spending and welfare spending. My disaggregation of the analysis of US total military spending into analysis of major subcategories of military spending has likewise revealed no such tradeoffs.

RECENT TRADEOFFS Korb (1987:166) has pointed out that ‘the FY1985 defense budget was more than double that of the FY1980 budget, the last full budget of the Carter


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Administration. From FY1980 to FY1985 the defense budget grew from $142.6 billion to $286.8 billion.’ Even in constant prices, the increase over that time period was in excess of 50 percent. During the Carter years, military expenditures accounted for 22–23 percent of total federal outlays and 4.8– 5.0 percent of the gross national product. During the Reagan years, they rose to about 25–29 percent of total outlays and 6.0–6.6 percent of the GNP. Both Russett (1982:776) and Wildavsky (1988:380) pointed out that the buildup has resulted in tradeoffs between military spending and civilian spending. Kamlet et al. (1988:1304) have shown that defense spending was higher and controllable domestic spending substantially lower under Reagan ‘than would have been the case under pre-Reagan budgetary priorities.’7 As Wildavsky (1988:380) pointed out: ‘domestic policy became defense policy in that slimming the former became the way to fatten the latter. Defense policy became domestic policy in that more for defense became less for domestic, mostly welfare programs…The Reagan administration sought to get [for defense] as much as it could as fast as it could for as long as it could.’ My study examines specific tradeoffs between welfare spending and (a) military personnel expenditures, (b) operation and maintenance outlays, (c) procurement spending, and (d) research and development expenditures. The results (Table 9.2) clearly show that the tradeoff in the 1980s was between the development and procurement of military systems and investments in education. To be more specific, procurement and R&D expenditures grew every year during that period by an average of more than 10 percent, while education expenditures were cut (in constant prices) in five out of the seven years on an average of almost 5 percent (1.3 percent if 1982 is excluded). Military personnel and operation and maintenance outlays rose, on average, by only 3.8 and 3.6 percent respectively. Health expenditures grew by 3.7 percent annually (see Table 9.2). TABLE 9.2 Percent change in defense, education, and health expenditures, 1981–87 (constant 1982 prices)

Sources: Derived from US Department of Defense, annually; US Office of Management and Budget, annually, Historical Tables: Budget of the U.S. Government.

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III: DEFENSE SPENDING AND ECONOMIC PERFORMANCE TABLE 9.3 Resource allocation in the DoD: the Reagan years vs the Carter years

Sources: Derived from US Office of Management and Budget, annually, Budget of the U.S. Government.

One explanation for the weapon systems/welfare tradeoff is that the Reagan administration has not only raised military expenditures substantially, but also changed priorities in the Department of Defense by putting much more emphasis on the purchase of equipment and material (i.e. the capital-and technology-intensive procurement and R&D programs) than on operating programs (i.e. the labor-intensive military personnel and operation and maintenance programs; see Table 9.3). More than 55 percent of the growth in military spending between FY1982 and FY1986 went to procurement of weapon systems and the development of new systems. About 20 percent of the total DoD budget increase went to operation and maintenance programs, while less than 20 percent of the total growth was allocated to the military personnel subcategory of the budget (see US Office of Management and Budget, annually). Consequently, procurement outlays in the late 1980s accounted for almost 29 percent of the DoD budget, compared with less than 20 percent a decade ago. Research and development spending accounts for more than 12 percent of the budget, compared with only 9-10 percent a decade ago. Operation and maintenance expenditures account for 27-28 percent compared with about 32–33 percent in the mid-1970s, while military personnel outlays account for only slightly more than 27 percent of the defense budget in recent years, compared with 34-35 percent a decade ago (US Office of Management and Budget, annually). Despite claims by administration officials (US Department of Defense 1988:129) that ‘the recent defense buildup was not funded at the expense of vital domestic programs,’ there is clear evidence that the buildup has resulted in cuts in education expenditures, for which the administration has, evidently, less commitment than for health programs.


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CONCLUSIONS This chapter examined the guns-welfare tradeoff at a less aggregated level than has been done previously. The results are consistent with the findings of Domke et al (1983), Russett (1982), and Clayton (1976) of no evidence of defense-welfare tradeoffs in the pre-Reagan era. Although there may be years in which R&D or procurement spending increased and welfare spending decreased, the pattern is not common enough to indicate a tradeoff between these spending categories over the entire period. As Domke et al. (1983:33) point out, ‘defense and welfare expenditures appear…to be driven by separate sets of determinants which do not require one to be systematically sacrificed for the other.’ These conclusions are reinforced by the disaggregated analysis. The rising costs of many welfare programs (e.g. Medicare) and the ‘uncontrollable’ nature of many of these programs might be important determinants. Another explanation might be the political ‘acceptability’ of deficit spending until the mid-1980s. It should be pointed out that my analysis is concerned only with the direct budgetary tradeoff between guns and butter. It might be, however, that the indirect, second- or third-order (multiplier) effect of increased military spending, once played out through the whole economy, is actually negative.8 Deger (1986:190) has noted that, as defense spending increases, it influences inflation, taxation, forced saving, and various programs and will therefore reduce the potential increase in welfare spending. Furthermore, the level of military expenditures as a proportion of the GNP is already high in the United States by West European standards (Ward 1984), while the level of social welfare spending, compared with most European countries, was moderate in the 1950s and 1960s (Clayton 1976:378–9). More research on the indirect effects of increased defense spending on welfare spending is therefore needed. As for the Reagan years, the analysis reveals the existence of tradeoffs between investments in the development and production of weapons systems and spending on education. The tradeoff could have even been more severe: during the six years Republicans controlled the Senate, Secretary Weinberger’s defense requests were reduced by an average of 7 percent, more than any previous Secretary of Defense (Korb 1987:168), and Reagan’s requests for additional cuts in welfare spending were not accepted fully by Congress. Kamlet et al. (1988:1304) showed that the Reagan administration departed dramatically from the ‘broad budgetary priorities’ of other administrations. This chapter has shown that the defense-welfare tradeoff in the 1980s was specifically between investments in weapons systems and investments in human capital (and not between military personnel and education, operation


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and maintenance and health, or military personnel and health). Since priority is now being given to deficit reduction, it is difficult to imagine drastic increases in allocations to both weapons systems and welfare expenditures, especially since the tradeoff during the Reagan years was evident in an expanding budget with a huge deficit. The Bush administration will have to decide on whether to continue the present trend, to reverse the trend, or to allocate less to both guns and butter.

NOTES Reprinted from The American Political Science Review (December 1989), by permission of the American Political Science Association. I thank Bruce M.Russett for sharing his data on defense expenditure and economic wellbeing with me, and Robert A.Bernstein for helpful suggestions. The research was partially supported by a summer grant from the Military Studies Institute at Texas A&M University. 1 2 3 4 5 6 7 8

For a comprehensive review of the literature on this topic see Chan (1985). Other components of the Department of Defense budget are military construction, family housing, and allowances. Huisken (1982) points out that military industrial activity can be viewed as labor-intensive only at the stage of final assembly of weapon systems. According to Berryman’s data, however, the military cannot be viewed as an ‘employer of last resort’(1988:4). One may argue that the cost of the government’s bail-out of defense industries (the socalled ‘welfare capitalism’) also comes at the expense of other programs. Available from the author. Kamlet et al. (1988) found, however, that uncontrollable domestic spending was higher under Reagan than under his predecessors. Deger (1986) showed that, while the first-order effects of military spending on growth in less developed countries are often positive, the multiplier effects are clearly negative. Mintz and Ward (1989) showed that military spending and corporate profits are typically interrelated. Smith (1980) found that, while an increase in defense expenditures does not significantly affect the social wage in developed countries, the burden falls on other programs, e.g. investment.

REFERENCES Berryman, S.E. 1988. Who Serves? The Persistent Myth of the Underclass Army. Boulder, CO: Westview Press. Binkin, M., Eitelberg, M.J., Schexnider, A.J., and Smith, M.M. 1982. Blacks and the Military. Washington, DC: Brookings Institution. Chan, S. 1985. The impact of defense spending on economic performance: a survey of evidence and problems. ORBIS 29:403–34.


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Clayton, J.L. 1976. The fiscal limits of the warfare—welfare state: defense and welfare spending in the United States since 1900. Western Political Quarterly 29:364–83. Deger, S. 1986. Military Expenditures in Third World Countries: The Economic Effects. London: Routledge & Kegan Paul. DeGrasse, R.W., McGuinness, E., and Ragen, W. 1983. Military Expansion, Economic Decline. New York: Council on Economic Priorities. Domke, W.K., Eichenberg, R.C., and Kelleher, C.M. 1983. The illusion of choice: defense and welfare in advanced industrial democracies, 1948–1978. American Political Science Review 77:19–35. Galbraith, J.K. 1967. The New Industrial State. Boston, MA: Houghton Mifflin. Huisken, R. 1982. Armaments and development. In H.Tuomi and R.Vayrynen (eds), Militarization and Arms Production, pp. 3–25. New York: St Martin’s. Kamlet, M.S., Mowery, D.C., and Su, T. 1988. Upsetting national priorities: the Reagan administration’s budgetary strategy. American Political Science Review 82:1293–307. Korb, L.J. 1987. Spending without strategy. International Security 12:166–74. Marfels, C.. 1978. The structure of the military industrial complex in the United States and its impact on industrial concentration. Kyklos 31:409–23. Mintz, A. and Ward, M.D. 1989. The political economy of military spending in Israel. American Political Science Review 83 (2):521–33. Peroff, K. and Podolak-Warren, M. 1979. Does spending on defense cut spending on health? British Journal of Political Science 9:21–39. Russett, B.M. 1969. Who pays for defense? American Political Science Review 63:412–26. Russett, B.M. 1982. Defense expenditures and national well-being. American Political Science Review 76:767–77. Smith, R. 1980. Military expenditure and investment in OECD countries 1954–1973. Journal of Comparative Economics March. US Department of Defense. Annually. The Department of Defense Annual Report. Washington, DC: US Government Printing Office. US Office of Management and Budget. Annually. Budget of the U.S. Government. Washington, DC: US Government Printing Office. US Office of Management and Budget. Annually. Historical Tables: Budget of the U.S. Government. Washington, DC: US Government Printing Office. Ward, M.D. 1984. Differential paths to parity: a study of the contemporary arms race. American Political Science Review 78 (2):297–317. Wildavsky, A. 1988. The New Politics of the Budgetary Process. Glenview, IL: Scott, Foresman.

CHAPTER 10

Guns, Butter, and Debt: Balancing Spending Tradeoffs between Defense, Social Programs, and Budget Deficits Jin Whyu Mok and Robert D.Duval

The objective of this chapter is to provide empirical evidence of budgetary tradeoffs between defense and various domestic programs in the US federal budget for the period 1954–86. To accomplish this objective, we operationalize the idea of budgetary tradeoffs, incorporate the budget deficit as an additional component of the tradeoff, develop an alternative budgetary indicator, and test its utility in detecting spending tradeoffs. The most common form of resource allocation in policy making is the budget. In budget-making, the total available revenue in a given year is distributed over various spending categories, presumably in accordance with the level of demands (MacRae and Wilde 1979). Nonetheless, many believe that apparent tradeoffs exist between ‘guns and butter.’ This dilemma depicts spending in military and social policy areas as inversely related to each other. As a nation’s military expenditures increase, the benefits which accrue from social policy expenditures must suffer, ‘if only by a diminution in the rate of increase’ (Dabelko and McCormick 1977:146). For instance, increasing tensions between the superpowers are frequently seen as an important factor influencing strong budgetary commitments to defense among many Western nations. On the other hand, those who support various social programs clearly believe that military programs have resulted in significant tradeoffs to the detriment of the poor, the retired, the disabled, or other beneficiaries of social programs. Yet, in one of the more sophisticated empirical studies examining budgetary tradeoffs between spending categories, Domke et al (1983) conclude that the 196

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idea of choice in budgetary decision making is largely illusory. Specifically, they attempt to clarify the issue of tradeoffs by examining expenditure patterns between defense and welfare for the United States, United Kingdom, Federal Republic of Germany, and France since World War II. After classifying expenditure tradeoffs as either long term or short term, they report longterm tradeoffs but fail to detect short-term tradeoffs in expenditure patterns.1 They then argued that a replacement effort by government through increases in taxes or deficit financing explains this finding. They conclude that: Although there may be years in which one increases and the other decreases, the pattern is not common enough to produce a significant negative reaction to the relationship between two spending categories (i.e., defense and welfare) over the entire period. Defense and welfare expenditures appear, on the basis of these analyses, to be driven by separate sets of determinants which do not require one to be systematically sacrificed for the other. (Domke et al. 1983:33)

Earlier studies, upon which Domke et al. place their conceptual base, are by Pryor (1968) and Russett (1969, 1970, 1982). Among a group of 14 capitalist and socialist countries in the period 1950–70, Pryor (1968:123–4) finds no relationship between short-term deviations (percentage changes) or trends (percentage of total expenditures) in defense and total civilian expenditures. Russett (1982) also evaluates the existence of expenditure tradeoffs between defense spending and social spending and the impact of defense spending upon various social programs, such as housing and education. He too is unable to detect a consistent negative relationship between them. In an earlier study (1969), however, Russett argues that, in the US, defense and civilian spending trends were strongly and negatively associated over the period 1939–68. For example, virtually all of 20 expenditure categories in the study show a negative correlation with defense, with the strongest relationships appearing between defense and federal civilian purchases, state/local consumption, total welfare spending, and state/local spending for health (Russett 1969). Others have focused upon specific spending categories, such as education, health, and housing (Peroff 1977; Peroff and Podolak-Warren 1979). Ames and Goff investigate the potential tradeoffs between defense and educational spending among a group of Latin America nations over the period 1948–68, arguing that ‘education spending and defense spending both rise and fall at the same time’ (1975:181). Neither gains at the expense of the other, although some other expenditures ‘must be negatively related to their [defense and education] changes.’ Turning to the relationship between defense and health spending, Peroff (1977) and Peroff and Podolak-Warren (1979) find that US federal

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expenditures for health are negatively related to defense. However, no association is detected in other specific health spending categories such as health research. They conclude that, since federal health expenditures represent large dollar amounts, ‘when a policy begins to represent a significant share of the budgetary pie, that policy becomes more politically salient’ and, as a result, more ‘sensitive to defense spending’ (Peroff and Podolak-Warren 1979:39). Caputo’s findings, however, do not substantiate the argument by Peroff and Podolak-Warren. Caputo finds a positive and significant association between defense and total health spending in the US and asserts that ‘increased defense did not lead to a decrease in health expenditures’ (Caputo 1975:439). In short, previous research reveals at best mixed evidence concerning the relationship between defense and various social spending programs. Some argue that explicit tradeoffs occur, while others reject that exchange. The idea of expenditure tradeoffs between defense and social spending remains intuitively appealing, because the movement to the welfare state by the mid 1950s had become an ‘accepted responsibility of the government’ (Huntington 1975:208) and thus ‘politically resistant to the arms squeeze’ (Russett 1970:148). This disagreement within the previous empirical studies is reexamined here by testing the following general hypothesis: H1:

Changes in defense spending are negatively related to changes in all non-defense spending categories.

COMPETING AND ADDITIONAL HYPOTHESES There are a number of additional considerations which must be addressed in any model which predicts or explains levels, changes, or patterns in military spending. Beyond some marginal increment or decrement, changes in spending over the years are, as noted, generally believed to be a reflection of shifts in governmental policy priorities. In military spending, changes in expenditures are usually thought to be the result of some external threat, perceived or actual, to the physical security of the nation. This is, in essence, the wellknown ‘action and reaction’ (arms race) hypothesis, although problems with this perspective have been well documented on various grounds.2 Yet arms races do not directly concern us here owing to the logic of our inquiry. The existence of an arms race may well ensure that there are increases in defense spending. They may well cause budgetary resources to be expended for defense rather than for social welfare. But, as noted, the task at hand is not to predict defense spending, but merely to demonstrate


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that, as expenditures in one category go up, they go down in some other budget item. Inclusion of an arms race model would therefore distort the empirical analysis to the degree that Soviet spending causes an increase in defense spending which, when balanced against domestic priorities under budgetary constraints, produces a decline in social welfare spending. This research endeavors to provide description, not causal explanation, and therefore must omit variables irrelevant to this task, and their attendant statistical artifacts.3 There is a substantial body of literature which falls under the same conditions as the arms race model. The impact of domestic politics upon the appropriation process is another candidate. A sizable body of literature has evolved around bureaucratic politics and other models of decision making (Marra 1986), reactive linkage models (Ostrom 1978), and political-business cycles (Monroe 1983; Nordhaus 1975; Tufte 1978; Zuk and Woodbury 1986), all of which contribute to the explanation of spending changes but would mask spending tradeoffs in a regression context. The background economic conditions which determine when or how budgetary tradeoffs would occur have also been widely discussed. For instance, Russett (1982:767) argues that budgetary tradeoffs between defense and nondefense spending would occur ‘if a nation increases the resources it devotes to military activities without increasing total product.’ However, budgetary tradeoffs will not occur if governments are able to expand revenues either through increases in total product or by increasing taxes or deficit financing, because ‘increasing the pie may alleviate difficult choices’ (Eichenberg 1981:11). Others assert that budgetary tradeoffs would also occur in a situation of increasing total expenditures, however financed. Even in a society experiencing budgetary growth, some spending categories may get more than others, although every spending category could conceivably experience gains. For instance, ‘the increase in the level or amount for welfare is not as large as it would be if [the] defense increment was [sic] smaller’ (Peroff 1977:370). In addition, a government’s fiscal capacity reflects its ability to utilize resources for various societal needs. Countries with rapid economic growth may feel better able to indulge themselves in the ‘luxury of elaborate defense programs’ (Benoit 1973:275). Similarly, Domke et al. (1983), Caputo (1975), and Nincic and Cusack (1979) report that changes in US defense spending are sensitive to the availability of resources, e.g. increases in total spending with statistically significant positive regression coefficients. Out of all of this discussion, surprisingly little direct attention has been directed towards deficit spending. Clearly borrowing may be a policy mechanism to ameliorate the need for spending tradeoffs (Russett 1982; Ward and Mahajan 1984). In a balanced budget with fixed resources, the desire for

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increases in any category must of necessity result in decreases in other categories. Contemporary deficit financing, however, allows one to defer such decisions to future budgets, effecting a three-way tradeoff. In other words, in order to spend more on defense (or social welfare) you must spend less on social programs (or defense), unless you borrow. Tradeoffs should be more observable in low deficit years, and more difficult to observe as deficits increase. Detection of such tradeoffs through empirical means should therefore improve when one controls for the budget deficit. Thus, one may argue that higher levels of defense spending need not be at the expense of social spending, but are more than offset by the increment in revenues if a dynamic expansion of the economy is achieved or by borrowing. Revenues may be increased through taxation or governments may finance expenditures through deficit financing. Since both mechanisms come into play in determining appropriation levels, any search for spending tradeoffs must include or control for these factors through some means. Consequently, a hypothesis complementary to the central one previously stated is: H2: Increases in revenue or deficits lead to increases in spending in all categories, therefore such increases will be positively related to changes in defense spending.

THE CONCEPTUALIZATION OF BUDGETARY TRADEOFFS The central task undertaken here is a clarification of the general notion of a tradeoff. What constitutes a tradeoff? What kinds of budget indicators should be used to detect tradeoffs in budget studies? It must be emphasized at this point that, in searching for tradeoffs, we do not intend specifically to measure them, but rather concur with Domke et al. that the existence of tradeoffs is confirmed if there is a statistically significant negative relationship between appropriate measures of budget changes. Hence confirmation of this hypothesis would provide evidence that there is indeed a tradeoff. We are therefore trying to test not for causation, but rather for an appropriate level of association. Tradeoffs, as they are described in the literature, are opportunity costs. Since an opportunity cost is a forgone benefit that occurs when someone selects one option at the expense of one or more other options, it fits the conceptual intent of a tradeoff quite well. Given a fixed total budget, opportunity costs are incurred when budgeting for a spending item is possible only by either taking or not allocating funds to others. Therefore, ceteris


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TABLE 10.1 Comparison of budget indicators in two hypothetical scenarios

paribus, the budget allocation to defense spending contributes negatively to the size, absolute or relative, of the budget for other spending categories. At this point, most budget studies proceed with one of two operationalizations of this tradeoff. Some argue that the tradeoff between spending items occurs in their share of the budget in a given year (Ames 1977; Hayes 1975; Pryor 1968; Russett 1969). This operationalization is often termed a long-term tradeoff. For this measurement, the budget indicator is generally that sector’s percentage of total spending. Others contend that one should look for short-term tradeoffs, which should be observed as a negative relationship in budget changes from year 1 to year 2—the percentage change in spending across any two given years (Eichenberg 1981; Domke et al. 1983; Russett 1971, 1982). To demonstrate how the choice of indicator will measure budget changes differently, two hypothetical budget allocations between defense and welfare are considered in Table 10.1. Assume that, given the total budget for year 1, budget allocations for defense and welfare are the same in both scenarios. However, in year 2 the size of the total budget in scenario 2 is twice that of scenario 1, but the percentage share of defense and welfare to the total budget is the same for both two scenarios: 55.3 percent for defense and 46.7 percent for welfare. Simple percentage The most frequently used measure of a budget spending category is the ratio of its expenditure level to the total budget. That is, the percentage expresses expenditures for a policy in terms of total resources, be it total expenditures

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of the government or economic capacity of the nation, e.g. gross national products or gross domestic products (Ames 1977; Hayes 1975; Peroff 1977; Peroff and Podolak-Warren 1979; Russett 1969, 1970, 1982). When the percentage is expressed in terms of GDP or GNP, then it is believed to measure the burden of spending on society. If, on the other hand, it is expressed in terms of the total expenditures of the government, it reflects policy priorities. Thus, the larger the percentage is for a specific program, the higher priority the government gives it. Trends in these percentages are also believed to measure the long-term patterns of governmental policy priorities since they are not concerned with year-to-year changes in levels of spending (Domke et al. 1983). Referring again to the scenarios in Table 10.1, the defense and welfare percentages of the total budget are 60 percent and 40 percent for year 1, and 53.3 percent and 46.7 percent for year 2, for both scenarios. Thus, if we compare year 1 with year 2 in both scenarios, a decline is observed in the share for defense, while increases are observed in the share of welfare relative to the total. An advantage of this measure is that the percentages do not vary with the absolute magnitude of expenditures as long as each item’s share of the total remains the same. This measure, however, has an important limitation. Since the percentage of the share to the total is calculated independently from one year to the next, year-to-year fluctuations are not easily observed. Percentage change measure Studies which examine the patterns of year-to-year changes in budget allocations have used the percentage change as a measure of the yearly fluctuation in expenditures (Caputo 1975; Domke et al. 1983; Eichenberg 1981; Kelleher et al. 1980; Russett 1982). The percentage change indicates how the current year’s allocation of a spending category changes compared with its allocation in the previous year. There is a general consensus that the use of percentage changes in budgetary studies is appropriate because ‘resource allocation is focused almost entirely on marginal changes: decisions that matter are framed in terms of yearly changes from existing totals and the concerns of policy makers are focused on the potential for the short-term relationship’ among spending categories in budget allocations (Eichenberg 1981:37). The calculation is straightforward:

where Xi,t is the size of expenditures for spending category i at year t.


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In scenario 1, the percentage changes in defense and welfare are 33.3 percent and 75 percent, respectively. In scenario 2, on the other hand, the changes are 166.7 percent for defense and 250 percent for welfare. Thus, this measure gives the idea, like the percentage measure, that welfare in both scenarios has a larger percentage increase than defense. This measure, however, has two major problems. First, it does not provide adequate criteria to examine patterns in the relationship between spending categories relative to changes in the total budget, since total budget size has nothing to do with the calculation of percentage changes in specific categories. In other words, a 33 percent change in defense in scenario 1 does not indicate anything about its relationship to the change in the total budget. In fact, in this case, defense experiences a 17 percent relative loss because the percentage change in the total budget is 50 percent. If the growth in the budget were equitably shared, all categories would realize a 50 percent increase. Another serious limitation is that the percentage change measure is very sensitive to the absolute size of the budget in each spending category. Notice that, in year 2, both defense and welfare have the same percentage of the total budget in both scenario 1 and 2, even though the total budget for scenario 2 is twice that of scenario 1. However, the values of the percentage change reported in scenario 2 are more than twice those of scenario 1. While scenario 2 is undoubtedly an unrealistic depiction of high growth, it does serve to point out the sensitivity of this measure to the magnitude of change in the total budget. Both of these operationalizations of tradeoffs suffer from an important shortcoming. It is not a convincing argument that policy makers would be interested in knowing only the extent of either short- or long-term tradeoffs between budget items. Rather they are interested in knowing, if possible, both forms of the tradeoff. In other words, budgetary tradeoffs should be examined from both short- and long-term perspectives at the same time. The relative change To capture both the short- and long-term aspects of budget behavior, efforts have been made to construct alternative operationalizations. In particular, Gist (1982) recognizes the difficulties associated with the use of the percentage change measure, and suggests using the ‘share of increments relative to existing share of totals’ (Gist 1982:871). This measure allows one to evaluate the magnitude of increments made to spending categories in terms of their share of a base year’s total.4 One interesting characteristic of this measure is that the range of the values is virtually infinite. If the value of the ‘share of increments’ for a spending

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category is larger than 100 percent, it indicates that that spending category receives more of an increase than its share of the existing total. On the other hand, if it is less, then that spending category experiences a decrement.5 As Table 10.1 demonstrates, the share of increments for defense in scenario 1 is 66.7 percent, whereas it is 150 percent for welfare. On the other hand, in scenario 2, it is 83.3 percent for defense and 125 percent for welfare. Thus, relative to a score of 100 percent indicating a category holding its own, this measure reports that in both scenarios, welfare has increased, whereas defense experiences a decrement. Although significant improvement is achieved in adjusting for the unequal size of the spending categories for the measurement of budget changes, this measure is still sensitive to the absolute size of spending items, even when their relative share of the total budget remains the same. This problem can be demonstrated by comparing both scenarios. Since the index value of 100 indicates that no changes are made, in scenario 1 the score of 66.7 percent indicates that defense experiences a 33.3 percent loss relative to its existing share of the total. In scenario 2, the loss for defense is only 11.7 percent, although its share of the total budget for year 2 remains the same for both scenarios. What is required is a measure which will capture the movement of the budget allocation without being overly sensitive to the level of overall increases. The budgetary tradeoff between changes in spending categories is thus operationally defined in this study as the existence of a negative relationship between changes in spending categories as measured by their percentage changes relative to existing total spending. Termed simply a relative change, this indicator measures the difference between the proportion of the total budget a spending item represents in year 1 and year 2. This difference is then compared with its proportion to the total budget in year 1. Thus, the two steps incorporate both aspects of the long-term (proportional share) and short-term (percentage change) changes. Failure to adjust for the budget base results in insensitivity to different budget sizes when calculating budget changes. To correct this problem, the percentage change measure is adjusted by incorporating the budget base in measuring budget changes, and can then be used to capture budgetary tradeoffs. Identified simply as a ‘relative change’ score, this measure provides the magnitudes of marginal increments or decrements in terms of their share of percentage changes relative to existing totals. It also provides clear directions of budget changes over two years—negative for marginal decrements and positive for marginal increments. The alternative measure is thus arguably superior in identifying the tradeoff relationship between budget items. If the value calculated by this measure for a spending category is larger than zero, it indicates that an increment is made in its share of the current


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year’s total relative to its share of the previous year’s total. On the other hand, if the value is less than zero, that spending category experiences a loss relative to the previous year’s share of the total. Although the range of the values could theoretically be infinite, in practice it is between—100 percent and+100 percent. This is because the likelihood of one budget category doubling its percentage share from one year to the next is very low.6 For instance, if defense has 20 percent of the total budget in year 1, then, in order for defense to have more than a+100 percent change in its share, it would have to receive more than 40 percent of the total in year 2. The relative change measure is represented by the following equation:

where Xi,t is the budget for category i in year t, and Tt is total spending in year t. Again using the hypothetical figures reported in Table 10.1, from year 1 to year 2 defense experiences a loss of 11.1 percent relative to its proportional share of the existing total, i.e. the total of year 1. On the other hand, welfare has a gain of 16.7 percent. This measure provides a negative sign for defense and a positive sign for welfare, indicating a clear direction for the change. Thus easy interpretation of who gains and by how much is quite possible. More importantly, it is not sensitive to the absolute size of budgets, either spending categories or totals as reported in both scenarios. This is because, in measuring the changes, the size of the total budget is used to adjust the changes for each budget item. This measure would be particularly useful in comparative research when states or nations with markedly different budget sizes are to be compared.

ANALYSIS To test whether there have indeed been tradeoffs in the US federal budget process, changes in defense spending are regressed on changes in several sectors of the budget. In particular, a search for tradeoffs with welfare, education, veterans’ benefits, health, housing, agriculture, natural resources, labor, governmental operational expenses, and overall social programs is undertaken. The budget data used in the study are available from the US Office of Management and Budget (1989) for the period 1940–89.

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In order to develop an intuitive feel for the overall pattern in budget levels between defense and social programs, spending levels for several sectors of the budget are depicted in Figure 10.1. There are no real surprises in this plot. Defense remains the largest single component of the federal budget, with income security, social security, and interest on the debt all increasing substantially during the last two decades. The federal budget, with only occasional exceptions, is composed of monotonically increasing expenditure series. Even controlling for inflation does little to offset this impression. Clearly defense does have several plateaus where it does not consume a growing portion of the budget. But, by and large, the constant 1985 dollar graph provided in Figure 10.2 does little to either confirm or refute the tradeoff hypothesis. One does, however, get the impression that the rates of change vary for these programs, and that a systematic search for patterns might be fruitful. Using regression analysis, the percentage change in defense spending is regressed on percentage changes in each of these budgetary components. In addition to the percentage change in spending categories, the percentage change in total spending is also included to control for enhanced economic FIGURE 10.1

Federal expenditures: defense, welfare, and debt, 1940–89 (current dollars)

Source: US Office of Management and Budget 1989.

