Advances in Taxation, Volume 17

LIST OF CONTRIBUTORS Kenneth E. Anderson Department of Accounting and Information Management, University of Tennessee, ...

Author: Suzanne M. Luttman

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LIST OF CONTRIBUTORS Kenneth E. Anderson

Department of Accounting and Information Management, University of Tennessee, TN, USA

Anne L. Christensen

College of Business, Montana State University, MT, USA

Mary Ann Hofmann

Walker College of Business, Appalachian State University, NC, USA

Ira Horowitz

University of Florida, FL, USA

Cynthia M. Jackson

Accounting Group, College of Business Administration, Northeastern University, MA, USA

Rex Karsten

Department of Management, University of Northern Iowa, IA, USA

Claire K. Latham

Department of Accounting, College of Business, Washington State University, WA, USA

Tracy S. Manly

School of Accounting, University of Tulsa, OK, USA

James J. Maroney

Accounting Group, College of Business Administration, Northeastern University, MA, USA

William A. Raabe

Ohio State University, OH, USA

Timothy J. Rupert

Accounting Group, College of Business Administration, Northeastern University, MA, USA vii

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LIST OF CONTRIBUTORS

Dennis Schmidt

College of Business, Montana State University, MT, USA

Craig T. Schulman

Department of Economics, Texas A&M University, TX, USA

Deborah W. Thomas

Department of Accounting, Sam M. Walton College of Business, University of Arkansas, AR, USA

Gerald E. Whittenburg

School of Accountancy, College of Business Administration, San Diego State University, CA, USA

EDITORIAL BOARD Kenneth E. Anderson University of Tennessee

Beth B. Kern Indiana University-South Bend

Caroline K. Craig Illinois State University

Gary A. McGill University of Florida

Anthony P. Curatola Drexel University

Janet A. Meade University of Houston

Ted D. Englebrecht Louisiana Tech University

Michael L. Roberts University of Colorado-Denver

Philip J. Harmelink University of New Orleans

David Ryan Temple University

D. John Hasseldine University of Nottingham

Dan L. Schisler East Carolina University

Peggy A. Hite Indiana University-Bloomington

Toby Stock Ohio University

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AD HOC REVIEWERS Bruce Lubich University of Maryland – University College

Lawrence Brown Georgia State University Michael Calegary Santa Clara University

Steven Matsunaga University of Oregon

Deborah Garvey Santa Clara University

John Phillips University of Connecticut

Jeffrey Gramlich University of Southern Maine

Debra Sanders Washington State University

Robert Halperin Hong Kong Polytechnic University

Michael Schadewald University of WisconsinMilwaukee

Cherie Hennig Florida International University

Jerrold Stern Indiana University

Mary Ann Hofmann Andrews University

Robert Yetman University of California – Davis

Yongtae Kim Santa Clara University

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STATEMENT OF PURPOSE Advances in Taxation is a refereed academic tax journal published annually. Academic articles on any aspect of Federal, state, local, or international taxation will be considered. These include, but are not limited to, compliance, education, law, planning, and policy. Interdisciplinary research involving economics, finance, or other areas also is encouraged. Acceptable research methods include any analytical, behavioral, descriptive, legal, quantitative, survey, or theoretical approach appropriate to the project. Manuscripts should be readable, relevant, and rigorous. To be readable, manuscripts must be understandable and concise. To be relevant, manuscripts must be directly related to substantive issues inherent in the system of taxation. To be rigorous, manuscripts should scrupulously follow the tenants of sound research design and execution. Conclusions must follow logically from the evidence and arguments presented. Reasonable assumptions and logical development are essential for theoretical manuscripts. AIT welcomes comments from readers. Additional information regarding the journal is available at the Advances in Taxation link at http://cms.scu.edu/business/accounting/ait.cfm Editorial correspondence pertaining to manuscripts should be forwarded to: Professor Suzanne Luttman Santa Clara University Accounting Department 500 El Camino Real Santa Clara, CA 95053 Suzanne Luttman Series Editor

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AN EXAMINATION OF TAX SCHOLARS’ PUBLICATIONS Anne L. Christensen and Claire K. Latham ABSTRACT This study examines the research productivity of three samples of tax scholars with accounting Ph.Ds. We compare publication activity in the pre-tenure period for each sample and in the first 25, 15, and 10 years for scholars whose careers began in 1977/1978, 1987/1988, and 1993/1994, respectively. The percentage of publications in ‘‘academic’’ journals in the pre-tenure period has increased from 38 to 42 to 47 percent for the 77/78, 87/88, and 93/94 tax scholars, respectively. The average number of academic and professional publications combined were 3.51 for 77/78 scholars, 5.87 for 87/88 scholars, and 4.00 for 93/94 scholars.

INTRODUCTION Has the publication activity of tax accounting scholars changed over time? In a study of where the 25 most productive accounting faculties published from 1973 to 1977, Windal (1981, p. 656) states, ‘‘Tax specialists, of course, tend to publish in tax journals.’’ He then identifies tax journals as The Journal of Taxation, Taxes, and the Tax Adviser, a selection which indicates that he expects tax scholars to publish their research primarily in ‘‘professional’’ journals, i.e., journals read primarily by tax practitioners. Kozub, Sanders, and Raabe (1990) studied publication productivity by business Advances in Taxation, Volume 17, 3–35 Copyright r 2007 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1058-7497/doi:10.1016/S1058-7497(06)17001-5

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4

ANNE L. CHRISTENSEN AND CLAIRE K. LATHAM

school tax faculties from 1981 to 1988 in eight academic and 22 professional journals. They found that faculty members at eight of the 35 most prolific tax publication schools published primarily in ‘‘academic’’ journals, i.e., journals directed toward academic audiences. Yet, at the three most productive schools in their study, the tax scholars also published a significant number of articles in professional journals. The purpose of this study is to examine the overall publication productivity of tax scholars and to determine how much tax scholars publish in tax, accounting, and other professional and academic journals in different stages of their careers. Individuals listed in Prentice-Hall Accounting Faculty Directories (Hasselback, 1978–1997) with a teaching or research interest in tax are designated tax scholars.1 It is important to develop an understanding of tax scholars’ publication activity because it is closely linked to promotion and tenure decisions (Henderson, Ganesh, & Chandy, 1990) as well as salary (Gomez-Mejia & Balkin, 1992). This information also may be helpful in setting performance goals for and evaluating tax scholars at different stages of their careers. There is increasing emphasis on assessment in university settings, including assessing publication activity across scholars at different stages in their careers (Swanson, 2004). In keeping with this growing interest, our purpose is to capture a broad range of publication activity across different journal classifications from the careers of scholars who have emphasized tax as a specialty. Across universities, differences in focus and standards can signal that publications in some journals are more highly valued than those in other journals (Schultz, Meade, & Khurana, 1989; Cargile & Bublitz, 1986). As the mission of a particular school changes over time, so too may its emphasis on publications in different types of journals. Some universities may emphasize and reward publication in professional journals as building bridges to the professional tax community. Other universities may emphasize publication in academic journals as expanding the boundaries of knowledge and the reputation of the school. Still other schools may value publications in educational journals as a means of improving pedagogy. The degree to which work in other business disciplines is acknowledged also varies among universities (Swanson, 2004). While there appears to be no single standard for all universities for the publication activities of tax scholars, we can see how much and where these scholars have successfully published in different time periods in the past. This study contributes to the tax scholar research productivity literature by examining intradisciplinary and interdisciplinary publications in a wide range of journals in several different time periods. We provide measures of

An Examination of Tax Scholars’ Publications

5

research productivity in tax, accounting, and non-tax/non-accounting journals in early as well as later time periods in scholars’ careers. Publication activity in the highest-rated accounting journals is noted. Our productivity measures are further divided into separate measures of publications in journals with primarily professional or academic readership, thereby extending the discussion raised in prior literature. We select three samples of tax scholars who received an accounting Ph.D. and then took tenure track positions at U.S. universities. We then examine their publication records in the first seven years of their careers as well as during later time periods. We refer to scholars in the first seven years of their careers as new scholars. The ‘‘93/94’’ sample consists of 1993 and 1994 graduates, the ‘‘87/88’’ sample of 1987 and 1988 graduates, and the ‘‘77/78’’ sample of 1977 and 1978 graduates. We then search ABI Inform, CCH Federal Tax Articles, the EconLibrary Database, and the Social Science Citation Index to develop publication records for each member of our samples.2 We classify academic publications into three categories based on the journals in which the articles appeared (1) tax, (2) accounting, and (3) nontax/non-accounting journals. We adopt the same classification strategy for publications in professional journals. We also create a separate category for publications in education journals. Academic and professional journals are then differentiated on the basis of primary readership, which is determined on the basis of publications such as Cabell’s Directory of Publishing Opportunities in Accounting: 2001–2002. In terms of overall productivity, we find that the 93/94 new tax accounting scholars published an average of 4.0 articles in the first seven years of their careers compared to 5.87 articles for the 87/88 scholars and 3.51 for the 77/78 scholars. We observe that while publications in professional journals continue to be a significant part of tax scholars’ research portfolios, the percentage of publications in academic journals has increased from 38 to 42 to 47 percent, respectively for 77/78, 87/88, and 93/94 new tax scholars. In the latter part of their careers, the percentage of publications in academic journals for the 77/78 and 87/88 scholars declines slightly, but not significantly. In addition, we find that the aggregate number of articles published in The Accounting Review by tax scholars in the first seven years of their careers decreased from twelve to nine to four by the 77/78, 87/88, and 93/94 scholars, respectively. The remainder of this article is organized as follows. The next section describes the motivation and research questions. We then discuss the research design followed by the results. The paper concludes with a discussion of the findings and implications for future research.

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MOTIVATION AND RESEARCH QUESTIONS Overall Research Productivity Measures Kozub et al. (1990) provide evidence on the publication activity of business school tax faculty in 30 journals (eight academic and 22 professional) from 1981–1988. Their study is one of the few studies that specifically examines the productivity of tax faculty and it includes many more tax journals than any prior study. Christensen, Finger, and Latham (2002) show that research productivity measures are affected by the number and type of journals included. Their study documents considerably greater research productivity for new accounting scholars when publications in non-accounting journals are included in the productivity measures. This held true for scholars employed at both accounting doctoral and non-doctoral granting institutions. As our starting point, we determine the research productivity of new tax scholars using productivity measures that include publications from an extensive list of journals. The first research question is: Question 1. How productive are new tax scholars when the productivity measures include publications from an extensive list of tax, accounting, and non-accounting journals? We compute the average number of publications per new scholar in all types of journals as well as in academic and professional journals. These averages are computed separately for the 93/94, 87/88, and 77/78 scholars. We further divide the samples into individuals employed at accounting doctoral granting and non-doctoral granting schools because prior research shows higher research productivity levels for the doctoral granting schools (Christensen et al., 2002; Read, Rama, & Raghunandan, 1998; Englebrecht, Iyer, & Patterson, 1994; Campbell & Morgan, 1987; Milne & Vent, 1987).3 Differences in Productivity Measures for Publications in Professional and Academic Journals Windal (1981) suggested that tax faculty would direct their publication efforts toward a professional audience. However, Kozub et al. (1990) find evidence of significant tax faculty publication efforts directed at both professional and academic audiences. Bricker and Previts (1990) provide evidence that as the nature of the professoriate changed and accounting scholars were required to have doctorates, accounting scholars shifted their research efforts toward questions of interest to an academic audience rather than a professional audience.