Guns, butter and debt FIGURE 10.2

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Federal expenditures: defense, welfare, and debt, 1940–89 (constant 1985 dollars)

Source: US Office of Management and Budget 1989.

capacity in the standard manner. This is essentially the basic model used in most other regression-based studies. The results are provided in Table 10.2. The first observation that we can make from these results is that in several areas of the federal budget there is some evidence that a systematic tradeoff against defense exists. For 6 out of 17 specific functional areas of spending the regression coefficients are indeed negative and significant. There is, therefore, some evidence that, as defense expenditures have increased, these policy areas have suffered. Interestingly enough, the finding of a tradeoff between defense and veterans’ benefits seems quite counter-intuitive to the classic ‘guns versus butter’ argument. Several social programs, however, fail to produce a significant relationship. Spending on education and social security are in the direction hypothesized, but are decidedly too weak to place any confidence in them. Health and Medicare in fact produce a significant positive relationship with defense spending when we employ two-tailed test criteria. Taken altogether, these findings are moderate confirmation of the central hypothesis. These results are also consistent with the literature in that limited evidence for the existence of tradeoffs is provided and they reflect the general failure to find a systematic tradeoff between social spending and defense. The change in total spending, is of course, significant, as one would expect. If the pie grows, the pieces all grow as well. Changes in total spending are

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TABLE 10.2 Defense and social spending tradeoffs: percentage change measure, 1954-86

Notes: Values in parentheses are t-statistics. The Durbin-Watson d is provided for all OLS runs without significant autocorrelation. The Ljung-Box Q statistic is provided for all AR1 runs. =significant at p 艋=.05 †=significant at p 艋=.10


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significant in all but one program area, Medicare. Also, in every case, the Durbin-Watson d was either statistically significant or in the inconclusive range. As a result, the Cochrane-Orcutt technique was employed to remove the presence of the serial correlation. As seen in Table 10.3, our other fiscal capacity measure indicates that deficit spending is only occasionally related to changes in defense spending when we employ percentage change scores. The tradeoff relationship remains substantially unchanged in statistical confidence, and there is little gain in explanatory power, as evidenced by the adjusted R2. This provides only modest support for the inclusion of the deficit variable. However, there appear to be few costs owing to its inclusion. One positive effect of its inclusion is the reduction of autocorrelation for spending on veterans’ benefits, natural resources, and justice. Turning to the relative change indicator, Tables 10.4 and 10.5 offer somewhat better evidence for tradeoffs than the percentage change tables.7 Now eight spending categories exhibit the tradeoff relationship, owing to the addition of spending on business and commerce and agriculture. Again health and Medicare remain counter to the standard hypothesis, but the literature leads us to anticipate this conclusion. In addition to a marginally better finding using the relative change indicator, we also note that serial correlation is reduced. Almost one-third of the models could be fit with OLS, indicating that the degree of misspecification present in the percentage change model is reduced somewhat. Table 10.5 furthers this impression with the addition of the deficit. Of the 17 spending categories, 14 are statistically related to the level of the deficit, leaving its impact clear. While adding little to the percentage change tests, it has a substantial impact upon the relative change estimations. In addition, only four of the models exhibited enough serial correlation to warrant correction. If serial correlation is indeed an indicator of misspecification, the relative change model seems substantially more suited to the task than the percentage change indicator. While the R2’s are not comparable, one additional basis for comparison is to note that, in the majority of the cases, the t-statistics for the tradeoff coefficients are often stronger for the relative change indicator.

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TABLE 10.3 Deficit, defense, and social spending tradeoffs: percentage change measure, 1954–86

Notes: Values in parentheses at t-statistics. The Durbin-Watson d is provided for all OLS runs without significant autocorrelation. The Ljung-Box Q statistic is provided for all AR1 runs. =significant at p 艋=.05 † =significant at p 艋=.10


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TABLE 10.4 Defense and social spending tradeoffs: relative change measure, 1954–86

Notes: Values in parentheses are t-statistics. The Durbin-Watson d is provided for all OLS runs without significant autocorrelation. The Ljung-Box Q statistic is provided for all AR1 runs. =significant at p艋=.05 †=significant at p 艋=.10

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TABLE 10.5 Deficit, defense, and social spending tradeoffs: relative change measure, 1954–86

Notes: Values in parentheses at t-statistics. The Durbin-Watson d is provided for all OLS runs without significant autocorrelation. The Ljung-Box Q statistic is provided for all AR1 runs. =significant at p 艋=.05 †=significant at p 艋=.10


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FINDINGS AND CONCLUSION There are a number of interesting implications of this study. First, this study finds fairly strong evidence for the existence of certain spending tradeoffs. Like several studies noted earlier, the tradeoff is not observed when one attempts to detect tradeoffs by looking for relationships between percentage change scores for health and education. This analysis concurs with Domke et al. that there are no systematic tradeoffs between defense and selected social programs, but finds substantial evidence that tradeoffs do exist for a wide variety of domestic programs. The relative change measure provides somewhat more satisfactory evidence than the percentage change measure. Not only is the relative change indicator conceptually more appealing than percentage changes, since it adjusts changes in a budget item to compensate for its share of the overall budget, it performs better when put to the test. Needless to say, a $10 billion reduction in defense is a much smaller change for the military than would be $10 billion removed from housing or some other social program budget. The relative change measure adjusts for this proportional impact. In looking at budgetary data, it seems somehow appropriate that this analysis offers incrementally better findings than the literature has typically provided this hypothesis. When the impact of specific budget categories is examined in their relation to changes in defense spending, however, the existence of across-the-board tradeoffs cannot be confirmed, yet selected social programs clearly bear the brunt of defense spending increases (or vice versa). Furthermore, this study effectively demonstrates that the results of empirical analysis can be somewhat different depending upon how the notion of budgetary tradeoffs is operationalized. After a thorough inspection of the mechanism of measuring changes in budget categories, the relative change alternative to the standard percentage change measure was developed and tested. This indicator does provide for a stronger conclusion, and it seems preferable on numerous counts. It would seem, therefore, that the key to the detection of tradeoffs lies in how we choose to look at change in budgetary decisions.

NOTES The authors would like to thank David Hedge, Joseph Stewart, Max Stephenson, Richard Stoll, and Alex Mintz for many thoughtful comments along the way. 1

Budgetary tradeoffs can be classified as short-term, long-term, and decision points


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2

3

4

5

6

7

(Eichenberg 1981:12; Domke et al. 1983:21). A short-term tradeoff is the pattern of changes in which expenditures for a policy are negatively related to changes in spending from one year to the next. A long-term tradeoff occurs, on the other hand, when trends in a policy’s share of spending in national resources (or budgets) are negatively related to trends in other spending. Finally, a decision point tradeoff is an explicit choice of central decision makers to spend more for a policy at the expense of other programs. This model is often criticized as too simple to describe the complex process of defense policy decision making. Nincic and Cusack (1979:102), for example, state that ‘the model pays little attention to the matter of how actual decisions are made or to the institutional procedures surrounding them.’ As a result, they argue, nothing of the actors and interests involved, or of the perceptions and motivations of the relevant parties, can be scrutinized. For an extensive review of arms race models, see Moll and Luebbert (1980). Inclusion of irrelevant variables, while not biasing the coefficient estimates, does inflate coefficient variances, reducing the efficiency of the estimators. Such inclusion potentially damages the statistical power of the t-tests for the detection of tradeoffs. See Kmenta (1986) for an econometric discussion of specification error. The computational formula for the share of increments proposed by Gist (1982:871) takes the form:

In its original form, the value of 1.0 indicates no change in budget allocation. Thus Gist argues, if an agency or budget item gets higher than 1.0 in its share of increment in the yearly budget changes, it is successful in budget politics. A similar measure which is called the ‘priority score’ is also available (Natchez and Bupp 1973), but Gist sees it as deficient because it artificially sets a zero-sum situation which forces tradeoffs in every case of budget allocation. This assertion should be interpreted with the understanding that, if the measure is to be utilized for the case of the program-level budget study, it is certainly possible to observe more than doubled budget changes from year to year. This concern is raised by Natchez and Bupp (1973) and others who have been involved in the debate over incrementalism in budgeting. This inference is based upon the confidence levels observed and not goodness-of-fit statistics since the R2 statistics should not be compared between the two tables. The dependent variables are not identical, thus the R2’s are not directly comparable. So, while it appears that this model is weaker in what it explains, it is important that we remember that this regression analysis is not explaining overall changes in the budget as indicated by changes in total spending.

REFERENCES Ames, B. 1977. The politics of public spending in Latin America. American Journal of Political Science 1 (1):149–76. Ames, B. and Goff, E. 1975. Education and defense expenditure in Latin America, 1948–1968. In C.Liske, W.Loehr, and M.McCamant (eds), Comparative Public Policy. New York: Halstead. Guns, butter, and debt 215


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Benoit, E. 1973. Defense and Economic Growth in Developing Countries. Lexington, MA: D.C. Heath. Caputo, D. 1975. New perspectives on the public policy implications of defense and welfare expenditures. Policy Science 6:423–46. Dabelko, D. and McCormick, J. 1977. Opportunity costs of defense: some cross-national evidence. Journal of Peace Research 14 (2):145–54. Domke, W., Eichenberg, R., and Kelleher, C. 1983. The illusion of choice: defense and welfare in advanced industrial democracies, 1948–1978. American Political Science Review 77:19–34. Eichenberg, R. 1981. Defense/welfare tradeoffs in West German budgeting. PhD dissertation, University of Michigan. Gist, J. 1982. ‘Stability’ and ‘competition’ in budgetary theory. American Political Science Review 76:859–72. Hayes, M. 1975. Policy consequences of military participation in politics: an analysis of tradeoffs in Brazilian federal expenditures. In C.Liske et al. (eds), Comparative Public Policy. New York: Halstead Press. Huntington, S. 1975. The United States. In M.Crozier, S.Huntington, and J.Watanuki (eds), The Crisis of Democracy. New York: New York University Press. Kelleher, C., Domke, W., and Eichenberg, R. 1980. Guns, butter and growth: patterns of public expenditures in four western democracies, 1920–1975. In E.Fedder (ed.), Defense Politics of the Western Alliance. New York: Praeger. Kmenta,J. 1986. Elements of Econometrics. New York: Macmillan. MacRae, D. Jr and Wilde, J. 1979. Policy Analysis for Public Decisions. North Scituate, MA: Duxbury Press. Marra, R. 1986. A cybernetic model of the U.S. defense expenditure policy making process. International Studies Quarterly 29:357–84. Moll, K.D. and Luebbert, G.M. 1980. Arms race and military expenditure models. Journal of Conflict Resolution 24:153–85. Monroe, K. 1983. Political manipulation of the economy: a closer look at political business cycle. Presidential Studies Quarterly 13:37–49. Natchez, P. and Bupp, I. 1973. Policy and priority in the budget process. American Political Science Review 67:951–63. Nincic, M. and Cusack, T. 1979. The political economy of U.S. military spending. Journal of Peace Research 16:105–15. Nordhaus, W. 1975. The political business cycle. Review of Economic Studies 42:169–90. Ostrom, C. 1978. A reactive linkage model of the U.S. defense expenditure policy making process. American Political Science Review 72:941–57. Peroff, K. 1977. The warfare-welfare tradeoffs: health, public aids and housing. Journal of Sociology and Social Welfare 4:366–81. Peroff, K. and Podolak-Warren, M. 1979. Does spending for defense cut spending on health? British Journal of Political Science 9:37–49.

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Pryor, F. 1968. Public Expenditures in Communist and Capitalist Nations. Homewood, IL: Irwin. Russett, B. 1969. Who pays for defense? American Political Science Review 63:412–26. Russett, B. 1970. What Price Vigilance? New Haven, CT: Yale University Press. Russett, B. 1971. Some decisions in the regression analysis of time-series data. In J.F.Herndon and J.L.Bernd (eds), Mathematical Applications in Political Science. Charlottesville, VA: University Press of Virginia. Russett, B. 1982. Defense expenditure and national well-being. American Political Science Review 71:767–77. Tufte, E. 1978. Political Control of the Economy. Princeton, NJ: Princeton University Press. US Office of Management and Budget. 1989. Historical Tables: Budget of the United States Government. Washington, DC: US Government Printing Office. Ward, M.D. and Mahajan, A.K. 1984. Defense expenditures, security threats, and governmental deficits: a case study of India, 1952–1979. Journal of Conflict Resolution 28: 382–419. Zuk, G. and Woodbury, N. 1986. U.S. defense spending, electoral cycles, and Soviet-American relations. Journal of Conflict Resolution 30 (3):445–68.

CHAPTER 11

Defense Budgeting, Fiscal Policy, and Economic Performance Stephen J.Majeski

It is commonly perceived by both government and non-governmental officials that US government defense spending has a significant effect on the performance of the US economy. The perceived effects of defense spending permeate the actual budgetary debate every fiscal year. The budget debate for fiscal 1991 concerning the size of the federal government deficit, reductions in defense and non-defense spending increases, and possible tax increases is simply the latest version of the continuing argument concerning the links among these budgetary, fiscal, and macroeconomic variables. Is it better to reduce budgetary increases in the defense and/or non-defense areas to reduce the size of the federal budget deficit or to increase taxes? Do increases in defense spending necessitate, for fiscal reasons, tradeoffs in entitlements and other social programs? Do increases in defense spending spur economic growth and create employment without boosting inflation by tightening the money supply through deficit spending? With improved US–Soviet relations, the perceived improved security situation (itself debated among liberals and conservatives), budget deficits, and the ‘no new taxes’ pledge, it is not surprising that the Bush administration’s first fiscal budget scaled down Defense Department appropriations. Yet budgetary, fiscal, economic, and political realities forced even the more security-conscious Reagan administration to propose compromises in the size and rate of increase in military expenditures. This was true even before Gramm-Rudman and the decline in political clout of the administration as a consequence of the Iran-Contra affair. For example, from an original projection in January 1983 of $321.6 billion, the President’s request to Congress in January 1984 was reduced to $305.0 billion. This internal administration reduction reflected not only political realities but the work of the Office of Management and Budget (OMB) and the Council of Economic Advisers and their concern with budget deficits and their effects on the economy, the money 217

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supply, interest rates, inflation, and real growth. Congress, as well, was concerned about the deficit for both political and economic reasons and produced independent projections on the expected growth and size of the deficit. Several alternative plans (packages of reductions in defense and nondefense spending, tax increases, and other measures) were proposed in Congress as alternatives to the administration’s package. The administration then made a proposal (Weinberger to Congress, 1984) to deal with the deficit. The administration proposed a $14.0 billion cut in defense spending to bring the total to $291.1 billion. The proposed defense cuts were cast in conditional terms: only if non-defense cuts and tax loophole tightening were also passed by Congress would the administration go along with the whole package designed to reduce deficits. This debate reflects politics, particularly during an election year when no one really wanted tax increases. It also reflects the simple fact that fiscal, budgetary, and monetary policy must be coordinated if there is to be any success in controlling their subsequent impact on macroeconomic variables. The problem is that policy makers do not agree on how budgetary, fiscal, and monetary policy must be coordinated. They propose theoretically incompatible but politically viable plans about defense spending, taxation, non-defense spending, deficits, economic growth, and inflation. The fact that there is little agreement among policy makers about the precise relationships among these budgetary, fiscal, monetary, and macroeconomic variables should not be surprising. It simply mirrors scholars’ theoretical confusion (see Chan 1985 for a survey of evidence and problems). Nowhere is this theoretical confusion more graphic than in the debate concerning the link between defense spending and inflation. Starr et al. (1984) document strong and persuasive theoretical arguments for three positions: defense spending affects inflation, inflation affects defense spending, and defense spending and inflation are unrelated. Some of the arguments are strictly incompatible, but most suggest that, for different sets of conditions, different relations hold between defense spending and inflation. Defense spending may be linked to inflation but that relationship appears to be affected by other policies and conditions. Defense spending can lead to inflation but it depends of whether one cuts back on non-defense spending, or deficit spends (which may generate long-term inflation). Whether deficit spending causes inflation and how quickly that occurs also appears to depend upon the state of economy (degree of capacity being utilized). Also, the link may well depend upon the methods used to increase defense spending: increased revenues through taxation, reductions in nondefense spending (the guns/butter tradeoff), or deficit spending (Carnegie Endowment for International Peace 1981; DeGrasse 1983; US Congressional Budget Office 1983).

Defense budgeting, fiscal policy, and economic performance

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In this analysis, an effort is made to assess ‘causal’ relationships between defense spending and other budgetary, fiscal, and macroeconomic variables. Based on this analysis, an interactive budgetary, macroeconomic model with a focus on defense budgeting is constructed, estimated, and analyzed. This will allow a careful examination of the impact of defense spending on the economy.

DEFENSE SPENDING AS A BUDGETARY TOOL The belief that military expenditures affect national economic conditions rests on the Keynesian proposition that recessions occur when aggregate demand falls short of productive capacity. This creates, among other things, unemployment and negative growth. The method used to increase aggregate demand is to increase government expenditures. Hitch and McKean (1961) argue that defense spending is a large enough component to buoy total spending so as to make a deficiency in total demand less probable. Others (Cypher 1977; Smith 1977) argue more strongly that defense spending not only is accountable for fluctuations in GNP but is largely responsible for economic stability. More recently, the Council on Economic Priorities noted that military spending is the largest mechanism available to the federal government to stimulate the economy with purchases (DeGrasse 1983). Indeed, there is some empirical evidence linking military spending and changes in growth and aggregate demand. Nincic and Cusack (1979) demonstrate that there is a weak but significant bivariate link between military spending and real GNP per capita. Cusack and Ward (1981) show that changes (decreases) in aggregate demand are related to increases in defense spending. There is also evidence which implies that policy makers may manipulate defense spending for political gain. Nincic and Cusack (1979) and Cusack and Ward (1981) report results which show that US defense spending appears to follow electoral cycle patterns.1 The theoretical arguments and empirical results just presented might lead one to conclude that direct and powerful links should exist between defense spending and economic growth as well as other macroeconomic variables. However, a number of scholars (Crecine 1971; Fischer and Crecine 1981; Fischer and Kamlet 1984; Huntington 1961) have argued that, while defense spending is a controllable and malleable budgetary tool, defense budgeting decisions can only be understood in the context of non-defense budgeting desicions and fiscal and economic policy objectives. In a simple but illuminating way, Crecine captured this point in what he labelled ‘the Great Identity’: planned defense spending plus planned non-defense spending is equal to expected total federal revenues and the expected federal budget deficit. Thus,

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while it is plausible to assume that fiscal, non-defense, and defense spending policies are formulated independently, it is more likely that they are formulated interdependently, where compromises are reached among those policy-making groups representing defense, non-defense, and fiscal requirements.2 If defense, non-defense, and fiscal policy are formulated interdependently (where tradeoffs and compromises are reached), then it would be surprising, though not impossible, to find direct, independent links between defense spending and macroeconomic variables. A series of bivariate Direct Granger causality tests between four critical defense budgeting decisions—the Defense Service Agencies’ request for defense, the presidential budget request for defense, the congressional appropriation for defense, and actual defense expenditures—and five selected macroeconomic was performed to assess the existence and form of the direct relations among these variables.3 The variables employed and the data sources are discussed in the Appendix to this chapter. The time frame employed in this analysis covers the period 1953–80. The Reagan period is not included because others have shown that the Reagan administration departed dramatically from the broad budget priorities of other administrations (Kamlet et al. 1988; Mintz 1989). Thus, we would not expect to find similar budgetary, fiscal, and economic patterns in that time period. These four defense budget decisions are the most prominent and important decisions in a very lengthy budget process (Majeski 1983; Ostrom 1978). They are distinct defense budget decisions which can have independent effects on macroeconomic performance. It can be argued that requests and appropriations may have more direct and important effects on the economy than actual expenditures because economic experts may use them to form expectations of spending and deficits which, in turn, affect their economic choices and ultimately economic performance. The Granger causality results are reported in Table 11.1.4 The values reported in the table are F-statistics. A significant F-statistic allows for the rejection of the appropriate null hypothesis. For example, a significant Fstatistic in the column labelled ‘Independent’ implies that the null hypothesis —the two variables are independent—can be rejected. Similarly, a significant F-statistic under the column ‘X → Y’ (X ‘causes’ Y) means that the null hypothesis that X does not cause Y can be rejected. The final column labelled ‘Lag (0)’ contains the contemporaneous cross-correlations of the residuals of the two estimated equations. A significant contemporaneous crosscorrelation implies that the two time series may be simultaneously related.5 The Granger causality results reported in Table 11.1 indicate that budgetary decisions on defense spending are, in general, not related to— neither affect nor are affected by—macroeconomic variables. As expected, defense budgeting decisions do not appear to directly affect macroeconomic performance. There


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TABLE 11.1 Defense budgeting and macroeconomic variables: Granger causality results

Key: Lag (0) contemporary cross-correlation of residuals of simultaneous estimated equations implies cross-correlation exceeds two approximate standard deviations F-ratio: Independence One way

.05=2.29 .05=2.71

.01=3.23 .01=4.07

is one striking exception. The Granger results indicate that there is a very strong link between the Defense Service Agencies’ (DSA) budget request and the money supply represented by M1 and M2. The results suggest that both these macroeconomic indicators are affected by or caused by prior DSA requests. This is an unexpected result and will be examined in more detail later.6 Defense budgeting decisions do not appear directly to affect macroeconomic performance. It also appears that the reverse is the case; that is, macroeconomic performance does not directly affect defense budgeting decisions. The Fstatistics reported in the column head ‘X→ Y’ of Table 11.1 indicate that none of the macroeconomic variables ‘cause’ any of the four defense budgeting decisions. Whatever effects, if any, defense budgeting decisions have on

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macroeconomic performance, and vice versa, must be assessed within the context of non-defense budgeting and fiscal decisions (the remaining components of the ‘Great Identity’). While each component of the ‘Great Identity’ has significant economic, political, and/or strategic importance, the federal deficit appears to attract the most attention. Indeed, Crecine (1975) and Fischer and Kamlet (1984) argue that the size of the planned federal deficit is the principal macroeconomic tool available to the President. Fischer and Kamlet (1984) suggest that policy makers have limited abilities to manipulate total federal revenues. Revenues can be generated by tax increases and/or an improved national economy. Tax law changes are difficult to achieve and less malleable than fiscal or spending policy.7 Attempting to generate changes, much less improvements, in economic performance has proved difficult and highly unpredictable. Ward and Mahajan (1984) make a similar argument which they feel applies to developing countries as well as to advanced industrial nations such as the United States. Why? Policy makers believe that fiscal health and control reflected in the size of the deficit have a significant impact on the national economy. The implication is that fiscal decisions should directly affect macroeconomic performance. The reverse should also hold, particularly for the generation of federal revenues. Establishing such links is important since it is assumed that defense and nondefense budgeting decisions are directly related to fiscal policy. If fiscal policy, particularly in the form of deficits, is not related to economic performance, then there is little reason to assume that defense spending has much indirect impact on economic performance. A series of bivariate direct Granger causality tests was performed to assess the existence and form of direct relations between the five selected macroeconomic indicators and three fiscal policy variables—federal revenues, total federal spending, and federal deficits. The results are reported in Table 11.2. As might be expected, the null hypothesis of independence can be rejected in a number of instances. Federal revenues, total outlays, and deficits are not independent of one or more macroeconomic variables. However, while all three fiscal variables appear to be ‘caused’ or affected by one or more macroeconomic variables (see significant F-statistics under the column ‘X→V’), not one of the fiscal variables ‘causes’ or affects any of the five macroeconomic variables. The general picture, based upon the Direct Granger causality results reported in Tables 11.1 and 11.2, is not very promising. For the most part, defense budgeting decisions appear to be independent of macroeconomic performance and fiscal decisions, and while affected by economic performance, do not appear to affect economic performance. The implication is that, while defense budgeting and fiscal policy are, in part, controlled by economic performance, they are not (or cannot be) used to control or manipulate


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TABLE 11.2 Fiscal and macroeconomic variables: Granger causality results

Key: Lag (0) contemporary cross-correlation of residuals of simultaneous equations implies cross-correlation exceeds two approximate standard deviations F-ratio: Independence One way

.05=2.29 .05=2.71

.01=3.23 .01=4.07

except for federal government deficit: Independent One way

.05=2.36 .05=2.78

.01=3.36 .01=4.22

economic performance. Such conclusions, while reflecting the Granger results, should be examined more carefully. First, there are theoretical reasons buttressed by descriptive evidence to believe that defense budgeting and fiscal policy not only are affected by, but affect, economic performance. Second, the Granger results, coupled with the contemporaneous crosscorrelation of residuals, do suggest that budgetary and fiscal decisions may ‘cause’ some of the macroeconomic variables. Finally, simultaneous and interactive affects for defense budgeting and fiscal policy variables on macroeconomic performance may have been overlooked or obscured.

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A MODEL OF DEFENSE BUDGETING, FISCAL POLICY, AND MACROECONOMIC PERFORMANCE The task here is not to construct and test a ‘complete’ model of the defense budgeting process or a ‘complete’ macroeconomic model of the US economy. Instead, a plausible model of the defense budgeting-fiscal process with an emphasis on the links between defense budgeting and macroeconomic performance, defense budgeting and fiscal policy, and fiscal policy and macroeconomic performance is developed and tested. This approach is designed to provide a framework to assess the importance and plausibility of the possible linkages among these variables suggested by descriptive evidence, theory, and the Granger causality results reported earlier. The three budgeting and fiscal variables of concern are the change in levels of military expenditures (⌬ME), the change in the size of the federal deficit (⌬FD), and the change in the rate of change of non-military expenditures (⌬⌬NME). Non-military expenditures are included rather than revenues for two reasons. First, since it has been argued that deficit policy is the main fiscal instrument and that revenues are essentially fixed (difficult to manipulate or control), the inclusion of non-military spending brings in the third and final malleable component of the ‘Great Identity.’ Second, it provides an opportunity to assess the relative effects of military and nonmilitary spending on deficits and economic performance. The model is cast in terms of rates of change because policy decisions to manipulate fiscal or economic conditions are reflected in changes in spending and deficit levels rather than in absolute levels. Manipulation and control are attempted by increasing or decreasing spending and/or deficit rates rather than by altering absolute levels. Non-military expenditures have increased in every fiscal year since 1953 with one exception. Thus, unlike military expenditure, policy makers have not been successful in making absolute reductions in nonmilitary spending. Policy makers and others know that non-military expenditures will increase (even with recent budget cuts). What is important and what is assumed to affect fiscal policy and economic performance is how fast it increases (⌬⌬NME). The first step in developing a model of the interaction between budgeting decisions, fiscal policy, and economic performance is to produce a set of equations for each of the budgetary, fiscal variables discussed above. Once this is accomplished, then the system of interactive equations containing equations for other determined endogenous and exogenous variables can be estimated and analyzed. The problem of producing reasonable individual equations is one of both inclusion and exclusion. Prior evidence, both theoretical and empirical, indicates that there are many potentially relevant explanatory variables for each of the dependent variables discussed above. A


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discussion and rationale of the set of explanatory variables for each one of the three budgetary and fiscal variables is provided below. This is followed by a brief discussion of the procedures used to eliminate some of the ‘irrelevant’ explanatory variables from each equation. Based on these results, the remaining relevant endogenous and exogenous variables are determined and similar procedures are used to produce individual equations for these variables. The estimation results of the final set of individual equations are provided. The change in military expenditures is assumed to be a function of security needs, fiscal constraints, and economic performance. The change in Defense Service Agencies’ request (⌬DSA) is used as an indicator of security needs. It is the least ‘contaminated’ budget measure of what is required to meet the perceived external threat. Most defense budgeting and arms race models usually incorporate a more direct measure of external threat, such as prior Soviet military expenditures. A review of these analyses suggests that Soviet military expenditures (or other indicators of threat) usually do not contribute significantly to an explanation of changes in military spending. This is particularly true when budgeting and fiscal factors are also considered (Majeski 1983). It is acknowledged that other defense budgeting decisions contribute more than the DSA request to explaining changes in military expenditures (Majeski 1983; Ostrom 1978). The DSA request is used here because, while it does capture some budgetary factors, it more clearly reflects security concerns and is less affected by fiscal and economic concerns. Therefore, it is more probable that independent measures reflecting fiscal and economic concerns will contribute significantly to explaining changes in military expenditures. It is assumed that the policy makers’ expectations of the federal deficit (rather than the actual deficit) are an appropriate indicator of fiscal policy constraint. Finally, while a case can be made to include most of the macroeconomic indicators, the Granger causality results suggest that only the current inflation rate (⌬INF) appears to affect the change in military expenditures.8 The change in the federal deficit is assumed to be a function of budgetary requirements and current and prior economic performance.9 The change in defense spending (⌬ME) and the change in the rate of change in non-defense spending (⌬⌬NME) are used as measures of budgetary decisions and requirements. Note once again that it is the acceleration of increases in nondefense spending rather than simply increases which, in combination with the other factors, affects the federal deficit. Based on the Direct Granger tests (for both revenues and deficits), current and prior economic performance measures which appear to affect deficits are current and prior changes in economic growth (⌬RGNP), the current inflation rate (⌬INF), prior changes in the money supply, and the prior unemployment rate (⌬UN).

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The acceleration of changes in non-defense expenditures is assumed to be a function of fiscal constraints and current and prior economic performance. Fiscal constraints in the form of expectations of changes in the current deficit (⌬EFD) and changes in prior actual deficit (⌬FD) are assumed to affect acceleration in changes in non-military spending. Economic performance in the form of current and prior changes in economic growth (⌬RGNP), current and prior inflation rates (⌬INF), and current and prior unemployment rates (⌬UN) is also assumed to affect acceleration in changes in non-military spending. The first step in developing a system of interactive equations representing budgeting, fiscal policy, and economic performance is to produce reasonable single equation representatives for the three dependent variables discussed above. Each equation was estimated initially with all the explanatory variables which appeared (based on theoretical grounds and prior empirical evidence) to be relevant for the specific dependent variable. Criteria for removal were essentially statistical. Variables which did not contribute significantly were removed and the equation estimated again. Those which appeared least significant were removed first. As a check, each removed variable was added individually to the final single equation to determine if it contributed significantly after other ‘irrelevant’ variables had been removed. The basic purpose of this process is to eliminate spurious and/or dominated (associations which reflect linkages between third variables) relationships between the explanatory variables and each of the dependent variables. The single equation estimation results for the three variables presented in Table 11.3 represent the end result of this process. Table 11.3 also contains single equation estimates for six macroeconomic variables. With the possible exception of the inflation rate, the Granger causality tests imply that these six variables are not ‘caused’ by the three budgetary and fiscal variables. Thus, they can be treated as exogenous variables. Equations were estimated for these six variables for two reasons. First, current or lagged values of these variables appear as explanatory variables for one or more of the three fiscal and budgeting variables (⌬INF(t), ⌬RGNP(t-1), ⌬M1CO(t-1)). For completeness, the equations for these variables should be specified and then estimated together with the equations for the dependent variables (Granger and Newbold 1977). The inclusion of ⌬INF, ⌬RGNP and ⌬M1CO has a cascade effect and so equations for ⌬M2CO, ⌬UN and ⌬M1CU were also estimated.10 Second, the specification and estimation of equations for the money supply variables provide an opportunity to assess the robustness of the Granger causality finding that prior changes in DSA requests ‘cause’ changes in the money supply. The same statistical procedures used to generate the single equation estimations for the budgetary and fiscal variables were employed on the six macroeconomic variables. The original set of potential explanatory variables

b

a

OLS estimates. none of the DW-d statistics is significant at the .01 level. c autocorrelation was a problem. GLS estimation results presented where ␳=-.18.

coefficient significant at the .05 level. coefficient significant at the .01 level.