7

They suggest that this shift may have isolated the academic community from the practice community. We examine whether new tax scholars, who started their careers in three different time periods, include publications in professional journals in their research portfolios. Hence, our second question is: Question 2. Has the quantity of new tax accounting scholars’ publications in professional journals changed over time? If we find that tax scholars who received their degrees at different points in time publish a substantial amount in professional journals as well as in academic journals, it suggests that tax scholars have not become isolated from the professional tax community. Publications in Highest Rated Journals New scholars’ publication records are evaluated in terms of both quantity and quality. A number of studies have measured perceptions of the quality of accounting, business, and tax journals over the years (Swanson, 2004; Brown & Huefner, 1994; Hall & Ross, 1991; Hull & Wright, 1990; Raabe, Kozub, & Sanders, 1987). Although schools and individuals do differ in perceptions of which journals are of highest quality, we can use the consistently top-rated journals from prior studies to observe the frequency with which tax scholars publish in specific journals and whether there have been changes in publication rates over time. Thus our third research question is: Question 3. Has the tendency for new tax scholars, as a group, to publish in the highest rated tax and accounting journals changed over time? We provide information on the number of articles published by new tax scholars in highly rated as well as common outlets. Timing within Careers: Academic and Professional Publications The importance of publishing in academic journals has increased over time (Ettredge & Wong-On-Wing, 1991; Hagerman & Hagerman, 1989; Campbell & Morgan, 1987). Such pressure may lead tax scholars to focus their early research efforts on empirical or theoretical work publishable in academic journals. However, there is also pressure to have a sufficient number of publications in particular time periods. Zivney, Berton, and Gavin (1995, p. 11) found that only 40 percent of accounting graduates publish in academic accounting journals and 23 percent publish in what they define as the top three accounting journals (The Accounting Review, Journal

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of Accounting Research, and Journal of Accounting and Economics). Hence, to have a sufficient number of publications, new scholars may also direct their efforts toward applied research that is published in professional journals. As the number of years since obtaining the doctoral degree increases, scholars may believe that it is increasingly difficult to undertake empirical or theoretical research. Such individuals may believe that they are more likely to be successful in undertaking applied research, publishable in professional journals. In contrast, scholars may hone their empirical or theoretical research skills over time and thus develop a competitive advantage for later career publishing in academic journals. The fourth research question addresses the timing of types of publications within scholars’ careers: Question 4. Do publications in professional journals versus academic journals typically occur earlier or later in the careers of tax accounting scholars? To examine this question that considers a much longer timeline, we include tax scholars’ publications in academic and professional journals from before the Ph.D. was granted through year 10 for the 93/94 scholars, year 15 for the 87/88 scholars, and year 25 for the 77/78 scholars (hereafter, ‘‘Expanded 93/94,’’ ‘‘Expanded 87/88,’’ and ‘‘Expanded 77/78’’ samples). Publications in Different Types of Journals To gain additional understanding of the research and publication activities of tax scholars, we further classify publications into those published in tax journals (e.g., The Journal of the American Taxation Association and The Tax Adviser), those published in accounting journals (e.g., The Accounting Review and Journal of Accountancy), and those published in business and society journals (e.g., Journal of Finance and Journal of European Business). We also examine publications in education journals by tax scholars (e.g., Issues in Accounting Education and Journal of Accounting Education). We then address the fifth research question: Question 5. Has the tendency for tax scholars to publish their research in tax, accounting, business and society, or educational journals changed over time? Publications in tax journals are likely to advance knowledge within the tax community, while publications in accounting journals are likely to


9

advance knowledge in the broader accounting community. Publications in business and/or society journals reach audiences outside the accounting discipline and may be viewed favorably or unfavorably depending upon the mission of the particular school. Publications in educational journals may be included in either research or teaching portfolios of scholars, again depending upon the mission of the school.

RESEARCH DESIGN Selection of Tax Scholars This paper provides evidence on changes in outlet choice by new tax scholars over time. To examine these changes, we compile samples of tax graduates in three different time periods and focus on their publication portfolios before graduation and in the six years following the Ph.D.4 These publications were likely to be considered in the scholars’ tenure decisions.5 We use the Accounting Faculty Directory (Hasselback, 1996) to identify all tax scholars who obtained their degrees from U.S. universities. To increase the sample size, we pool 1994 and 1993 tax graduates, making the assumption that there are no systematic differences between successive years. We compile two additional samples to compare with the 94/93 sample. One sample is made up of 1987 and 1988 tax graduates and the other consists of 1977 and 1978 tax graduates.6 Only tax scholars listed as ‘‘Assistant’’ or ‘‘Associate’’ were included in the samples to ensure they were tenure-track. We determine the scholars’ first employers and omit scholars with non-U.S. employers. This process results in a 93/94 sample of 51 tax scholars, an 87/88 sample of 46 tax scholars, and a 77/78 sample of 45 tax scholars. The employers of tax scholars in the three samples are further classified by whether they offer accounting doctoral programs. Of the 51 scholars in the 93/94 sample, 11 were employed at universities with accounting Ph.D. programs. The 87/88 sample contains 23 of 46 and the 77/78 sample includes 26 of 45 scholars employed by schools with accounting Ph.D. programs. Measures of Productivity Consistent with a number of other studies that examine the productivity of scholars who receive tenure (Christensen et al., 2002; Englebrecht et al., 1994; Hagerman & Hagerman, 1989; Campbell & Morgan, 1987;

10


Milne & Vent, 1987), we measure productivity by counting published articles. As noted previously, we measure new tax scholar productivity by including articles that were likely to be considered for tenure decisions. Therefore, we include all pre-Ph.D. publications (with no time limit), publications in the year of graduation, and publications within the following six years. We include only articles that exceed two pages in length and exclude book reviews, dissertation summaries, and commentaries. We do count discussant comments that are published in journals such as the Journal of Accounting Research Supplement and The Journal of the American Taxation Association Supplement.7 For research question 4, which examines publication activity over a longer time horizon, we extend the time frame to include publications through year 10 for the 93/94 scholars, 15 for the 87/88 scholars, and 25 for the 77/78 scholars. Publication Data After selecting the tax scholar samples, we searched ABI Inform, CCH Federal Tax Articles, the EconLibrary Database, and the Social Science Citation Index to develop comprehensive publication records for each member of our samples.8 We conducted an author name search for the scholars in each database and used cross-references to ensure that we also captured those publications in which our scholars were not the lead authors.9 We classified both academic and professional publications into three categories based on the journals in which the articles appeared tax, accounting, and non-tax/non-accounting journals. We consider journals with the word ‘‘tax’’ in the title as tax journals and journals with the word ‘‘accounting’’ or ‘‘auditing’’ as accounting journals.10 We also include publications in education journals as a separate category. Academic and professional journals are differentiated on the basis of primary readership according to Cabell’s Directory of Publishing Opportunities in Accounting (Cabell & English, 2001– 2002a), Cabell’s Directory of Publishing Opportunities in Economics, and Finance (Cabell & English, 2001–2002b), Cabell’s Directory of Publishing Opportunities in Management (Cabell & English, 2001–2002c), Cabell’s Directory of Publishing Opportunities in Marketing (Cabell & English, 2001–2002d), The Author’s Guide to Accounting and Financial Reporting Publications (Vargo & Vargo, 1998–1999), and the International Guide to Accounting Journals (Spiceland & Agrawal, 1988). Our sample scholars published in 212 different journals. Using the classification scheme noted above, three of the journals are classified as academic tax, 28 as academic


11

accounting, and 75 as academic non-tax/non-accounting. Within the professional journal classification, 29 are classified as tax, 23 as accounting journals, and 50 as non-tax/non-accounting journals. Four of the journals are classified as education journals.11 A list of the journals in which our scholars published along with the corresponding classification and the number of articles published in each journal is provided in the appendix.

RESULTS Overall Research Productivity Measures To address the first question, Table 1 presents research productivity measures for the 93/94, 87/88, and 77/78 samples. Counting a comprehensive list of academic, professional, and educational journal publications results in a smaller percentage of non-publishers than found in many prior studies of accounting research productivity (Christensen et al., 2002; Read et al., 1998; Englebrecht et al., 1994). Among the 93/94 tax scholars, only five or 9.8 percent had no publications. For 87/88 and 77/78 tax scholars, only four (8.7 percent) and eight (17.8 percent) scholars had no publications.12 Twenty scholars (29 for 87/88, 11 for 77/78) published articles in both academic and professional journals. In contrast, 12 scholars (6 for 87/88, 12 for 77/78) published exclusively in academic journals and 14 scholars (7 for 87/88, 14 for 77/78) published exclusively in professional journals. The average number of publications per 93/94 (87/88; 77/78) scholar was 4.00 (5.87, 3.51). This average includes those scholars who had no publications.13 When tax scholars employed at schools with accounting Ph.D. programs are compared to scholars employed at schools without accounting Ph.D. programs, we find fewer non-publishers and a higher average number of publications at the Ph.D. granting institutions for all three samples. As indicated in Table 1, at Ph.D. granting institutions, only one individual in each of the three samples had no publications, while four, three, and seven individuals in the 93/94, 87/88, and 77/78 samples at non-doctoral granting institutions had no publications. The 93/94 scholars employed at doctoral granting schools had an average of 4.64 publications compared to 3.82 publications at non-doctoral granting institutions (t ¼ 0.79, p ¼ 0.217).14 The average number of publications for 87/88 (77/78) scholars employed at doctoral granting institutions was 7.70 (4.88) compared to an average of 4.04 (1.63) for scholars employed at non-doctoral granting institutions (87/88 t ¼ 2.78, po0.01; 77/78 t ¼ 3.35, po0.01).15

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Table 1.

Research Productivity Statistics for 93/94, 87/88, and 77/78 Ph.D. Tax Graduates.

Number of

Tax Scholars All

Employed at schools with Ph.D. programs

Employed at schools without Ph.D. programs

Total tax scholars 51 (n) Non-publishers 5 Total tax scholars 46 with publications Total tax scholars 20 with publications in both academic and professional journals 12 Tax scholars with publications in academic journals only 14 Tax scholars with publications in professional journals only Total number of 204 publications

46

45

51

46

45

11

23

26

11

23

26

40

23

19

40

23

19

4 42

8 37

16 35

7 39

5 40

1 10

1 22

1 25

2 9

1 22

1 25

4 36

3 20

7 12

14 26

6 17

4 15

29

11

7

21

23

6

15

10

2

13

14

14

14

1

5

8

9

6

12

13

9

7

4

4

7

6

7

6

8

2

5

7

2

1

7

14

15

9

10

0

3

8

1

2

5

14

4

6

14

7

5

270

158

96

252

506

51

177

127

29

159

325

153

93

31

67

93

181


93/94 87/88 77/78 93/94 87/88 77/78 93/94 87/88 77/78 93/94 87/88 77/78 93/94 87/88 77/78 93/94 87/88 77/78 (1) (1) (1) (2) (2) (2) (1) (1) (1) (2) (2) (2) (1) (1) (1) (2) (2) (2)

95

113

60

49

96

156

42

86

50

23

72

133

53

27

10

26

24

23

109

157

98

47

156

350

9

91

77

6

87

192

100

66

21

41

69

158

Distribution of total publications per scholar Mean 4.00 5.87 3.51 1.88 5.48 11.22 Median 3.00 5.00 2.00 2.00 4.50 7.00 Standard 3.01 4.77 3.57 1.90 5.94 14.68 deviation Distribution of total academic publications per scholar Mean 1.86 2.46 1.33 0.96 2.09 3.47 Median 1.00 1.00 1.00 0 1.00 1.00 Standard 2.28 3.16 2.10 1.54 2.30 5.38 deviation Distribution of total professional publications per scholar Mean 2.14 3.41 2.18 0.92 3.39 7.76 Median 2.00 3.00 1.00 0 1.00 3.00 Standard 2.55 3.88 3.26 1.57 5.78 14.58 deviation

4.64 4.00 3.56

7.70 6.00 5.35

4.88 3.50 3.79

2.64 3.00 1.80

6.91 12.46 5.00 8.50 6.50 16.34

3.82 3.00 2.86

4.04 3.00 3.24

1.63 1.00 2.19

1.68 1.00 1.90

4.04 2.00 5.05

9.53 6.00 12.29

3.82 3.00 3.19

3.74 3.00 3.90

1.92 1.00 2.48

2.09 2.00 1.92

3.13 3.00 2.38

5.12 2.00 6.50

1.32 1.00 1.64

1.17 1.00 1.34

0.53 0 1.02

0.65 0 1.27

1.04 0 1.69

1.21 1.00 1.69

0.82 1.00 0.87

3.96 3.00 4.67

2.96 1.00 3.69

0.55 0 1.04

3.78 7.35 1.00 3.00 6.68 16.21

2.50 2.00 2.75

2.87 2.00 2.89

1.11 0.00 2.21

1.03 1.00 1.69

3.00 1.00 4.82

8.32 5.00 12.32


Total number of publications in academic journals Total number of publications in professional journals

Notes: (1) represents first seven years of publication records; for 1977 graduates, it is years 1977–1983, for 1978, it is years 1978–1984, for 1987, it is years 1987–1993, for 1988, it is years 1988–1994, for 1993, it is for years 1993–1999, and for 1994, it is for years 1994–2000; (2) represents publication records up through year 25 for the 77/78 scholars (for 1977 graduates, it is years 1984-2002, for 1978 graduates it is years 1985– 2003), records up through year 15 for 87/88 scholars (for 1987 graduates, it is years 1994–2002, for 1988 graduates, it is years 1995–2003); records up through year 10 for 93/94 scholars (for 1993 graduates it is years 2000–2003, and for 1994 graduates, it is years 2001–2004).

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Differences in Publication Outlet Over Time Question 2 explores whether the tendency of new tax scholars to publish in professional journals has changed over time. As indicated in Table 1, the 93/94 tax scholars published 53.4 percent (109/204) of their articles in professional journals compared to 58.1 percent (157/270) for 87/88 tax scholars and 62 percent (98/158) for 77/78 tax scholars. The average number of published professional articles for 93/94 tax scholars was 2.14, which is less than the average number for 87/88 tax scholars, 3.41 articles, but not much less than the average number for 77/78 tax scholars, 2.18 articles. An ANOVA test indicates the difference among the average number of professional articles for these three groups of scholars is not significant (F ¼ 2.325, p ¼ 0.102).16 These results indicate that publications in professional journals may have declined somewhat but continue to be an important component of the research portfolios of new tax scholars. The average number of academic articles for the 93/94, 87/88, and 77/78 tax scholars is 1.86, 2.46, and 1.33, respectively. The differences in these averages are not statistically significant (ANOVA, F ¼ 2.21, p ¼ 0.113). However, when both professional and academic articles are added together, the overall average number of articles for the 87/88 tax scholars (5.87) is significantly greater than the overall average for the 93/94 tax scholars (4.00) and the 77/78 tax scholars (3.51) (ANOVA, F ¼ 4.865, po0.01). Publications in Highest Rated Journals Question 3 examines the frequency with which new tax scholars publish in highly rated journals.17 Table 2 presents the number of articles published in selected journals for the 93/94, 87/88, and 77/78 tax scholars. We find the number of articles published by tax scholars in The Accounting Review steadily declined from 12 articles (0.27 per scholar) by the 77/78 scholars to nine (0.20 per scholar) by the 87/88 scholars and four (0.08 per scholar) by the 93/94 scholars. During the same time period, the number of articles published in The Journal of the American Taxation Association steadily rose from four (0.09 per scholar) by the 77/78 scholars to 18 (0.39 per scholar) by the 87/88 scholars to 25 (0.49 per scholar) by the 93/94 scholars. The tax scholars in our three groups almost never publish in Accounting, Organizations, and Society, but occasionally publish in the Journal of Accounting and Economics, the Journal of Accounting Research, and the National Tax Journal. Differences in the years that various journals actually began publication make it difficult to draw conclusions regarding the tendency for tax

Publications of 93/94, 87/78, and 77/88 Tax Ph.D. Graduates in Selected Journal.