Notes:

TABLE 11.3 Single equation estimates

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for each of the six macroeconomic variables was based on standard macroeconomic theory, prior empirical analysis, and Granger causality results reported earlier. It should be obvious that this is not an effort to build or test a complete macroeconomic model. It is, rather, an effort to construct and estimate reasonable specifications of the macroeconomic variables. Admittedly, the specifications are not complete and some potentially relevant variables may likely be excluded. However, most of the typically cited relevant variables were included in the initial specification. The single equation estimation results of the rates of change of the budgetary fiscal and macroeconomic variables presented in Table 11.3 are quite interesting. 11 All three posited explanatory variables contribute significantly to an explanation of the change in military expenditures.12 The acceleration in changes in non-military expenditures has some surprises. First, the effects of fiscal constraint in the form of current expectations of the deficit and prior actual deficits are not very significant. Second, among the economic variables, only the current inflation rate and prior real growth contribute significantly. Surprisingly, current and prior unemployment rates do not appear to affect the acceleration of changes in non-military spending. The equation for the rate of change in the federal deficit supports the importance of increases in the rate of non-military expenditures and the prior change in the money supply. Prior federal government receipts do not turn out to affect significantly the change in the deficit nor does the prior change in the unemployment rate. The estimation results for the inflation rate, change in RGNP, and the change in the unemployment rate reflect the dominant importance of prior changes in the money supply. The inflation rate is mainly determined by current and prior changes in the money supply and current changes in total federal government outlays.13 Changes in the prior deficit (significant in a bivariate setting) no longer contribute significantly to explaining the inflation rate. Changes in real growth are also a function of changes in the money supply as well as changes in the unemployment rate and a variable (MIL) which measures military conscription (see Barro 1977). Since MIL is large when war efforts are large, its significant positive effect on real growth is probably a function of war efforts, because war involvement usually helps to spur economic growth.14 The unemployment rate is affected by the money supply, military conscription (a large draft reduces unemployment), and the real growth rate (increases in real growth lead to decreases in unemployment). Note that the bivariate links between the unemployment rate and the acceleration of non-military expenditures and the change in the current expected deficit no longer are significant. The three money supply equations (M1-constant dollars, M2-constant dollars, M1-current dollars) are generally a function of the prior inflation


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rate, the change in the prior federal deficit, the growth rate, and, surprisingly, changes in the prior DSA request. When the inflation rate increases in the previous year, the money supply is tightened. Increases in the prior federal deficit create a tightening of the money supply. Prior real growth is related to a tightening of the money supply. Finally, prior increases in the rate of change of the DSA request (an indicator of increases in defense spending) are positively related to increases in the money supply. As an additional check on the money supply/DSA request relationship, the prior changes in total government outlays and non-defense spending were included in the estimation of the money supply equations. In no instance was any of these expenditures variables significant. Due to the apparent simultaneous, interactive nature of the process, the individual equations were re-estimated as a system and the results are presented in Table 11.4.15 In general, the results of the estimated system are similar to the single equation estimates. Most of the changes in the parameter estimates are slight. However, the results reported in Table 11.4 do reflect the interactive nature of the budgeting, fiscal, macroeconomic process. Most of the relationships isolated for the non-interactive single equation results remain significant with some important exceptions. The two budgeting decisions, ⌬ME and ⌬⌬NME, are still strongly affected by the changes in current inflation rate. However, fiscal constraints, either in the form of the prior change in the actual deficit or the expectation of the change in the deficit, no longer appear to affect significantly these budgeting decisions. Current security requirements and organizational momentum in the form of changes in the Defense Service Agencies’ request and the current inflation rate remain crucial determinants of the change in military expenditures. As might be expected, both are positively associated with changes in military spending. The acceleration of non-military spending remains positively related to the change in the current inflation rate and negatively related to prior changes in real economic growth. Increases in non-military spending are accelerated following declines in real growth. This result may reflect a conscious attempt to stimulate growth through government spending, including increases in non-military spending. However, because declines in real economic growth are strongly linked to increases in unemployment, it may also reflect the necessities of non-military spending increases. Fiscal policy, reflected by changes in the federal deficit, remains strongly a function of the acceleration of non-military spending. Accelerating nonmilitary spending generates increases in the deficit. The change in the federal deficit is no longer affected significantly by prior changes in the money supply. The results for the measures of macroeconomic performance (⌬INF,

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TABLE 11.4 Three-stage least squares estimates: system estimation

Notes: coefficient significant at the .05 level. coefficient significant at the .01 level.

⌬RGNP, ⌬UN) remain essentially unchanged from the single equation results. The change in the inflation rate remains largely a function of the change in the current money supply and changes in total government spending. Changes in real growth also remain largely a function of current and prior changes in the money supply and the current change in the unemployment rate. The change in the unemployment rate remains affected by prior changes in the money supply but is largely a function of current changes in real growth. Finally, the measures of change in the money supply remain a function of prior changes in macroeconomic performance (inflation and growth), prior fiscal restraint (changes in the deficit) and prior changes in security requirements (changes in Defense Service Agencies’ requests).


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CONCLUSIONS This analysis has focused on the potential effects of defense spending on fiscal policy and macroeconomic performance. The results obtained from a simultaneous equation model of government budgeting, fiscal policy, and economic performance indicate that the relationships among the components are interactive and complex. There is no evidence that defense spending directly affects either fiscal policy or economic performance. Simple bivariate associations between changes in military spending, real growth, and the federal deficit appear to be spurious and are eliminated when other factors are taken into account. Indeed, the acceleration of non-military spending appears to have had a much more important and direct impact on the federal deficit and the inflation rate. Whatever effects policy makers may have hoped to create, if any, in fiscal policy and economic performance by manipulating the more controllable area of defense spending, they appear to be swamped by the seemingly uncontrollable acceleration of non-military spending. While defense spending does not appear to directly affect fiscal policy or economic performance, a number of other important relationships emerge. First, changes in defense spending are affected by the current inflation rate. Indeed, there appears to be a ‘simultaneous’ relationship between government spending (both military and non-military) and inflation. Second, the acceleration of non-military spending appears to have a significant but indirect effect on economic performance. The federal deficit and the money supply are the crucial intervening variables in the non-military spendingeconomic performance relationship. Current acceleration of non-military spending is a principal determinant of the change in the federal deficit. Prior changes in the federal deficit are an important determinant of current changes in the money supply, which, in turn, is an important determinant of economic performance. Finally, the analysis suggests a possible indirect link between changes in military spending and economic performance. Once again, the money supply is a crucial intervening variable. Prior changes in the Defense Service Agencies’ request were found to ‘Granger cause’ changes in the money supply. The very strong bivariate relationship withstood the multivariate simultaneous equation analysis. Even with the inclusion of the theoretically relevant explanatory variables (economic growth, federal deficits, the inflation rate), prior changes in DSA request remain highly significant. Prior changes in DSA request appear to represent or have a non-spurious and economically independent effect on the money supply. Two conclusions can be drawn. First, the effect is still spurious and will be eliminated if other relevant economic determinants are included. Second, the DSA request, employed here as an indicator of external threat and security needs, does

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affect money supply decisions.16 While the first conclusion cannot be dismissed, most of the typically prominent relevant economic indicators have already been included in the analysis.17 This leaves us with the second conclusion; however, before this can be accepted as plausible, a reasonable explanation must be offered for the relationship. A potential solution is to assume that the Federal Reserve, whose policies most affect the money supply, views or uses prior changes in DSA requests as an indicator of expected increases in security needs and defense spending. (Note a similar argument can be made for the other relevant explanatory variables—prior change in the inflation rate, prior change in the federal deficit, prior change in real growth.) Recall that money supply decisions are not affected by actual changes in military spending. Why might expectations of military spending be relevant to money supply decisions? It is not because they are direct indicators of future deficits. Prior actual deficits are already included in the money supply equations and changes in the deficit are largely determined by the acceleration of non-military expenditures. However, large increases or decreases in DSA requests do indicate that the administration perceives greater security threats. While cuts in budget requests for military spending by the President and Congress almost always follow, increased threats do translate into increased expenditures. Large increases in the security threat turn out to be a delayed (one-year) indicator of large increases in the deficit, and the empirical evidence suggests that those whose actions must directly affect the money supply may pick up on that relationship. The results of this analysis do show that the relations among budgetary choices, fiscal policy, and macroeconomic performance are complex and interactive. As a result, the typical simplified solutions offered to manipulate and control these budgetary and macroeconomic variables are not likely to be successful, and conclusions drawn from the examination of isolated associations are likely to be quite misleading. The relationships determined in the analysis among budgetary, fiscal, and macroeconomic indicators are plausible. However, before any policy implictions are drawn, these relationships must be examined more closely and tested more rigorously. Certainly, a more complete and carefully specified model of the economy, as well as budgetary and fiscal decision making, must be incorporated. In addition, the role of expectations must be assessed carefully and modeled more explicitly.


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APPENDIX: VARIABLES AND DATA SOURCES

NOTES 1

2

The use of electoral patterns and cycles to determine if there is manipulation of the economy for political gains is based on the work of a number of economists and political scientists (Frey and Schneider 1978; Hibbs 1977; Keech 1980; Kramer 1971; MacRae 1977; Nordhaus 1975; Tufte 1978). Fischer and Crecine (1981) and Fischer and Kamlet (1984) present a strong argument for interdependence and provide significant empirical support for that position. They do note that there is some descriptive evidence to suggest that defense spending policy decisions have been made independently of non-defense and fiscal policy decisions. However, their analysis indicates considerable interdependence among these variables for most of the post-World War II era.


234 3

4

5

6

7

8

9

10

11

The Granger causality approach is a statistical procedure which is very useful in determining if there are correlational links among two time series. It is particularly helpful in determining lagged relationships and the directions of relationships. A variable X is said to ‘Granger cause’ another variable Y, if ‘Y can be better predicted from the past X and Y than the past of Y alone, other relevant information being used in the prediction’ (Pierce 1977:11). The Granger approach is used frequently in economic and business analysis and has been employed by political scientists (see Majeski and Jones 1981; Freeman 1983; and Starr et al. 1984). For an excellent discussion of the Granger causality approach and its relevance for the analysis of political relationships, see Freeman (1983). The residuals from the estimated equations were analyzed for higher-order autocorrelation using the Box-Ljung small sample Q statistic (Box and Ljung 1976). None was statistically significant at the .05 level, so autocorrelation is not a problem. The presence of significant contemporaneous cross-correlation of residuals can have many causes. Therefore, it can be used only to suggest the possibility of simultaneous relationships. Nonetheless, it is helpful since the Direct Granger approach cannot deal with simultaneous or ‘instantaneous’ ‘causality.’ The results imply that there is no link between military expenditures and the nominal growth rate (NGNP), contrary to similar comparisons made by Nincic and Cusack (1979). The inflation results confirm the negative results reported by Starr et al. (1984). The Reagan tax cut, coupled with forecasts of increases in economic growth and nondefense spending ‘cuts,’ is a novel approach to coping with large deficits. As Fischer and Kamlet (1984) comment, it may reinforce the historical aversion to tax cuts. Based on preliminary statistical results, three other variables were considered but excluded from further analysis. A dummy variable to capture US war involvement was not found to contribute significantly. An electoral cycle variable was included but found to be irrelevant. Finally, the typical measure of bureaucratic momentum—prior changes in military expenditures—was also found not to contribute significantly. This is not atypical when rates of change of budgetary variables are examined. It is obvious that deficits are a function of spending and revenues. Since it has been assumed that spending is malleable and revenues essentially fixed, I have chosen to include spending and those economic factors which affect revenues rather than revenues directly. If an equation for ⌬INF is included and the final specification is represented in Table 11.3, then an equation for ⌬M2C0 should also be included. This is what is meant by a cascade effect. The lists of variables chosen for each variable presented below are those generally cited by researchers as being potentially relevant (see Barro 1977, 1978; Fair 1978; Mishkin 1982a, 1982b). INF UN RGNP M1Co M2Co M1Cu

12

— M1Co(t), M1Co(t–1), M2Co(t), M2Co(t–1), FD(t–1), ME(t–1), NME(t–1), FGO(t), MIL(t), M1NW(t) — RGNP(t), RGNP(t–1), MIL(t),M1NW(t), M1Cu(t), M1Cu(t–1), M1Cu(t–2) — UN(t), UN(t–1), MIL(t), M1Co(t), M2Co(t), M2C0(t–1), INF(t), INF(t-1) — UN(t–1), RGNP(t–1), INF(t–1), DSA(t–1), M1Co(t–1) — UN(t–2), RGNP(t–1), INF(t–1), DSA(t-1), M2Co(t–1) — UN(t), UN(t–1), DSA(t–1), NGNP(t), FD(t-1), M1Cu(t–1)

The inflation result does not conflict with those of Starr et al. (1984), since their analysis of the relationship between defense expenditures and inflation specifically ruled out instantaneous or simultaneous interaction.

Defense budgeting, fiscal policy, and economic performance 13

14

15

16 17

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Changes in military spending and non-military spending were also tested separately. However, while non-military spending contributed more significantly than military spending, total federal outlays proved to have the most significant effect on the inflation rate. This is a typical argument, particularly among ‘radical’ economists. However, increased defense spending to sustain a war effort is normally linked to nominal growth rather than real growth because of increases in inflation. The link between war and inflation (see Hamilton 1977; Stein 1980) is reasonably well documented. However, inflation has been delayed or deferred by deficit spending (usually not taxation or non-defense spending cuts), so real growth is experienced until the effects of deficit spending produce inflation. Three-stage least squares (3SLS) is employed because of the covariance across equations. Employing 3SLS improves the efficiency of 2SLS estimates if there is significant covariance across equations. A third conclusion is possible. Prior changes in DSA requests are spurious and their significance reflects the importance of other non-economic factors. As Beck (1984) discusses, many different independent variables could be used because there is no theory to show what the Federal Reserve actually does focus upon to make decisions that affect the money supply. Beck does argue that, since the Federal Reserve does attempt to affect future policy, leading indicators are more sensible than ‘coincident’ or ‘lagging’ indicators as independent variables. His argument hinges on their use as economic forecasts.

REFERENCES Barro, R.J. 1977. Unanticipated money growth and unemployment in the United States. American Economic Review 67:101–15. Barro, R.J. 1978. Unanticipated money, output and the price level in the United States. Journal of Political Economy 86 (4):549–80. Beck, N. 1984. Domestic political sources of American monetary policy 1955–82. Journal of Politics 46 (3):786–817. Box, G.E.P. and Ljung, G.M. 1976. A modification of the overall chi-square test for lack of fit in time series models. Technical Report No. 477, Department of Statistics, University of Wisconsin—Madison. Carnegie Endowment for International Peace. 1981. Challenges for U.S. National Security: Defense Spending and the Economy. New York: author. Chan, S. 1985. The impact of defense spending on economic performance: a survey of evidence and problems. Orbis 29:403–34. Crecine, J.P. 1971. Defense budgeting. In W.W.Cooper, R.F.Byrne, A.Charnes, O.A. Davis, and D.Gilford (eds), Studies in Budgeting, pp. 210–61. Amsterdam: North Holland. Crecine, J.P. 1975. The shape of the defense budget: internal DoD resource allocation. In Appendices: Commission on the Organization of the Government for the Conduct of Foreign Policy, Vol. 4. Washington, DC: US Government Printing Office. Cusack, T.R. and Ward, M.D. 1981. Military spending in the U.S., U.S.S.R., and China. Journal of Conflict Resolution 25:429–69. Cypher, J. 1977. Capitalist planning and military expenditures. Review of Radical Political Economics 6:1–19.

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DeGrasse, R.W. 1983. Military Expansion and Economic Decline: The Impact of Military Spending on U.S. Economic Performance. Armonk, NY: Council of Economic Priorities/ M.E.Sharpe. Fair, R.C. 1978. The sensitivity of fiscal policy effects to assumptions about the behavior of the Federal Reserve. Econometrica 46:1165–79. Fischer, G.W. and Crecine, J.P. 1981. Defense spending and non-defense spending, and the need for fiscal restraint: two models of the presidential budgetary process. Arms Control 2: 65– 106. Fischer, G.W. and Kamlet, M.S. 1984. Explaining presidential priorities: the competing aspirations levels model of macrobudgetary decision-making. American Political Science Review 78 (2):356–71. Freeman, J.R. 1983. Granger causality and time series of political relationships. American Journal of Political Science 27:327–58. Frey, B.S. and Schneider, F. 1978. An empirical study of politico-economic interaction in the United States. Review of Economics and Statistics 60:174–83. Granger, C.W.J. and Newbold, P. 1977. Forecasting Economic Time Series. New York: Columbia University Press. Hamilton, E.J. 1977. The role of war in modern inflation. Journal of Economic History 37:13– 19. Hibbs, D.A. Jr 1977. Political parties and macroeconomic policy. American Political Science Review 71:1467–87. Hitch, C. and McKean, R. 1961. The Economics of Defense Spending in the Nuclear Age. Cambridge, MA: Harvard University Press. Huntington, S.P. 1961. The Common Defense: Strategic Programs in National Defense. New York: Columbia University Press. Kamlet, M., Mowery, D.C., and Su, T. 1988. Upsetting national priorities: the Reagan administration’s budgetary strategy. American Political Science Review 82:1293–307. Keech, W.R. 1980. Elections and macroeconomic policy optimization. American Journal of Politics 24:345–67. Kramer, G. 1971. Short term fluctuations in U.S. voting behavior, 1896–1964. American Political Science Review 60:131–43. MacRae, D. 1977. A political model of the business cycle. Journal of Political Economy 85: 239–63. Majeski, S.J. 1983. Mathematical models of the U.S. military expenditure decision-making process. American Journal of Political Science 27:485–514. Majeski, S.J. and Jones, D.L. 1981. Arms race modelling: causality analysis and model specification. Journal of Conflict Resolution 25:259–88. Mintz, A. 1989. Guns versus butter: a disaggregated analysis. American Political Science Review 83 (4):1285–93. Mishkin, F.S. 1982a. Does anticipated monetary policy matter? An econometric investigation. Journal of Political Economy 80 (1):22–51. Mishkin, F.S. 1982b. Does anticipated aggregate demand policy matter? Further econometric results. American Economic Review 72 (4):788–803. Nincic, M. and Cusack, T.R. 1979. The political economy of U.S. military spending. Journal of Peace Research 26:101–15.


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Nordhaus, W.D. 1975. The political business cycle. Review of Economic Studies 42:1690–190. Ostrom, C.W. Jr. 1978. A reactive linkage model of the U.S. defense expenditure policymaking process. American Political Science Review 72:941–57. Pierce, D. 1977. Relationships—and lack thereof—between economic time series, with special reference to money and interest rates. Journal of the American Statistical Association 72:11– 22. Smith, R.P. 1977. Military expenditures and capitalism. Cambridge Journal of Economics 1:61– 76. Starr, H., Hoole, F.W., Hart, J.A., and Freeman, J.R. 1984. The relationship between defense spending and inflation. Journal of Conflict Resolution 28:103–22. Stein, A.A. 1980. The Nation at War. Baltimore, MD: Johns Hopkins University Press. Tufte, E. 1978. The Political Control of the Economy. Princeton, NJ: Princeton University Press. US Congressional Budget Office. 1983. Defense Spending and the Economy. Washington, DC: US Government Printing Office. Ward, M.D. and Mahajan, A.K. 1984. Defense spending, security threats and government deficits: a case study of India, 1952–1979. Journal of Conflict Resolution 28:382–419.

CHAPTER 12

Military Burden and Economic Hegemonic Decline: The Case of the United States Chi Huang and Francis W.Hoole

Is Paul Kennedy correct when he suggests that if ‘too large a proportion of the state’s resources is diverted from wealth creation and allocated instead to military purposes, then it is likely to lead to a weakening of national power over the longer term’ (Kennedy 1987: xvi) and ‘[g]reat powers in relative decline instinctively respond by spending more on “security”’ (Kennedy 1987:xxiii)? More importantly, for our purposes, are these insights useful in understanding what has happened to the United States in the post-World War II era? The latter question was debated in the 1988 presidential campaign in the United States and has also received serious consideration in the academic literature (e.g. Huntington 1988; Kupchan 1989). We will attempt to contribute to this ongoing dialogue by examining in a systematic empirical manner the relationship between military burden and economic hegemonic power for the United States during the 1951–85 era. We begin by examining the concepts of economic hegemony and military burden and discussing how they are measured. Our basic orientation toward the empirical examination of the relationship between our indicators of these concepts is then discussed and the results of our analysis are presented. Finally, our conclusions are formulated and a perspective is offered on the relationship between military burden and economic hegemonic power for the United States during the postWorld War II era.

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Military burden and economic hegemonic decline

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ECONOMIC HEGEMONY It is difficult to think of a concept that has been more widely discussed recently by students of international relations than hegemony. Neo-Marxist scholars such as Bergesen (1985), Chase-Dunn (1981), and Wallerstein (1974, 1980) have considered it within the context of a world systems approach, whereas individuals such as Modelski (1987a, 1987b) and Thompson (1983a, 1983b, 1988) have utilized it in a theory of the long cycle. Still others, such as Gilpin (1981) and Keohane (1980, 1984), have given hegemony a major role in their approach to international political economy, whereas researchers such as Doran (1983a, 1983b, 1985) and Doran and Parsons (1980) with their power cycle theory, and Organski and Kugler (1980), with their transition model, utilize the changing status of hegemonic power in their explanations of global conflict. Some scholars, such as Kennedy (1987), have taken a clear historical approach to hegemony, while others, such as Vayrynen (1983, 1987), have been more eclectic in orientation. Numerous others, such as Hoole and Huang (1989b), Krasner (1981), Rapkin (1987), Rupert and Rapkin (1985), and Russett (1985) have also contributed additional perspectives to the dialogue concerning hegemony. Upon close examination it becomes clear there is not a single definition of the concept of hegemony that is embraced by all scholars. One of the more widely discussed and debated definitions has been presented by Keohane (1984:32): ‘The theory of hegemonic stability…defines hegemony as preponderance of material resources.’ He goes on to note (1984:32): ‘Four sets of resources are especially important. Hegemonic powers must have control over raw materials, control of sources of capital, control of markets, and competitive advantages in the production of highly valued goods.’ It is worth noting that this definition gets at the essence of hegemony as employed by numerous scholars and, in our opinion, it is not unreasonable to use it as a representative definition of the concept of hegemony. There appears to be widespread agreement that World War II clearly established the United States as the hegemonic power in the global system. Indeed, the early post-World War II era saw the United States with a far greater ‘preponderance of material resources’ (Keohane 1984:32), in both absolute and relative terms, than any country in the history of the modern global system. There is, however, serious disagreement about whether there has been a decline in the hegemonic power of the United States during the post-World War II era. Many scholars, such as Gilpin (1981), Kennedy (1987), Keohane (1984), Krasner (1981), and Rupert and Rapkin (1985), appear to believe that the United States has since 1945 seen a significant loss of hegemonic power, whereas others such as Huntington (1988), Kugler and

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Organski (1989), Russett (1985), and Strange (1982) remain somewhat skeptical about this proposition. At least part of the difference of opinion seems to revolve around whether the focus is on economic resources or a broader conception of resources which also includes more traditional indicators of power such as military and political capabilities and whether the emphasis is on ‘power base…[or] power as control over outcomes’ (Russett 1985:208). Another distinction which can divide studies of hegemony is whether the focus is on absolute or relative measures of resources. The strongest case for the decline argument can be made when the emphasis is on the power base and relative measures of economic resources. Indeed, what Huntington (1988:76) calls ‘declinist writings’ have, he argues, emphasized three core propositions: ‘the United States is declining economically compared to other market economy countries…, economic power is the central element of a nation’s strength, and hence a decline in economic power eventually affects the other dimensions of national power…, the relative economic decline of the United States is caused primarily by its spending too much for military purposes’ (Huntington 1988:76–7). Interestingly, Huntington states that in ‘discussing declinist ideas, I will rely primarily on Kennedy’s writing and statements, since they have had the greatest impact on public debate in the United States’ (1988:76). Because it is our intention to examine empirically the third of these socalled declinist propositions it seems only fair to do so in a manner which is consistent with the first two declinist propositions. Hence, we will focus on the relative economic power base of the United States in the post-World War II era. This is clearly consistent with Kennedy’s orientation:

…so far as the international system is concerned, both wealth and power are always relative and should be seen as such. (Kennedy 1987:xxii) …the United States’ favorable economic position at that point in history [1945] was both unprecedented and artificial, (p. 432) The real question was not ‘Did the United States have to decline relatively?’ but ‘Did it have to decline so fast?’ (p. 432)

Accordingly, in operationalizing the concept of economic hegemony we decided to employ a measure of the United States’ percentage of the gross national product of the larger family of nations. This indicator not only is employed by Kennedy but is also widely used in the literature dealing with hegemonic power. Fortunately, it was possible to obtain for the 1951–85 era annual estimates

Military burden and economic hegemonic decline FIGURE 12.1

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Military burden and economic hegemony of the US, 1951–85

of the gross national product of the United States and of the developed market economies (the first world) from the Office for Development Research and Policy Analysis of the United Nations in New York.1 Using current dollar figures, we calculated the annual United States percentage of the total gross national product of the developed market economies. These data are plotted in Figure 12.1. It is interesting to note that in 1951 the United States share of the gross national product was 59 percent, whereas by 1980 it was 35 percent, before beginning an upward trend which reached 45 percent in 1985. The economic hegemonic decline of the United States, of course, was not a constant one. There were decreases in 24 different years and increases in 10 years. The range of annual changes was from -3.4 percent in 1973 to+3.8 percent in 1981, with an average magnitude of change of -0.4 percent. The relative decline of the economic power base of the United States in the post-World War II era is primarily the story of the US decline within the group of developed market countries, which includes nation-states such as Japan and West Germany. It is captured by the information contained in Figure 12.1.

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MILITARY BURDEN Discussions of military spending, both as cause and as effect, are frequently found in both the academic literature and the popular media. There is, however, no common agreement regarding either the determinants of defense spending or its impact or whether its consequences are negative or positive. There does appear to be agreement that military spending is of sufficient significance that careful analyses of it are of considerable importance. Indeed, it might be argued that this importance is demonstrated by the publication of the book in which this chapter appears. The academic literature contains a wide variety of perspectives and approaches to the study of military spending. For example, a neo-Marxist approach has been employed by numerous scholars such as Griffin et al. (1982), Smith (1977), and Szymanski (1973), whereas others such as Ostrom (1977, 1978) and Ward (1984) utilize a policy-making and action-reaction orientation. Some scholars such as Mintz (1989), Mintz and Huang (1991), and Russett (1982) focus upon the relationship between defense expenditures and welfare spending, whereas others such as Starr et al. (1984) have examined the relationship between defense spending and inflation. Various scholars such as Nincic and Cusack (1979) and Krell (1981) have examined the economic causes of defense spending, whereas others such as Cappelen et al. (1984), Duchin (1983), Grobar and Porter (1989), Gyimah-Brempong (1989), Lindgren (1984), Mintz and Huang (1990), and Rasler and Thompson (1988), have studied various aspects of the impact of defense spending upon economic performance. An especially valuable evaluation of the literature dealing with the impact of defense expenditures on economic performance can be found in Chan (1985). Kennedy’s focus is upon what is known in the literature dealing with defense spending as military burden, which is defined for a country as the total military expenditures as a proportion of the gross national product of the country. For example, recall Kennedy’s use of the ‘proportion of the state’s resources…allocated…to military purposes’ (Kennedy 1987:xvi). Elsewhere he talks about ‘defense expenditure…as a proportion of nation product’ (1987:433) and speculates about the impact on hegemonic decline of military expenditures when they represent different percentages of a country’s gross national product (1987:532, 609). Accordingly, in operationalizing the concept of military burden we decided to employ an annual measure which states military expenditures for the United States as a percentage of the gross national product of the United States. This indicator not only is employed by Kennedy but is also widely used in the literature dealing with defense expenditures. It was possible to obtain for the 1951–85 era annual estimates of the


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military expenditures and the gross national product for the United States from the US Department of Commerce’s publications The National Income and Product Accounts of the United States, 1929–1982 (1986) and Survey of Current Business (1987). Using current dollar figures, we calculated the annual military burden of the United States. These data are plotted in Figure 12.1. The proportion of gross national product devoted to defense spending in the United States has actually been declining during the 35-year time period being examined. The defense burden was near 10 percent in the 1950s, close to 8 percent in the 1960s, and during the 1970s dropped below 7 percent. In terms of changes, the sharpest increase (+3.0 percent) and decrease (-2.0 percent) occurred at the beginning and end of the Korean war. The most persistent military buildup during peacetime occurred during the Reagan administration, with an average annual change of +0.25 percent between 1981 and 1985. Overall, however, the average magnitude of change in military burden was -0.1 percent during the 1951–85 era. This is, of course, curiously unlike what we should expect to see in an era of economic hegemonic decline if Kennedy is correct.

THE RELATIONSHIP BETWEEN MILITARY BURDEN AND ECONOMIC HEGEMONY Rupert and Rapkin (1985:155–6) made the following observation: Despite its theoretical centrality, capability decline [economic hegemony] is often regarded as so evident a phenomenon as to obviate the need for detailed examinations beyond comparison of base and terminal year values of one or a few indices of capabilities. There is in fact surprisingly little systematic knowledge, even of a descriptive sort, of the process of decline.

In our opinion, this assessment, which appeared in 1985, of the paucity of knowledge of the process of economic hegemonic decline may be seen today as a bit of an overstatement. For example, Bergesen, in his neo-Marxist interpretation of cycles in the global economy, argues that ‘six cycles… [hegemony, colonization-decolonization, war-peace, mercantilism-free trade, economic expansion-contraction, and merges among business firms] are all causally interconnected and reflect the overall movement and laws of the global system as a whole’ (1985:329). Hoole and Huang (1989b), however, find in an empirical analysis of the global system for the 1954–85 era that changes in economic hegemony have an impact on the changes in civil war, international war, size of the global economy, and economic interdependence, but that changes in civil war, international war, size of the

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global economy, and economic interdependence do not have an impact on changes in economic hegemony. Furthermore, scholars such as Gilpin (1981), Keohane (1980), and Olson (1983) do suggest explanations of relevance for understanding economic hegemonic decline. However, it is the case today that there is no integrated set of explanations that has undergone rigorous empirical examination and received widespread academic endorsement as a plausible and acceptable basis for understanding economic hegemonic decline. We are interested, in this chapter, in building upon Kennedy’s (1987) explanation of economic hegemonic decline as being a function of military burden and we will examine empirically the question of whether the military burden of the United States contributed significantly to the economic hegemonic decline of the United States during the 1951–85 era. Incidentally, we know of no previous systematic empirical study which examines the relationship between our indicators of military burden and economic hegemony. The indicators of military burden and economic hegemony defined and operationalized above will be employed in our analysis. Because of Kennedy’s frequent use of phrases such as long term (1987:xxiii, 533), longer term (1987:xvi), and over time (1987:533) to describe the relationship between military burden and economic hegemony, we decided to conduct the analysis in a manner that would allow for the possibility of higher-order impacts of military burden upon economic hegemonic decline. Interestingly, Kennedy (1987:xxiii), as noted above, also suggests that economic hegemony may have an impact on military burden. Accordingly, we decided also to examine empirically this relationship for the United States for the 1951–85 era. Our reading of Kennedy suggests that this analysis also should allow for the possibility of long-term higher-order impacts (see also Mintz and Huang 1990, 1991). Kennedy is actually talking about a relationship between military burden and economic hegemony which contains a complex feedback mechanism. For example, notice his explanation of a dilemma facing countries in economic hegemonic decline:

as their relative economic strength is ebbing, the growing challenges to their position have compelled them to allocate more and more of their resources into the military sector, which in turn squeezes out productive investment and, over time, leads to the downward spiral of slower growth, heavier taxes, deepening domestic splits over spending priorities, and a weakening capacity to bear the burdens of defense. (1987:533)


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Hence Kennedy seems to be describing a system whereby economic hegemonic decline leads over time to an increased military burden, which in turn leads over time to more economic hegemonic decline. Accordingly, we decided to employ a system of equations in our analysis and to allow for the possibility of both long-term relationships and short-term oscillations between the two indicators. Taking all of this into account resulted in a decision to employ the approach to statistical analysis known as ‘Direct Granger causality’ (Freeman 1983; Hoole and Huang 1989a). A variable X is said to ‘Granger cause’ another variable Y, if ‘Y can be better predicted from the past X and Y together than the past Y alone, other relevant information being used in the prediction’ (Pierce 1977:11). The Granger approach allows us to ascertain whether military burden has an impact on economic hegemony, if economic hegemony has an impact on military burden, if there is a two-way relationship between military burden and economic hegemony, or if there is no relationship between military burden and economic hegemony. The basic Direct Granger approach would entail use of the following equations in our empirical analysis: (12.1) (12.2) where MB is military burden, EH is economic hegemony, t is a year, and u and v are the error terms and represent factors not explicitly incorporated in the equations. A higher-order impact of the variables is possible because of the summation signs, and oscillations in the impact of the variables are possible because the individual coefficients (p’s) are unconstrained in their ability to fluctuate between positive and negative values. A limited number of lags will be identified empirically and a model estimation process that takes into account the possible cross-correlation of error terms will be employed to capture the conception of the model as a system. Explanations of military burden and economic hegemony other than economic hegemony and military burden will be taken into account to the extent that their impacts have been systematic in the past or are reflected in the error terms. The test of the hypothesis that the p21,i parameters are jointly zero tells if military burden Granger causes economic hegemony, while a test of the hypothesis that the p12,i parameters are jointly zero indicates whether or not economic hegemony Granger causes military burden. If both null hypotheses are accepted, we conclude that there is no relationship between military burden and economic hegemony. If both null hypotheses are

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rejected, we conclude that there is Granger feedback between military burden and economic hegemony. However, as will be demonstrated shortly, this basic Direct Granger approach can soon become much more complicated as modifications and elaborations are introduced to take into account factors such as stationarity, co-integration of the time series of data, and long-term equilibrium in the relationship between variables.