Journal (year started)

Articles Published Both before and within Seven Years of Receipt of Ph.D.

Articles Published after Seven Years

Publications by scholars in the 87/88 sample (N ¼ 46 scholars)





J. of Am. Tax Assoc. (1979) Adv. In Taxation (1987) National Tax J. (1948)

25 (13)a 4 (4) 2 (2)

18 (13) 10 (7) 3 (3)

4 (4) 0 2 (2)

16 (10) 7 (6) 1 (1)

18 (11) 2 (1) 5 (5)

7 (6) 2 (2) 4 (3)

Acct. Horizons (1987) Acct. Org. & Soc. (1976) Accounting Review (1926) Cont. Acct. Res. (1984) J. of Acct. & Econ. (1979) J. Acct. & Pub. Pol. (1982) J. of Acct. Research (1963)

3 (3) 0 4 (3) 2 (2) 5 (3) 5 (5) 5 (4)

5 (4) 0 9 (6) 3 (3) 2 (1) 2 (2) 4 (4)

0 1 (1) 12 (10) 0 3 (2) 3 (3) 8 (4)

3 (3) 0 4 (3) 3 (3) 4 (2) 0 4 (3)

9 (5) 1 (1) 17 (7) 7 (3) 3 (2) 5 (4) 15 (6)

0 0 6 (5) 0 2 (2) 2 (1) 4 (4)

J. of Taxation (1915) Tax Adviser (1910) Tax. for Acct. /PTSb (1938) Taxes (1923)

3 (2) 17 (7) 12 (9) 8 (5)

10 (7) 16 (8) 17 (9) 23 (11)

4 (3) 18 (10) 25 (10) 15 (7)

17 (9) 44 (14) 28 (11) 36 (10)

0 9 (2) 0 7 (4)

7 26 17 14

(6) (15) (11) (11)

15



Table 2.

16

Table 2. (Continued ) Journal (year started)


Articles Published after Seven Years






15 (11) 5 (3) 5 (4)

13 (9) 11 (8) 5 (5)

7 (5) 2 (2) 0

14 (8) 6 (4) 4 (4)

35 (9) 6 (5) 29 (6)

8 (4) 6 (5) 3 (3)

Acct. Ed. J. (1988) J. of Acct. Ed. (1983) Iss. in Acct. Ed. (1983)

2 (2) 2 (2) 0

5 (4) 3 (3) 5 (4)

0 1 (1) 0

4 (4) 2 (2) 1 (1)

0 6 (6) 1 (1)

0 3 (3) 1 (1)

Total

124

162

109

135

284

64

CPA Journal (1931) J. of Accountancy (1906) Nat. Pub. Acct. (1956)

a

13 scholars published 25 articles in JATA in the time period that stretches from before they earned their Ph.D. through 6 years following graduation. b In 1998, Warren, Gorham, and LaMont combined Taxation for Accountants and Taxation for Lawyers into Practical Tax Strategies.




17

scholars from different time periods to publish in highly rated journals. We also note that only few articles by tax scholars are published in accounting education journals. Timing within Careers: Academic and Professional Publications Question 4 explores whether publications in professional journals or academic journals occur earlier or later in tax scholars’ careers. Table 3 shows when academic and professional articles occur during tax scholars’ careers. For example, if a 93/94 tax scholar published two articles in academic journals in year five, both articles would be included in the 17 articles for year five in Panel A of Table 3. The number of publications of each type relative to year of graduation for the 93/94, 87/88, and 77/78 tax scholars is presented in Panels A, B, and C, respectively. When we compare the number of publications in academic journals to the number of publications in professional journals each year, we do note some differences. The 93/94 scholars published the largest number of professional articles in the pre-Ph.D. time period and the largest number of academic articles in year six. This result suggests that these scholars experienced success during their doctoral programs in writing articles targeted toward professional journal audiences. The large number of academic publications in year six is consistent with scholars publishing as many articles as possible before tenure. For the 93/94 tax scholars, nearly 50 percent of the articles in professional journals were published by year four and over 50 percent of the articles in academic journals were published by year five. We then compare the proportion of publications in professional journals to academic journals in the pre-tenure time period (pre-Ph.D. through six years after Ph.D.) with the post-tenure period (year seven through year 10) and find no significant differences (X2 ¼ 0.523, p ¼ 0.536).18 Table 3 Panel B provides an expanded time horizon for publications by 87/88 tax scholars. We note that the greatest number of professional publications occurs in year three and the greatest number of academic publications occurs in year five. Over 50 percent of both academic and professional articles are published by year six. We compare the proportion of publications in professional journals for both the primary time period (pre-Ph.D. through six years after the Ph.D.) to the secondary time period (years seven to 15 after the Ph.D.). There was no statistically significant difference (X2 ¼ 0.476, p ¼ 0.490) between the early period (58 percent in professional journals) and the later period (62 percent in professional journals).

18

Table 3. Timing of 93/94, 87/88, and 77/78 Tax Ph.D. Graduates’ Publications Relative to Year of Graduation. Panel A: 93/94 sample (N ¼ 51 scholars) Year Relative to Graduation

All Publications #

Total

% of 300 Cum. %

32 10 11 26 24 30 35 36 28 23 20 25

10.7 3.0 3.7 8.7 8.0 10.0 11.7 12.0 9.4 7.7 6.7 8.4

300

100%

10.7 13.7 17.4 26.1 34.1 44.1 55.8 67.8 77.2 84.9 91.6 100.0

Publications in Professional Journals

#

% of 144

Cum. %

#

% of 156

Cum.%

10 3 6 12 9 16 17 22 16 15 11 7

6.9 2.1 4.2 8.3 6.3 11.1 11.8 15.3 11.1 10.4 7.6 4.9

6.9 9.0 13.2 21.5 27.8 38.9 50.7 66.0 77.1 87.5 95.1 100.0

22 7 5 14 15 14 18 14 12 8 9 18

14.1 4.5 3.2 9.0 9.6 9.0 11.5 9.0 7.7 5.1 5.8 11.5

14.1 18.6 21.8 30.8 40.4 49.4 60.9 69.9 77.6 82.7 88.5 100.0

144

100%

156

100%

Panel B: 87/78 sample (N ¼ 46 scholars) Year Relative to Graduation

All Publications #

Pre-Ph.D. 0 1

19 11 17

Publications in Academic Journals

% of 522 Cum. % 3.6 2.1 3.3

3.6 5.7 9.0

# 5 2 6

% of 209 2.4 1.0 2.9

Cum. % 2.4 3.3 6.2

Publications in Professional Journals #

% of 313

Cum.%

14 9 11

4.5 2.9 3.5

4.5 7.3 10.8


Pre-Ph.D. 0 1 2 3 4 5 6 7 8 9 10


Total

46 53 39 48 37 39 36 32 26 25 21 23 24 26

8.8 10.2 7.5 9.2 7.1 7.5 6.9 6.1 5.0 4.8 4.0 4.4 4.5 5.0

522

100%

17.8 28.0 35.5 44.7 51.8 59.3 66.2 72.3 77.3 82.1 86.1 90.5 95.0 100.0

20 20 21 22 17 14 14 13 7 12 7 9 8 12

9.6 9.6 10.0 10.5 8.1 6.7 6.7 6.2 3.3 5.7 3.3 4.3 3.8 5.7

209

100%

15.8 25.4 35.4 45.9 54.1 60.8 67.5 73.7 77.0 82.8 86.1 90.4 94.3 100.0

26 33 18 26 20 25 22 19 19 13 14 14 16 14

8.3 10.5 5.8 8.3 6.4 8.0 7.0 6.1 6.1 4.2 4.5 4.5 5.0 4.5

313

100%

19.1 29.6 35.4 43.7 50.1 58.1 65.1 71.2 77.3 81.5 86.0 90.5 95.5 100.0

Panel C: 77/78 sample (N ¼ 45 scholars) Year Relative to Graduation

All Publications % of 664 Cum. % 10 7 23 22 28 19 24 25 30 42

1.5 1.1 3.5 3.3 4.2 2.9 3.6 3.8 4.5 6.3

1.5 2.6 6.1 9.4 13.6 16.5 20.1 23.9 28.4 34.7

#

% of 216

3 1 5 6 13 8 12 12 10 17

1.4 0.5 2.3 2.8 6.0 3.7 5.6 5.6 4.6 7.9


Cum. %

#

% of 448

Cum.%

1.4 1.9 4.2 7.0 13.0 16.7 22.3 27.9 32.5 40.3

7 6 18 16 15 11 12 13 20 25

1.6 1.3 4.0 3.6 3.3 2.5 2.7 2.9 4.5 5.6

1.6 2.9 6.9 10.5 13.8 16.3 19.0 21.9 26.3 31.9

19

Pre-Ph.D. 0 1 2 3 4 5 6 7 8



2 3 4 5 6 7 8 9 10 11 12 13 14 15

20

Table 3. (Continued ) Panel C: 77/78 sample (N ¼ 45 scholars) Year Relative to Graduation

All Publications % of 664 Cum. %

Total

26 27 28 27 33 31 22 30 38 18 17 28 30 28 27 10 14

3.9 4.1 4.2 4.1 5.0 4.7 3.3 4.5 5.7 2.7 2.5 4.2 4.5 4.2 4.1 1.5 2.1

664

100%

38.6 42.7 46.9 51.0 56.0 60.7 64.0 68.5 74.2 76.9 79.4 83.6 88.1 92.3 96.4 97.9 100.0

#

% of 216

6 9 7 11 11 12 8 9 14 3 6 7 4 6 6 7 3

2.8 4.2 3.2 5.1 5.1 5.6 3.7 4.2 6.3 1.4 2.8 3.2 1.9 2.8 2.8 3.2 1.4

216

100%


Cum. %

#

% of 448

Cum.%

43.1 47.3 50.5 55.6 60.7 66.3 70.0 74.2 80.5 81.9 84.7 87.9 89.8 92.6 95.4 98.6 100.0

20 18 21 16 22 19 14 21 24 15 11 21 26 22 21 3 11

4.5 4.0 4.7 3.6 4.9 4.2 3.1 4.7 5.4 3.3 2.5 4.7 5.8 4.9 4.7 0.6 2.5

36.4 40.4 45.1 48.7 53.6 57.8 60.9 65.6 71.0 74.3 76.8 81.5 87.3 92.2 96.9 97.5 100.0

448

100%


9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25



21

The longest publication time horizon is presented in Table 3 Panel C for the 77/78 tax scholars. For these scholars, we find that over 50 percent of their academic publications occur by year 11 and over 50 percent of their professional publications occur by year 13. We test for differences in the proportion of publications in professional journals for both the pre-tenure and post-tenure periods. In the pre-tenure period, 62 percent of publications were in professional journals; this percentage increased to 69.1 percent in the post-tenure period. But again, there are no statistically significant differences among these percentages (X2 ¼ 2.641, p ¼ 0.104). Publications in Different Types of Journals The fifth research question considers whether tax accounting scholars publish their research in tax, accounting, business and society, or educational journals. Table 4 presents the number and percentage of academic and professional publications in each category for 93/94, 87/88, and 77/78 tax scholars in the first seven years of their careers. This same information is provided for the 93/94 scholars for years seven through 10 after the Ph.D., for 87/88 scholars for years seven through 15 after the Ph.D., and also for years seven through 25 for the 77/78 tax scholars. The 93/94 tax scholars in the first seven years of their careers published 32.6 percent of their academic articles in tax journals, 43.2 percent in accounting journals, 20.0 percent in non-tax/non-accounting journals, and 4.2 percent in educational journals. When professional journals are considered, these scholars published 45.9 percent in tax journals, 33.0 percent in accounting journals, and 21.1 percent in non-tax/non-accounting journals. Excluding the publications in educational journals, the proportion of articles in tax, accounting, and non-tax/non-accounting journals is neither statistically different (X2 ¼ 3.57, p ¼ 0.17) for academic and professional publications in the first seven years of their careers nor statistically different in years seven through 10 (X2 ¼ 0.455, p ¼ 0.80). In the first seven years of their careers, the 87/88 tax scholars published 27.4 percent of their academic articles in tax journals, 36.3 percent in accounting journals, 23.0 percent in non-tax/non-accounting journals, and 13.3 percent in education journals. In contrast, 63.1 percent of their professional articles appeared in tax journals, 28.0 percent in accounting journals, and 8.9 percent in non-tax/non-accounting journals. Again excluding education articles, we find the proportion of articles in each of the remaining three categories does differ significantly for academic and professional publications (X2 ¼ 27.073, po0.01). In years seven through 15, and again

22

Table 4. Journal Classification

Professional tax Professional accounting Professional nontax/nonaccounting Total professional Total articles


Articles Published after Seven Years Through year 10

Through year 15

Through year 25

Publications by the 93/94 sample (N ¼ 51 scholars)






32.6% 43.2%

27.4% 36.3%

11.7% 51.7%

26.5% 53.1%

26.0% 39.6%

15.4% 53.2%

20.0%

23.0%

30.0%

10.2%

25.0%

26.3%

4.2% 100% (95 articles) 45.9% 33.0%

13.3% 100% (113 articles) 63.1% 28.0%

21.1%

8.9%

100% (109 articles)

100% (157 articles)

204

270

6.7% 10.2% 9.4% 100% (60 articles) 100% (49 articles) 100% (96 articles) 75.5% 17.4%

36.2% 53.2%

61.5% 27.6%

5.1% 100% (156 articles) 46.9% 37.7%

7.1%

10.6%

10.9%

15.4%

100% (156 articles)

100% (350 articles)

252

506

100% (98 articles) 100% (47 articles) 158

96


Academic tax Academic accounting Academic nontax/nonaccounting Education Total academic

Publications of 93/94, 87/88, and 77/78 Tax Ph.D. Graduates by Journal Classification.


23

excluding education articles, the proportions for tax, accounting, and nontax/non-accounting publications in professional journals continue to be significantly different (X2 ¼ 25.64, po0.01) from those in academic journals. During the first seven years of their careers, the tax scholars who received their Ph.Ds in 1977 or 1978 published 11.7 percent of their academic articles in tax journals, 51.7 percent in accounting journals, 30.0 percent in non-tax/ non-accounting journals, and 6.7 percent in education journals. These percentages are very different than those for professional articles of which 75.5 percent were published in tax journals, 17.4 percent in accounting journals, and 7.1 percent in non-tax/non-accounting journals (X2 ¼ 57.139, po0.01). The percentages of tax, accounting, and non-tax/non-accounting articles in academic and professional publications continues to differ significantly in the post-tenure time period from year seven to 25 (X2 ¼ 42.21, po0.01). In summary, the results for the 93/94 scholars are very different than those for both the 87/88 and 77/78 scholars. In every time period, the 87/88 and 77/78 tax scholars had a much greater percentage of their professional articles published in tax-oriented journals. Their academic articles were more often targeted toward a broader accounting audience. There are fewer academic tax journals than accounting journals. In addition, several of the tax journals did not come into existence until a later time period, which may account for the difference in academic publication results between the 93/94 scholars and both the 87/88 and 77/78 scholars. We also find the proportions of academic tax, accounting, and non-tax/ non-accounting articles differ significantly between the 77/78 and 87/88 scholars and the 77/78 and 93/94 scholars, but not significantly between the 87/88 and 93/94 scholars in the first seven years of their careers.19 As noted previously, the proportion of academic tax publications in the total academic portfolio increases from 11.7 percent (77/78 sample) to 32.6 percent (93/94). It also is interesting to note the portion of tax scholars’ publication activity in academic journals that are neither tax nor accounting journals. Of the total academic publications, 30.0, 23.0, and 20.0 percent of the 77/78, 87/88, and 93/94 scholars’ publications, respectively, are in non-tax/ non-accounting journals such as the Journal of Finance and the Journal of Economic Psychology.

DISCUSSION This study documents some changes in the publication activity of tax accounting scholars, particularly when we contrast our latest sample, the 93/94

24


scholars, with the two earlier groups. Looking first, however, at overall productivity measures, we note that all three samples of tax scholars possess a significantly smaller percentage of non-publishers and a higher average number of publications per scholar when the productivity measures include all types of publication outlets (i.e., tax, accounting, non-tax/non-accounting in both academic and professional journals). Similar to the findings in prior research (Christensen et al., 2002), publication activity is greater in schools with accounting Ph.D. programs. A substantial number of tax scholars publish in both academic and professional journals, indicating that the isolation of the academic tax community from the practice tax community may not be as pronounced as has been suggested (Bricker & Previts, 1990). Although publications in academic journals as a whole are increasing, a substantial number of tax articles authored by academicians continue to be published in professional journals. Hence, collectively, tax scholars’ research portfolios reflect a balance between publications accessible to academic and professional audiences. Additionally, a comparison of the timing of these academic and professional journal publications across the expanded time periods of the 87/88 and 77/78 samples shows no statistically significant differences. The balance of professional and academic articles is maintained over the extended careers of tax scholars. The research focus, rigor, and training in Ph.D. programs may account for the increase in the overall number of publications in academic journals over time. The creation of additional journals may serve to offset the low acceptance rates in some journals. Further, the reward structure within the academic community and reduced teaching loads are likely to contribute to continuous publication efforts over tax scholars’ careers. Finally, the mission of a particular school to expand the boundaries of knowledge, build bridges to the professional community, or improve pedagogy is likely to influence the research and publication activities of tax scholars. We also see a change in the latest scholar group with regards to publications in professional journals. Of the three groups, the 93/94 scholars published the largest number of professional articles in the pre-Ph.D. period. The increase in professional journal publications in this early time period may reflect an increased pressure to publish before exiting the doctoral program but also may support an early understanding of the applicability of one’s research to the broader professional community. The results for the 93/94 scholars also differ from the 87/88 and 77/78 scholars in terms of where their professional articles are published. In every time period, the 87/88 and 77/78 tax scholars have a greater percentage of


25

their professional articles in tax journals and a smaller percentage of academic articles published in tax journals. This percentage is closer to being equal for the 93/94 sample. Further, examining professional journal activity, we see a shift in outlet choice by the 93/94 scholars from professional tax to professional accounting and non-tax/non-accounting. In contrast, looking at academic journal activity, we see a shift in publications from academic accounting to academic tax. As noted previously, differences in the years various journals began publication challenge our ability to compare publication activity. For tax scholars in the 93/94 and 87/88 samples, we do find an increase in the number of articles published in The Journal of the American Taxation Association and Advances in Taxation, a decrease in the number published in The Accounting Review and only occasional publications in Accounting, Organizations and Society, the Journal of Accounting and Economics, and the Journal of Accounting Research. These findings are consistent with the intertemporal evidence of Swanson (2004), who shows the proportion of accounting faculty publishing in four major journals declining over the time period 1980–1999 (The Journal of Accounting & Economics, Journal of Accounting Research, The Accounting Review, and Contemporary Accounting Research), as well as additional evidence of an increase in competition measured by an increase in the average number of co-authors. It underscores the importance of The Journal of the American Taxation Association and Advances in Taxation as outlets for academic tax publications and provides support for the suggestion of Swanson (2004, p. 249) ‘‘to allow the most highly rated journal in an accounting faculty member’s primary area of interest (that is, finance, managerial, auditing, systems, or tax) to be treated as a major journal.’’ Our results should be considered in light of several limitations. First, the tax scholars in the 77/78 and 87/88 samples must have remained in academia at least through 1996. Second, fewer 93/94 tax scholars were first employed at accounting Ph.D. granting institutions than the 87/88 and 77/78 tax scholars. The publication activity of scholars who completed their Ph.Ds in other years may differ from those in the years we selected. Third, as in many prior productivity studies, we count dissimilar publications without adjusting for quality and we give full credit to all authors. Giving equal weight to sole-authored and co-authored publications may increase the number of publications examined in totality. Englebrecht et al. (1994, p. 67) suggest the ‘‘lack of a logical rule for employing differential weights to co-authored and sole-authored publications preclude(s) any such classification’’ in studies of this type. Finally, our findings are limited by any inaccuracies that may be present in the databases used.

26


This study provides a comprehensive examination of where tax scholars have directed their research efforts. It documents a long-standing and continuing stream of publications directed toward the professional tax community, while observing an increase in academic publications, many of which appear in academic tax journals. There is increased interest in assessment in university settings, including reporting and evaluating publication activity of researchers at different stages of employment and when adjusting salaries. Though we do examine the period of time that is typically viewed as the tenure clock, we include additional time period comparisons. Depending on the research expectations of a university, the results of this study could be constructive in both establishing goals for and in evaluating performance of tax scholars annually and at other traditional milestones in their academic careers.

NOTES 1. The 1996 Prentice-Hall Accounting Faculty Directory was selected to allow for the lag time that may have occurred in 1994 graduates being listed in the directory. Some of the selected individuals had one or more other teaching or research interests. 2. We also searched the Lexis/Nexis Index of Law Review Articles, but did not find any additional publications by the individuals in our samples. We did find one law review article by a member of one sample listed in CCH’s Federal Tax Articles. 3. We collected information on scholars who moved from doctoral granting schools to non-doctoral granting schools and vice versa during the pre-tenure period (Hasselback, 1978–1997). We noted no significant differences in the overall mean and median number of publications by scholars at doctoral and non-doctoral granting schools when adjustments are made for school changes. Hence, we classify scholars strictly on the basis of their first school of employment after the doctoral degree. 4. Tax scholars with a J.D. or L.L.M. were only included in the study if they also had a Ph.D. This decision was made because the type of research training undertaken in Ph.D. programs differs from that in J.D. and L.L.M. programs. 5. Some universities consider only publications of scholars while in residence for tenure and promotion decisions. We provide information so that the mean number of publications can be calculated excluding those that occurred prior to completing the Ph.D. 6. We chose 1988 graduates in order to provide a seven-year time period that includes 1988 through 1994. We then increased the sample size by pooling the 1988 graduates with the 1987 graduates. The earliest sample (1977 and 1978) allows us to compare findings from a decade earlier. 7. In cases where the same article may have been reprinted in another journal, with a different title, authors were given credit for two publications. In cases where the title did not change, as in articles first published in Taxation for Accountants and then reprinted in Taxation for Lawyers, the authors were given credit for a single publication.


27

8. The reader is referred to Christensen et al. (2002) for a comprehensive discussion of ABI Inform and the Social Science Citation Index. The EconLibrary (formerly the Economic Literature Database) updates the Accounting Literature Index and several other indexes to include 475 journals of economics, finance, accounting, insurance, and real estate. The CCH Federal Tax Articles also includes a number of journals specializing in tax that are not incorporated in the other databases searched. 9. We recognize that the databases we searched are unlikely to contain 100 percent of the publications of our scholars. We obtained vitae from a subset of our scholars and compared the publication records we developed from the various databases to the publication records on specific vitae. We did discover some publications on the vitae that were not included in our data set. These journals tended to be of a more specialized nature, such as The Marquette Sports Law Journal and The Behavior Therapist. There were articles also in the study dataset that were not reflected on the vitae. Follow-up phone calls to these scholars indicated that the vitae contained only selected publications. Because not everyone responded to our request for vitae, we included only publications that were included in the databases. This approach creates consistency in the treatment of all scholars in our samples. 10. Management Accounting has been renamed Strategic Finance, which we also classify as an accounting journal. 11. Books, monographs, and other non-journal publications are omitted from this study although they are considered for promotion and tenure purposes at most schools. 12. Christensen et al. (2002) use 1987/88 and 1977/78 samples comprised of scholars from all the accounting disciplines. They note that 34% of the 1987/1988 sample and 51% of the 1977/1978 sample did not publish. Using the Accounting Literature Index, Read et al. (1998) examine publication productivity of accounting faculty promoted during the period 1987–1994 and find 40% (0%) of faculty at nondoctoral granting institutions (doctoral granting institutions) have no publications. Examining accounting faculty who were promoted in 1987, 1988, and 1989, Englebrecht et al. (1994) determine that approximately 2–38 percent of the individuals promoted are non-publishers with the low end of the range being for individuals at accredited doctoral-granting institutions and the high end being for faculty at nonaccredited, non-doctoral granting institutions. 13. Excluding non-publishers, the average number of publications is 4.44 for the 93/94 scholars, 6.43 for the 87/88 scholars, and 4.27 for the 77/78 scholars. 14. This is a one-tailed test as we expected scholars employed at doctoral granting institutions to have a larger number of publications than those employed at nondoctoral granting institutions (Christensen et al., 2002; Read et al., 1998). 15. The average number of publications for each group over different time periods may be calculated using Table 3. 16. These are two-tailed tests as we did not have any a priori expectations that one group would publish more in professional or academic journals than another group. 17. We rely on highly rated journals listings from prior studies. Read et al. (1998) base their listing of the top nine journals on a study by Brown and Huefner (1994), who asked senior faculty to rank 44 journals. We include their journals and add The National Tax Journal, which was included on the senior faculty list but not in their study, as it was not part of the data source they used (Accounting Literature Index).

28


For journals not included in Table 2, the reader is referred to the appendix, which provides frequency counts for all the journals in which the sample scholars are published. 18. These are two-tailed tests as we did not have any a priori expectations that the proportion of publication in professional journals would change from one time period to another. 19. The test statistic for the differences in proportions for 77/78 and 87/88 is X2 ¼ 8.975, p ¼ 0.03; the 77/78 and 93/94 is X2 ¼ 9.136, p ¼ 0.028; and for 87/88 and 93/94 is X2 ¼ 5.944, p ¼ 0.114.