THE EMPIRICAL ANALYSIS The Direct Granger method is equivalent to testing hypotheses in the context of a vector autoregression (VAR) system. Accordingly, we began our analysis with a focus on the warning of Engle and Granger (1987:259) that, if a vector of time series is co-integrated, that is, if each element of the vector first achieves stationarity after differencing but a linear combination of their levels is already stationary, then a typical VAR ‘will be misspecified if the data are differenced, and will have omitted important constraints if the data are used in levels.’ To avoid such misspecification, a VAR in differences must also include the lagged levels of variables. Therefore, the procedure we followed was: (1) to examine the individual series for stationarity; (2) to run a regression in levels and use its residuals to test for co-integration; (3) to model the dynamics in terms of the (appropriately adjusted, if necessary) VAR system; and (4) to test competing hypotheses within the framework of such a VAR model. We first applied Box and Jenkins’ (1976) univariate autoregressiveintegrated moving average (ARIMA) model to identify each of the time series. Given the gradual declining trend of both defense burden and economic hegemony, it is not surprising that their autocorrelations taper off slowly, which is an indication of nonstationarity. Since both series reach stationarity after first differencing, they are integrated of order 1, or I(1). For the differenced defense burden variable, it was found that a secondorder autoregressive model, or AR(2), fits the data best. For the differenced economic hegemony variable, a first order autoregressive model, or AR(1), provides the best fit. Hence the levels of defense burden and economic hegemony can be represented by ARIMA (2, 1, 0) and ARIMA (1, 1, 0) models respectively. Since both military burden and economic hegemony are correlated highly over time (r=.933) and both are I(1), it is plausible that they are cointegrated. That is, there may exist a linear combination of MBt and EHt which is already stationary. To test for co-integration, we first ran two possible co-integrating regressions: MBt on EHt and EHt on MBt, and then


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used the co-integrating Durbin-Watson (CRDW), Dickey-Fuller (DF), and augmented Dickey-Fuller (ADF) tests on the residuals (which are called by Engle and Granger, 1987, the ‘error correction terms’). The ADF test allows for more complicated dynamics by including lagged differences among the regressors. Following the recommendation of Engle and Yoo (1987:157), we used Akaike’s (1973, 1974) information criterion (AIC) and Schwarz’s (1978) criterion (SC) to choose the number of lags. Both the AIC and SC selected a one-lagged difference to be included in the ADF test. Table 12.1 reports the coefficient of the co-integrating regression and the results of the three tests. All of the test statistics exceed the 0.05 significance level provided by Engle and Yoo (1987). The ADF tests (recommended by Engle and Granger 1987) on both co-integrating regression residuals are significant at the 0.01 level.2 Therefore, we rejected the null hypothesis that the two series are non-co-integrated. The implication of rejecting the null hypothesis of non-co-integration for our study is that a typical bivariate VAR model in differenced variables will be misspecified. Engle and Granger (1987) demonstrate that co-integration implies the presence of the lagged levels of the variables in a VAR in differences. This means that the correct bivariate VAR model for this study should include not only the distributed lags of changes of defense burden and economic hegemony, but also the lagged levels of them. We assumed that ⌬X,=(⌬MBt ⌬EHt)’ is a stationary Gaussian stochastic process which can be approximated by the following vector autoregressive representation of order p, or VAR(p):

so that only contemporaneous correlations can occur. Given the large number of parameters in the system, we had to determine the lag order, p, which best summarized the data, and then treat the chosen VAR(p) model as the framework within which to test competing hypotheses (Huang 1989). Again, we relied upon two standard information criteria (AIC

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III: DEFENSE SPENDING AND ECONOMIC PERFORMANCE TABLE 12.1 Co-integration tests

Key: CRDW=the co-integrating regression Durbin-Watson. DF=Dickey-Fuller test. ADF=augmented Dickey-Fuller test.

and SC) to select the lag length within a reasonable range. To take into account the information that the two differenced series are AR(2) and AR(1) respectively, and to ensure that the assumptions of the error terms in a VAR are met, we set the minimum possible lags at 2. We fixed the maximum possible lag at 6 in order to balance the need to detect the longer-term relationships between the two series, on the one hand, and the demand for enough degrees of freedom to maintain good statistical properties, on the other hand. As shown in Table 12.1, both AIC and SC reach minimum at the lag length of 2, which indicates that a VAR(2) model can be used as the baseline model. The ordinary least squares (OLS) estimates of the parameters of the chosen VAR(2) model and their standard errors are shown in Table 12.3. Before we tested competing theories based on these results, however, we performed some diagnostic tests. Specifically, to make sure that the assumptions of error terms were satisfied for the VAR(2) model, a multivariate portmanteau test, called the Q statistic, which was first suggested by Hosking (1980) and later modified by Li and McLeod (1981) for small and moderate sample sizes, was calculated for five lags and compared with a chi-square distribution with 12 degrees of freedom.3 A Q of 15.007 is not statistically significant at either the 0.05 or the 0.10 level. Therefore, we accepted the null hypothesis that the disturbances of the VAR(2) system comprised a vector of white noise. An examination of the TABLE 12.2 Determination of VAR order based on AIC and SC

Note: a Minimum value.


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TABLE 12.3 Parameter estimates of VAR(2) model

Notes: Figures in parentheses are estimated standard errors. statistically significant at the 0.05 level. statistically significant at the 0.01 level.

contemporaneous disturbance covariance matrix reveals that off-diagonal elements, which represent the instantaneous cross-covariance of the residuals in equations (12.1) and (12.2), may be significantly different from zero. Indeed, a Lagrange multiplier test (see Breusch and Pagan 1980) of =3.695, which is statistically significant at the 0.10 level, confirms that the disturbances of the two equations are contemporaneously correlated. Engle and Granger (1987:259) have shown that a bivariate co-integrated system must have a causal ordering in at least one direction. It remains to be determined in which direction Granger causality flows over time. Since noncausality can be ruled out, there are only three possible causal orderings. All of them can be tested as various restrictions on the off-diagonal elements of the coefficient matrices of the chosen VAR(2) model, A, B1, and B2. The first possibility is that the burden of military spending, either its lagged level or its past changes, or both, causes the relative decline of economic hegemony. In reference to the notations in equation (12.3), this causal ordering implies that either ␣21⫽0 or ß21,i⫽0 (for i=1, 2), or both. The second possibility is just the opposite, that is, economic hegemony causes defense spending. This second possible causal ordering implies that either (␣12⫽0, or ß12,i⫽0 (for i= 1, 2), or both. The third possibility is that there is a feedback relationship between defense spending and economic hegemony over time. This feedback

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TABLE 12.4 Results of joint-hypothesis tests

Note: All the joint hypotheses are tested in the context of a system estimated by Zellner’s seemingly unrelated regression (SUR) technique.

relationship can be realized in six different ways: (1) ␣12⫽0 and ␣21⫽0,(2) ß12,i⫽0 and ß21,i⫽0, (3) ␣12⫽0 and ß21,i⫽0, (4) ␣21⫽0 and ß12,i ⫽0, (5) ␣12 ⫽0 and ␣21⫽0 and ß12.i⫽0 or ß21.i ⫽0, or (6) all six off-diagonal coefficients are significantly different from zero. The results of joint-hypothesis tests are presented in Table 12.4. The most general null hypothesis that all six off-diagonal coefficients are not different from zero is easily rejected. This means that at least one coefficient is significantly different from zero. The second and third types of feedback can be ruled out because their null hypotheses cannot be rejected. The first type of feedback, though significant at the 0.05 level, is actually due to ␣21 alone since the t-statistic of ␣12 is not statistically significant even at the 0.20 level. This knowledge also allows us to rule out the fifth type of feedback, which also involves ␣12. The fourth type of feedback relationship, which involves both ␣21 and ß12,1 being significant, receives support. Hence there is empirical support for the idea that the lagged level of the defense burden causes a positive change in economic hegemony, which in turn causes a positive change in the defense burden of the following year. Kennedy (1987) is correct in suggesting that the variables have an impact on one another. But, whereas he predicts negative impacts, we actually discovered positive impacts in a model which allowed only for simple direct impacts.


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A LONG-TERM EQUILIBRIUM INTERPRETATION The findings reported in the previous section focused on relatively simple and straightforward relationships between the variables. However, after reflecting upon Kennedy’s argument again, we wondered whether we had been unfair to the argument by not introducing enough complexity into the analysis. After all, not only does Kennedy emphasize a long-term (1987:533) orientation but he also emphasizes relationships between trends (1987:433) and discusses equilibrium, harmony, balance, and rough balance (1987:446) between variables such as defense burden, consumption, investment, and longterm economic hegemonic decline. In order to be fair to Kennedy’s argument we decided to introduce modifications which would give our empirical analysis a long-term equilibrium interpretation. If Kennedy’s argument is interpreted as involving long-run equilibrium relationships, then the co-integration tests may be used to establish the validity of using error correction models discussed by Salmon (1982) and Granger and Weiss (1983) in this analysis. That is, the co-integrating regressions can be interpreted as estimating the long-run components of variables which obey equilibrium constraint ⌰⬘Xt=0, while their stationary residuals represent the deviations from equilibrium, or the ‘equilibrium errors.’ If a proportion of the disequilibrium from one period is assumed to be corrected in the next period, an error correction mechanism is built into the model. The reason why only a proportion of errors is corrected in each time period is that people are assumed to make decisions based on incomplete information. Granger (1986) demonstrated that, if elements in a vector of time series Xt are co-integrated, then there always exists an error correction representation of the form: (12.5) where ⌽ is a (2 X1) vector, Zt-1 is the equilibrium error, and ut is a zero mean white noise vector with

so that only contemporaneous correlations can occur. A comparison of equations (12.5) and (12.4) immediately reveals their similarities. The error correction terms (Zt-1) on the right-hand side of equation (12.5) permit a gradual adjustment toward a new equilibrium, and can be estimated by the lagged residuals from the co-integrating regressions.

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III: DEFENSE SPENDING AND ECONOMIC PERFORMANCE TABLE 12.5 Parameter estimates of error correction model

Notes: Figures in parentheses are estimated standard errors. statistically significant at the 0.05 level. statistically significant at the 0.01 level.

RBt are the OLS residuals from regressing MB, on EHt, and RHt are the OLS residuals from regressing EHt on MBt.

Therefore, by replacing MBt-1 and EHt-1 in the first part of equation (12.3) with the residuals from co-integrating regression, i.e. RBt-1, and by replacing the same two terms in the second part of the equation with RHt-1 we can reanalyze the relationships between military burden and economic hegemony with ordinary least squares.4 The parameter estimates of this error correction model are reported in Table 12.5. In comparing the results in Table 12.3 and Table 12.5, we find that the coefficients attached to the lagged changes of defense burden and economic hegemony are very similar in regard to signs, magnitudes, and statistical significance. Interestingly, in Table 12.5, the coefficient attached to RBt-1 (␾1) is not statistically significant even at the 0.20 level, while the coefficient attached to RHt-1(␾2) is statistically significant at the 0.05 level. The error correction model separates ‘equilibrium’ behavior from shorterterm reactions to changes in defense burden and economic hegemony. In the equilibrium analysis, the changes in the defense burden of the United States and the changes in its economic hegemony status tend to be proportional to each other. If this equilibrium is disturbed, then a dynamic adjustment process ensues which pushes the system toward a new equilibrium. The statistical significance of ␾2 and the insignificance of ␾1 suggests that defense burden


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may indeed be ‘weakly exogenous’ in Engle et al.’s (1983) sense. That is, in the long run, the change in economic hegemony tends to respond in the opposite direction to the deviations of defense burden from its equilibrium relationship with economic hegemony. The changes in defense burden, on the other hand, do not respond to the deviations from equilibrium in the long run. Instead, the current changes in defense burden are responding positively to the changes in economic hegemony in the previous period. In other words, the proportion of the US GNP allocated to the defense purpose is likely to be affected by the incomplete information on its short-term economic status in the group of industrialized countries. However, the ‘errors’ of such allocation decisions are likely to be ‘corrected’ in the long run in its economic hegemony. For example, a good economic performance in the previous period may generate overly optimistic expectations from the decision makers and thus too high a proportion of GNP may be allocated to the defense sector (i.e. a positive short-term effect). In the long run, however, heavy defense burden causes the decline of the US economic status (i.e. a negative long-term effect), which in turn imposes a constraint on US military spending in the short run (again, a positive short-term effect since military burden declines together with lower economic hegemony). Hence, given a long-term equilibrium interpretation, there is empirical support for the part of Kennedy’s argument regarding the long-term impact of military burden upon economic hegemonic decline. However, we find no significant long-term impact of economic hegemonic decline on military burden and even discover a short-term impact of economic hegemony upon military burden which goes in the opposite direction from that suggested in Kennedy’s argument.

CONCLUSIONS Perhaps the most succinct version of Kennedy’s argument regarding the relationship between military burden and economic hegemony is to be found in the following words: ‘Great powers in relative decline [economic hegemonic decline] instinctively respond by spending more on “security” [increasing their military burden] and thereby divert potential resources from “investment” and compound their long-term dilemma [accelerate their economic hegemonic decline]’ (Kennedy 1987: xxiii). Our analysis of the case of the United States from 1951 to 1985 provided only partial support for this viewpoint. When a complex and sophisticated long-term equilibrium was built into the model, it was found that there is indeed a one-way longterm relationship between military burden and economic hegemony. When


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the military burden of the United States deviated in a positive manner from this subtle equilibrium, it produced a negative impact on the economic hegemony status. Hence there is support for what has become the best-known part of Kennedy’s argument. However, we did not find that during the 1951– 85 era the United States, which was in a long-term economic hegemonic decline (given our definition of the variable, economic hegemony) during this period, instinctively responded by spending more on security, hence increasing its military burden. Indeed, we identified no significant long-term impact of economic hegemony on military burden and even discovered a positive shortterm impact. That is, in the short run, military burden increased and decreased with economic hegemony. Kennedy’s argument is a subtle, complicated, and sophisticated one that requires subtle, complicated, and sophisticated empirical analyses. Naturally, our analysis was constrained by the variables and data employed, by our model specification, and by the techniques used in the data analysis. Different results might be provided by the use of different variables, data, modeling traditions, or statistical techniques. However, we would emphasize that, in our opinion, our approach was a reasonable one and we believe the results may be fairly robust. We hope that our analysis makes a contribution to the accumulation of knowledge regarding an interesting and important topic the relationship between military burden and economic hegemonic decline.

NOTES 1 2

We are grateful to Madalena Cerami for providing the data. Of course, she is not responsible for any errors we may have made in the analysis. The augmented Dickey-Fuller (ADF) tests of co-integration used in the analysis are described below in greater detail. We first treat the defense burden, MB, as the dependent variable and the co-integrating regression gives: MBt=-6.380+0.297 EHt+RBt,

DW=1.109

R2=0.871

with a t-ratio of 14.943 on economic hegemony, EH. (RB refers to the OLS residuals, or the ‘error correction terms,’ of this equation.) The ADF test with one lag, which was chosen by both Akaike (1973, 1974) and Schwarz (1978) information criteria, gives: ⌬RBt = -0.0620.696 RBt–1+ 0.449 ⌬RBt–1+et (-0.856) (-6.462) (4.538) The t-ratio for the coefficient attached to RBt–1 is -6.462 and exceeds the 1 percent critical value (4.12) provided by Engle and Yoo (1987:158) for a sample size of 50, which is the smallest sample size simulated by them. Then we reverse the co-integrating regression by treating EH as the dependent variable; the ADF test statistic of -4.61 8 also exceeds the 1 percent critical value. Although we have only 33 observations in both co-integration tests, it seems safe to reject the null hypothesis of non-co-integration given the fact that the two t-ratios exceed the critical values for a sample size of 50 by fairly large margins.

Military burden and economic hegemonic decline 3

4

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The calculation of the Q statistic is limited to five lags because Hosking (1980) has warned that the number of lags taken into account should not exceed the square root of the total number of observations. For our VAR(2) model, the effective sample size is 32. We applied OLS to each equation because the two-step estimator for an error correction model suggested by Engle and Granger (1987:260) required only single equation least squares.

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PART IV

Issues in Defense Spending

CHAPTER 13

Issues in Defense Spending: Plausibility and Choice in Soviet Estimates Robin F.Marra and Charles W.Ostrom, Jr

One would think that, in the attempt to build and estimate empirical models of US and Soviet military expenditures, the choice of the data themselves would be relatively straightforward. In this chapter we demonstrate that this choice is not unambiguous. In so doing, we raise a number of data-related issues and questions which need to be addressed by modelers of a US–Soviet military expenditure arms race. At the outset, it should be noted that we focus our discussion on estimates of Soviet military expenditures, since these seem to be the ones which generate the greatest controversy. In addition, while our comments are aimed primarily at the research/modeling community, they could just as easily have been directed to the policy-making establishment. We believe that the plausibility requirements which we outline are equally applicable to both groups. By way of concluding we suggest that the empirical fit of one’s models (and, hence, the subsequent inferences which one is able to draw) is likely to be affected by the particular data series employed. Both modelers and policy makers recognize that an estimate of Soviet defense activities is of major importance. Why is the Soviet estimate so crucial? For one thing, [T]he amount and type of military spending by a country are important…as a measure of its intentions, and the threat that country may pose to its neighbors. (From an address by President Ronald Reagan to the Second UN General Assembly Special Session on Disarmament, 17 June, 1982)

Moreover, as Abraham Becker, a senior economist at the Rand Corporation, has noted, considerable information can be conveyed easily in a summary fashion. 261

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Estimates of Soviet military outlays are made for four main purposes—comparisons with US expenditures to indicate relative size, determination of the structure of Soviet outlays in various breakdowns, measurement of the rate of change of total Soviet expenditure and its components, and estimation of the ‘burden’ of Soviet defense…. (From testimony before the Subcommittee on Oversight of the Permanent Select Committee on Intelligence, US House of Representatives, Ninety-Sixth Congress)

In the same testimony Becker noted that these estimates also carry sizable political importance. [the political importance] is obviously the most significant element of all. If the estimates were of no consequence to major elements of the US government’s program, we would obviously devote no attention to it, and whatever controversies would beset it would be and would remain obscure….

In other words, a Soviet estimate can be a convenient summary measure which provides information as to the capabilities, goals, and commitments of that nation. Moreover, it is a measure which potentially carries a certain amount of clout in the political process which produces US military expenditures. Given the enormous economic and political changes which have taken place within the Eastern bloc, one might question whether the nature of the Soviet estimate itself will retain its current meaning. In other words, given the sizable troop reductions throughout Europe, the popular rejection of exclusive rule by the Communist Party, and the ongoing arms control dialogue between the superpowers, is the Soviet threat diminished? Proponents of the position that such a threat is indeed lessened by the political, economic, and military restructuring of Eastern Europe argue that the US can expect to realize a ‘peace dividend’ within a relatively short period of time. Such a dividend might then be spent on social programs or might be used to reduce the US federal budget deficit. A more cautionary approach is advocated by those who fear a period of instability on the European continent and who suggest that the presence of US military forces will be a stabilizing factor. At the same time, there is a certain vocal contingent within the Western alliance which is much less sanguine about the prospects of the current Soviet leadership (namely, Gorbachev) to survive politically. Fearing the return of the Soviet ‘hardliners,’ this view holds that a more prudent policy would be to resist massive cuts in US military spending until the situation within the Soviet Union and Europe stabilizes. It is impossible to predict at this juncture which position will come to dominate US defense planning. The earliest indication that we have is

Plausibility and choice in Soviet estimates

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contained within President Bush’s proposed budget for fiscal year 1991 (FY91). It calls for a modest increase in the size of the defense budget which, when adjusted for the expected rate of inflation, actually translates into a 2 percent decrease over the FY90 levels. Under the President’s plan, defense is slated for similar cuts over each of the next four years. There will be considerable pressure for the Democrats in the House and Senate to reduce the defense budget even further. This sense of urgency will be heightened by both the fiscal strains imposed by massive budget deficits as well as by recent public opinion which suggests that three out of every four Americans polled expect the improvement in East-West relations to permit sizable cuts in US defense spending. In this era of uncertainty, one thing is certain: the political battle over the size and shape of the US military budget will be no less intense in an era of rapid political and economic change within the Eastern bloc. Moreover, given the predominant role which estimates of Soviet military capabilities have played in past budget disputes, the credibility of such estimates will come under even more intense scrutiny. For this reason, the questions of plausibility and choice in the Soviet estimate are even more salient than at any previous time. In the sections which follow we shall examine several issues surrounding the generation and use of estimates of Soviet military expenditures. We begin by raising two relatively simple technical issues: do the data exist and how were they generated. Following this we examine the most widely available data sets from several different perspectives including, but not limited to, (1) the source of the data; (2) metric employed; (3) time frame examined; and (4) the timing of assumed reaction between US and Soviet military expenditures. Finally, based upon these concerns we provide several illustrations of the possible differences among the various data series one could employ.

TECHNICAL ISSUES There are essentially two primary technical issues that need to be addressed: (1) do the data exist? and (2) how were they produced? While the answer to the first question would appear to be obvious, there are several ‘temporal’ concerns which we shall raise below. The fact that several Soviet data sets exist provides greater choice for researchers but it also raises the question of whether one data set is ‘better’ than another. While we may not definitively answer this question, we will provide some criteria by which such judgments may be made.

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In terms of how a particular Soviet data series was produced, there are several possibilities which we will mention briefly. (For fuller analyses of these methods, interested readers should see, for example, Burton 1983, Cockle 1978, or Holzman 1980, 1982, 1989.) First, one could simply use the single line-item ruble figure reported by the Soviets each year. This figure, however, is typically met with near-universal skepticism outside of the Eastern bloc. Most analysts feel that it is a gross understatement of the budgetary resources allocated for defense in the Soviet Union. Even Gorbachev’s surprise announcement in early 1989 of a revised (upward) defense budget figure was characterized in the West as being too low, though it represented a fourfold increase over previous official estimates. Second, some have attempted to augment this official estimate by examining the rest of the Soviet budget. The use of so-called ‘budget residuals’ is based upon the assumption that some monies appearing under other categories (e.g. the All-Union Science Budget) are actually part of the overall Soviet defense effort and, as such, should be included in any Soviet estimate. The problem with this procedure is that there is no agreed-upon method for determining which budget categories should be included or how much of each category should be allocated to the defense total. An example of this approach can be found in Lee (1977). Given the difficulties associated with the use of official Soviet budget figures, some analysts have tried to limit the scope of the estimation problem by simply focusing on weapons production. Cockle (1978) terms this the ‘hardware approach’ and notes that it is based upon an examination of industrial statistics. The problems associated with this approach are similar to those encountered with Soviet budgetary data, namely the lack of confidence one necessarily has in official Soviet statistics. Lee (1977), however, argues that the addition of his hardware statistics and research and development estimates to the official defense budget figures provides a reasonable estimate of the total Soviet defense effort. Nevertheless, in electing to use the Lee data the researcher should be aware of their potential shortcomings. A third approach to the Soviet estimate is that followed by the US Central Intelligence Agency (CIA). Referred to as the ‘building block method,’ this technique is based upon the estimation of what it would cost to duplicate the Soviet defense effort in the United States. In other words, the tangible elements of the Soviet military establishment, e.g. tanks, aircraft, etc., are counted up and then multiplied by some figure which represents the relative value of those items in US terms. Soviet manpower levels are also adjusted by factors representing US compensation rates. Moreover, the CIA produces both dollar and ruble estimates of Soviet military expenditures. Given that the entire process is quite elaborate and is shrouded in secrecy, the CIA


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estimates have naturally come under critical scrutiny from all sides. Some (e.g. Holzman 1980, 1982) feel that CIA dollar estimates overstate Soviet military expenditures, while others (e.g. Lee 1977; Rosefielde 1982) claim that the CIA has systematically underestimated the true Soviet defense effort. Our purpose is not to resolve the debate over the accuracy of the CIA estimates. Rather, at this juncture we wish only to point out that their approach is but one of several and, like the others, is plagued by certain difficulties. Assume:

Estimates of Soviet military expenditures which are produced on a regular basis are preferable to those which appear only sporadically.

RESEARCH CHOICES Given the existence of several ‘Soviet estimates,’ what are the choices available to the research community? What decisions or criteria structure these choices? In this section we shall raise a number of questions, the answers to which will largely determine which of the several existing data sets one is likely to choose. Source of data In terms of the source of the data it would appear as though the relevant issue revolves around whether one opts for data produced by private institutes and individuals or for those generated by US government agencies. Of the former type at least three data sources are readily available: (1) the World Armaments and Disarmament Yearbook series produced by the Stockholm International Peace Research Institute (SIPRI); (2) data collected and published by the International Institute for Strategic Studies (IISS); and (3) a Soviet estimate developed by William Lee (1977). Of US government sources, the estimates produced by the CIA can be found in a slightly modified form in World Military Expenditures and Arms Transfers, an annual publication of the US Arms Control and Disarmament Agency (ACDA). We shall subsequently refer to these data as the ACDA/CIA estimates. Yet we do not wish to imply that these are the only sources for a Soviet estimate. One could, for example, use the data reported by Steven Rosefielde (1982). A discussion of other sources may be found in the SIPRI Yearbook 1988 (pp. 133–5). The choice of a particular data set should be based, in part, on the availability of the data. This availability criterion eliminates, for example, the estimates produced by the US Defense Intelligence Agency (DIA). Even

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though it is generally believed that these estimates are routinely higher than those produced by the CIA, the fact remains that DIA’s estimates are not in the public domain (see, for example, Holzman 1989:105 ff). Of the data generated by private institutions, the SIPRI and IISS estimates have an advantage over others in that they have appeared with greater regularity in annual volumes and yearbooks. Given a choice between these two basic sources (private institutes vs US government agencies), is either one preferable? What sort of factors might one take into consideration? The answers to these questions would seem to depend largely upon the assumptions one is willing to make about the nature of defense budgeting decision making. If, for example, one assumes that decisions regarding the level and composition of US military expenditures are made by living humans who are themselves part of some US government entity, then it would seem reasonable to assume that these decision makers would use input from other government agencies in determining the extent of the military threat posed by the USSR. If, on the other hand, one assumes that defense expenditure decisions simply occur in some mechanistic fashion, then, perhaps, the source of the estimates of Soviet defense expenditures is less consequential. As Wildavsky (1964) and others have suggested, the US budgetary process is fundamentally a political process. There is no reason to believe that the defense portion of the budget is immune to this surrounding political debate. As recent experience has shown, decision makers must continually guard against both congressional and executive efforts to control defense expenditures. And, as we have shown elsewhere (Ostrom and Marra 1986), there is strong empirical support for the assumption below. Assume:

US government decision makers will use input from other government agencies in determining the extent of the USSR threat.

Even if one is willing to make this assumption, though, there are several additional questions that should be given consideration. Specifically, do the results of one’s empirical analysis depend upon which data source is used? Cusack and Ward (1981), for example, found that the SIPRI, IISS, and Lee data were highly correlated with each other in terms of the levels of Soviet military expenditures, though substantially less so when first differences were compared. More important, however, was that Cusack and Ward were unable to find any empirical support for a military expenditures arms race between the United States and the Soviet Union, regardless of the data set employed. This finding underscores a related question, namely, does the use of one data set enhance the prior probability of the entire empirical enterprise? In


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other words, given certain important characteristics of a Soviet estimate, are we more or less likely to obtain a significant empirical relationship between these estimates and US military expenditures? We shall not elaborate here on what these characteristics might be. However, some simple features of a Soviet estimate would be the sign and size of the annual changes (i.e. whether Soviet defense expenditures are increasing or decreasing and by how much) as well as the imputed gap between US and Soviet military spending. Metric While most groups involved in the production of Soviet estimates generate both dollar and ruble totals, it is the dollar amounts which appear to have the greatest utility for US defense planners. William Colby, a former director of the CIA, provides a simple justification for the use of dollar amounts: [T]he purpose of working out the dollar comparisons is to help us in our decisionmaking about our budgets. (From testimony before the Joint Economic Committee of Congress, Ninety-Fourth Congress)

And, as Cockle (1978) has pointed out, the dollar amounts provide an indication of the relative size of the Soviet military effort in terms which are readily understood in the West. Assume:

Dollar estimates of Soviet military expenditures are more meaningful to US defense planners than corresponding ruble estimates.

Relatedly, there is the issue of whether one should employ constant dollars or current dollars. If the former is the choice, then there is the question of which base year to use. When one examines the existing research in this field there is no clear pattern or consensus as to whether current or constant money prices should be used. There is even some dispute within the policy-making community, though once, in response to Secretary of Defense James Schlesinger, then House Appropriations Chairman George H.Mahon (Democrat, Texas) complained [y]ou talk of reduction of the defense budget in terms of constant dollars. We cannot do anything about constant dollars. (Defense Monitor 1975:2)

Given that US defense budgets must be proposed, appropriated, and spent in current dollars, and given the alleged reactivity of such budgets to Soviet military expenditures, current prices facilitate comparisons between the two defense efforts.

268 Assume:


The US budget is spent in current dollars. Debates over this budget take place in current dollars. Opportunity costs are calculated in terms of current dollars. The most meaingful comparisons with Soviet bud getary efforts, therefore, are in current dollars.