ACKNOWLEDGMENTS The authors gratefully acknowledge the financial support for this research that was provided by Montana State University and Washington State University. In addition, we would like to thank Rosanne Mohr, Timothy Rupert, Debra Sanders, the anonymous reviewers and the Editor, Suzanne Luttman for helpful comments and suggestions on the manuscript.

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Ettredge, M., & Wong-On-Wing, B. (1991). Publication opportunities in accounting research journals: 1970–1988. Issues in Accounting Education, 6(Fall), 239–247. Gomez-Mejia, L. R., & Balkin, D. (1992). Determinants of faculty pay: An agency theory perspective. Academy of Management Journal, 35(5), 921–955. Hagerman, R. L., & Hagerman, C. M. (1989). Research promotion standards at selected accounting programs. Issues in Accounting Education, 4(Fall), 265–279. Hall, T. W., & Ross, W. R. (1991). Contextual effects in measuring accounting faculty perceptions of accounting journals: An empirical test and updated journal rankings. Advances in Accounting, 9, 161–182. Hasselback, J. R. (1978–1997). Accounting faculty directory. Englewood Cliffs, NJ: PrenticeHall. Henderson, G., Jr., Ganesh, K., & Chandy, P. R. (1990). Across-discipline journal awareness and evaluation: Implications for the promotion and tenure process. Journal of Economics and Business, 42(4), 325–351. Hull, R. P., & Wright, G. B. (1990). Faculty perceptions of journal quality: An update. Accounting Horizons, 4(March), 77–98. Kozub, R. M., Sanders, D. L., & Raabe, W. A. (1990). Measuring tax faculty research publication records. Journal of the American Taxation Association, 12(Fall), 94–101. Milne, R. A., & Vent, G. A. (1987). Publication productivity: A comparison of accounting faculty members promoted in 1981 and 1984. Issues in Accounting Education, 2(Spring), 94–102. Raabe, W. A., Kozub, R. M., & Sanders, D. L. (1987). Attitude measurement and the perceptions of tax accounting faculty publication outlet. Journal of Accounting Education, 6(Spring), 45–57. Read, W. J., Rama, D. V., & Raghunandan, K. (1998). Are publishing requirements for accounting faculty promotions still increasing? Issues in Accounting Education, 13(May), 327–340. Schultz, J. J., Meade, J. A., & Khurana, I. (1989). The changing roles of teaching, research, and service in the promotion and tenure decisions for accounting faculty. Issues in Accounting Education, 4(Spring), 109–119. Spiceland, J. D., & Agrawal, S. (1988). International guide to accounting journals. New York, NY: Markus Weiner Publishing, Inc.. Swanson, E. P. (2004). Publishing in the majors: A comparison of accounting, finance, management and marketing. Contemporary Accounting Research, 21(Spring), 223–255. Vargo, R. J., & Vargo, M. T. (1998–1999). The author’s guide to accounting and financial reporting publications (Revised Ed.). Lodi, CA: Vargo Publishing. Windal, F. W. (1981). Publishing for a varied public: An empirical study. The Accounting Review, 56(July), 653–659. Zivney, T. L., Berton, W. J., & Gavin, T. A. (1995). A comprehensive examination of accounting faculty publishing. Issues in Accounting Education, 10(Spring), 1–25.

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APPENDIX List of Journalsa Academy of Management Executive (PN) (1) Accountancy Ireland (PA) (1) Accounting and Business Research (AA) (2) Accounting and Finance (PA) (1) Accounting Educator’s Journal (ED) (11) Accounting Enquiries (AA) (4) Accounting Historians Journal (AA) (2) Accounting Horizons (AA) (20) Accounting, Auditing & Accountability Journal (AA) (3) Accounting, Organizations and Society (AA) (2) Advances in Accounting (AA) (12) Advances in International Accounting (AA) (4) Advances in Public Interest Accounting (AA) (1) Advances in Quantitative Analysis of Finance and Accounting (AA) (2) Advances in Taxation (AT) (25) Administration and Society (PN) (1) Akron Business and Economic Review (PN) (2) American Business Law Journal (PN) (1) American Business Review (PN) (3) American Economic Review (AN) (1) Applied Financial Economics (AN) (3) Appraisal Journa1 (PN) (2) Arkansas Business and Economic Review (PN) (1) Asian Pacific Journal of Management (AN) (1) Auditing: A Journal of Practice and Theory (AA) (15) Australian Accountant (PA) (1) Behavioral Research in Accounting (AA) (3) Benefits Quarterly (PN) (1) British Accounting Review (AA) (1) British Tax Review (PT) (3) Business (PN) (2) Business Communication Quarterly (PN) (1) Business Forum (PN) (1) Business History (AN) (1) Business Quarterly (PN) (1) CA Magazine (PA) (5) Canadian Journal of Economics (AN) (1) Competitiveness Review (PN) (1) Computers in Accounting (PA) (2)


APPENDIX (Continued ) List of Journalsa Contemporary Accounting Research (AA) (15) Corporate Accounting (PA) (1) Corporate Controller (PA) (2) Corporate Tax (PT) (3) S Corporations: The Journal of Tax, Legal and Business Strategies (PT) (3) CPA Journal (PA) (92) Decision Sciences (AN) (1) Economic Journal (AN) (1) Economic Letters (AN) (1) Engineering Economist (PN) (1) Estate Planning (PN) (3) Financial Accountability and Management (AA) (1) Financial Analysts Journal (PN) (2) Financial Management (PN) (2) Financial Review (AN) (2) Financial Services Review (AN) (2) Government Accountants Journal (PA) (2) Government Finance Review (PN) (2) Housing Policy Debate (AN) (2) Internal Auditing (PA) (7) Internal Auditor (PA) (10) International Journal of Accounting and Education Research (ED) (9) International Journal of Forecasting (AN) (1) International Tax Journal (PT) (14) Issues in Accounting Education (ED) (8) Ivey Business Journal (PN) (2) Journal of Accountancy (PA) (36) Journal of Accounting & Economics (AA) (19) Journal of Accounting and Public Policy (AA) (17) Journal of Accounting Education (ED) (17) Journal of Accounting Literature (AA) (7) Journal of Accounting Research (AA) (40) Journal of Accounting, Auditing and Finance (AA) (14) Journal of Accounting, Auditing and Taxation (AA) (6) Journal of Agricultural Taxation and Law (PT) (1) Journal of American Academy of Business (AN) (1) Journal of Applied Business Research (AN) (11) Journal of Applied Economics (AN) (1) Journal of Asset Protection (PN) (1)

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APPENDIX (Continued ) List of Journalsa Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal Journal

of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of of

Bank Taxation (PT) (1) Business (PN) (3) Business and Economic Studies (AN) (1) Business Ethics (AN) (6) Business Research (AN) (2) Business, Finance and Accounting (PA) (18) Compensation and Benefits (PN) (3) Corporate Accounting and Finance (PN) (20) Corporate Taxation (PT) (8) Cost Management (AA) (1) Economic Behavior and Organization (AN) (1) Economic Issues (AN) (2) Economic Psychology (AN) (3) Economic Theory (AN) (2) Economics and Business (PN) (1) Environmental Economics and Management (AN) (1) Finance (AN) (4) Financial Economics (AN) (5) Financial Planning (PN) (4) Financial Research (AN) (2) Financial Service Professionals (PN) (3) Financial Statement Analysis (AN) (1) Forecasting (AN) (3) General Management (PN) (1) Health Economics (AN) (1) Housing Economics (AN) (1) Housing Research (AN) (1) International Business Studies (AN) (2) International Taxation (PT) (2) Law and Economics (AN) (3) Legal Studies (AN) (1) Lending and Credit Risk Management (PN) (1) Macroeconomics (AN) (1) Management Accounting Research (AA) (3) Marketing (AN) (1) Mathematical Economics (AN) (1) Operations Management (AN) (1) Organizational Behavior (AN) (2) Partnership Taxation (PT) (3)


APPENDIX (Continued ) List of Journalsa Journal of Pass Through Entities (PA) (2) Journal of Pension Planning and Compliance (PN) (1) Journal of Political Economy (AN) (1) Journal of Professional Services Marketing (AN) (1) Journal of Property Management (PN) (2) Journal of Public Budgeting, Accounting and Financial Management (AA) (1) Journal of Real Estate Finance and Economics (AN) (2) Journal of Real Estate Research (AN) (1) Journal of Real Estate Taxation (PT) (17) Journal of Retirement Planning (PN) (1) Journal of Small Business Management (PN) (1) Journal of Small Business Research (AN) (2) Journal of State Taxation (PT) (2) Journal of Tax Practice and Procedures (PT) (1) Journal of Taxation (PT) (41) Journal of Taxation of Corporate Transactions (PT) (2) Journal of Taxation of Estates and Trusts (PT) (1) Journal of Taxation of Investments (PT) (19) Journal of the American Real Estate and Urban Economics Assoc. (PN) (1) Journal of the American Society of CLU and CHFC (PN) (3) Journal of the American Taxation Association (AT) (88) Journal of the Marketing Research Society (AN) (2) Journal of Theory Decisions (AN) (1) Journal of Urban Economics (PN) (1) Journal of World Trade (PN) (1) Lecture Notes in Economics and Mathematical Systems (AN) (1) Local Government Studies (PN) (1) Long Range Planning (PN) (2) Louisiana CPA (PA) (1) Louisiana Law Review (AN) (1) Management Accounting (PA) (25) Management Accounting Quarterly (PA) (1) Management and Decision Economics (AN) (2) Management International Review (AN) (1) Management Science (AN) (1) Managerial Auditing Journal (PA) (9) Managerial Finance (AN) (4) Mid-American Journal of Business (AN) (3) Multinational Business Review (PN) (1)

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APPENDIX (Continued ) List of Journalsa National Public Accountant (PA) (46) National Tax Journal (AT) (17) Nonprofit Management and Leadership (PN) (1) Nonprofit World (PN) (2) Ohio CPA Journal (PA) (12) Oil and Gas Tax Quarterly (PT) (5) Organizational Behavior and Human Decision Processes (AN) (4) Plant Engineering (AN) (1) Practical Accountant (PA) (13) Practical Tax Strategies (PT) (20) Production and Inventory Management Journal (AN) (1) Property Tax Journal (PT) (1) Psychological Reports (AN) (2) Public Administration Review (AN) (1) Public Finance Quarterly (AN) (2) Public Opinion Quarterly (AN) (2) Rand Journal of Economics (AN) (1) Real Estate Accounting and Taxation (PT) (4) Real Estate Appraiser and Analyst (PN) (1) Real Estate Law Journal (PN) (18) Real Estate Review (PN) (7) Regional Science and Urban Economics (AN) (1) Research in Accounting Ethics (AA) (4) Research in Accounting Regulation (AA) (4) Review of Accounting Studies (AA) (5) Review of Business and Economic Research (AN) (1) Review of Financial Economics (AN) (2) Review of Financial Studies (AN) (2) Review of Taxation of Individuals (PT) (9) Small Business Controller (AN) (2) Small Business Taxation (PT) (1) Social Science Quarterly (PN) (1) Socio Economic Planning Science (AN) (1) South Dakota Business Review (PN) (2) Southern Economic Journal (PN) (1) Spectrum (AN) (1) SRA Journal (PN) (1) Strategic Financeb (PA) (5) Systems: The Journal of State Government (AN) (1)


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APPENDIX (Continued ) List of Journalsa Tax Advisor (PT) (130) Tax Executive (PT) (4) Tax Notes (PT) (20) Tax Notes International (PT) (2) Taxation for Accountants (PT) (79) Taxation for Lawyers (PT) (1) Taxes (PT) (103) The Accounting Review (AA) (52) The Oxford Economic Papers: New Series (AN) (1) Total Quality Management (AN) (1) Transportation Journal (AN) (1) Trusts and Estates (PN) (3) Woman CPA (PA) (5) World Bank Economic Review (AN) (1) a

Code: AA (Academic Accounting), AN (Academic Non-Accounting), AT (Academic Tax), ED (Education), PA, (Professional Accounting), PN (Professional Non-Accounting, Non-Tax), PT (Professional Tax). Number in parentheses is number of articles published by sample scholars. b Formerly titled Management Accounting.

TAX PLANNING FOR THE LOBBY TAX Mary Ann Hofmann ABSTRACT In 1993, Congress eliminated the business deduction for lobbying. The disallowance extends to dues paid to tax-exempt trade and labor associations when those organizations conduct lobbying activities. Associations are required to notify members regarding the portion of their dues that is non-deductible or pay a flat 35% tax on their lobbying expenditures. This study examines the factors considered by associations in making the pay-or-notify decision, looking for evidence that associations consider the marginal tax rates of their members to insure that the party with the lowest marginal rate pays the tax. Data is obtained from the IRS and is supplemented by data collected in a mail survey. The evidence suggests that associations do not necessarily attempt to minimize the total tax cost to all parties. This study identifies a situation where non-profit firms might fail to implement an optimal tax planning strategy, and where the absence of a competitive market allows this inefficiency to persist.