At least two additional questions or concerns can be raised in the context of the debate between current and constant dollars. First, given the artificial nature of the pricing structure in the Soviet Union, does the difference between the two money series make much substantive sense? Second, and more importantly, the use of a constant dollar series involves an arbitrary choice of a base year. The 1989 ACDA volume, for example, reports military expenditures in both current and constant 1987 prices. The previous volume (ACDA’s World Military Expenditures and Arms Transfers 1987), however, reported current and constant 1984 prices. Not only is one forced to make an arbitrary choice regarding the base year, if one wishes to combine several series from the same source one must convert at least one of the series into an entirely different metric. We are not convinced that this is an error-free enterprise. There is an even greater dilemma if one adopts a behavioral perspective on the US-Soviet arms race. What, exactly, would 1984 prices mean to a policy maker who is trying to respond to a potential threat from the USSR in 1970? By the same token, what would a Soviet estimate expressed in 1970 prices mean to that same defense planner in 1984? This entire conversion enterprise is made even more suspect when, as we shall illustrate below, one considers that many of the estimates are themselves revised from one volume to the next. Lastly, it must be asked why people use constant dollars in the first place. Does the use of a constant dollar series act as a filter? If so, are the empirical results invariant to the filter employed? Time frame Within the literature there appears to be the near-universal assumption that the more data one has, the better off one necessarily is. Ward (1984), for example, opted for the IISS data largely because, at the time, they were the longest-running series. We have also been guilty of assuming that one should conduct one’s analyses using as long a time frame as the data permit (see Marra 1985; Ostrom 1978). Since this is such a standard practice in the modeling community, is there any reason to question the underlying logic? We believe that there is. For one thing, there is no evidence to suggest that US defense planners were overly concerned with the magnitude of Soviet military expenditures prior to 1964. As Prados (1982:245) observes:


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Estimates of Soviet military spending were a product of McNamara’s tenure at the Pentagon when, in order to have Soviet spending data to incorporate into systems analysis studies, the secretary of defense put substantial pressure on CIA to produce such estimates.

It is also worth noting that the first ACDA volume appeared at this time and contained a single estimate of Soviet military spending—for 1964. Therefore, in terms of public evidence we can find none which substantiates a claim that Soviet defense spending prior to 1964 was of great concern to anyone within the US government. Consequently, use of pre-1964 data must be suspect. Assume:

The US government did not begin to monitor Soviet expenditure be havior formally until 1964.

It is also instructive to consider in brief the history of the SIPRI data set. Although the first SIPRI volume did not appear until 1969 it contained military expenditure estimates dating back to 1948. In other words, it would seem to be reasonable to assume that almost all of the data in this initial volume had been estimated retrospectively. This assumption, in turn, leads us to ask whether the pre-1969 SIPRI data possess any special characteristics, for example, whether it might have been generated mechanically. While the SIPRI volume does not provide much information regarding the estimation techniques employed, one is left with the impression that, at least in the case of the USSR, official government estimates serve as the primary source. Given the dubious nature of these official Soviet pronouncements, one must necessarily lose some confidence in the SIPRI series. And, while we are not accusing SIPRI of producing Soviet estimates in a mechanical fashion, it is interesting to note that these estimates can be modeled quite nicely with a first-order autoregressive process. The nature of the pre-1969 SIPRI estimates notwithstanding, it is important to question whether or not this time frame is relevant to the study of an arms race between the two superpowers. As we have shown, there is, at least in terms of military expenditures, reason to doubt whether US defense planners were overly concerned with Soviet activities pre-1964. This observation, in turn, raises the serious question of whether results which are based upon pre1964 data are subject to construct validity problems. We also wish to raise the following question: Why, with few exceptions, has the modeling community apparently ignored US defense spending during the Reagan era? Part of the answer undoubtedly lies in the reality of academic publishing i.e. for some journals there is a backlog of one to two years in terms of the acceptance of a manuscript and its publication. Another reason, however, may be that the Reagan spending levels and changes seem ‘atypical’

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from the perspective of most models. To see what we mean by this, consider defense spending during Reagan’s first years in office, in terms of both the level of expenditure as well as the change from the previous year. This information is presented in Table 13.1. In essence, defense spending under Reagan was somewhat irregular. During the first two years spending rose by approximately $27 billion each year. The third year, however, saw only a $17 billion increase, followed by two more increases of $26 billion and $20 billion, respectively. During the sixth year, spending increased by only $8.6 billion, a fact which the administration tried to characterize as a cutback. Whether it represented a cutback is not as important as the fact that, prior to Reagan, US defense spending appeared to follow a relatively constant pattern of spending increases. Consequently, explanations based upon simple linear trends were quite successful in accounting for these spending levels. Most existing models of US defense expenditures would have a difficult time ‘capturing’ or explaining the erratic nature of spending levels during this period. The problem is only exacerbated if one is interested in explaining annual changes in defense spending rather than levels. It would appear, then, that there are two issues related to the question of what the appropriate time frame is. First, modelers need to consider whether it makes any sense from a substantive, policy-making perspective to include data from the pre-1964 period. Second, we need to include as much information as possible from what is arguably one of the more interesting and dynamic periods in US defense spending history. A period of rapid acceleration in these expenditures, followed, as it was, by a period of deceleration, is not easily explained by a Soviet expenditure series which monotonically increases—a feature more characteristic of the SIPRI data than the ACDA/CIA data. For this reason alone the CIA estimates may be preferable to those produced by SIPRI. TABLE 13.1 US defense expenditures during Reagan’s first six years (current US$m.)


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Given a source, which series from source? Our discussion in this section begins with a few facts’ about estimates of Soviet military expenditures. First, no single volume or data source provides consistent data for the entire time period typically studied by the modeling community. Second, given a source (it matters not whether it be SIPRI or ACDA/CIA), it is the case that each volume is likely to contain ‘revisions’ of previous spending estimates. Third, these revisions may be either upward or downward, though the predominant trend has been to revise upwardly. Finally, looking at a particular year it is possible to identify a ‘drift’ in the estimates for this year over time. These ‘facts’ lead us to ask the following questions. First, what accounts for the ‘drift’ in these estimates over time? Second, which estimate for a given year should one employ—the first one, the most recent one, or some estimate in between? There is no clear consensus within the modeling community. In fact, it would be fair to say that, with a few exceptions, no one seems to be particularly concerned with or aware of this issue. Third, if one is using data which have been ‘retro-fitted,’ i.e. which have been mechanically revised or produced after the fact, how sensitive are one’s results to these data? Finally, is the use of retro-fitted data plausible from a substantive or theoretical perspective? To illustrate some of these concerns, one can turn to Table 13.2. This table contains the estimates of Soviet defense expenditures published in ACDA’s annual volumes, World Military Expenditures and Arms Transfers. Each column represents the estimates contained within a particular volume, whereas each row contains the estimates for a particular Soviet expenditure year as they appear initially and in subsequent volumes. What is immediately apparent from this table is the difficulty one would encounter in trying to create a Soviet expenditure series. Not only does ACDA limit its annual estimates to a 10- or 11-year period, but estimates for a single year are often changed. (It should be noted that similar concerns could be raised in connection with an analogous table of SIPRI data.) For example, what were Soviet defense expenditures in 1980? How did these expenditures differ from the previous year? As this table illustrates, the answers will depend upon the specific ACDA volume one employs. Soviet defense spending in 1980 ranges from a low figure of $196 billion to a high estimate of slightly more than $213 billion. Similarly, this estimated spending represented anywhere from an 11.67 percent to a 13.33 percent increase from 1979 levels. While it may be the case that these different estimates nevertheless represent similar orders of magnitude, there are important differences. This is especially the case if one is interested in examining changes, rather than levels, in Soviet defense spending.

Sources: US Arms Control and Disarmament Agency World Military Expenditures, 1966, 1967; World Military Expenditures and Arms Transfers, various years.

TABLE 13.2 ACDA/CIA estimates of USSR defense expenditures, 1961–87 (current US$m.)


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To chain or not to chain? The issue of ‘chaining’ derives directly from the discussion above and refers to which of several estimates for a specific year one actually uses. It should be pointed out that the central question is not which estimates are the more accurate, but rather which ones have the highest prior probability of being representative of the information available to defense planners at the time their budgetary decisions were made. It has been our contention (see Ostrom and Marra 1986) that the contemporaneous estimate of Soviet defense expenditures is the one most likely to have been used by US decision makers. Assume:

It is necessary to ‘chain’ estimates from different volumes into a data set that covers the period under study.

In operational terms, this means that the initial estimate of Soviet defense expenditures for a particular year is the one that we have included in our data set of Soviet estimates. In Table 13.2 we have underlined these initial estimates. The result is a data set which has been ‘chained’ together and which covers the period from 1964 to 1987. This approach is not without its difficulties, nor is it the only way that one could combine several data sets into a larger one. One could, for example, simply take the 11 years of estimates contained in a current ACDA volume and chain them with a set of estimates for prior years contained in a different volume (e.g. the 1967–76 volume). From our perspective, what is important is whether chaining rules which incorporate revised or updated estimates lead to different answers. More crucial, perhaps, is the question of which set of estimates was available to US defense planners during the period when their budgetary requests were being formulated. It is to this last issue that we now turn.

Timing of reaction In part, this final concern has to do with the lag structure relating US and Soviet military expenditures. While some might feel that this is a question which can be established empirically, we believe that plausibility considerations must be paramount in this determination. Merely to regress or correlate one expenditure series with another using multiple leads or lags is to obviate the need for theoretical or substantive plausibility. In addition, such ad hoc procedures provide little protection against spurious inferences. The central question, therefore, revolves around what information is/was available to US defense planners at the time of their budgetary decision-making. During the Senate Watergate Hearings, Howard Baker, Senator from

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Tennessee, gained national exposure and prominence for his persistent questioning of witnesses. In particular, Baker queried, ‘What did the President know and when did he know it?’ It seems reasonable to us to hold policy makers and the modeling community to a similar standard. In other words, what information regarding Soviet military expenditures is available to US defense planners, and when is it available? We term this approach the Howard Baker (HOBA) standard. What if, like so many others, we make the following assumption about the timing of the reaction between US and Soviet defense expenditures? Assume:

The military expenditure reaction of the US to the USSR (and vice versa) is contemporaneous.

Is this assumption tantamount to the inference that US expenditures in year t are a function of Soviet expenditures in the same year? We believe that there are several substantive reasons why this would be an erroneous assumption. First, existing Soviet estimates are often expressed in terms of calendar years. The US budget cycle, though, is based on a 1 October to 30 September fiscal year. The US budget process is such that planning (in terms of agency requests) begins in the fall of the previous year (e.g. during the fall of 1989 programe requests were being developed for the 1991 fiscal year). This suggests that, at best, US defense planners would have estimates of Soviet military expenditures for the 1988 calendar year. Second, by all accounts the estimation process itself is quite complex and time consuming. We do not know how long this process takes, but we do know that the ACDA volume which was released in June 1989 contains Soviet estimates through 1987. Since these figures are based upon CIA data, it seems reasonable to conclude that 1987 or 1988 would be the latest year for which reliable estimates were available to policy makers. Therefore, by employing the HOBA standard, we would anticipate, at minimum, a threeyear lag structure between US and Soviet military expenditures (i.e. US spending at time t will be a function of estimated Soviet spending for year t-3). This three-year information lag is the twin product of the complexity of the CIA’s estimation process as well as the timing sequence of the US and Soviet budget cycles. The HOBA approach also enables us to answer some of the questions which we posed earlier. For example, the use of revised estimates for prior years would seem to be inconsistent with the HOBA standard, since this information could not have been available to US defense planners at the time they were formulating their budget requests. Nor would this information be available later in the cycle when Congress is appropriating funds and Defense is expending them. Applying the HOBA standard also suggests that analyses which incorporate retro-fitted data are


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inappropriate. By extension, this implies that the use of pre-1964 data may be problematic. Summary of research choices In the preceding pages we have offered a number of assumptions and observations which lead us to prefer one set of Soviet estimates over other possible choices. Our recommendations have been based, in part, upon what we term the ‘Howard Baker test,’ i.e. what information regarding Soviet defense expenditures was available to US defense planners and when. Consequently, we feel that a current dollar series spanning the period from 1964 to the present, and which has been ‘chained’ together in a specific fashion, represents the ‘best estimate’ of Soviet military expenditure behavior during this period. Moreover, we feel that there is ample evidence which suggests that estimates generated by US government agencies (e.g. the CIA) are more likely to be employed by US decision makers. And, given the timing of the two budget cycles and the complexity of the CIA’s estimation process, we feel that, at minimum, a three-year lag structure should be incorporated into models of a US-Soviet military expenditure arms race. Of course, this entire discussion is based upon the notion that the data one employs will have an impact on subsequent empirical analyses. While space precludes a full examination of this assumption, in the final section we shall illustrate some of the possible within-series variations one could generate using the ACDA/ CIA data.

ILLUSTRATIONS OF DIFFERENCES IN THE ‘SOVIET ESTIMATE’ Implicit in Table 13.2 is the fact that, using the information contained in several ACDA volumes, one could produce a variety of ‘Soviet estimates’ simply by employing different chaining rules, time frames, base years for computing changes, etc. Rather than presenting an exhaustive listing of these variations, Table 13.3 focuses on two measures of ‘levels’ and three of ‘changes.’ As will be seen, the estimated levels are much more highly correlated than the estimated changes. The first two columns present the levels and changes one obtains by using the ‘Howard Baker approach,’ i. e. by taking the first reported Soviet estimate for a given year. While the HOBA levels are unremarkable in their steady upward movement, there are several noteworthy points associated with the estimated changes. First, during the initial years of the series (1965– 73) the changes are relatively small (i.e. less than $10 billion). This time

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TABLE 13.3 Variations in ACDA/CIA estimates of Soviet military spending (current US$m.)

frame also corresponds to the period when US attention was directed away from the USSR and toward the war in Southeast Asia. With the end of US involvement in that conflict, however, US policy makers could and did address themselves to the ‘threat’ posed by the Soviet Union. The resulting estimates, which show sizable increases from 1974 through 1982, corroborate the alarums sounded by the defense and intelligence communities throughout this period. The most interesting period, though, is the one which immediately follows. The 1985 and 1986 ACDA volumes are noteworthy in that each offered substantial downward revisions in their Soviet estimates. By employing the HOBA method the resulting changes work out to be a paultry


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$1 billion and $2 billion for 1983 and 1984, respectively. These diminished estimates are then followed by the two most recent volumes, and each of these offers figures which have been revised in an upward fashion. In short, the HOBA changes for 1983 and 1984 present a formidable challenge to action-reaction models of US–Soviet military spending. While the US spending figures show sizable increases (see Table 13.1), the Soviets were apparently holding steady. The novelty of the estimated changes for these two years is highlighted by the fact that the next three changes are each in the $12–15 billion range. As an alternative, ‘current’ estimates of Soviet military spending can be found by taking the most recent figures published for each year. Whereas the HOBA levels are obtained from the lower diagonal of Table 13.2, the current estimates are to be found along the upper diagonal. Even though the two series are highly correlated with each other (r=.997), there are important differences. For one thing, the ‘current’ series is far less variable. Not only is the standard deviation some $5 billion less, but the mean is slightly higher than that of the HOBA series ($153.5 billion vs $150.7 billion). In addition, some of the differences associated with specific years are quite large (e.g. 1965, 1972, 1976). Third, the apparent stagnation in Soviet spending for 1983 and 1984 suggested by the HOBA series is eliminated. Finally, the two series present views of the change in Soviet military expenditures over the 1965–87 period which differ in the degree of the enormity of this increase. The current estimates suggest that Soviet spending increased by 478 percent during this period, whereas the HOBA estimates indicate a much larger increase of 658 percent. The last column of Table 13.3 presents the annual changes in the Soviet estimate which one would infer by inspection of each ACDA volume. In other words, ‘Reported changes’ are those which are computed by comparing the last estimate in each volume with the previous year’s estimate in the same volume. For example, the 1966–67 volume contained estimates of $40 billion for both 1964 and 1965 as well as an estimate of $47 billion for 1966. Therefore, the reported change for 1966 was $7 billion. By using the HOBA approach the change from 1966 to 1967 is $5 billion ($47 billion vs $52 billion). The change implied by the 1969 edition, however, is only $3 billion ($49 billion vs $52 billion). By revising the 1966 estimate from $47 billion to $49 billion, ACDA is reducing the apparent size of the 1967 increase. For a more dramatic comparison, look at various estimates of the 1982– 83 change. As noted above, the HOBA method suggests a very minor increase of $1 billion. If one simply relied upon the figures contained in the most recent (1988) edition, the rise in Soviet spending is significantly larger ($12.8 billion). Even if you relied upon the 1985 volume when it was released, you

278 FIGURE 13.1

IV: ISSUES IN DEFENSE SPENDING Variations in ACDA/CIA Soviet estimates, 1965–87

would be led to the conclusion that Soviet spending had increased from $243.8 billion to $258 billion—an increase of $14.2 billion. Clearly, these last two estimated changes present a strikingly different view from the one that the HOBA method generates. In fact, Figure 13.1 illustrates how these three change series have varied over the entire 1965–87 period. It can be seen that there are several years in which there is considerable variation among the three series. The intercorrelations (Table 13.3, bottom) are also considerably smaller than those between the levels. This finding underscores and extends the observation of Cusack and Ward (1981) that the first differences of the SIPRI, IISS, and Lee data were correlated to a much lesser degree than were their levels. Not only are there sizable differences between different data sources but, as we have shown, there can be considerable variations within the same data source. It should be evident that the empirical inferences that one is able to draw regarding the alleged reactivity of US military spending to similar expenditures by the USSR will be affected by the particular data set which one employs.


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CONCLUDING OBSERVATIONS It should be apparent from the preceding discussion that the choice of a Soviet estimate is not an automatic, nor is it a neutral, one. Not only are there a number of data sources from which to choose, but there are a multitude of potential Soviet estimates within each source. The intent of this chapter has been to raise several issues that might facilitate choice among the many options. As this chapter is being written there is an indication that another Soviet estimate might be available in the near future. We are referring to ‘official’ budget figures released by the Soviet government. As indicated earlier, Gorbachev’s announcement on 30 May, 1989 that Soviet military expenditures were roughly 9 percent of GNP (77.3 billion rubles or $128 billion) caught many Western observers off-guard. Even though this figure was much lower than US estimates, it was still four times larger than any previously published Soviet figures. Consequently, it was not immediately dismissed out of hand. What, then, are the implications of a ‘credible’ Soviet estimate generated by the Soviets themselves? First, it should be noted that, even if the Soviets were to produce an ‘accurate’ retrospective series, such data would not be usable within the guidelines established by the Howard Baker test. In other words, such figures, however accurate, would not have been available to US defense planners at the time their budgetary decisions were being made. Second, the accuracy (i.e. credibility) of such estimates can be judged only ex post facto in light of the subsequent budgetary debates within the US. Third, this temporal caveat does not mean that such a series would be of no value. For example, such a series would permit a more accurate assessment of trends in Soviet spending, relative defense efforts between the two superpowers, etc. Finally, there is at least one practical reason why a ‘true’ Soviet estimate might be preferred over one produced by, for example, agencies of the US government. As our previous research has shown (Ostrom and Marra 1986), the driving effects of CIA estimates of Soviet defense spending on US expenditures open the potential for political manipulation of these estimates. In other words, US defense planners might, in the face of budgetary cutbacks, be tempted to inflate the estimate of the Soviet threat in order to justify US spending increases. A Soviet-produced estimate might de-couple US political concerns from military spending decisions. And, perhaps more importantly, the development of a ‘true’ Soviet estimate might once and for all enable researchers to test competitive action-reaction models of defense spending by the superpowers. In sum, we have tried to suggest that plausibility considerations, coined broadly in terms of what information is most likely to have been available to

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US defense planners, should be the guiding hand which directs these choices. While we are partial to the HOBA estimates, we recognize that other researchers may opt for a different set based upon each’s conception of ‘plausibility.’ Finally, throughout this chapter we have suggested that the quality and nature of one’s empirical inferences will, in part, be a function of the data one employs. The inability of many researchers to find a reaction between US and Soviet military spending may be less the product of conscious choices by policy makers and more a result of the data choices made by the modeling community.

REFERENCES Burton, D.F. 1983. Estimating Soviet defense spending. Problems of Communism 32:85–93. Cockle, P. 1978. Analysing Soviet defence spending: The debate in perspective. Survival 20: 209–19. Cusack, T.R. and Ward, M.D. 1981. Military spending in the United States, Soviet Union, and People’s Republic of China. Journal of Conflict Resolution 25:429–69. Holzman, F. 1980. Are the Soviets really outspending the U.S. on defense? International Security 4:86–104. Holzman, F. 1982. Soviet military spending: Assessing the numbers game. International Security 6:78–102. Holzman, F. 1989. Politics and guess work: CIA and DIA estimates of Soviet military spending. International Security 14:101–31. Lee, W.T. 1977. The Estimation of Soviet Defense Expenditures, 1955–75: An Unconventional Approach. New York: Praeger. Marra, R.F. 1985. A cybernetic model of the U.S. defense expenditure policymaking process. International Studies Quarterly 29:357–84. Ostrom, C.W. Jr. 1978. A reactive linkage model of the U.S. defense expenditure policymaking process. American Political Science Review 72:941–57. Ostrom, C.W. Jr. and Marra, R.F. 1986. U.S. defense spending and the Soviet estimate. American Political Science Review 80:819–42. Prados, J. 1982. The Soviet Estimate: U.S. Intelligence Analysis and Russian Military Strength. New York: Dial Press. Rosefielde, S. 1982. False Science: Underestimating the Soviet Arms Buildup: An Appraisal of the CIA’s Direct Costing Effort, 1960–80. New Brunswick, NJ: Transaction Books. Stockholm International Peace Research Institute. Various years. World Armaments and Disarmament: SIPRI Yearbook. London: Taylor & Francis.


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US Arms Control and Disarmament Agency. 1966. World wide Defense Expenditures and Selected Economic Data, 1964. Washington, DC: Economics Bureau, ACDA. US Arms Control and Disarmament Agency. 1967. World wide Defense Expenditures and Selected Related Data, 1965. Washington, DC: Economics Bureau, ACDA. US Arms Control and Disarmament Agency. 1968, 1969, 1970, 1972. World Military Expenditures, 1966; 1969; 1970; 1971. Washington, DC: US Government Printing Office. US Arms Control and Disarmament Agency. 1968, 1969, 1970, 1972. World Military Expenditures, 1966–67; 1969; 1970; 1971. Washington, DC: US Government Printing Office. 74; 1966–75; 1967–76; 1968–77; 1969–78; 1970–79; 1971–80; 1972–82; 1985; 1986; 1987; 1988. Washington, DC: US Government Printing Office. Ward, M.D. 1984. Differential paths to parity: a study of the contemporary arms race. American Political Science Review 78:297–317. Wildavsky, A. 1964. The Politics of the Budgetary Process. Boston, MA: Little, Brown.

CHAPTER 14

Expectations and the Dynamics of US Defense Budgets: A Critique of Organizational Reaction Models John T.Williams and Michael D.McGinnis

Debates over military budgets are affected by changes in both the domestic and international political environments. The substantial military buildup under the Reagan administration was inspired by threatening external events such as the Soviet intervention in Afghanistan, but it was also restrained by widespread concerns with the budget deficit. The reforms instituted by Gorbachev and recent dramatic changes in Eastern Europe have set the stage for significant cutbacks in US military personnel in Europe and in overall military spending, but the continued need for military forces even in a ‘postcontainment’ era will significantly reduce the magnitude of any ‘peace dividend.’ Domestic political concerns will also limit reductions in military spending, as evidenced by the congressional resistance automatically generated by an effort to close military bases in the United States. Although domestic and international factors interact in complex ways to affect military spending levels, it has become a standard analytic practice to separate them into two distinct categories and to compare the relative magnitude of internal and external factors in statistical analyses of arms race models. Most of these empirical analyses indicate that domestic factors are generally more influential than external factors (Isard and Anderton 1985; McGinnis 1991; Moll and Luebbert 1980; Russett 1983; Zinnes 1980), and a series of influential articles has focused on models of the political processes through which the United States military budget is set (Ostrom 1977, 1978; Ostrom and Marra 1986; Majeski 1983a, b, 1989; Marra 1985).1 In contrast to the two unitary states included in Richardson’s (1960) action-reaction 282

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model, these ‘organizational reaction’ models of the defense budgetary process treat the military bureaucracies, President, and Congress as separate organizations, each following different decision rules (or reaction functions) reflecting their differing perspectives and interests. The primary motivation for these organizational reaction models is their increased realism, but these models also unnaturally constrain the range of behavior available to individuals competing to influence state policy. In this chapter we investigate a more general model based on application of rational choice theory to individual policy actors. Actors’ expectations play a prominent role in this interpretation, for defense policy is driven by their efforts to anticipate future security threats. We first contrast the logical underpinnings of both approaches and then analyze data on the US defense budgetary process from this expectational viewpoint.

CONTRASTING PERSPECTIVES ON MODELS OF BUDGETARY POLITICS Organizational reaction models of budgetary processes vary in details of operationalization and methodology. Most define the organizational structure of the US defense budgetary process as including four stages: (1) the budgetary request of the defense agencies (or services), (2) the presidential budget request, (3) congressional appropriations, and (4) actual Department of Defense expenditures. Ostrom (1977, 1978) adds a step for supplemental appropriations, and Ostrom and Marra (1986) and Majeski (1989) exclude, respectively, defense agency requests and actual expenditures from their analyses. All works treat the decision of the previous stage as setting the ‘base’ for the next organization’s decision, except Marra (1985:373), in which it serves as a ‘final check’ on the appropriateness of one’s behavior. Finally, except for the initial article by Ostrom (1977), environmental variables are included in each model to represent adjustments made to this base. Particular prominence is attached to Soviet military expenditures as a measure of the security threat facing the United States, but a variety of other measures of domestic or international economic and political conditions are included in various models. Despite differences in detail, all budgetary process models of the arms race share a common inspiration in several related and important traditions in the study of individual cognition and the behavior of organizations. From the classic work of Simon (1945, 1958) they take the general concept of ‘bounded rationality,’ based on the tendency of individuals and organizations to ‘satisfice’ rather than find the single best option. From Lindblom (1959) they draw a picture of the democratic process of political competition as a means of

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‘muddling through’ policy problems too complex to be solved by any collective process of rational calculation. From classic works on ‘behavioral organization theory’ by Cyert and March (1963) and March and Simon (1958) they take an emphasis on the highly structured nature of organizations, with each organization monitoring a limited part of its environment. Following Allison (1971) they contrast models of states as unitary rational actors with models of bureaucratic politics and organizational behavior that emphasize the routinized behavior of presidential advisers or bureaucratic organizations. But the strongest influence is Wildavsky’s (1964) development of the incrementalist interpretation of budgetary politics, in which the many actors involved adopt simple aids to decision in order to cope with the overwhelming complexity of the US budget. In particular, agencies use their own past decisions as well as those of other organizations to set their expected ‘base,’ and they make adjustments according to a variety of other cues. Typically, organizational reaction is contrasted with a model of rational choice in which individual actors examine all possible alternatives in great detail before making their selection. Yet it is well known that no rational actor would engage in such a time-consuming effort unless information search and evaluation were costless (see Hogarth and Reder 1986). We argue that the difference between rational choice models sensitive to information costs and the analyses of behavioral organization theory is more minor than is generally acknowledged. Simon, Lindblom, and Wildavsky all place great emphasis on the reasonableness of the practice of adopting simplified heuristic rules as a means of coping with complexity, and their analyses identify an impressive array of effective decision aids developed by policy makers. Furthermore, both Lindblom and Wildavsky emphasize the appropriateness of such practices for implementing the values of a democratic polity. In short, actors rely on decision aids not out of laziness but rather to better cope with a complex decision environment. Unfortunately, most applications of behavioral organization theory to specific models replace this appreciation for the reasonableness of heuristic aids with a view of decision makers as automatons unable to change their simple patterns of behavior. This tendency is clear in organizational reaction models of the arms race, for each organization is required to maintain a simple decision rule throughout the period under analysis, no matter what other changes occur. In times of relative stability it may be perfectly efficient to rely on simple heuristics, but actors should be allowed to modify their decision rules whenever they find it in their interest to do so. Participants in debates over security policy routinely base their arguments on their expectations of likely future threats. After all, it takes time to build weapons systems, especially systems based on new technologies, and so present allocations must by necessity be directed towards future threats. The way in


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which the behavior of any one individual is shaped by his or her expectations of the likely future behavior of other actors plays a prominent role in Wildavsky’s accounts, but formal specification of ‘mutual expectations’ lies beyond the scope of simple reaction models. For example, Majeski (1983a, b) specifies the rules by which actors make adjustments for past forecast errors (see also Majeski 1984, 1985). Even though any single updating rule can lead to persistent biases in some circumstances, his model does not allow actors to offset these biases by changing the way they form expectations. Why would any vigilant actor continue to make the same mistakes? It was precisely this concern with the imposition of unreasonable restrictions on the behavior of decision makers that inspired us to investigate the role that information and actors’ expectations play in sustaining the system of superpower rivalry (McGinnis and Williams 1989a, b; Williams and McGinnis 1988). We presume that each individual policy actor has certain goals that he or she seeks, with these goals being a complex mixture of his or her perception of individual, organizational, and national interests. Politics is highly competitive, and actors with different interests and perceptions will seek out information that they can use to shape the expectations and behavior of other policy actors. No one individual has access to all available information, but the competitive nature of policy debates virtually insures that any relevant information will be put forth by those actors whose interests it would serve to do so. We argue that the aggregate outcome of these complex processes of policy competition can come to resemble the outcome of an idealized process of ‘rational expectations,’ in which policy is based on unbiased expectations of all information relevant to future threats or other concerns relevant to security policy, such as the future opportunity costs of arms expenditures. Despite appearances to the contrary, domestic political competition proceeds remarkably efficiently, precisely because political actors are so persistent and clever at inventing new ways to better pursue their own interests. We use the rational expectations model as a point of departure for our analysis, for we realize that circumstances exist which limit the convergence of political competition to a perfectly efficient rational expectations equilibrium. By explicitly incorporating the tendency of cognitive and organizational effects to slow policy response to new information, the implications of persistent asymmetries can be examined. For example, as a consequence of deep suspicion of each other’s actions and intentions, opponents of increased military expenditures would be ill-advised to justify spending cuts in direct response to any overt cooperative act taken by the other superpower. A much more effective strategy would be to emphasize the detrimental economic consequences of high spending levels, since emphasis on general economic costs is more likely to be convincing to other political actors within the same state. Thus, the rivalry system as a whole

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should be more responsive to changes in hostility levels than to changes in levels of cooperation (McGinnis and Williams 1989b:1109–10). This difference may narrow as Gorbachev’s reforms continue to succeed, but even in the current climate of cooperation no arms control proposal, no matter how attractive, can have the immediate impact of, say, shooting down a civilian airliner.

THE LOGIC OF ORGANIZATIONAL REACTION MODELS We argue that the expectational approach has more in common with Wildavsky’s vision of budgetary politics than the simple organizational reaction models purporting to represent his perspective. Our work develops these same ideas in remarkably different forms, with sharply contrasting implications for analysis. For purposes of this comparison we use the following five basic ‘design principles’ as stated in a prominent example of the organizational reaction approach (Ostrom and Marra 1986:822): (1) (2) (3) (4) (5)

Organizations factor decisions into subproblems. Each organization deals with only a segment of the overall decision. All other things being equal, organizations do not change. A change in behavior requires a stimulus. An organization’s initial cue is taken from the previous step in the policy-making process. A limited set of environmental variables is monitored by the defense sector; consequently, much of the environment is ignored. Each organization adopts decision rules that are simple, additive, and temporally stable.