INTRODUCTION The IRC Section 6033 proxy tax, commonly known as the lobby tax, sets up a unique situation in which a tax-exempt association that engages in Advances in Taxation, Volume 17, 37–63 Copyright r 2007 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1058-7497/doi:10.1016/S1058-7497(06)17002-7

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lobbying activities can choose whether to pay a tax on those activities or to pass the incidence of the tax on to its members by making their dues a nondeductible expense. Even if one argues that the incidence of the tax ultimately falls on the members either way, the organization’s choice influences the rate at which the tax is paid – 35% if paid by the association, and anywhere from 0% to 50%, depending on the marginal tax bracket, if passed along to the members in the form of a disallowed deduction.1 This article explores the factors that influence the association’s choice of whether to notify members as to the non-deductibility of their dues or to pay the lobby tax. Specifically, it looks for evidence that trade, labor, and agricultural associations (hereafter referred to simply as associations) consider the marginal tax rates of their members to insure that the party with the lowest marginal rate pays the lobby tax. This is the first research study to examine empirically the lobby tax issue. The pay-or-notify decision is modeled using a binomial logistic regression. Data is obtained from the IRS Statistics of Income (SOI) Division and is supplemented by a mail survey of associations with lobbying activity. The evidence suggests that associations do not necessarily seek to minimize the total tax cost associated with the lobby tax. Non-tax considerations seem to drive the decision, but it is not clear that associations always make the optimal choice for their members. This study identifies a situation where nonprofit firms might ignore the ‘‘all parties, all taxes, all costs’’ tax-planning approach (Scholes et al., 2005) and where the absence of a competitive market allows this inefficiency to persist. The paper proceeds as follows. The next section describes the lobby tax and develops the primary research proposition. The third and fourth sections discuss the research method and the data, while the final sections present the results and conclusions.

BACKGROUND AND HYPOTHESIS DEVELOPMENT The Taxation of Lobbying In the United States, lobbying has become an accepted and ever-present part of the political system. Many large corporations, labor unions, professional associations, educational groups, medical interests, farm alliances, and various public interest and social issue groups maintain permanent lobbies in Washington, DC and in state capitals to promote and protect their interests (‘‘Lobbying,’’ 2001–2004; see also http://www.opensecrets.org). Trade and professional associations, labor unions, agricultural associations, and other

Tax Planning for the Lobby Tax

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alliances provide an important means of pooling resources to make lobbying more effective and efficient. One of the major functions of many such tax-exempt membership organizations is to advance their interests in the political arena (Hudson Institute, 1990). The potential for corruption, especially bribery of public officials, has given lobbying an unfavorable connotation and the federal government has made many attempts to regulate lobbying.2 The Internal Revenue Code also contains several disincentives for lobbying. While amounts spent on political campaigns or for ‘‘grass roots’’ lobbying generally have not been deductible for tax purposes, the Revenue Act of 1962 allowed a business deduction for expenses that are directly attributable to appearances before committees or individual members of federal, state, or local legislative bodies in connection with existing or proposed legislation that will, or may reasonably be expected to, affect such trade or business (P.L. 87–834 Sec. 3(a)). This Act also allowed a deduction for amounts expended in communicating information on legislative matters to trade or professional organizations of which the taxpayer was a member, as well as for dues paid to such an organization to conduct the actual lobbying.

The Section 6033 Proxy Tax The Omnibus Budget Reconciliation Act of 1993 brought an end to government subsidy of lobbying by eliminating the business tax deductibility of lobbying expenditures. Furthermore, it prevents taxpayers from obtaining an indirect deduction for the lobbying carried out through tax-exempt trade associations. Individuals or corporations paying dues to a non-profit organization, such as a trade association, that engages in lobbying activities are disallowed from deducting the portion of those dues allocable to lobbying activities, and lobbying expenses are presumed to be paid first from dues. If a non-profit membership organization fails to notify its members regarding the amount of their non-deductible dues, the organization itself must pay a flat 35% tax on its lobbying expenditures. This payment is the proxy tax, more commonly known as the lobby tax. In tax year 1998, 612 associations reported and paid a total of $10.8 million of lobby tax (Riley, 2002). Section 6033(e) of the Internal Revenue Code outlines the requirements for associations to report their lobbying activities or pay the lobby tax, and it created a fair amount of controversy when first enacted. The American Society of Association Executives (ASAE) predicted that the denial of a

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business deduction for lobbying expenditures would dramatically reduce lobbying activities by associations and thus severely limit the voice of their constituencies in government. In the words of ASAE’s government affairs issues analyst, ‘‘This curtailment of legislative speech not only threatens the legitimate interests of the association community, but it is a clear indicator of the lobby tax’s unconstitutionality’’ (Tenenbaum, 1994b, p. 55; Smith, 1995).3 A large part of the association community’s objection to this law is that it places an undue record-keeping burden on associations that lobby (Weiland, 1993; Tenenbaum, 1994a; Smith, 1995).

A Tax-Planning Model for the Lobby Tax Tax planning in the corporate world is best described by Scholes et al. (2005). Their book, Taxes and Business Strategy: A Planning Approach, presents a global framework for business decisions involving taxes. In essence, this approach involves maximizing the after-tax net cash flows to all parties to a business transaction. This framework, first published in 1992, has been widely adopted, and academic researchers have found evidence of its validity in a variety of empirical studies.4 For securities trading in public markets, and for publicly traded firms operating in competitive markets, the opportunities for arbitrage seem to ensure that the optimal tax-planning approach is followed, but the question remains: does optimal tax planning apply to non-profit firms operating in a non-competitive environment? The lobby tax, therefore, provides an opportunity to examine tax planning in the non-profit sector. Several recent studies have examined taxes in the non-profit setting – specifically the Unrelated Business Income Tax (UBIT). Sansing (1998) explores analytically the impact of the UBIT in inducing productive efficiency among nonprofits. Yetman (2001) finds evidence that charitable non-profits shift expenses from exempt activities to taxable activities to minimize the UBIT (see also Omer & Yetman, 2003). Hofmann (2006) finds similar evidence using a sample of non-charitable nonprofits. These studies suggest aggressive tax planning (or perhaps even tax evasion) on the part of exempt organizations subject to the UBIT. The lobby tax could be susceptible to a similar type of cost allocation bias. When an association engages in in-house lobbying activities, a portion of administrative overhead costs must be allocated to lobbying expense, and thus be subject to the lobby tax. Clearly, a carefully designed cost system could minimize such allocations. The focus of this article, however, is not on the allocation of expenses to lobbying.


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Rather, taking the lobbying expenses reported as given, this study explores the association’s choice of whether to pay the lobby tax or shift it to members as a disallowed deduction. If the corporate model applies to the non-profit world, the goal of tax planning for the lobby tax should be to maximize net after-tax cash flows to all parties. Since the pay-or-notify decision primarily involves cash outflows, the objective would be to minimize the total tax and non-tax costs to the association and its members. Consider, for example, an association whose membership consists of self-employed professionals, each of whom is in the 25% marginal federal income tax bracket and is subject to the 15.3% selfemployment tax. If this association collects dues of $100,000 per year and spends $50,000 on lobbying, it would have to either notify the members that 50% of their dues are not deductible or pay $17,500 (35% $50,000) in lobby tax (which it possibly could re-coup through higher dues assessments). Fig. 1 illustrates three available alternatives. The decision to notify the members has a zero tax cost to the association but a cost of $18,682 in additional taxes paid by the members. In Alternative B, the association pays the tax. Consequently, the services the members receive are reduced by $17,500, but they avoid $18,682 in taxes. Alternative C, where the association pays the tax and increases dues by an offsetting amount, has the same net result for the association as Alternative A but at a much lower cost to the members, since the dues are tax-deductible. Before one can choose the optimal alternative, one must compare the $17,500 reduction in services to the $18,682 increase in taxes or the $10,961 after-tax increase in dues. For lack of evidence to the contrary, the initial assumption is that members value the services provided by the association on a dollar-for-dollar basis (this assumption is revisited in the Sensitivity Analysis section of the paper). Thus, members should prefer the $17,500 reduction in services (Alternative B) to the $18,682 increase in taxes (Alternative A). Likewise, they should prefer the $10,961 after-tax increase in dues (Alternative C) to the $17,500 reduction in services (Alternative B). Therefore, Alternative C is the optimal choice. Some general propositions emerge from an examination of Fig. 1. Alternative B will be preferable to Alternative A whenever the members’ combined marginal tax rate (CMTR) with respect to the dues deduction is greater than 35%. The CMTR equals the change in total tax liability (selfemployment taxes plus income tax) resulting from the deduction of $1 of association dues; Appendix A shows the derivation of the formula. Alternative C will be preferable to Alternative B if members can take advantage of an increased tax deduction for the increased dues, but will be preferable

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Assumptions: • The association collects dues revenues of $100,000 annually. • The association spends $50,000 annually on lobbying. • The members are all self-employed, subject to a 25% marginal federal income tax rate and a 15.3% self-employment tax rate (1/2 of which is deductible for AGI). • The members currently deduct their association dues on Schedule C. • Administrative costs of notification or payment are approximately equal. • State and local income taxes are ignored. Alternative A: The association notifies members that 50% of dues are non-deductible. Consequences to Association No tax consequences No cash flow consequences No change in level of services provided

Consequences to Members Loss of $50,000 deduction, resulting in aggregate increased taxes of $18,682* No change in association services

Alternative B: The association pays the 35% lobby tax. Consequences to Association Increased tax of $17,500 Decrease in cash flow of $17,500 $17,500 decrease in services provided

Consequences to Members No loss of deduction or tax increase No dues increase $17,500 reduction in services received

Alternative C: The association pays the 35% lobby tax and raises dues to compensate.

Consequences to Association Increased tax of $17,500, offset by dues No net cash flow consequences No change in level of services provided

Consequences to Members Increased dues, increased deduction: after-tax cost of dues increase, $10,961** No change in association services

*$50,000 additional self-employment income *0.9235* 15.3% = $7,065 additional self-employment tax [$50,000 – ½($7,065)]* 25% = $11,617 additional federal income tax $11,617 + $7,065 = $18,682 increase in tax liabilities (combined marginal tax rate = 37.4%) **$17,500 reduction of self-employment income *0.9235 * 15.3% = $2,473 self-employment tax savings ($17,500 –1,236.5) *25% = $4,066 federal income tax savings from increased dues deduction. $17,500 increase in dues less total tax savings of $6,539 = $10,961 after-tax cost of dues increase

Fig. 1.

An Illustration of the Pay-or-Notify Decision.

to Alternative A whenever the CMTR exceeds 26%. Proofs of these propositions appear in Appendix B.5 The Research Proposition In the simplified example shown in Fig. 1, all of the members were in the same self-employment and income tax brackets. Actually, members will face CMTRs ranging from 0% to 51%. Rather than seeking to minimize the total


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taxes paid by all parties, the association is more likely to attempt to please the greatest number of members. Members in a marginal tax bracket at or below 26% or those who do not or cannot deduct the dues as a business expense or employment-related expense will be best served by being disallowed the deduction for the dues (rather than having to pay higher dues or receive diminished services). On the other hand, members in a combined marginal tax bracket (with respect to the dues deduction) above 26% will prefer that the association pay the lobby tax. Thus, the research proposition is: The probability that an association pays the lobby tax is positively associated with the proportion of its membership that is in a combined marginal tax bracket (with respect to the dues deduction) exceeding 26%.

Non-tax costs also need to be considered, such as record-keeping and administrative costs that might vary between the two alternatives and across firms. The lobbying expenditures must be tracked whether for disclosure or for lobby tax computation, so basic record-keeping costs should not differ between the two options (Tenenbaum, 1994b). Disclosure of lobbying activity usually takes place on the dues assessment notice, so no additional mailings are required for firms choosing to notify. Associations that pay the lobby tax must file Form 990-T; thus, associations that do not have Unrelated Business Income to report incur an incremental filing cost.6 In addition to administrative costs, the political costs of the choice must be considered. To implicitly pass the incidence of the tax to the membership, the association must disclose the extent of its lobbying activities. An article in Association Management suggested that some associations might be reluctant to disclose lobbying expenses to members because they fear that members may disapprove of how much (or how little) of their dues are being spent on political activities (Hopkins & Tesdahl, 1995).7 Finally, associations also likely vary as to budgetary and cash flow constraints. These nontax costs and constraints must be included in the decision model.

RESEARCH METHOD The Logit Regression Model The choice of whether to disclose the lobbying expenditures or pay the lobby tax can be analyzed using a binomial logistic (logit) regression model.8 The general form of this model is PAY ¼ f fCMTR; non-tax factors and control variablesg

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where the dependent variable PAY takes on the value of one if the association elects to pay the lobby tax and zero otherwise, and CMTR measures the proportion of the membership with a CMTR above the specified cut-off. Non-tax factors and control variables include the size of the association, the proportion of revenue derived from dues, the proportion of total expenses devoted to lobbying, the proportion of dues spent for lobbying, administrative costs of notification versus paying the lobby tax, cash flow constraints, etc. See Table 3, which appears later in this article, for a complete description of the model and definitions of the variables.