Together, these five principles imply an approach to the analysis of decision making under uncertainty that has very wide appeal. However, we argue that these principles are based on questionable assumptions about political behavior. Furthermore, these five principles imply an unnecessarily narrow approach to research that is ultimately unable to support progress in the scientific explanation of budgetary politics. We have no qualms about the explicit meaning of the first two principles, but we do question some claims implicit in each. The first principle states the obvious fact that no one actor controls the output of the budgetary process. However, even if most actors pay attention to only part of the problem, the attention of any specific actor need not be limited to the particular variables monitored by its organization. Although organizational charts may convey


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an impression of a neat division of responsibility, in reality astute bureaucratic actors will pay attention to any factor that bears on their fate, whether or not that factor falls within their official range of responsibility. The second principle applies to any decision model, for even a rational actor will continue to choose the same alternative in the absence of any changes in constraints. Ostrom and Marra use this principle to implicitly justify their exclusive focus on explaining changes in bugetary allocations, a standard practice in this literature. However, the absolute levels of budgetary allocations also matter in policy debates, and we see no reason to eliminate this information from our analysis. The remaining principles highlight contrasts between reaction and expectational approaches to modeling budgetary politics. Principle 3 focuses attention on the sequence of decision making, with each organization conditioning its decision on the decisions made by the organization immediately preceding it. Thus, the President’s budget request is conditioned on the defense services request, and congressional appropriations are directly affected by these presidential requests. This is far too constraining a notion, for politics is a game of anticipation and action, not just reaction. Actors in each organization will strive to anticipate the likely behavior of organizations that act later in time. According to Wildavsky (1964:24), ‘Participants seek out and receive signals (indicators) from the Executive Branch, Congress, clientele groups, and their own organizations in order to arrive at a composite estimate of what to ask for in the light of what they can expect to get.’ Rather than passively awaiting signals, political actors actively seek to anticipate future developments. The defense services would never formulate a budget request without careful consideration of what the President is likely to include in his budget, and no President wants to submit a budget that Congress ignores as totally unrealistic. It is precisely this anticipation of the likely behavior of other actors that reaction models are so poorly equipped to incorporate. Yet such expectations are crucially important. Again quoting Wildavsky (1964:23), ‘Budgeting proceeds in an environment of reciprocal expectations that lead to self-fulfilling prophecies as the actions of each participant generate the reactions that fulfill the original expectations.’ This view hardly seems conducive to analysis of a near sequence of decisions. Principle 4 augments the partitioning of decision problems imposed in principle 1 by further requiring that those actors involved in the defense sector monitor only a limited set of variables. Yet defense allocations do not occur in a vacuum. In general, if paying closer attention to some part of the environment helps advance the interests of some actors involved in the political process, then that part of the environment will not be ignored. After all, actors that restrict their attention to certain variables undermine their ability

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to win budgetary battles. What effective policy advocate would ignore any aspect of the environment that helps support his or her cause? Principle 4 leads directly to the mode of analysis characteristic of organizational reaction models. If each organization monitors only certain parts of the environment, then it becomes possible to identify the most important environmental variables and include them in the equation representing the decision rule for that organization. Indeed, this type of analysis is characterized by the imposition of a large number of a priori restrictions concerning which variables affect which organizations. Statistical analysis of organizational reaction models requires the further imposition of the restrictions in principle 5, namely, that decision rules are ‘simple, additive, and temporally stable.’ Additive decision rules allow application of regression techniques, but they have no substantive justification. In fact, they directly contradict Wildavsky’s (1988:29) disdain for the ‘addingmachine approach to the budgetary process—looking at the process as a matter of adding up a number of signals in a neat total.’2 Information flows from a wide variety of sources, and a calculator need not be required to base decisions on a large reservoir of information. Furthermore, even if actors use simple decision rules, they do not need to keep using the same rule no matter what other changes occur. Temporal stability of decision rules hardly seems appropriate for a process that undergoes such frequent change as the budgetary process in the United States. Budgetary processes may be stable in the superficial sense that major reorganization of the bureaucratic structure is relatively rare. Within existing structures, changes in behavior occur frequently, with individuals being generally very creative in the types of information and arguments they use to justify their proposed policies. Wildavsky (1964) stresses the complicated patterns of cue-taking and political compromise that underlie what may appear to be a simple process of incremental change. Organizational reaction models supposedly provide more realistic models of political behavior, but no static model of choice can consistently represent the very dynamic processes of budgetary politics. Any fixed rule for information use can fail miserably during a time of change, when those individuals best capable of dealing with new information have a much greater chance of winning the budgeting game. Again, Wildavsky’s (1964:28) assessment provides an important contrast: From time to time agencies are affected by emergent problems, current events which no one is in a position to predict but which radically alter budgetary prospects for particular programs. A change in missile technology, a drought, a new plant disease, advances in Soviet military capability, developments in the cold war, and


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similar events may drastically improve the prospects for some programs and possibly lead to restrictions on others. The agency that is able to exploit the recognized need arising from these events is in an excellent position to expand its budgetary support and it is frequently expected to do so.

The prevalence of unexpected change in both the domestic and international political environments undermines the whole logic of organizational reaction models. Decision rules must be updated in order to adjust to new information, because established decision rules will not in general remain useful in the face of unexpected changes in the environment. The importance of new information in the adjustment of military budgets demonstrates the need for a radically different modeling strategy. If analysts can be given the freedom to include new variables after decision makers have already done so, why not focus our analysis on the ability of decision makers to adapt to new circumstances? We consider it counterproductive to focus one’s attention on continually improving the fit of any single model, when the relevant behavior changes far too frequently for any single model to continue to be relevant. Only if each organization faces a stable environment could a single decision rule continue to prove effective for vigilant political actors, and precisely this very restrictive situation is insured by principle 5. The assumption of temporal stability also justifies forecast accuracy as a criterion to judge the empirical fit of organizational reaction models of the budgetary process. That is, if the underlying process is stable then it is a simple matter to extrapolate estimated models into other time periods. The restrictions imposed in organizational reaction models do indeed produce close fits with data, but this success should not be over-interpreted. Most time series data have so much serial correlation that many models will fit a given set of data fairly well. Thus, the fact that any given time series model fits well is not surprising. Often-used step-by-step specification searches compound this problem, as a large number of specifications will fit the serially correlated data equally as well.3 Earlier works realized that the complex nature of budgetary processes imposes limitations on our ability to predict future outcomes. The models are not predictive because the budget process is only temporarly stable for short periods. We have found cases in which the coefficients of the equations change, i.e., cases in which there are alterations in the realized behavior of processes…. We can predict only when the process remains stable in time. If the decision rules of the participants have changed, our predictions may be worthless; in our models, either the coefficients have shifted or, more seriously, the scheme has changed. (Davis et al. 1966:542; emphasis added)

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Although stated explicitly only by Ostrom and Marra, these five principles summarize a widely used operationalization of the SimonLindblomWildavsky worldview. In contrast, Davis et al (1966) make no claims that their models represent the actual process of decision; instead, they explicitly adopt the ‘as if justification. Yet subsequent budgetary process models are presented as ever-closer approximations to real decision processes, even though these processes are far less stable and individual decision makers far more flexible than this approach can allow. An alternative approach is to admit that the world of politics is much too complicated for these five principles to provide an adequate basis for research, and instead to develop models that allow individual actors the flexibility to pursue their interests as they best see fit.

TOWARDS LESS RESTRICTIVE MODES OF ANALYSIS It is well understood that rational actors need not examine all available information and rank all the possible alternatives before choosing the absolute best option. Real decision makers must choose under uncertainty, and rational choice theory indicates that information will be sought only until its costs outweigh its expected benefits. However, rational decision makers will definitely collect and use cheap information, and this simple idea conveys a fundamental contrast between a rational choice view of the policy process and the organizational reaction approach. This contrast can be sharpened by comparing two pictures of domestic political competition. In the first version bureaucrats and members of Congress act as if they follow simple and stable decision rules, making their actions very predictable. Any stimuli these actors respond to must also be relatively predictable, or else they would never have settled on these particular heuristic rules. In this picture political actors are little more than automatons, capable only of reacting to predictable events and incapable of innovating. The second picture includes the same actors, with perhaps the same set of initial decision rules. However, in this case these actors are playing much more complicated games, and they treat decision rules as tools useful for dealing with typical situations in standard ways. During times of change these actors do not automatically retain the same rules, but instead look for alternative ways of coping with uncertainty. They do this because they realize that by following an ineffective rule they virtually insure that they will be out-maneuvered by their more skilled competitors. In general, those actors able to excel in an environment of uncertainty will have the most influence over policy.


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The first picture comports with organizational reaction models, while the second one is consistent both with rational choice in an uncertain environment and with the general Simon-Lindblom-Wildavsky framework in which decision makers are flexible enough to adjust to new information and situations. Neither of the latter interpretations suggests a specific operationalization of the policy process. Conversely, organizational reaction models require the imposition of a large number of a priori restrictions. Soviet military expenditures could conceivably affect US military spending levels in many different ways, but an organizational reaction model must exactly specify all feasible effects. If organizations are reacting to past events, then current Soviet expenditures cannot directly affect US spending; in Ostrom (1978) the defense services presume that the Soviets will spend approximately the same as they did the previous year. It may also be difficult to believe that the US can observe what the Soviets actually spent last year; in Majeski (1983b), agencies form expectations of current Soviet expenditures as a function of Soviet expenditures three years earlier. Ostrom and Marra (1986) defend this specification in more detail, by positing a two-year lag between the time that the Soviets actually spend money on their defense and the time that the CIA can estimate this spending and report to the President and Congress, plus an additional one-year lag because of the length of the budgetary decision process in the US. They further argue that analysis must be based on the actual pieces of information available to US policy makers at the time, so they insist on using the contemporary CIA estimate as published by US Arms Control and Disarmament Agency (the official version remains classified), rather than data series that have been subsequently corrected. This three-year lag may seem intuitively plausible, but consider the behavior of individuals and organizations that is necessary for this model to be accurate. In focusing on this single indicator of Soviet expenditures, political actors would need to ignore all other evidence about Soviet actions and intentions. To do so they would even have to ignore the bulk of the information provided by the CIA, which routinely provides multi-year projections of expected future Soviet expenditures and procurement (see Prados 1986). Why would any competent policy maker consider any single piece of information in isolation? Quite the contrary, it is precisely the projections of future Soviet efforts that are most likely to be effective in policy debates, since military procurement decisions necessarily deal with expected future threats, not with the relative situation as it was three years ago. Indeed, the announcement of the Soviet estimate may itself be anticlimactic, coming as it does long after other pieces of evidence of recent Soviet behavior have been reported by other means. If participants in policy debates act on the basis of previously available

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information, then they will have already formed expectations about likely Soviet expenditures. As a consequence, only that part of the Soviet estimate that is unexpected will have any real effect on the process when it is announced, since vigilant policy makers will have already accounted for that part of Soviet spending that is predictable. In short, decision makers make rather more sophisticated assessments of the Soviet threat than taking a single number from among the many projections offered them by the CIA and other organizations. Ostrom and Marra try to capture this sophistication by including variables such as the spending gap or trends in spending changes, but no single decision model can do justice to the complex ways in which this crucially important aspect of defense policy is considered. By admitting the inherent difficulty of operationalization we are led to adopt an alternative approach to empirical evaluation of models based on this second picture of budgetary politics. The central tenet of this approach is that the analysis of time series data should rely as little as possible on a priori restrictions, because the ability of political actors to form expectations about the future and act on innovations in the environment imply that we do not have the type of information necessary to specify any particular model of the defense budgeting process. However, we can still evaluate the overall dynamics of budgetary processes as reflected in the historical data.

VECTOR AUTOREGRESSION MODELS Unrestricted time series methods are appropriate for evaluating data on defense spending and related aspects of superpower rivalry. Because rational actors use much information to revise important expectations, and because much information is important in the formation of expectations, the a priori restrictions typically used in estimating difference equations are often ill advised. Structural models are very difficult to identify if expectations are formed rationally, and we find interpretation of unrestricted difference equations as reduced forms rather than as structures a much more promising line of inquiry.4 Sims’ (1980) development of vector autoregression (VAR) models as interpretable reduced forms resulted from the same concerns with macroeconomics as we have with defense budgeting models (see also Freeman et al. 1989). In VAR models the same number of lags of all variables are included on the right-hand side of the equation for each variable included in the model. Under rational expectations, the estimated system of difference equations defines the expectations of political actors, and innovations are defined as that portion of each variable that is not predictable through least squares projections. Alternatively, if each actor interprets information


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according to simple heuristics, then our estimation can be interpreted as the average response of the defense budgeting system to unexpected changes in any of the variables. To the extent possible, this method lets the data speak for themselves. In this chapter we apply VAR models to the intermediate steps in the US defense budgeting process emphasized in organizational reaction models. In this analysis we use research methodologies appropriate to the study of expectational models to examine the types of variables usually included in organizational reaction models. Direct comparison is, of course, impossible, because of different interpretations of data and of statistical tests. Yet, by playing on their court, so to speak, we highlight the differences between the reaction and expectational approaches. One important difference is that we do not see the bureaucratic, presidential, and congressional outputs of the budget process as simply a series of decisions ordered in time. Instead, we see each as different manifestations of the same underlying dynamic process. They occur at different times and are controlled by different (although overlapping) sets of actors, but they should all be responsive to the same influences. That is, since actors are attuned to innovations in the system, wherever and whenever they occur, any unexpected change in the environment that affects one aspect of this process should affect all the others as well. Furthermore, if policy competition is as intense as we claim, then innovations in these related outputs should be correlated contemporaneously. Because of their temporal arrangement it may appear as if exogenous shocks are propagated from one stage to the next, but in reality the response to any innovation is affected by actors’ expectations of the likely response of actors at subsequent stages as much as it is constrained by actions taken at previous steps. This more complex view of politics necessarily directs attention to the overall dynamic behavior of the system as a whole, in sharp contrast to the estimation of static decision rules characterizing empirical analysis of organizational reaction models. Our VAR model includes four variables measured from 1953 to 1979: DSAt = an aggregation of defense services’ requests (Majeski 1983b). PBRt = an aggregation of presidential defense budget requests (Congressional Quarterly). USAt = US military expenditures (SIPRI).5 SOVt = Soviet military expenditures (SIPRI).6 All data are expressed in constant 1970 dollars.7 The temporal limits are set by the defense service request variable. Defense agency requests are not available for the period prior to 1953, and in 1980 Department of Defense

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(DoD) budgeting methods changed sharply, with increased interaction with the Office of Management and Budget (Wildavsky 1988:365), and so no meaningful separate defense agency requests are available after this period. We estimate a VAR model including three lags of each variable in each of the four equations. That is, we estimate the following model:

Each Bj is a 4x4 coefficient matrix and et is a 4-vector of error terms. Given the short span of our data and the large number of parameters to be estimated, we restrict the VAR by using Bayesian methods (McGinnis and Williams 1989b; and Sims 1982). Conventional estimation requires a relatively large number of fixed parameters in comparison to free parameters, and most regression procedures require that many potential coefficients be set to zero to obtain relatively precise estimates. Zero restrictions of this type are contra-indicated by our decision-making approach, and therefore Bayesian restrictions provide a method for producing relatively precise estimates of the dynamics without imposing a priori restrictions based on supposed prior knowledge. We use prior coefficient means that are neutral (corresponding to a ‘random walk’), and prior distributions around these means are relatively ‘loose’ or wide.8 The estimates must be given a Bayesian interpretation, but, since we are searching for dynamic patterns in the data and do not focus exclusively on standard errors, the distinction between Bayesian and classical interpretation in our case is quite small. These neutral priors force the data to ‘work harder’ to show a relationship between variables. As a consequence of using this Bayesian methodology, we can be more confident that any relationship we identify really does exist, and we are less likely to overemphasize small and insignificant relationships.

RESULTS We follow standard practice by not lising all 48 individual coefficient estimates, since any single coefficient is difficult to interpret in this mode of analysis. Instead, we use the moving average representation (MAR) of the VAR to examine the dynamic response of the system to an innovation or unexpected shock in a variable. The MAR is obtained by inverting the coefficient matrix, and it allows for the system to be written as a summation of all past shocks. Thus, it is perfect for tracing the effect throughout the system of a shock in a single variable.


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Results of MAR analyses are typically presented in graphical form (see Figure 14.1). The size of each innovation equals one standard deviation unit of the disturbance terms for that variable, as estimated with the VAR. This innovation can therefore be thought of as typical of random shocks that have entered the system in this historical sample. As we emphasized earlier, decision rules of actors will be temporally unstable. Since the reduced-form VAR parameter estimates are a function of these decision rules, these estimates may also be unstable. Yet, the MAR analysis is still useful because it is robust to parameter instability. Litterman (1980) shows that correcting for instability in VAR estimates actually results in poorer forecasts. That is, using all past information produces a more realistic dynamic response of variables than if we somehow tried to account for changing decision rules, primarily because decision rules also change in the future. A weighted average of all past data provides for a typical response given the uncertainty about how decision rules will change in the future. This mode of analysis (innovation accounting) requires the imposition of some contemporaneous causal ordering among innovations in the included variables. Each variable is subject to exogenous shocks of various types, and unexpected changes in some variables will have immediate effects on some other variables. For a given contemporaneous ordering, innovations in a given variable immediately affect innovations in all variables listed later in the ordering, whereas earlier variables are affected only after a lag. It is standard practice to impose a simple causal chain, or triangular ordering.9 We use the contemporaneous ordering of defense agency requests, presidential request, US expenditures, and Soviet expenditures. The choice of ordering for the first three variables in the system captures the temporal sequence of the defense budgetary process. The agencies use all past information to make their recommendations, the President then finalizes a budget, Congress appropriates, and expenditures result.10 Any unexpected shock at any stage in this process will immediately be passed on to subsequent stages. Unfortunately, the placement of Soviet expenditures is problematic, since its innovations do not influence the other variables contemporaneously under this ordering. In a simple causal chain, there is no best ordering for US and Soviet expenditures. 11 By placing Soviet expenditures last in the order, any interpretation of the direct effects of US expenditures on Soviet expenditures will be misleading, as will any attempt to evaluate the effects of unexpected changes in Soviet expenditures on all stages of the US budgetary process. Therefore, in this chapter we focus on the impact of the defense budgeting process on the military spending of both states. It may appear that a more natural representation of the process would be to place Soviet expenditures at the beginning of the causal ordering, with

System-response to innovations (constant 1970 US$ bn.)

Note: Each response chart represents the response over ten years of each row variable to a one standard deviation positive shock (innovation) to the column variable.

Figure 14.1


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Soviet behavior affecting all stages of the US budget process. However, this causes problems for our interpretation because of the close contemporaneous correlation between US and Soviet expenditures that we have identified in our previous research. By keeping the spending terms close together we minimize the distortion introduced by relying on a simple causal chain. Furthermore, all organizational reaction models lag Soviet expenditures, as much as three years. This contemporaneous ordering similarly imposes a lag, in the sense that innovations in Soviet expenditures would not affect the stages of the US process until the following year. Finally, our focus in this chapter (as well as in the process model literature) is on relationships among organizations internal to the United States, and our ordering reflects this focus by keeping the temporal ordering of these three stages clear. Yet Soviet expenditures cannot be left out of the model, for they play an important role in expectation generation. As shown in Figure 14.1, after an innovation in defense agency requests the presidential budget request also increases, but at only one-quarter of the level of the change in agency requests. Furthermore, only one-quarter of the increased presidential request is passed on to increases in the actual military budget. Overall, then, innovations in defense agency requests have a very minor effect on actual expenditures. Indeed, Table 14.1 shows that at most only about 2 percent of the forecast error in US expenditures is accounted for by innovations in defense agency requests.12 However, approximately 30 percent of the forecast error in the presidential budget request is accounted for by defense agency requests. Thus, Congress appears to discount defense agency requests, although the President does not. The large variation in defense agency requests suggests why they are so heavily discounted in the budgetary process. Typical disturbances for agency requests (constant $8 billion) are more than twice as large as are typical disturbances for the President’s budget request and actual military spending (approximately $4 billion). That is, the defense agencies appear to act more independently of the system of defense budgeting than do the President and Congress, and they seem to suffer from this behavior. Thus, if these agencies do indeed play games with the defense budgeting process, they are only marginally effective at achieving increased funding as a result. An innovation in the President’s military budget request influences military spending more directly, with about one-third of the request funded through the appropriations process and spent by the military. Furthermore, while Soviet spending does not respond to agency requests, the Soviets do respond strongly to unexpected changes in the presidential budget. This result suggests that the Soviets may treat the military budget requested by the President as an indicator of overall US policy. US presidents often justify increases in military allocations as sending a signal of resolve to the Soviets, and, even if the

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TABLE 14.1 Decomposition of error variance of moving average representation

Note: Each entry represents the percentage of forecast error (k years ahead) in the row variable that is due to innovations in that column variable.

President’s desired increases do not survive congressional debates, he may act in other ways to implement a tougher posture towards the Soviets. Thus, presidential budget requests signal likely US foreign policy postures much more directly than defense agency requests. In fact, as shown in Table 14.1, the decomposition of error variance indicates that, in years immediately following an innovation, the Soviets respond more strongly to the presidential budget request than they do to actual US expenditures, and in all years both of these variables account for a large proportion of the variance in the Soviet military budget. Figure 14.1 also shows that agency requests and the presidential budget respond positively to innovations in US military spending. A suggestive qualitative pattern is that both agency and presidential requests continue to


299

increase as the actual budget decreases towards its previous levels. In our earlier work we have pointed out the tendency for US expenditures to decay more quickly after an exogenous shock than Soviet expenditures, a tendency we interpret as a consequence of the more highly competitive nature of US policy debates. That is, groups opposed to increases (or decreases) in military spending are better able to mobilize public support to offset these recent trends, and thus US spending projections display shorter cycles than Soviet spending projections. The analysis presented here indicates that Congress is more attuned to these pressures than either the President or the military bureaucracies, which is perfectly consistent with the well-renowned congressional sensitivity to changes in public opinion. Conversely, for the case of defense agency requests one gets the impression of organizational inertia, since they continue to go in the same direction for several years running. Because of the ordering problem we will not interpret responses to innovations in Soviet spending. The natural contemporaneous increase in US military expenditures would be held at zero, thus producing a very unnatural response chart. It would be more realistic to insist that any shock in one state’s expenditures is also immediately felt in the other state’s expenditures. An approximation could be obtained by adding the contributions of innovations in the two expenditure terms. Since Soviet innovations have such small effects on our data, defense agency and presidential responses to US spending innovations can be interpreted as a consequence of some simultaneous joint innovation in both US and Soviet spending. These conclusions are further supported by an examination of the contemporaneous correlations among the error terms in each of our four equations, as listed in Table 14.2. In our previous analysis of US and Soviet expenditures alone we obtained a contemporaneous correlation of .56 (Williams and McGinnis 1988:985). In Table 14.2 this correlation has been reduced to .39, indicating that the other variables included go some ways toward explaining the correlation between innovations in Soviet and US

TABLE 14.2 Contemporaneous correlation of innovations

Note: These innovations are from a vector autoregression model including three lags of each variable.

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military expenditures. For both spending terms the correlation with presidential budget request is considerably larger than for the defense services’ request, suggesting that the former more effectively conveys information relevant to their rivalry than the latter. These two intermediate steps are themselves correlated at the level of .55. In combination, these results suggest that, although the defense services react to much of the same information as does the President in preparing his budget request, the service request is otherwise isolated from the rest of the process.

CONCLUSION We have provided only a sample of the type of analyses that could be applied to VAR models including different variables. For example, the apparent importance of presidential budget requests as a signal of US policy invites comparison with our previous analysis of diplomatic hostility and US GNP as informational variables relevant to US and Soviet military spending levels (McGinnis and Williams 1989b). However, the results presented here should suffice to demonstrate the sharp contrast between organizational reaction models of the defense budgetary process and more general models that allow actors to change their behavior in response to changing circumstances. On first sight organizational reaction models may seem more plausible, because they purport to represent the sequential structure of decision. However, these models impose restrictions on the behavior of political actors that are simply untenable. Political processes of competition are far too complex to be directly represented in structural models, but analysis of VAR models can help reveal important aspects of the dynamic interaction of policy variables. Our analysis of the bureaucratic context of defense budgeting demonstrates two major conclusions. First, defense agency requests do not influence the system very much. Second, the Soviets respond to both presidential budget requests and actual expenditures. Presidential requests provide the Soviets with a useful indicator of likely US policy, whereas defense service requests do not, since they are so highly discounted by other actors. Thus, both findings support expectational models of the arms race, where decision makers in both countries look for signals of what other actors are doing and discount actions that are not important for understanding the process. Our conclusion that defense agency requests are not influential in determining US military expenditures contrasts sharply with previous studies, but those works failed to account for the richness of past information. Once we control for the history of the defense budgeting process, variations in agency requests reflect very little of direct relevance to the budgetary process. This is not to say that the agencies’ preparation of a budget is unimportant,


301

but it does indicate that other participants in the budgetary process correctly interpret these requests as what Wildavsky told us they are: a political tool. When placed in the context of complicated patterns of political competition among sophisticated actors, such transparent ploys provide virtually no leverage over policy.

NOTES 1

2 3 4 5

6 7

8

9

This modeling tradition was inspired by earlier, more detailed analyses of the defense budgetary process (Crecine 1971; Crecine and Fischer 1973; Stromberg 1970) and by classic works on non-defense budgetary processes (Davis et al. 1966; Hoole 1976; Wildavsky 1964). Majeski (1989) also criticizes this assumption of additive decision rules, and advocates use of if-then statements and artificial intelligence models. Specification searches of this type serve to underestimate the actual uncertainty in the data and overestimate the precision of estimates. See Sims 1986. The unrestricted system of difference equations can be interpreted as the reduced form of some unknown structure. We depart from the tradition of conventional budgetary process models by using data on US military expenditures expressed in calendar years. To ensure comparability across countries, SIPRI adjusts US budgetary figures, officially expressed in fiscal years, to calendar year data. We use this data series to insure comparability with our earlier results. In any event, this measure is very highly correlated with actual fiscal year appropriations, and the responses of a VAR using data on outlays in fiscal years were very similar to those reported here. For a brief analysis of CIA estimates of US and Soviet military expenditures, see McGinnis and Williams (1989b:1109). Data used to test the defense budgetary process models have been expressed in current dollars, because policy makers supposedly think only in current dollar terms (see Ostrom 1977:252). We argue that inflation is routinely taken into account in policy debates, and we use data in constant dollars in order to focus on real changes in expenditure levels. Besides, by doing so we remove an obvious source of trend in the data. We use the same Bayesian priors as in McGinnis and Williams (1989b). These place restrictions on the relative weight of each variable in each regression. The overall tightness of the prior placed on a variable’s own lag is .2. All other priors are scaled to the lefthand-side variable, and all other weights are selected relative to this initial specification. A variable’s own lags receive full weight, and all other variables in each equation receive one-half the weight of the lagged left-hand-side variables. In addition, short lags receive more weight than longer lags, with a decay of 1/lag. Variation of priors around this specification did not qualitatively change any of the findings reported here. To obtain a simulated dynamic response to an innovation, we must account for the contemporaneous correlations among innovations. Choleski decomposition is used to factor the covariance matrix of innovations into a triangular matrix, thus producing an ordered chain of innovations, with the first variable affecting all others contemporaneously, the second variable influencing all but the first, etc. The dynamic responses of variables are usually robust to choices of orderings, unless correlations are large. Below, we report


302

10

11

12

which relationships are sensitive to ordering assumptions. For more detail on this method of dynamic response analysis, see Sims (1980) and Freeman et al. (1989). We treat congressional appropriations as the final step in the budgetary process, even though actual expenditure levels are also affected by DoD discretionary authority and other factors. Elsewhere we have dealt with this dilemma by maintaining simultaneous shocks to both states’ expenditures (McGinnis and Williams 1989b; Williams and McGinnis 1988), but this approach requires restrictions that are less appropriate for interpreting a series of budgetary actions. The decomposition of error variance is useful for tracing the relative strengths of influences across variables. If one variable influences another, then that variable’s innovations should create innovations in other variables. The figures listed in Table 14.1 provide the proportion of error variance that can be attributed to innovations in each variable.

REFERENCES Allison, G.T. 1971. Essence of Decision: Explaining the Cuban Missile Crisis. Boston, MA: Little, Brown. Crecine, J.P. 1971. Defense budgeting. In W.W.Cooper, R.F.Byrne, A.Charnes, O.A. Davis, and D.Gilford (eds), Studies in Budgeting, pp. 210–61. Amsterdam: North Holland. Crecine, J.P. and Fischer, G.W. 1973. On resource allocation in the U.S. Department of Defense. In C.P.Cotter (ed.), Political Science Annual 4:181–236. Cyert, R.M. and March, J.G. (eds) 1963. A Behavioral Theory of the Firm. Englewood Cliffs, NJ: Prentice-Hall. Davis, O.A., Dempster, M.A.H., and Wildavsky, A. 1966. A theory of the budgetary process. American Political Science Review 60:529–47. Freeman, J.R., Williams, J.T., and Lin, Tse-min. 1989. Vector autoregression and the study of politics. American Journal of Political Science 33:842–77. Hogarth, R. and Reder, M. (eds) 1986. Rational Choice: The Contrast Between Economics and Psychology. Chicago: University of Chicago Press. Hoole, F.W. 1976. Politics and Budgeting in the World Health Organization. Bloomington, IN: Indiana University Press. Isard, W. and Anderton, C.H. 1985. Arms race models: a survey and synthesis. Conflict Management and Peace Science 8:27–122. Lindblom, C.E. 1959. The science of muddling through. Public Administration Review 19: 79– 88. Litterman, R. 1980. Techniques for forecasting with vector autoregressions. PhD dissertation, University of Minnesota. McGinnis, M.D. 1991. Richardson, rationality, and restrictive models of arms races. Journal of Conflict Resolution 35:443–73.


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McGinnis, M.D. and Williams, J.T. 1989a. Bayesian rationality and superpower rivalry: a game theoretic model. Paper presented at the Annual Meeting of the Midwest Political Science Association, Chicago, IL, 14–16 April 1989. McGinnis, M.D. and Williams, J.T. 1989b. Change and stability in superpower rivalry. American Political Science Review 83:1101–23. Majeski, S.J. 1983a. Dynamic properties of the U.S. military expenditure decision-making process. Conflict Management and Peace Science 7:65–86. Majeski, S.J. 1983b. Mathematical models of the U.S. military expenditure decision-making process. American Journal of Political Science 27:485–514. Majeski, S.J. 1984. The role of expectations in arms acquisitions processes: the U.S.–U.S.S.R. case. International Interactions 11:333–56. Majeski, S.J. 1985. Expectations and arms races. American Journal of Political Science 29: 217–45. Majeski, S.J. 1989. A rule based model of the United States military expenditure decisionmaking process. International Interactions 15:129–54. March, J.G. and Simon, H.A. 1958. Organizations. New York: Wiley. Marra, R.F. 1985. A cybernetic model of the U.S. defense expenditure policy-making process. International Studies Quarterly 29:357–84. Moll, K.D. and Luebbert, G.M. 1980. Arms race and military expenditure models: a review. Journal of Conflict Resolution 24:153–85. Ostrom, C.W. Jr. 1977. Evaluating alternative foreign policy decision-making models: an empirical test between an arms race model and an organizational process model. Journal of Conflict Resolution 21:235–66. Ostrom, C.W. Jr. 1978. A reactive linkage model of the U.S. defense expenditure policymaking process. American Political Science Review 72:941–57. Ostrom, C.W. Jr. and Marra, R.F. 1986. U.S. defense spending and the Soviet estimate. American Political Science Review 80:819–42. Prados, J. 1986. The Soviet Estimate. Princeton, NJ: Princeton University Press. Richardson, L.F. 1960. Arms And Insecurity: A Mathematical Study of the Causes and Origins of War. Pittsburgh, PA: Boxwood Press. Russett, B.M. 1983. International interactions and processes: the internal vs. external debate revisited. In A.W.Finifter (ed.), Political Science: The State of the Discipline, pp. 541–68. Washington, DC: American Political Science Association. Simon, H.A. 1945. Administrative Behavior. New York: Macmillan. Simon, H.A. 1958. Models of Man. New York: Wiley. Sims, C.A. 1980. Macroeconomics and reality. Econometrica 48:1–48. Sims, C.A. 1982. Policy analysis with econometric models. Brookings Papers on Economic Activities 1:107–64. Sims, C.A. 1986. Comment [on Ray Fair, Specification, Estimation, and Analysis of Macroeconomic Models], Journal of Money, Credit, and Banking 18:121–6. Stockholm International Peace Research Institute (SIPRI), Various years. World Armaments and Disarmament. London: Taylor & Francis. Stromberg, J.L. 1970. The Internal Mechanisms of the Defense Budget Process—Fiscal 1953– 1968. Santa Monica, CA: Rand, RM-6243-PR. Wildavsky, A. 1964. The Politics of the Budgetary Process. Boston, MA: Little, Brown.

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Wildavsky, A. 1988. The New Politics of the Budgetary Process. Glenview, IL: Scott, Foresman. Williams, J.T. and McGinnis, M.D. 1988. Sophisticated reaction in the U.S.–Soviet arms race: evidence of rational expectations. Americal Journal of Political Science 32:968–95. Zinnes, D.A. 1980. Three puzzles in search of a researcher. International Studies Quarterly 24: 315–42.

CHAPTER 15

Conclusions: If the Times Are A’ changing Davis B.Bobrow

The previous chapters have provided a set of rich, empirical analyses of the causes and effects of US defense budgets and spending during what we have come to call the cold war. That is, their conclusions are based on the past. My intent is more speculative, a corollary of addressing the future. It is by now commonplace to recognize that future US defense budgets will be formed and used in a qualitatively different context. Some of those changes in context are largely in place—sharp changes in: relative national economic performance, resources, and confidence; distributed technological competence (especially on the part of japan); the ‘twin deficit’ situation of the United States; the labor force composition of the US in the coming decades (heavy on minorities and women), with its current corollary of educational inadequacy; the escalating costs of advanced military systems; and the de facto dual use character of major sunrise technology families and manufacturing sectors. In those respects the times have already changed. Other changes are in swift transition from substantial portents into realities that are potentially hard to reverse. Foremost among these is a shift in Soviet priorities from military emphases to domestic economic modernization, from external activism based on massive military power to a far more complex mixture of economic and political initiatives, from coercive diplomacy to a military burden-sharing diplomacy and from economic autarky to substantial participation in the capitalist world economy. The manifest erosion of Communist Party control and centralized authority in the Soviet Union does not guarantee order; it does guarantee internal pre-occupation. The Warsaw Pact is in the process of dissolution, economically and militarily. Delay in its political entombment follows primarily from concern to avoid conservative reversion in the Soviet Union and to hedge against re-emergent German power. 305

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CONCLUSIONS

The combination of East European changes and unprecedented economic integration among the EC countries has made Europe the most dynamic and fluid world region—at least by the measure of media treatment and political and business elite attention. Europe was always central to the US–Soviet military confrontation and Europe has changed. Some of the consequences are unclear; for example, the likelihood of ethnic and communal conflicts reminiscent of the Balkans of the early twentieth century. Some are clear: military power has declined in value for managing US and Soviet security interests in Europe, while Europe increasingly has come to divert US and Soviet security attention from other regions. The joint effect is to devalue in general the military instrument for both US and Soviet security policy, or at least to cast doubt on the need for current budgets and weapons stocks. After all, about 40 percent of US defense spending has supposedly been for the NATO mission. The Warsaw Pact threat has commonly been used to justify needed quantities of conventional forces and ‘gray’ nuclear/conventional weapon systems such as submarinelaunched cruise missiles. The spate of changes in politics, economics, technology, and society has run far ahead of actual reductions of superpower military personnel and equipment, or even pullbacks and elimination of redeployment logistical assets. They have run even further ahead of cancellation of military R&D programs, substantial elimination of military R&D and production capacity, or internationally monitored conversion of large parts of technology and industry. Unlike earlier periods of detente, we now are in one where ‘political facts’ are outpacing ‘military words.’ More globally, Asian nations are having to reassess the prospects for their ‘Pacific Century.’ Asia stands out for its unrepentent communist elites, its still-growing arms industries, and its almost urgent efforts to relate directly to East and West Europe, in contrast to a primarily US orientation. Nations in other parts of the world worry about the possibilities of receiving only ‘benign neglect’ from the superpowers because of their reduced value as military ‘strategic assets.’ These portents and realities may not make it realistic to assume that peace has ‘broken out.’ They do make it unrealistic to assume that the basic premises of the cold war period should be treated as everlastingly valid or guaranteed to retain their domestic potency in the US political economy. This does not justify discarding history, as revealed in the previous chapters. It does justify seriously considering the possibility that the various factors and relationships found in history will operate in the future with significantly different values or even signs. Much of what follows explores possible futures based on the findings presented earlier, but in terms of different settings for key factors. One may disagree with some of the methods and inferences used by other

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contributors to this volume, or puzzle about less than compatible findings. Nevertheless, the variables emphasized in previous chapters will continue to operate in the American political economy that bears on defense spending.

LEGACIES Before turning to speculation about the future, it seems helpful to summarize several facets of defense spending and US public opinion in the recent past and the present. These provide important points of departure for the coming years. The Reagan years (according to data from the House Budget Committee, the Defense Comptroller, and the office of Senator John McCain) saw the following percentage shifts between FY1980 and 1989: defense spending up 47 percent; interest payments up 93 percent; payments to individuals (including but not limited to entitlement programs) up 28 percent; and other non-defense spending down 38 percent. The period witnessed a doubling of defense budget authority in current dollars between FY80 and FY85, and by 53 percent in inflation-adjusted dollars. Within those totals, the hardware, ongoing investment side of the defense budget rose from 38 percent in FY80 to peak at 48 percent in FY86 (defined to include RDT&E (research, development, test, and evaluation), procurement, and military construction). Within the strategic program element of the budget, bombers were the major beneficiary for FY80–89, and planned to be for FY90–94, a historically unprecedented degree of sustained emphasis. Outside of the Department of Defense budget per se, the nuclear weapons related programs of the Department of Energy manifested their historic pattern of tracking with changes in defense finances (Kriegsman and Bobrow 1985). Nevertheless, the strategic forces’ share of the defense budget remained near its historical average (about 11 percent), unlike the Kennedy administration surge. Beginning with FY86, the Congress has in effect cut the defense budget by more than 11 percent in constant dollars. It cut the FY81–89 Secretary of Defense requests by more than 150 percent in current year dollars (Kaufmann 1989:61). Defense spending fell short of historical highs as a share of GNP. And, by the time it took office, the Bush administration had ample reason to believe, as did the Soviets, in the untenability of the 3–4 percent annual real growth in defense spending necessary to maintain current force structure and complete planned procurements. That goal had been abandoned by former Secretary of Defense Carlucci in the late Reagan years. To complicate policy choices further, yet to be used defense spending authority tends to be ‘responsible for about 40 percent of current-year

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CONCLUSIONS

Defense spending’ (Kaufmann 1989:49). These funds are concentrated in the areas of RDT&E, procurement, and construction mentioned earlier. Defense spending cuts on the more quickly responsive elements of the budget amount to cuts in current capabilities and readiness, i.e. in those parts of the US military posture available now, before any negotiated arms reductions would take effect. In contrast, cuts in RDT&E and procurement affect the future. In short, the defense budget has built-in commitments and funds for substantial future investment (of about $270 billion) combined with plans for the decade of the 1990s that will require a total of about $900 billion (Kaufmann 1989:83). The implications of these matters are not purely short-term ones. With regard to military spending directly, they suggest that: (1) (2)

(3)

(4) (5) (6)

defense spending was effectively capped several years ago; defense investment also has been capped but in a way that poses unavoidable choices between abandoning whole systems or deferring procurement of significant numbers; advocates of investment are locked in a fierce budget battle with advocates of current capabilities, and that the strength of the former depends on confidence in Soviet intentions; the strategic forces’ budget offers only a limited target and within it bombers are the most vulnerable accounts; Department of Energy weapons programs face almost certain severe constraints, with implications for nuclear force modernization; and the Congress is both able and willing to slash Secretary of Defense requests and to impose real purchasing power cuts on administration defense requests.

More broadly, they point to the operation of a significant de facto winning coalition among the advocates of defense spending and entitlement programs, a coalition able to succeed at the expense of other non-military programs even if success involves creating dramatically enlarged non-discretionary deficit financing burdens. As for public opinion, a Times–Mirror–Gllup poll just before the 1988 presidential election found very substantial majorities of Americans giving top priority to cuts in the federal budget deficit, laws to protect the environment, and negotiated arms reductions with the Soviet Union (New York Times, 27 November 1988). Shortly after the election, a New York Times–CBS survey reported substantial majorities for no new taxes, increased spending on education and the environment, and, again, negotiated nuclear arms reductions with the Soviets (New York Times, 27 November 1988). An August 1989 Business Week-Harris poll found 68 percent of a national sample

Conclusions TABLE 15.1 US public opinion, mid-1989

Source: Tokyo Broadcasting System and CBS (polling 26–29 June 1989).

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CONCLUSIONS

viewing ‘the “economic threat from Japan” as a more serious threat to the future of the United States than the military threat from the Soviet Union’ (Packard 1989). In June of 1989, a CBS–Tokyo Broadcasting System–German TV survey probed US public opinion, with results reported in Table 15.1. The data present a picture of a mass public lacking in optimism about the national future, unwilling to depart sharply from established defense levels of spending and global deployments and commitments, deeply divided about Soviet intentions, and concerned about national needs in education and the environment. That general characterization applies to self-reported Bush voters as well as to the national sample as a whole. More specifically, substantial pluralities see economic conditions worsening to the detriment of the next generation. Very large minorities see a future of economic decline relative to Japan, and the public is split down the middle on US power decline more comprehensively. On defense matters, the center of gravity (especially among Bush voters) lies with stable defense spending, with Bush voters in particular strongly expecting further nuclear arms reduction. Yet the public is almost evenly divided on whether or not to trust Soviet intentions. Although substantial minorities favor cuts in overseas troop deployments, the most common sentiment is for the status quo. Majorities favor continuing forward nuclear deployments, and overwhelming majorities support security commitments to the US’s two most prominent foreign security partners. Support for greater efforts in education and the environment predominates, especially so among Bush voters. We can sum up the legacies as combining a longing for costless macroeconomic reform, a desire to maintain military security policy fundamentals, and a climate that fosters demands for greater non-military spending on education and the environment without massive, or perhaps even generally very noticeable, reductions of established levels of military spending. Of at least equal importance, it is no longer feasible to combine a flat defense budget in nominal or real terms with meeting defense promises for enhanced national military power and planned procurements. Since relative power is just that, arms reduction could provide a possible escape from the budget bind, but hardly if pursued even at INF rates of speed. Accordingly, battles for resources within the defense sphere are unavoidable. We know from prior periods that such internecine warfare usually involves a significant amount of fratricide between military services and advocates of different new weapon systems. At the same time, that fratricide has in the past provided large amounts of ammunition for those more generally inclined to restrain military spending.

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APPLYING THE PRESENT AND THE PAST TO THE FUTURE Against this background, the future can be assessed from two points of departure. The first treats the future as if the primary determinants are public opinion and the recent budgetary facts just noted. The second assumes that the regularities noted in the other chapters in this volume continue to operate, perhaps in muted form, in the changed world briefly sketched in the introduction to this chapter. As we shall see, both approaches lead to substantially similar expectations. Polls and recent budgetary experience do not make policies, but they do influence at least the public face of policy if only because of the inducements they provide. What would an American administration do if it wished to avoid expending its energies in fruitless budgetary battles and to appeal to the public that appears in the reported poll results? First, it would have to seem to be addressing economic concerns and Japan’s relative acceleration but without being able to rely on a sense of consensus on the urgency of drastic change. That is, it would have to rely on steps to constrain total federal budget growth, and demonstrate concern for economic competitiveness and technology advance. With the revenue side of limits in terms of tax increases, the Federal Reserve would become a crucial actor, and within defense budgets preference would go to those elements associated with technological leadership and sunrise industrial sectors. More generally, leverage within the executive branch would shift away from defense and toward key economic policy institutions such as the Departments of Commerce and Treasury, the Office of Management and Budget, and the Office of the US Trade Representative. Second, the administration would proffer a defense budget relatively stable in current year dollar terms, follow a two-track strategy of declared commitments to military strength and nuclear arms reduction, pledge fidelity to established security commitments, and seek greater burdensharing to comply with plurality preferences for foreign basing and allay the concerns of large minorities. A combination of funding already in the pipeline, arms control commitments, desires for technology leadership, and public caution all press for a de facto ‘build down’ posture. Third, it would display heightened commitments to education and environmental quality. Given resistance to tax increases, it would in resource allocation terms seek non-budgetary levers to do so and only increase funding for those programs by reallocation from other programs. A flat defense budget in nominal terms would allow for any growth in revenues to be so used, but only if the burdens of interest payments on the deficit can be contained, a possibility that would benefit from low interest rates as manipulated by the Federal Reserve.

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CONCLUSIONS

How do these expectations compare with those that can be derived from the previous chapters? The Soviets, should they continue current policy lines, will not present the spending and appropriations stimuli of hostile actions or significantly increased military spending in real or nominal terms, however measured (Marra and Ostrom, Chapter 13). Thus one major factor impelling increases in US efforts noted by Domke and Williams and McGinnis (Chapters 3 and 14) will not do so. Accordingly, one set of considerations conducive to public support for increased defense monies (Stoll, Chapter 4) will be lacking. This need not translate into cuts in US military spending (Mayer, Chapter 2) for some time; that is, the response to Soviet restraint will be damped in budgetary terms. Constraints on cuts will be further bolstered by a substantial floor under public opinion support for very substantial defense funding (Stoll, Chapter 4). Soviet restraint will also deprive an American president of some situations that plausibly warrant uses of force short of war. If Russett and Barzilai (Chapter 8), and the other studies they cite, are correct, such actions will retain their electoral attractiveness. Those available will, however, not be such as to justify sharp increases in defense spending since they will not generate a credible case for increases in force structure or requirements for expensive new high-technology systems. That is, a defense budget on the order of $300 billion should provide the means to deal with militarily minor actors. Demands for greater national attention to education, and by inference to the environment, will be in a tradeoff at the margin with defense funding, in particular for procurement and R&D (Mintz, Chapter 9; Mok and Duvall, Chapter 10). The battleground will most likely be that of increments, not the established funding base. A climate of emphasis on the young rather than the old will have the effect of at least continuing the already established lid on procurement and R&D share of military spending, and weakening the extent to which domestic welfare claims can be met by health programs directed toward elderly segments of the population. That is, even if a de facto coalition persists between advocates of those two forms of expenditures, it will have less clout. The initial tendency of any president responsive to Defense Department budget requests in the context of the procurement bow wave of financial requirements will be to seek education- and environment-related activities that do not impact on the federal budget. Yet public opinion will call for more. Since the Congress is less responsive to defense requests than the President (Williams and McGinnis, Chapter 14), and can also read public desires, it can be expected to pursue education and environment measures that do impact on the federal budget. It is then reasonable to expect that the

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adverse tradeoffs to defense in the budget competition with education and the environment will primarily come from the Congress. It is also reasonable to expect that a president who wishes to mute the adverse impacts of those tradeoffs on the defense budget will seek to make issues other than education as salient as possible, issues where arguably defense monies can contribute. The ‘war on drugs’ is illustrative. The argument to this point emphasizes the low probabilities both of increases in military spending and appropriations and of substantial reductions in established spending levels, at least in nominal terms. It suggests that whatever cuts occur in real or nominal terms will be made at the congressional stage of the budget process rather than at earlier stages. And it contends that heightened demands for educational and environmental efforts will take the form of congressional allocations of budget increments that favor those areas rather than defense or entitlement programs directed at the elderly. Much of this sounds like the late Reagan years. One might argue for a bolder forecast of substantial nominal defense cuts based on a cumulative impact of Soviet behavior that would manifest an upward spiral of tension reduction. The findings in the earlier chapters suggest otherwise. Williams and McGinnis (Chapter 14) suggest that defense and presidential budget submissions will continue to increase, even in the face of congressional cuts. Domke (Chapter 3) argues that the early years of a presidency are the most likely time to see major departures from previous patterns of defense budget requests, yet the Bush administration has yet to display such inclinations to any marked extent. Mayer (Chapter 2) concludes that defense contracts are important political plums and thus, by implication, that Congress will be loathe to curtail them unduly. Further, since the defense and presidential requests are unlikely to be cut back sharply, the Congress can impose significant reductions on those requests and still maintain the nominal value of the defense budget. Reductions in that nominal value are not needed to present the appearance and reality of softening the planned defense posture in the face of Soviet restraint and other national needs. Maintaining the nominal value of the defense budget also can be presented as in line with the caution about Soviet intentions widespread among the public. An apparently status quo budgetary posture also is necessary to maintain a facade of credibility about continued commitment to existing security guarantees and forward deployments. The appearance of caution and a continued supply of plums also are served by the reservoir of yet to be used obligational authority already granted to the Defense Department. With regard to the big systems parts of the defense budget, these considerations all add up to a de facto ‘build down’ posture that maintains at least the facade offeree modernization.

314

CONCLUSIONS

‘Build down,’ with a flat or declining budget in real terms, can have either of two consequences if the unit costs of nuclear and conventional instruments of destruction are rising (Ward and Davis, Chapter 5). If other military accounts are preserved, total destructive power will decline. If those other accounts (primarily personnel and war consumables) are cut, then war fighting readiness will decline. Either outcome can of course be presented as a constructive, but prudent, response to the changes discussed earlier. They each offer some sorts of arms reduction and confidence building. If one assumes some real US economic growth, a flat or declining military budget in real terms will reduce the military burden as a percentage of national economic activity (Huang and Hoole, Chapter 12). Flat nominal defense spending and a ‘build down’ approach make it impossible to have a ‘peace dividend’ of the size and application that would trigger internationally exceptional real growth (Huang and Hoole). Accordingly, share of global economic activity will continue to decline, and with it so might the military burden assumed by the US economy (Chapter 12). Flat nominal defense spending seems then to meet a variety of political imperatives and to be responsive to both Soviet military power and initiatives for international normalization. What it does not do is readily accommodate some sort of strategic security rationale for choosing between claimants on limited defense budgetary resources. Mounting claims are a clear Reagan legacy. Tendencies toward stable military service shares (Domke, Chapter 3), interfere with serious priority setting, as do congressional stakes in contracts for constituents. The likely result is behavior that amounts to disproportionate imposition of cuts on those military accounts which do not provide notable political plums and also fall outside of the historically stable area of personnel expenditures. That means cuts in readiness and sustainability. Yet the feasibility of those cuts is limited by public support for current alliance commitments and wariness of the Soviets. This leaves the budget pattern of deferring hard choices through procurement stretch-outs and reduction in the numbers of units. While financially inefficient, that course of behavior across the board minimizes inter-service friction, allows a president to claim continued commitment to military strength, and allows legislators to display simultaneous concern for limiting defense costs and assiduously pursuing district benefits. Systems are neither killed nor bought in useful quantities. The treatment of the B-2 Stealth bomber is illustrative, as is the continuing congressional tendency to refuse to end funding for systems even in the face of Defense Department urging to do so. A flat defense budget in nominal terms, that is, a declining one in real terms, inherently works to lessen the importance of military spending as a tool of macroeconomic management. Even if Cusack (Chapter 6) is correct in his historical view of defense spending as a tool to deal with economic

Conclusions

315

downturns and their unemployment corollary and managing the electoral cycle, it will shrink in attractiveness for those purposes. That seems assured given the combination of overall budget constraint imposed by the twin deficits and the economic stimulation and job-creating inefficiency of the defense budget instrument compared to other types of spending (Majeski, Chapter 11). This is not to argue that the US military budget will become irrelevant to the domestic political economy, only much less important. In an efficient market, entrepreneurs and financial intermediaries already will have begun to act on the prospect of reduction well before the actual events. The budget shrinkage is likely to have already been factored into market behavior and discounted, as with some kinds of combat (Chan, Chapter 7). In sum, expectations derived from political opportunism and quantitative historical perspectives tend to converge. They both suggest a future of a shrinking defense budget in real terms and a rather flat one in nominal terms. These prospective gross outcomes will be accompanied by repeated furors over particular big ticket item expenditures absent a compelling and fresh strategic vision, a rather unlikely prospect for the remainder of the current administration. A successful macroeconomic soft landing engineered by the Federal Reserve would bolster that forecast. Only a sharp reversal in Soviet policy or very quick, deep-cut conventional and not only strategic arms control agreements and implementation would change it.

POSTSCRIPT The expectations in the previous paragraphs, drafted in mid-fall of 1990, seem to be substantially born out by the Fiscal Year 1991 budget proposed President Bush (Budget of the United States, FY 1991, 1990) and the major European troop cuts in his State of the Union speech later the same week. A build down posture is evident in the military proposals, with phasing out of old battleships and bombers, while maintaining investments in new strategic systems. Forces in being, especially in the Army, are traded off for future hardware. While some of the plums associated with homeland military bases are threatened, there are obvious opportunities to revive the plums by pulling forces back into continental from overseas deployments. The nominal defense budget request actually rises, while allegedly declining in real terms by 2.5 percent. Proposed outlays are an especially indicative measure of changing priorities when compared with the pre-budget baseline for FY91. Defense shows a decline of only 1.1 percent, and an increase from nominal FY90 outlays. Room is left for congressionally imposed cuts, or modified presidential submissions based on accelerated arms reduction, while still maintaining prioryear levels of nominal spending.

316

CONCLUSIONS

The accounts for the elderly do not fare well, with social security flat and Medicare reduced by more than 5 percent. Yet the presidential submission does little more for natural resources and the environment (+0.6 percent) or for the future human capital accounts (education, training, employment, and social services), recommended for a 1 percent increase in outlays above the baseline. As for the congressional stages of the FY91 budget process, political benefits associated with defense spending are hardly likely to vanish so long as defense spending remains more than 20 percent of the national budget, and major firms and regions are seriously dependent on defense employment. These imperatives, combined with others for education and the environment, imply more of the general patterns of the late Reagan years. Shattering of these familiar patterns must await an ‘arms discard’ race becoming the main event, taking the center ring, in the East-West security circus. That possibility can only gain momentum from regional developments that hold out what in the Vietnam era was known as the Aitken option — ‘declare victory and come home.’ Of course, that would require confidence on the part of US and Soviet elites that American withdrawal would not unleash newly troubling security threats from other parties.

REFERENCES Budget of the United States Fiscal Year 1991. 1990. Washington, DC: US Government Printing Office. Kaufmann, W.W. 1989. A defense agenda for Fiscal Years 1990–1994. In. J.D.Steinbruner (ed.), Restructuring American Foreign Policy, pp. 48–93. Washington, DC: Brookings. Kriegsman, W.R. and Bobrow, D.B. 1985. LANL Weapons Resources: An Exploration of Historical Patterns. Arlington, VA: Mesa Consulting Group. Packard, G.R. 1989. Name-calling could lead to worse. The Japan Times, 13 October: 20.

Appendix: The Political Economy of Defense Spending Data Set Alex Mintz and Chi Huang

TABLE A1 Defense and the economy, 1947–87

TABLE A1 contd.

Appendix

321

TABLE A1 contd.

Source: Mintz and Huang (1991), based on various publications of the US Government. Data in constant 1982 prices, calendar years.

322

APPENDIX

TABLE A2 ‘Guns’ vs ‘Butter’

Source: Mintz and Huang (1991), based on various publications of the US Government. Data in constant 1982 prices, calendar years.

Appendix

323

TABLE A3 National defense: outlays by subjunction, 1962–88 (current US$m.)

Source: Office of Management and Budget (various years), Historical Tables: Budget of the United States Government, Washington, DC: US Government Printing Office.

INDEX Numbers in bold refer to figures or tables where these are separated from their textual reference Abolfathi, F. 53, 55, 61 (n1), 64 Abdolali, N. 176, 179 Abramowitz, A. 176, 177 ACDA 85, 87, 265 action-reaction model 115–16, 282 Afghanistan 62, 282 Agbese, P. 1, 8 aggregate indicators 144–5 aircraft, combat 82, 83 Aitken 316 Akaike, H. 255 Alexanders 137, 151 Ale, M. 136, 151 Allison, G.J. 4, 8, 284, 203 allocation, for defense budget: categories 35–7; inter-service 33–4, 37–42; structure 34; variations 46–9 Allvine, F.C. 141, 151 Alt, J. 4, 5, 6, 176, 177 Amemiya, T. 256 Ames, B. 197, 201, 202, 214 Anagnoson, J.T. 21, 30 Anderton, C. 282, 302 Arab 7, 10, 166, 167, 169, 170, 171, 173, 175, 177, 186 Arab-Israeli conflict 166, 179 Arbit, H.L. 137, 140, 151 Argentina 159 Arian, A. 160, 164, 177, 178 Arkin, W. 101 Arms control 42 Arms Control and Disarmament Agency see ACDA arms race 2, 3, 4, 7, 8, 9, 10, 11, 66, 81, 95, 98, 99, 102, 115, 129, 131, 174, 181, 195, 198, 199, 214, 215, 257, 258, 261, 266, 268, 269, 275, 281, 282, 283, 284, 300, 302, 303, 304 Aronson, S. 164, 177 Asch, P. 136, 151 Australia, defense burden 111 Austria, defense burden 111 Averitt, R. 6, 9 Azar, E.E. 96, 101

Bachelier, L. 137, 151 Baker, H. 273–4, 275, 279 Ball, R. 138, 151 ballistic missiles 3; Soviet 76, 77; US 69, 77, 72 bang per buck ratios 87–8 Baran, P.A. 142, 151 Barnett, M. 1, 5, 7, 9, 11 Barzilai, G. 8, 167, 176, 177, 312 Bayesian methods 294 Beaver, W.H. 137, 142 Beck, N. 157, 178 Becker, Abraham 261–2 Begin, M. 165 Belgium, defense burden 111 Ben-Gurion, D. 169 Ben-Hanen, U. 176, 178 Benoit, E. 199, 215 Benson, J. 160, 176, 178 Bergeson, A. 101 Bergson, A. 101 Bernd, J. 216 Berryman, S. 194 Bickel, J. 46, 50 Binkin, M. 188, 194 Bjerkholt, O. 255 Blechman, B. 56, 57, 62, 65, 164–5, 166, 178 Bobrow, D.B. 142, 151, 307, 316 Boldt, B.L. 137, 140, 151 bombers, long-range:Soviet 74–5, 76, 77; US 69–70, 71, 72 Bond, D. 95, 101 borrowing, and budgets 199–200 bounded rationality 283 bounded rationality theory 283 Bourne, R. 155 Bowring, J. 6, 9 Box-Jenkins time series analysis 118 Brody, R. 152, 160, 176, 178 Brown, G.F. 1, 3, 9 Brown H. 38 Brown, P. 138, 151 Brown, T, 176, 178 Brownian motion, market behaviour 137, 138

325

326 Bruawoy, M. 31 Brenner, M. 138, 151 Breusch, T. 249, 255 Brezinski, Z. 99, 101 Britain 159, 162, 173, 180 Brown, F. 152 Brzoszka, M. 168, 178 budget: borrowing 199–200; deficit 217– 19;obligated 18–19; PPBS 37, 41, 43; see also defense budget budgetary allocations 287; categories 201–5; changes 202–5; see also defense budget budgetary process 119, 196; Congress 283, 290–1; policies 218; politics 283–6; stages 35–7; top-down 115; winners 35, 37, 45, 46, 48; see also tradeoffs build down 311, 313–14 Bupp, I. 214, 215 bureaucratic momentum 119, 120 Burton, D. 264, 280 Bush, G. 52, 55, 66, 263, 309, 310, 315 Bush administration 52, 194, 217, 263, 307, 313 business confidence 143 business cycles 15, 31, 118, 130, 153, 157, 158, 257; politically manipulated 6, 117, 118 Byrne, I. 9 Byrne, R. 302 Calleo, D.P. 111, 129 CALM 115, 116 Cambodia 160 Cameron, D.R. 113–14, 129 Campbell, D.T. 155, 179 Canada, defense burden 111 Cantril, A. 178 capitalism 112–14; and countercyclical tools 142; and fiscal policy 116–17 Cappelen, A. 242, 255 Caputo, D. 198, 199, 202, 215 Caribbean 160 Carlucci, Frank 38, 307 Carter, J. 30, 38, 40, 41, 42, 48, 158, 161, 191, 192 Carter, defense budget 190–1 Carter administration 38, 42–3, 45, 49, 106, 161, 190 Casdtler, F. 130 Central America 160 Central Europe 65 Central Intelligence Agency (CIA) 87, 94, 264, 265, 266, 267, 269, 270, 271, 272, 274, 275, 276, 278, 279, 280, 291, 292, 301 Chan, S. 2, 8, 9, 10, 142, 151, 194, 218, 242, 255, 315 Chang, E.C. 139, 151

INDEX Charres, A. 9, 302 Chase-Dunn, C. 239, 255, 257 Chile 9 China 9, 129, 145 Choleski 301 Chrystal, A. 4, 5, 6, 176, 177 Clark 64 Clayton, J.L. 185, 186, 187, 193, 194 Cochran, T.B. 68, 69–70, 74, 75, 101 Cockle, P. 264, 267, 280 Cohen, S. 95, 101 Colby, W. 267 cold war 104, 106, 109, 110, 127, 289, 306 Collins, J. 68, 69, 70, 74, 75, 82, 101 Competing Aspiration Levels Model 115, 116 Conflict and Peace Data Bank (COPD AB) 96, 101 Congress 2, 3, 17, 18, 19, 20, 29, 30, 31, 35, 37, 48, 53, 62, 118, 158, 163, 186, 217, 218, 262, 267, 274, 297, 299, 307, 308, 312, 313 Congress: budgetary decisions 283, 290–1; defense budget 38; elections 26–7; federal budget 38 Congressional Budget Office 30, 31, 35, 218 conscription 228 construction, military 48–9, 110 contract awards 18–21, 30, 88, 89; as countercylical tools 16; credit-claiming 19, 26, 27; defense activity level 29; DoD 19, 22–5; and elections 21–8; employment 17, 22, 187; as political plums 313; timing 26 conventional military capabilities 82–3, 88 Cooper, G. 144, 154 Cooper, W. 9, 302 Cootner, P. 151, 153 corporatism 113, 114, 129, 130 corporatism, index of 113–14 corporate indicators for US 89 corporate insiders 140 Costener, H. 130 Cotter, C. 302 Cotton, T.Y.C. 164, 178 countercylical use of military spending 118 Cozier, M. 215 Crawford, N. 68, 75, 101 Crecine, J.P. 3, 9, 51, 115, 129, 219–20, 222, 301, 302 credit-claiming and contract awards 19, 26, 27 Crespi, I. 158, 178 Crockett J. 152 cruise missiles 3 cruise missiles, air-launched 70 Cuban missile crisis 141, 152, 302 Cusack, T.R. 1, 3, 6, 7, 8, 9, 10, 15, 31, 34, 51, 104, 116–17, 118, 119, 129, 130, 199, 214,