The Marginal Tax Rate Variable It is not possible to determine the marginal tax rates of the members of each association, but demographic information about each organization’s membership is used to estimate the proportion of members in a marginal tax bracket above 26%. Basically, members fall into one of four possible tax-status categories: employed individuals (wage-earners), self-employed individuals (including sole proprietors and partners), corporations, or taxexempt organizations. Each category faces a different marginal tax rate with respect to the deduction for association dues. Obviously, tax-exempt members derive no benefit from the deduction of membership dues and thus face a marginal tax rate of zero. Corporate tax rates range from 15% to 35%. Corporations with taxable income below $75,000 face a marginal tax rate of 25% or less. The remainder falls into the 34% or 35% marginal income tax brackets. For corporations making the ‘‘S’’ election, income and deductions flow through to the shareholders and are taxed at their personal rates. In 1997, the lowest individual tax bracket is 15%; the next one is 28%. Detailed data regarding specific members are unavailable; it seems reasonable to assume that the majority of corporate members have sufficient income to be in a marginal tax bracket above 26%. Members who are wage earners may deduct dues paid to an association as an unreimbursed employee expense, reported on Schedule A of the Form 1040. Individuals in the highest marginal tax bracket who are able to take advantage of such a deduction could save up to 39.6% (in 1997). However, unreimbursed employment-related expenses can be deducted only to the extent they exceed 2% of adjusted gross income (AGI); and the taxpayer gains no tax benefit unless total itemized deductions exceed the standard deduction. Furthermore, itemized deductions are subject to phase-out for high-AGI taxpayers. Owing to these significant limitations, the actual tax


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savings from deducting association dues is likely to be zero for a substantial proportion of wage-earner members. Employees who are reimbursed by their employers under an accountable plan report no income or deduction relating to the dues, and thus face a marginal tax rate of zero. Therefore, the assumption is that the majority of employed members face a CMTR of zero with respect to the dues deduction.9 Self-employed individuals have the most to gain from the membership dues deduction. For self-employed individuals, including sole proprietors and partners, the business deduction for membership dues reduces both taxable income and self-employment income, so the tax savings is two-fold. One-half the self-employment tax is deductible for AGI, and in 1997 only the first $65,400 of self-employment income is subject to the Social Security portion of the self-employment tax. Under the 1997 tax rates, the CMTR with respect to the dues deduction could range from 17% to 51%. Fig. 2 shows the possible combinations of self-employment tax and income tax rates. Only taxpayers in the lowest income tax bracket whose employment/ self-employment income exceeds $65,400 (an unlikely combination) will have a CMTR below 26%. Thus, the CMTR26 variable is operationalized as the percentage of the association’s members who are corporations or selfemployed. Question 10 in the survey instrument asks the association to furnish the percentages of its membership that fall into each of the four taxstatus categories. Owing to the possible inaccuracy of these percentages or the assumptions regarding the marginal tax brackets of members in each category, the CMTR26 variable is subject to measurement error.

Marginal Income Tax Bracket 15% 28% 31% 36% 39.6%

CMTR for Taxpayers whose FICA income $65,400** 17% 30% 33% 38% 42%

*

∆SE Tax = $1 x 0.9235 x 15.3% ∆Income Tax = [$1 – ½(SE Tax)] * Marginal Income Tax Rate CMTR = ∆SE Tax + ∆Income Tax

**

∆SE Tax = $1 x 0.9235 x 2.9% ∆Income Tax = [$1 – ½(SE Tax)] * Marginal Income Tax Rate CMTR = ∆SE Tax + ∆Income Tax

Fig. 2.

Combined Marginal Tax Rates with Respect to $1 of Dues Deduction for Self-Employed Association Members in 1997.

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Non-Tax and Control Variables A variety of variables are used to control for the non-tax costs that might differ between the pay and notify alternatives. The size of the association serves to control for budgetary constraints. Smaller firms may be less prepared to notify members as to the non-deductibility of dues but also may be less likely to have sufficient cash flow to pay the lobby tax. Thus, it is impossible to predict the sign of the relationship between size and the choice to pay the lobby tax. The SIZE variable is measured as the natural log of total assets at the end of the year. The ratio of current assets to total assets, CURRENT, is a measure of liquidity.10 Firms with greater liquidity should be better able to pay the lobby tax, so a positive association is predicted for CURRENT. The administrative costs of filing Form 990-T to report and pay the lobby tax are not measurable, but the SOI data does include an indicator for firms filing Form 990-T due to having Unrelated Business Income exceeding $1,000. For these firms, the decision to pay the lobby tax will not result in additional filing costs. The 990-T variable, therefore, is predicted to have a positive coefficient. Other factors that might influence the pay-or-notify decision relate to the significance of dues as a source of revenue, DUES%REV; the relative proportion of total expenses represented by lobbying, LOB%EXP; and the relative proportion of dues spent for lobbying, LOB%DUES. The larger the proportion of an association’s total revenues derived from dues, the more sensitive it should be to the preferences of its members, suggesting a positive relationship with the choice to pay. The larger the proportion of an association’s total expenditures devoted to lobbying, however, the more significant the lobby tax cost will be to the association, suggesting a negative relationship. The larger the proportion of dues spent for lobbying, the greater will be the loss of the dues deduction for the members, suggesting a positive impact on the association’s decision to pay the lobby tax.

THE DATA Statistics of Income Data The IRS’s SOI Division’s 1994–1997 Exempt Organization Microdata records are the primary source of data. The SOI collects this data from a stratified random sample of all Forms 990 filed in each year. Sampling rates vary from 100% for the largest firms (total assets>$10 million) to 2% for


47

the smallest firms. The data include most of the line items on Form 990 and its supporting schedules. SOI compiles the returns of 501(c)(4), (5), and (6) organizations – trade, labor, and agricultural associations – separately from those of 501(c)(3) charities. Besides revenue and expense numbers and beginning and ending balance sheets, Forms 990 filed by associations contain information regarding membership dues, lobbying expenses, notification to members of non-deductibility, and the election to pay the lobby tax. Although the lobby tax law became effective in 1994, data from the first few years of its existence may not fully reflect informed tax planning, for reasons that follow. The law requires associations not wishing to pay the lobby tax to estimate their lobbying expenses for the coming year and notify members in advance. Organizations unprepared for this law were forced to pay the lobby tax for the first year or two (Riley, 2000). Furthermore, the final Treasury regulations, which provide guidelines for the allocation of costs to lobbying, were not issued until 1995. Until then, there was some confusion as to how to implement the new law (Tenenbaum, 1995). Thus, to avoid including observations where the choice was not a deliberate one, this study examines only data from 1997. By then, associations should have had time to absorb the implications of the new law and to choose purposefully how best to handle the lobby tax. Fig. 3 reproduces the section of Form 990 dealing with the lobby tax provisions. Questions 85a and 85b seek to eliminate organizations not subject to the Sec. 6033(e) provisions – organizations whose members are unable to deduct their dues, and organizations with lobbying expenses below the $2,000 de minimis threshold. Associations answering ‘‘Yes’’ to either question are directed not to complete parts 85c through 85h. In the 1997 SOI data set, 784 of the 4,446 Section 501(c)(4), (5), and (6) associations responded ‘‘Yes’’ to the first question. These associations would be ones whose members are either non-profit organizations or employed individuals who probably cannot take advantage of the deduction for unreimbursed employee expenses. Another 1,625 answered ‘‘Yes’’ to the second question, on line 85b. A ‘‘No’’ answer implies that the organization had lobbying expenditures exceeding $2,000, but of the 2,037 firms answering ‘‘No,’’ only 580 actually reported any lobbying expenses on line 85d. This omission may reflect blatant tax evasion – a refusal to report lobbying expenses – but one would speculate that firms wishing to hide the amount of their lobby expenses likely would not admit to having such expenses in the first place. It is also possible that the IRS SOI Division coded all missing responses as ‘‘No.’’ Thus, it is assumed that the 1,457 firms answering ‘‘No’’ to line 85b

48

Fig. 3.

MARY ANN HOFMANN

Part VI, Line 85 from Page 5 of the 1997 IRS Form 990 Return of Organization Exempt from Income Tax.

but reporting no lobbying expenses on line 85d either were confused by the question or had their responses miscoded. In any event, 580 associations reported lobbying expenses on line 85d. Of those, 20 observations were eliminated for data irregularities, leaving 560 associations with lobby expenses.11 The Mail Survey To more fully address the lobby tax issue, a mail survey was developed to collect additional data (see Appendix C).12 The survey questions examine changes in membership numbers, changes in lobbying activity, changes in record-keeping and tax compliance costs, and factors considered in making the decision of whether or not to pay the lobby tax. Question 10 in the survey instrument asks the association to furnish the percentages of its membership that fall into each of four tax-status categories. Surveys were mailed to the 551 firms for whom addresses could be obtained.13 One hundred eight associations responded, representing a response rate of approximately 20%.14 Only 92 of the responders provided information on the demographics of their memberships, which is necessary to estimate the marginal tax rate. Descriptive Statistics Descriptive statistics for the SOI and survey samples are presented in Table 1. As discussed earlier, the SOI data are a stratified random sample, so

Descriptive Statistics.

Panel A: The SOI Sample

Total assets (mean) Minimum Median Maximum Current/total assets (mean) Minimum Median Maximum Total revenues (mean) Minimum Median Maximum % of revenues from dues (mean) Minimum Median Maximum % of expenses for lobbying (mean) Minimum Median Maximum

Panel B: The Survey Sample

n ¼ 560

Payers n ¼ 83

Notifiers n ¼ 477

p-value

n ¼ 92

Payers n ¼ 11

Notifiers n ¼ 81

p-value

$ 12,670,566 24,661 3,488,409 386,973,238 0.70

$17,799,346

$11,778,137

0.085

$21,122,883

$12,425,434

0.073

0.76

0.69

0.028

$13,465,346 154,859 5,881,742 58,595,820 0.71

0.78

0.70

0.296

$14,169,409

$11,904,159

0.727

28.1%

51.4%

0.025

1.8%

7.0%

0.006

0 0.76 1.00 $ 10,575,705 63,674 3,209,369 281,711,065 48.6% o1% 47.6% 100% 7.13% o1% 4.36% 96%

$12,909,415

$10,169,630

0.475

38.57%

49.68%

0.001

0.24 0.73 1.00 $12,175,004 169,669 4,821,844 88,774,628 48.6%

0.000

o1% 45.1% 100% 6.4%

1.63%

8.09%


Table 1.

o1% 3.8% 25%

49

50

Table 1. (Continued ) Panel A: The SOI Sample

% of dues spent for lobbying (mean) Minimum Median Maximum Number (%) of firms required to file a Form 990-T due to UBI>$1,000

Panel B: The Survey Sample

n ¼ 560

Payers n ¼ 83

Notifiers n ¼ 477

p-value

n ¼ 92

Payers n ¼ 11

Notifiers n ¼ 81

p-value

14.52%

7.73%

15.7%

0.000

13.3%

18.5%

12.6%

0.153

0.020

o1% 8.3% 63% 68 (74%)

60 (74%)

8 (73%)

0.929

o1% 9.61% 241% 354 (63.21%)

43 (51.81%)

311 (65.2%)

Notes: Payers are firms choosing to pay the lobby tax; notifiers are firms choosing to notify members as to the non-deductibility of dues. Pvalue measures the significance level for the test of differences in means.Source: The data come from the IRS Statistics of Income 1997 Exempt Organization Microdata records. The SOI sample consists of those associations identified as having lobbying expenses exceeding the $2,000 de minimis. Surveys were mailed to the 551 firms for whom addresses could be obtained; 108 responses were received, 92 with complete information.

MARY ANN HOFMANN


51

each observation is weighted by the inverse of its sampling rate. The means and medians for the survey sample are somewhat higher than for the population as a whole. It appears that the majority of the survey observations come from the middle two quartiles of the full sample. Also, some significant differences arise between the firms that paid the lobby tax and those that did not. In the full SOI sample, firms paying the lobby tax have a higher ratio of current assets, a lower percentage of revenues from dues, a lower percentage of total expenses for lobbying, and a lower percentage of dues spent for lobbying than those choosing to notify. The survey respondents paying the lobby tax receive a lower percentage of their revenues from dues and spend a significantly smaller percentage of their budgets for lobbying. Table 2 presents the results of the mail survey of firms identified as incurring lobbying expenditures. No unusual changes in membership numbers occur, nor does lobbying activity seem to have suffered the blow predicted by ASAE (Tenenbaum, 1994a). Responders report that record-keeping costs have increased since 1993 as predicted (Weiland, 1993; Tenenbaum, 1994a, b, 1995; Smith, 1995), but it is not clear that this increase necessarily relates to the lobby tax provisions. As discussed in the previous section of the article, associations whose membership is comprised primarily of employed individuals or non-profit organizations would not be expected to pay the lobby tax; and yet two such associations in the sample do so. Likewise, associations whose membership is comprised primarily of self-employed individuals would be expected to pay the lobby tax, yet 13 out of 15 such associations in the sample do not. Interestingly, tax factors are second among those chosen most frequently by survey respondents as significant to the pay-or-notify decision. Convenience of the members and/or the organization is first. Cash flow considerations, confidentiality regarding lobbying activity, and administrative costs are reported as significant factors less frequently. While responders report tax factors to be important in making the payor-notify decision, it is not clear that associations take the trouble to apply the professional tax-planning model in the strictest sense, that is, by minimizing the combined tax liability of both the organization and the members by allowing the party with the lowest marginal tax rate to bear the incidence of the lobby tax. Since one cannot be certain whether the surveys were completed by the individuals responsible for making the pay-or-notify decision, one cannot place too much reliance on the subjective survey questions. It is also not clear what the impact of non-tax factors might be; therefore, the question needs to be examined in a multivariate framework.