INDEX 215, 219, 242, 247, 278, 280, 314; contract awards 16; defense spending 15, 33; electoral 16, 21–8, 120, 141, 157 Cyert, R.M. 284, 302 Cypher 219 Czada 129 Czechoslovakia 62 Dabelko, D. 196, 215 Dann, L. 138, 151 data sources, military capability 68–82; Soviet 75 Davis, D. 7, 8, 314 Davis, O. 2, 4, 9, 289, 290, 301, 302 decision rules; additive 288; defense budget 4;innovations 299–300; simple 288; updated 289 defense; GNP 53, 66; policy 66–7; public opinion 308–10; social spending tradeoffs 208, 210, 211; and Soviet threat 65–7, 87– 90, 96–7, 98–100; strategic concerns 66; and veterans’ benefits 207 Defense agencies 36, 39, 41, 47, 295, 298, 299 defense agencies requests 283, 300–1 defense budget 1, 3, 20, 21, 26, 29, 32, 53, 54, 55, 57, 59, 222; actual/predicted 127; allocation 33, 34, 35–7, 39, 42–6, 46–9, 323; annual 16, 17, 18; autonomy 34; and Congress 38;continuity 44; decision rules 4; domesticfactors 103–4; employment 128–9 (n1); macroeconomic variables 221, 224– 30; model for 224–30; political processes 282–3; reducing 66; variation 47; see also tradeoffs defense burden 104, 105, 214, 242–6; and capitalism 142–3; compared 111; hegemony 246–50; GDP 105; international context 110–14; (1947–87) 319–21 defense contractors: major 90–4; net income 92; profits 91, 93; see also contract awards defense contracts see contract awards Defense Departments 20, 35, 38, 41, 217, 312, 313, 314 Defense Intelligence Agency 265–6 Defense Service Agencies (DSA) 225, 229, 231, 232 defense spending 1; arms race approach 2; as budgetary tool 219–23; cycles 33; domestic economy 88–90, 116–17, 199, 217, 282; and education 190; fluctuations 186; incremental approach 2, 3–4, 46; and inflation 218; linked to non-defense spending 198–200; for 1990s 308–10; political use 17–18; public opinion 52–5; used countercyclically 15; welfare tradeoff 185–92; see also defense budget

327 deficit, defense and social spending tradeoffs (1954–86): percentage change 210; relative change 212 deficit financing 200 Deger, S. 193, 194 DeGrasse, R.W. 7, 9, 185, 186, 187, 218, 219 DeLuca, D. 53, 64 democracies: and conflict 163–4; and discontent 155; and public opinion 52, 61 Dempster, M. 2, 4, 9, 302 Denmark, defense burden 111 Department of Defense see DoD detente 34, 67, 96–7, 306 deterrence 98, 99 Deutsch, K. 116, 129 developed countries 194, 222, 241 Devine J. 9, 31, 130, 256 disarmament, unilateral 65–6 DoD (Department of Defense): 17, 30, 32, 35, 36, 84, 85, 89, 90, 109, 118, 130, 293, 302, 307; authority 43; awards 21; budget 3–4, 28–9; budgetary components 110, 185;contract awards 19, 22–5; expenditure 283;goods and services 186–7; organizational posturing 33–4; Reagan administration 109;resource allocation 192 Dodd, P. 152 Doksum, K. 46, 50 dollar comparisons, Soviet budget 267–8 domestic political economy 66; competition for resources 290–1; and defense spending 88–90; 116–17, 199, 217, 282; security policies 1 Domke, W.K. 7, 8, 185, 187, 189, 193, 195, 196–7, 199, 200, 201, 202, 213, 214, 215, 312, 313, 314 Dow-Jones Index 144–5 Dow-Jones Transportation 145, 147 Dow-Jones Utility 145, 148 Downs, A. 4, 9 DSA (Defense Service Agencies) 225, 229, 231, 232 dual economy 6, 9, 10 Duchin 242 Dupuy, T. 82, 101 Duval, R. 8, 312 Eastern Europe 52, 60, 66, 262, 282 economic hegemony 111–12, 239–41, 243–6 economic stabilization 119, 120 education, and defense spending 190 Edwards, G.C. 158, 178 efficient-market hypothesis 136–40, 141 Egypt 169 Eichenberg, R. 195, 199, 201, 202, 214, 215 Eisenhower 33, 35, 37, 38, 39, 41, 45, 48, 49, 104, 161

328 Eisenhower administration 40, 42, 43, 161 Elder, R. 162, 178 elections: congressional 26–7; credit-claiming 19, 26, 27; economics 17, 156–9; GDP 162;Israeli 169–72; policy cycles 16, 21–8, 120,157; presidential 26–7, 119, 120; pressures121; unemployment 22, 118, 120– 1, 157 electoral cycles 6, 7, 10, 22, 117, 118, 119, 120, 126, 131, 141, 151, 157, 158, 163, 177, 178, 179, 181, 215, 219, 314 employment; and defense budget 128–9 (n1); contract awards 17, 22, 187; labor markets 112, 117 Engle, R. 246, 247, 249, 253, 254, 255 Entebbe hostage rescue 160 Enthoven, A.C. 37, 50 equilibrium, long-term 251–4 equity prices 136 equity shares 136 Erskine, H.G. 164, 178 Europe 15, 66, 160, 258, 262, 282, 305, 306, 315 expectational approach 285–6, 287 Falkland/Malvinas conflict 159, 180 Fama, E.F. 137, 138, 151 Fedder, E. 215 federal budget: allocations 107, 109; Congress 38; surplus/deficit 108, 224, 225 federal debt 106 Federal Reserve 157, 232, 311, 315 Federation of Atomic Scientists 65 Finifiter, A. 131 Finifiter, W. 180, 303 Finland, defense burden 111 fiscal constraints 229 Fischer, G.W. 3, 9, 115, 129, 219, 222, 301, 302 Fisher, L. 19, 30, 151 Fletcher 180 flexible response 41, 42 force, military, visible use 54, 66–7 Ford administration 42, 45 Ford, G. 30, 37, 38, 40, 41, 42, 45, 48 foreign policy, legislative constraint 159–60 Fox, J. 19, 31 France, defense burden 111 Frank, A. 6, 9 Freeman, J. 100, 101, 245, 255, 257, 292, 302 Freidan, J. 4, 9 Frey, B. 4, 9, 116, 120, 129, 130 Friedan, J.A. 5 Friend, I. 139, 152 Gaddis, J. 41, 50

INDEX Galbraith, J.K. 187, 195 Gallup polls 120, 123, 130, 308 GDP: defense burden 105; military spending 104; and presidential election 162 George, A. 256 Germany 111, 197 Germany, Federal Republic, defense burden 111 Gervasi, T. 68, 69, 74, 75, 101 Gilford, D. 9, 302 Gillespie, J. 2, 3, 9, 11 Gilpin, R. 4, 5, 6, 9, 239, 244, 256 Gist, J. 203, 214, 215 Gleditsch, P.N. 255 GNP 202; and defense 53, 66; and federal debt 106; implicit price deflator 57; and military spending 193; Soviet 94–5; US 240–1 Gochman, C. 180 Godfrey, M. 137, 152 Goertzel, Ted 117, 129, 130 Goff, E. 197, 214 Goldstein, J. 99, 101 Goldthorpe, J. 129 Goodman, A. 256 Gorbachev, M. 99, 262, 264, 279, 282, 286, 309 Gramm-Rudman 217 Granger causality approach 220–3, 225, 234 (n3), 245–6 Great Britain see United Kingdom Great Identity 219–20, 222, 224 Great Society 143 Greenberg, E. 18, 19, 31 Greenstein, F. 50 Griffin, L.J. 1, 3, 9, 15, 31, 118, 130, 242, 256 Griffith, R. 136, 152 Grobar, L. 242, 256 Groth, J.C. 140, 152 growth 140 guns versus butter 185–7, 188, 196, 322 Gurr, T.R. 163, 178, 180, 181 Gyimah-Brempong, K. 242, 256 Hanoi 161 Hanson, E.C. 1, 7, 10, 142, 146, 153 Hart, J. 237, 257 Harville, D. 136, 152 Hayes, M. 201, 202, 215 health, and defense tradeoffs 197–8 Hedge, D. 213 hegemony: economic 111–12, 239–41, 243–6; and military burden 246–50; stability 6 helicopters 82, 83 Hendry, D. 255 Henrekson, M. 129 Henry, D. 128, 130 Herbst, A.F. 141, 152

INDEX Herman, E. 152 Herndon, J. 216 Hibbs, D. 123–4, 129, 130, 176, 178 Hicks, A. 1, 10, 15, 31, 118, 130, 176, 179 hitch 219 HOBA standard 274, 275, 276, 277, 278, 280 Hoenig, M. 101 Hogarth, R. 284, 302 Holmes, J. 162, 178 Holsti, O. 152, 256 Holsti, P.L. 141 Holzman, F. 264, 265, 266, 288 Hoole, F. 6, 7, 8, 9, 237, 239, 243, 245, 256, 257, 301, 302, 313 Hong Kong stock market 142 Horowitz, D. 164, 177 Hosking, J. 248, 255, 256 Howard Baker Standard see HOBA standard Huang, C. 3, 6, 7, 8, 9, 10, 90, 102, 239, 242, 243, 244, 245, 247, 256, 257, 314 Huisken, R. 187, 194, 195 Hungary 62 Huntingdon, S.P. 2, 33, 37, 238, 239–40 Huntingdon, S. 9, 50, 198, 215, 219, 256 Huth, P. 164, 178 IISS 68, 69, 70, 75, 82, 101, 265, 266, 268, 278 increments 2, 3–4, 46; in budget decisions 34, 284, 312; changes 288; war costs 135 India 216 inflation: current money supply 228–30; defense spending 218; electoral impact 156– 7; war 143 innovations, in decision making 299–300 inter-service competition 37–42 International Institute for Strategic Studies see IISS International Monetary Fund (IMF) 105, 130 international tension, and stock market 141 Intifada 167 investments, and war 143 Iran 176, 178 Iran–Contra affair 159, 161 Iranian 159 Isard, W. 282, 302 Israel: 8, 10, 155, 156, 173, 176, 178, 179, 180, 195; data on conflicts 166; elections 169–72; foreign policy 160; government support in security crisis 160; Labour Party 168; military expenditure 158; military force for domestic political purposes 164–72; and Iraq 165 Italy, defense burden 111 Iyengar, S. 176, 178

329

Jacobson, C. 85, 101 Jacobson, G.C. 158, 178 Jacobson, H. 117–18, 121, 130 Jaffe, J. 140, 152 James, P. 176, 178 Japan 95, 111, 241, 305, 309, 310, 311 Jenkins, G. 118, 246, 255 Jensen, M.C. 139, 151, 152 Jervis, R. 176, 178 Job, B. 161, 172, 177, 180 jobs see employment Johnson, Lyndon 40, 41, 48, 143, 160, 161 Johnson, P. 255, 257 Jones, D. 41, 50 Jones, L.S. 70, 101 Kalecki, Michael 112, 130 Kamlet, M.S. 35, 50, 51, 115, 129, 188, 191, 193–4, 195, 219, 220, 222 Kanter, A. 33, 37, 40, 50 Kaplan, S. 56, 57, 62, 64 Karlin, S. 256 Katzenstein, P. 5, 9 Kaufmann, W. 64, 307, 308, 316 Kegley, C. 64, 131 Kelleher, C. 195, 202, 215 Keman, H. 113, 130 Kendall, M. 137, 152 Kennedy administration 41, 42, 161, 307 Kennedy, J. 34, 179 Kennedy, P. 8, 99, 101, 238, 239, 240, 242, 243, 244, 245, 250, 251, 253, 254, 256 Keohane, R.O. 5, 6, 9, 239, 244, 256 Kernell, S. 17, 31, 158, 176, 178, 179 Keynesian theory 112–14, 117, 219 Khouri, F. 169, 179 Kiefer, D.M. 115 Kiewiet, D. 176, 179 Kimpton 152 Kinder, D. 157, 176, 178, 179 Kindleberger, C. 6, 9 King, B. 145 Kissinger, H. 38 Kitfield, J. 90, 101 Klieman, A. 171, 179 Kmenta, J. 214, 215 Kon, S.J. 139, 152 Korb, L.J. 1, 3, 9, 38, 50, 190, 193, 195 Korea 2, 10, 11, 54, 164, 180 Korean 30, 34, 57, 119, 121 Korean War 34, 40, 43, 104, 110, 142, 149, 243 Kotz, N. 30, 31 Kramer, G.H. 17, 31, 176, 179 Krasner, S.D. 5, 9, 142, 152, 239, 256

330 Krell, G. 15, 31, 117, 130, 242, 256 Kriegsman, W. 307, 316 Kugler, J. 99, 102, 239, 256, 257 Kupchan, C. 238, 256 kurtosis 46 labor 113–14 Labour Party, Israel 168 lag structure 99–100, 273, 274, 291 Laird 37, 45 Lake, D.A. 4, 5, 9 Lambelet, J.C. 82, 101 Lane, D. 95, 101 Lanoue, D. 177 Latham, M. 137, 152 Latin America 197, 214 Lease, R. 152 least squares estimates 140, 230, 235, 248 Lebanon 164, 166 Lee, J. 176, 179 Lee, W.T. 264, 265, 266, 278, 280 leftist parties 113–14 Lehmann, B.N. 140, 152 Lehmbruch 129 Leng, R. 164, 179 Levine, H. 95, 101 LeVine, R.A. 155, 179 Levy, J. 176, 179 Lewellen, W.G. 139, 151, 152 Lewis-Beck, M. 176, 179 Li, W. 248, 256 liberalism 5, 6 Likud 168 Lin, T. 100, 101, 302 Lindblom, C. 283–4, 290, 291, 302 Lindgren, C. 242, 256 Liske, C. 214, 215 Litterman, R. 295, 302 Lorie, J.H. 137, 140, 144–5, 152 Loehr, W. 214 Lowi, T. 158, 179 Luebbert, G. 214, 215, 282, 303 Lute 64 Lybeck, J. 129 Lynn-Jones, S. 1, 10 MacKuen, M. 176, 178 MacRae, D. 196, 215 macroeconomic performance 221–2, 224–30 Mahajan, A. 199, 215, 222, 237 Mahon, G. 267 Majeski, S.J. 4, 8, 10, 220, 225, 282, 283, 285, 291, 293, 301, 303, 315 Malkiel, B. 151 Mandelbrot, B. 137, 152 Maoz, Z. 176, 178

INDEX March, J.G. 284, 302, 303 Marfels, C. 187, 195 market economy: adjusting 138–9; government intervention 112; movements 144; Marsh, D. 180 Markowitz, H.M. 144, 153 Marra, R. 4, 8, 10, 34, 51, 52, 64, 115, 123, 130, 160, 179, 199, 215, 266, 268, 273, 279, 280, 282, 283, 286, 287, 290, 291, 292, 303, 312 Marxism 5, 6, 142; see also neo-Marxist approach Maw, L.L. 18, 31 Mayer, K.R. 2, 7, 8, 27, 30, 31, 176, 179, 312, 313 Mayers, D. 151 McCain, J. 307 McCamant, M. 214 McCormick, J. 196, 215 McCubbins, M. 65, 84, 101 McGinnis, M.D. 8, 84, 99, 101, 282, 285, 286, 294, 299, 300, 301, 302, 303, 304, 312, 313 McGlothlin, W. 136, 153 McGowan, P. 64, 131 McGuiness, E. 9, 195 McGuire, C. 161, 180 McKean 219 McLeod, A. 248, 256 McMillan, S. 151 McNamara 38, 40, 43, 45, 269 McNamara’s defense department 37, 41 Medicare 193, 208, 209, 210, 211, 212, 316, 321 Melman, S. 6, 10, 94, 102, 142, 153 Mendel, R.A. 38, 45, 51 Merritt, R. 152 Mickle, M. 11 Middle East 160 Midlarsky, M. 179 military action 57, 170 military budget see defense budget military burden see defense burden military capabilities: conventional 82–3, 88; nuclear 67–82 military construction 36 military expenditures see military spending Military Keynesianism 103, 112, 113, 114, 130, 179 military personnel 36, 185, 323 military service, as benefit 188 military spending 157–8; changes in levels 224, 225; dynamics 114–16; external factors 115; GDP 104; GNP 193; internal factors 115; and political economy 4–8, 116–28;

INDEX and pump-priming 117; Soviet 85–7; US 15, 84–5; 105 military stockpiles 65, 67–83 military-industrial complex 6, 7, 10, 117, 142, 153, 156, 195 Milstein, J. 145, 146, 152 Mintz, A. 1–2, 3, 6, 7, 10, 15, 31, 37, 50, 90, 91, 92, 94, 102, 118, 130, 151, 176, 179, 194, 195, 213, 220, 242, 244, 256, 257, 312 Miroff, B. 159, 179 misery index 172, 177 (n18) mobilization, wartime 121 Modelski, G. 239, 257 modern world system 6, 7, 11 Modest, D.M. 140, 152 Mok, J. 8, 312 Moll, K. 214, 215, 282, 303 Monroe, K. 176, 180, 199, 215 monopoly sector firms 187 Moody 89, 90, 92, 102 Moore, A.B. 136, 137–8, 153 Moore, G.H. 136 Moregenstern, O. 137, 152 Morita 90 Morse, D. 139, 153 Moskos, C. 180 movements 144 Mowery, D.C. 35, 46, 50, 51, 195 Mueller, J.E. 54, 64, 146, 153, 176, 180 Natchez, P. 214, 215 national debts 135 National Security Council 38 national security policy 1–8, 174 NATO 11, 110–11, 306 Navy 42 neo-Marxist approach 239, 242, 243; see alsoMarxism Netherlands, defense burden 111 New Look, Eisenhower 42, 43 Niederhoffer, V. 140, 141, 153 Nigeria 2, 8 Nincic, M. 1, 6, 10, 15, 31, 34, 51, 52, 64, 104, 116–17, 118, 119, 130, 160, 180, 199, 214, 215, 219, 242, 257 Nixon administration 38, 42–3, 45, 49 Nixon, R. 37, 38, 40, 41, 42, 45, 48, 160 non-defense expenditures 224, 226 Nordhaus, W. 176, 180, 199, 215 Norpoth, H. 176, 180 Norris, R. 101 North, R.C. 141, 152 Norway, defense burden 111 nuclear capabilities: Soviet/US compared 66, 79, 80, 81–2; total, Soviet 78; total, US 73

331 nuclear delivery vehicle US 71 nuclear firepower: costs 87, 98; deliverable 80, 81 nuclear warheads 41, 67–8, 70, 72, 80 Nye, J.S. 1, 5, 9, 10 obligations, budgets 18–19, 20 OECD 94, 114, 128, 130, 195 Office of Management and Budget (OMB) 18, 34–5, 217, 294, 311 Office of Secretary of Defense (OSD) 41 Oginibene, P. 30, 31 Ohlson, T. 168, 178 Oliver, R. 128, 130 Olson, M. 111, 130, 244, 257 OMB 18, 34–5 O’Neill, D.E. 141, 151 operation and maintenance 36, 110, 185, 323 organizational reaction models 282–3, 286–90 Organski, A. 99, 102, 239, 240, 256, 257 Osborn, G. 64 Osborne, M.E.M. 137, 140, 153 Osirak 169 Ostrom, C.W. 2, 4, 8, 10, 15, 31, 34, 51, 52, 64, 67, 102, 115, 123, 130, 160, 161, 172, 177, 179, 180, 199, 215, 220, 237, 242, 257, 266, 268, 273, 279, 280, 282, 283, 286, 287, 290, 291, 292, 301, 303, 312 Packard, G. 310, 316 Padgett, J.F. 46, 51 Pagan, A. 249, 255 Page, B.I. 52, 64 Park, K. 2, 11 Park, T. 2, 10 Parsons, W. 239, 255 Patell, J.M. 140, 153 peace dividend 1, 10, 94, 99, 100, 256, 262, 282, 314 Pearce, D. 139, 153 Peroff, K. 187, 195, 197–8, 199, 202, 215 personnel expenditures 18, 110, 187–8 Piccini, R. 136, 143, 153 Pierce, D. 237, 257 Planning, Programming and Budgeting System see PPBS Podolak-Warren, M. 187, 195, 197, 198, 202, 215 policy cycles 176 (n4) political economy 1, 4–5, 21–8 political leaders 155 politics: and business cycle 6; compromise 288; leaders 155; military spending 113–14; public opinion 311–15; see also elections Porter, R. 242, 256 Power transition 99

332 PPBS 37, 41, 43 Prados, J. 268, 280, 291, 303 president 155; as commander-in-chief 161–2; and foreign policy actions 163; popular/ Congressional support 146, 158, 160, 161; and public opinion 60–1 presidential budget requests 283 presidential elections 26–7, 119, 120 presidential popularity 146, 158, 160, 161 Price, H. 176, 178 procurement 36, 48–9, 109, 110, 185, 186, 323 productivity comparisons 95 Pryor, F. 113, 130, 197, 201, 216 Przeworski, A. 113, 130 public opinion 122; defense spending 52–5; (1988–89) 308–10; policy 311–15; political leaders 55, 57, 60–1, 155; sampling 55–60 pump-priming 117 Pursell, C. 6, 10 Quandt, R. 151 Raab, R. 151 Ragen, W. 9, 195 Ragin, C. 169, 180 Rally ’round the flag 159–64, 179 Ramesh, S. 177 R & D see research and development Rapkin, D. 239, 243, 257 Rasler, K. 6, 7, 10, 242, 257 Rathjens, G. 2–3, 10 Rational choice 284, 291, 302 rational choice theory 283, 290 rational expectations model 285–6, 287 reactive linkage models 4 Reagan, R. 3, 24, 25, 33, 34, 38, 40, 41, 42, 45, 48, 49, 55, 58, 63, 66, 79, 99, 103, 107, 127, 128, 176, 178, 179, 188, 191, 192, 193, 194, 195, 220, 261, 270, 307, 313, 314, 316 Reagan administration 18, 23, 50, 57, 60, 109, 119, 217, 220, 243, 282; arms build-up 3, 24, 103, 127–8, 243; contract awards 25; defense budget 48, 106–7, 191, 220, 279– 80, 307, DoD 109; federal budget 107; modernization 43, 45; and public opinion 55, 57; resource allocation 42–6; service share shifts 42; and tradeoffs 188–90, 193–4 realism 5–6 recession: and low-level military force 162; political effects 156–7 Reder, M. 284, 302 Reichart, J. 8, 9 Renshaw, E.F. 140, 153 research and development 36, 109, 110, 185, 186–7, 323

INDEX Ricardo 5 Richard, J. 255 Richardson 38, 45 Richardson, L.F. 2, 4, 10, 115–16, 131, 282, 302, 303 Riddell, T. 135, 153 Ridel, R. 94, 102 Roberts, H.V. 137, 153 Rockwell International 90, 92 Rokkan, S. 152 Roley, V. 139, 153 Roll, R. 151 Rosefielde, S. 265, 280 Rosen, S. 6, 10, 142, 153 Rosenau, J. 152 Rosenberg, D. 68, 102 Rovner, M. 30, 31 Rubison, M. 9 Ruloff, D. 96, 97 Rumsfeld, D. 38, 45, 48 Rupert, M. 239, 243, 257 Russett, B. 1, 2, 6, 7, 8, 10, 53, 64, 115, 116, 131, 142, 146, 149, 153, 162, 163, 164, 172, 174, 176, 178, 180, 185–7, 188, 189, 190, 191, 193, 195, 197, 198, 199, 201, 202, 216, 239, 240, 242, 282, 303, 312 Sabrovsky, A. 180 Sachar, H.M. 165, 180 Salmon, M. 251, 257 Sam Lehman-Wilzig 168 Samuelson, P.A. 137, 138, 153 Sanders, D. 176, 180 Sandier, T. 100 Sands, J. 101 Sargent, T. 257 Sarkesian, S.C. 142, 153 scapegoating 159 Schexnider, A. 194 Schlarbaum, G. 152 Schlesinger, J. 38, 45, 267 Schmidt 129 Schmitter 129 Scholes, M.S. 138, 153 Schrodt, P. 9 Schwarz, G. 257 Schwarz’s criterion (SC) 247, 248, 254 Schwert, G. 139, 153 security market 143–4 Seligman, D. 139, 154 Shapiro, C. 52, 160 Shapiro, R. 64, 178 Sharet, Y. 169, 180 Sharpe, W.F. 139, 144, 153, 154 Shaw, R.P. 155, 180 shift index, inter-service rivalry 39–40, 41

INDEX Simon, D. 130, 160, 161, 179, 180 Simon, H.A. 283, 284, 290, 291, 303 Simonton, D. 176, 180 Sims, C.A. 257, 292, 294, 301, 302, 303 Singer, J. 116, 129, 152 SIPRI (Stockholm International Peace Research Institute) 68, 69, 70, 74, 75, 86, 87, 101, 102, 111, 131, 265, 266, 269, 270, 271, 278, 280, 293, 301, 303 Siverson, R. 256 Skocpol, T. 31 Slinkman, C.W. 141, 152 Smirlock, M. 139, 154 Smith, A. 5 Smith, K.W. 37, 50 Smith, M. 194 Smith, R.B. 94, 102, 164, 180, 194, 195, 237, 242, 257 Smith, T. 131 Snidal, D. 6, 10 Snyder, W. 136, 154 Sokolovsky 257 Solnik, B. 139, 154 Solt, M. 136, 154 Soviet 3, 7, 10, 29, 51, 62, 64, 67, 68, 79, 80, 81, 82, 83, 85, 86, 87, 100, 101, 116, 128, 129, 130, 131, 159, 180, 199, 216, 217, 282, 293, 297, 298, 299, 300, 301, 303, 304, 307, 308, 310, 313, 314, 315 Soviet defense expenditures: burden 95; changes 271; data 263–80; estimates 272, 274, 275– 8, 291–2, 295; and US spending, compared 115 Soviet Union 9, 52, 56, 57, 59, 60, 64, 69, 87, 88, 96, 98, 99, 160, 161, 180, 268, 308; economy 94–5; GNP 94–5; nuclear capabilities 74–7; percieved threats 15, 34, 261–3, 283, 312; power reduction 65–6; priorities shift 305; and public opinion 54; see also Soviet defense expenditures Sprague, J. 113, 130 stability: economic 119, 120; hegemonic 6; temporal 289 stabilization policies 119, 120 Standard and Poor Index 144–5 Starr, H. 2, 10, 237, 242, 257, 318 Stein, A. 164, 176, 180, 237 stock market: and business confidence 135; economic indicator 136–40; and electoral cycles 141; Hong Kong 142; movements 137; sensitivity to political events 141–4; Vietnam war 146–50; and war escalations 149 Steinbruner, J. 316 Stephenson, M. 213 Stewart, J. 213

333 Stockholm International Peace Research Institute see SIPRI Stockman, D. 18 Stohl, M. 164, 176, 180 Stoll, R.J. 7, 8, 57, 62, 64, 151, 161, 180, 213, 312 Stone, R.A. 160, 171, 180 Strange, S. 5, 11, 240, 257 strategic capabilities indicators 67–8 strategic delivery vehicles 79 strategic triad 67, 73, 74 Stromberg, J. 3, 11, 301, 303 Stubbing, R.A. 18, 31, 38, 45, 51 Sturm, S. 8, 9 Su, T. 195 Suedfeld, P. 161, 180 superpower rivalry 65, 96, 97, 285, 286 Swanson, P.J. 136, 154 Sweden, defense burden 111 Sweezy, P.M. 142, 151 Switzerland, defense burden 111 Szymanski, A. 142, 154, 242, 257 Tahim, G. 9 Taiwan 2, 9 tanks 82, 83 Temkin, B. 176, 178 Tet offensive 146, 147, 148, 149 Tetlock, P. 161, 180 Thatcher, M. 159, 176 Thompson, W. 6, 7, 10, 118, 176, 181, 239, 242, 255, 257, 258 threats, future 284–5 time series analysis 118, 165 Tonkin Gulf incident 160 total obligation authority 37 Tower, J. 48 tradeoffs 213–14 (n1); budgetary, conceptualization 200–5; deficit, defense and social spending (1954–86) 210; education 90; guns and butter 196; health 197–8; long term 197, 201; Reagan administration 188– 90, 193–4; recent 190–2; short-term 201; social spending 208, 210, 211; welfare/ defense 185–92, 316 transportation index 145, 147, 148 triad 67, 73, 74 Tufte, E.R. 6, 11, 17, 26, 31, 176, 181, 199, 216, 237 Tuomi, H. 195 unemployment: and contract awards 24, 27, 28; and elections 22, 118, 120–1, 157; nonmilitary spending 228; rate 122; real growth 230 United Kingdom 111, 162–3, 197

INDEX

334 United Nations 241, 261 US: defense burden 84–5, 111; GNP 240–1; military capabilities 69–74; military disputes 162, 164; post World War II 104–10, 240; and Soviet Union 66, 96 USSR see Soviet Union Urich, T. 139, 154 VAR (vector autoregression) 99–100, 246, 292–5 Vayrynen, R. 195, 239, 258 veterans’ benefits 135, 207 Vickers, D. 152 Vietnam 34, 35, 36, 42, 45, 54, 64, 109, 119, 135, 143, 145, 149, 150, 160, 164, 180, 316 Vietnam war 30, 43, 45, 46, 57, 104, 106, 110, 144, 145, 150, 153; economic interests 142; financial cost 135; inflation 143; service rivalry 41; stock prices 146–50 Vogt, W. 11 voters, and the economy 157 Wachtel, P. 139, 154 Wallace, M. 9, 31, 117, 130, 131, 256 war: actual expense/anticipated 143; defense spending 43, 119; democracies 163–4; incremental changes 135; inflation 143; public opinion 54; social impact 164; and stock market 143, 146–50 Wallerstein, I. 6, 11, 239, 258 Ward, H. 180 Ward, M. 1, 2, 3, 7, 8, 9, 10, 11, 65, 81, 82, 84, 102, 115–16, 118, 129, 131, 151, 166, 174, 176, 179, 181, 193, 194, 195, 199, 216, 219, 222, 237, 242, 258, 226, 268, 278, 280, 281, 314 weapons: conventional 82–3, 88; nuclear 41, 67–82; readiness 82; Soviet production 264; see also conventional military capabilities; nuclear capabilities

Warner, E. 66 Warsaw Pact 3, 15, 305, 306 Watanuki, J. 215 Watergate 273 Waud, R. 138, 154 Weinberger, C. 2, 18, 38, 193, 218 Weiss, A. 251, 256 Weissberg, H. 160, 181 welfare spending 185–92, 316; see also tradeoffs Wendt, A. 5, 7, 11 West 264, 267 Wildavsky, A. 2, 4, 9, 11, 34, 51, 187, 188, 191, 195, 266, 281, 284, 285, 286, 287, 288, 290, 291, 294, 301, 302, 303, 312 Wilde, J. 196, 215 Wilensky 129 Williams, J. T. 8, 84, 99, 100, 101, 285, 286, 294, 299, 300, 301, 302, 303, 304, 312, 313 Williamson, J. 139, 154 Wong, Y. 135, 180 Woodbury, N. 118, 119, 120, 121, 131, 199, 216 world-system approach 6, 7, 258 World War I 141, 164 World War II 111, 164, 180; and US hegemony 239–40 Wright, B. 68, 74, 102 Yawitz, J. 139, 154 year-end accelerations 19–20, 21, 29 Yom Kippur war 160, 167, 180 Yoo, B. 247, 254, 255 Zeckhauser, R. 111, 130 Zelikow, P. 56, 64 Zellner 240 Zinnes, D. 2, 9, 11, 176, 181, 282, 304 Zuk, G. 118, 119, 120, 121, 131, 176, 181, 199, 216 Zurich 117

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