52

MARY ANN HOFMANN

Table 2.

Survey Results: Lobby Tax Questions (n ¼ 92).

Survey Question

Change in membership from 1995 to 2000 Large decrease (>20%) Small decrease (5%–20%) Little change (5% to 5%) Small increase (5%–20%) Large increase (>20%) Change in amount spent for lobbying Small decrease No change Small increase Moderate to large increase Change in amount spent for record-keeping and tax return preparation: (no firms reported a decrease) No change Small increase Moderate to large increase Tax status of large majority (at least 75%) of members Employed and/or nonprofit Self-employed and/or corporate Self-employed Survey Question 16 – significant factors considered in lobby tax decisiona

Administrative costs of filing 990-T Administrative costs of notification Cash flow considerations Convenience of the members Convenience of the organization Confidentiality regarding lobbying activity Minimizing taxes for members Minimizing taxes for organization Organization is exempt from lobby tax Other a

Firms ranking this factor as

Number of Firms

Number electing to Pay Lobby Tax

7 22 28 22 13

1 2 3 2 3

1 81 4 6

0 11 0 0

38 37 17

4 6 1

13 67 15

2 7 2

% of sample ranking this factor in top 3

Firms ranking this factor in top 3 and electing to pay lobby tax

1

2

3

3

3

5

12.0%

1

5

5

8

19.6%

3

5 21

6 8

8 5

20.7% 37.0%

4 10

10

20

14

47.8%

4

2

2

5

9.8%

3

10

10

9

31.5%

9

34

7

7

52.2%

3

0

0

1

1.1%

0

5

1

3

9.8%

1

Choices are not mutually exclusive


53

Accordingly, a binomial logistic (logit) regression is used to test the research proposition.

RESULTS Several specifications of the logit model were run, with results reported in Table 3.15 Model One employs the entire SOI sample of associations with lobbying expenses, and includes only those variables available from the SOI data. The results imply that firms with higher ratios of current assets are more likely to pay the lobby tax, as predicted. LOB%EXP is negative and significant, implying that when lobbying expenses are large in relation to total expenses, the association is less likely to pay the lobby tax. Unexpectedly, firms already filing a Form 990-T appear less likely to pay the lobby tax (perhaps because they are already paying the UBIT). None of the other variables is statistically significant. A naive model would predict that no firms choose to pay and would be correct 85% of the time; it would correctly predict 0% of the payers and 100% of the notifiers for an overall accuracy rate of 85%. Model One correctly predicts 72% of the payers and 88% of the notifiers for an overall accuracy rate of 87% of the observations. Model Two incorporates the CMTR26 variable, which measures the percentage of association members facing a CMTR exceeding 26% (corporations and self-employed individuals). Since demographic data about the associations’ members are required to estimate CMTR26, this model is confined to the 92 firms providing that information in the survey. It appears that the probability of an association choosing to pay the lobby tax is not positively related to the percentage of members with a CMTR greater than 26%. The coefficient for CMRT26 is negative, though not statistically significant. The coefficient for LOB%EXP is negative and significant as before. For LOB%DUES, the coefficient is positive and significant, suggesting that when lobbying expenses are large in relation to total dues collected, the association is more likely to pay the lobby tax. This model correctly predicts 80% of the payers and 92% of the notifiers, for a 91% overall accuracy rate. Few good ‘‘goodness-of-fit’’ measures exist for logit regression models. The w2 statistics from the Log Likelihood Ratio test gives some assurance that the models are reasonably specified. In each case, the p-value for the w2 test statistic is below 0.01. McFadden’s pseudo-R2 gives some indication of the proportion of the variance explained by the model.16 The pseudo-R2 is 0.248 for Model One and 0.386 for Model Two; clearly neither model explains fully the pay-or-notify decision.

54

MARY ANN HOFMANN

Logit Regression Results.

Table 3.

PAY ¼ f Constant, SIZE, DUES%REV, LOB%EXP, LOB%DUES, CURRENT, 990T, CMTR, Survey Question Items (t-statistics in parentheses) Variable

SIZE

Predicted sign

Model 1 (n ¼ 560)

Model 2 (n ¼ 92)

Model 3 (n ¼ 92)

(?)

0.11 (1.21) 0.19 (0.34) 42.45 (6.16) 0.05 (0.07) 1.37 (2.25) 0.74 (2.66)

0.10 (0.25) 0.77 (0.38) 82.13 (2.47) 9.87 (2.22) 1.77 (0.73) 0.84 (0.80) 0.004 (0.29)

0.04 (0.11) 0.78 (0.39) 82.60 (2.50) 9.81 (2.20) 1.54 (0.66) 0.89 (0.80)

DUES%REV

(+)

LOB%EXP

()

LOB%DUES

(+)

CURRENT

(+)

990-T

(+)

CMTR26

(+)

CMTR35

(+)

QCONFID

(+)

QADMNOTIFY

(+)

QCONVMEM

(+)

Chi-square (likelihood ratio test) McFadden’s pseudo-R2 (see Note 16) % correctly predicted to pay % correctly predicted to notify Overall % correctly predicted

0.003 (0.19)

116.67 0.248 72 88 87

25.99 0.386 80 92 91

25.94 0.385 83 93 92

Model 4 (n ¼ 92) 7.85 (1.89) 10.01 (1.09) 936.93 (1.90) 187.48 (1.88) 11.40 (1.40) 9.18 (1.50)

0.11 (1.76) 0.69 (0.53) 11.21 (1.72) 24.75 (1.88) 55.17 0.393 91 99 98

Notes: PAY: an indicator variable, which equals one if the association elects to pay the lobby tax; SIZE: the natural log of total assets at the end of the year; DUES%REV: dues revenues as a percentage of total revenues; LOB%EXP: lobbying expenses as a percentage of total expenses; LOB%DUES: lobbying expenses as a percentage of dues collected; CURRENT: the ratio of current assets to total assets at year-end; 990-T: an indicator variable, which equals one if the association had to file a Form 990-T for UBIT; CMRT26 (35): the percentage of members facing a combined marginal tax rate above 26(35)%; QCONFID: the reversed survey ranking of the factor confidentiality regarding lobbying activity; QADMNOTIFY: the reversed survey ranking of the factor administrative costs of notifying members; QCONVMEM: the reversed survey ranking of the factor convenience of members. Significant at 0.10 (two-tailed test). Significant at 0.05. Significant at or below 0.01.


55

Sensitivity Analysis One of the primary assumptions underlying the research proposition is that members value the services received from the association dollar-for-dollar. If this assumption is not true, members may prefer a reduction in services to an increase in dues. Furthermore, the association may be unwilling or unable to increase the charge for dues (Weiland, 1993). Unfortunately, it was not possible to compile usable data regarding changes in membership fees.17 Where it is not feasible to offset the lobby tax payment with an increase in dues (in other words, when Alternative C in Fig. 1 is not an option), the association should pay the lobby tax only when the majority of the membership is in a tax bracket above 35%. To test this alternative scenario, CMTR26 is replaced with CMTR35, which measures the proportion of members with a CMTR above 35% – basically, only self-employed members.18 Model Three uses the CMTR35 variable. The results of this regression do not differ qualitatively from those for Model Two except that the coefficient for the tax variable is positive, though still not statistically significant. The predictive ability of Model Three is slightly better than that of Model Two, although the pseudo-R2 is virtually unchanged. Clearly, factors other than tax minimization dominate the pay-or-notify decision for the firms in this sample. Model Four incorporates the reversed rankings from some of the factors listed in Survey Question 16 (which asks associations to rank the factors affecting their decision in order of importance). Concerns about confidentiality, about the administrative costs of notification, or concern for the convenience of the members should lead a firm to choose to pay the lobby tax. Indeed, the coefficients for all three factors are positive, and the latter two are marginally significant. Model Four has the highest percentage of correct predictions for both payers (91%) and notifiers (99%), with an overall accuracy rate of 98%, and a pseudo-R2 slightly higher than Models Two or Three. However, one is uncertain whether the factors listed by the survey respondents are actually those considered before making the pay-or-notify decision or are simply after-the-fact justification for the decision. Thus, the predictive ability of Model Four may be overstated.

CONCLUSIONS These results fail to find evidence that associations apply optimal taxminimizing strategies when dealing with the Section 6033 lobby tax. If this

56

MARY ANN HOFMANN

failure accurately reflects the population, associations and particularly their members may be paying more taxes than necessary. Alternatively, the failure to find support for the research proposition could be the result of several other factors. The low survey response rate may have produced a sample that is not representative of the larger population. The many assumptions made in developing the constructs may not have produced a model capable of detecting the tax effect, especially in a small sample. The CMTR variable, in particular, is subject to measurement error, and this is likely to bias the statistical tests toward zero. The typical rationalization for failure to find firms minimizing all taxes for all parties (as in the Scholes et al., 2005 framework) is that non-tax costs dominate the decision. As mentioned earlier, lobbying expenditures must be identified and tracked under either alternative; notification requires only a short statement on the dues notice while payment requires the filing of Form 990-T and available cash. It is difficult to envision that any of these non-tax costs could be significant enough to drive the decision, but perhaps other costs are associated with notification or payment of the lobby tax that have not been identified. Of the two ‘‘errors’’ an association might make in regard to the lobby tax – paying the tax unnecessarily or failing to pay the tax when members would benefit – the first is understandably less common. In the response sample, only two of 16 firms with more than 50% of the members being employed or nonprofit (and thus unlikely to benefit from the dues deduction) chose to pay the lobby tax. In both cases, the dollar amounts involved appear to be immaterial; the tax on the lobby expenses is less than 1% of the association’s end-of-year assets and less than 5% of its end-of-year cash balance. On the other hand, 21 of 24 associations with greater than 50% of the members being self-employed (and 13 out of 15 associations with at least 75% of the members self-employed) did not pay the lobby tax, thereby depriving their members of tax savings exceeding the cost of the lobby tax. Several reasons may explain why an association might choose not to pay the lobby tax even though a majority of members are in a high tax bracket and thus would derive a benefit from the dues deduction. First, such decisions may be made by uninformed administrators. Most of the associations subject to the lobby tax are not subject to other forms of federal taxation (see Note 6), so their management may not be as knowledgeable or as sophisticated as corporate management when dealing with tax issues. Second, although the tax consequences are large in the aggregate, the disallowed dues deductions might be immaterial to individual members who pay modest annual dues. Nevertheless, the most compelling potential reason is that associations may face an inelastic demand curve. Since the services


57

and benefits they provide have no ready substitutes, many associations do not operate in a perfectly competitive market. Members who are dissatisfied with losing the tax deduction for their dues cannot shop around for a better trade association or labor union.19 In other words, no opportunities are available for ‘‘arbitrage’’ or ‘‘clientele’’ effects to efficiently allocate the lobby tax to the appropriate parties as Scholes et al. (2005) describe in the corporate setting (pp. 118–145). Thus, little incentive exists for management to seek the optimal tax strategy for the lobby tax, and the lack of market forces allows this inefficiency to persist. This is the first research study to empirically examine the lobby tax issue, and as such the analysis is preliminary at best. The results (or lack thereof) seem to support a conclusion that nonprofits are not necessarily efficient tax planners when it comes to the lobby tax; however, this conclusion is subject to the limitations discussed above. The lack of a positive finding for the tax variable and the speculation concerning the possible reason(s) may be as dissatisfying to the reader as to the author. Unfortunately, it seems impossible to resolve this issue with currently available data. The research question requires a more detailed survey or field study of the tax-planning attitudes and behaviors of exempt organizations subject to the lobby tax. The researcher would need to be able to identify the person in each organization (or the external tax preparer/advisor) who is responsible for the pay-or-notify decision. It would be important to determine how much associations know about the potential tax-status of their members, as well as whether and how that information is used in making the lobby tax decision. A truly comprehensive study would include a survey of association members to determine their attitudes about the goods and services they receive from the association (including its lobbying activities) as well as the value they place on the dues deduction.

NOTES 1. When Congress passed the lobby tax law, the top marginal tax rate for individuals was 39.6%. Add the self-employment tax (and adjust for the fact that onehalf is deductible for adjusted gross income), and the change in total tax liability from deducting $100 of trade association dues could approach $50. (Keep in mind that an individual would have to have significant non-employment-related income or income from a spouse in order to be in the top marginal bracket and still be subject to the Social Security portion of the self-employment tax). Recently, the top marginal rate for individuals has been reduced, and is currently 35%. In 2005, for self-employed individuals, the loss of a $100 deduction for trade association dues could increase final tax liability by as much as $40.

58

MARY ANN HOFMANN

2. The federal Regulation of Lobbying Act of 1946 required registration of and regular financial reports from all individuals and agents seeking to influence legislation. In 1995, Congress passed a new bill intended to strengthen registration and disclosure requirements. 3. ASAE brought suit (and lost) in U.S. District Court for the District of Columbia in an effort to prevent the IRS from enforcing the association-related provisions of the lobby tax law. They have since appealed to the Supreme Court. Their application for certiorari can be seen at http://www.asaenet.org/policy. 4. See Matsunaga, Shevlin, and Shores (1992) for an example of a test of the ‘‘all parties, all taxes, all costs’’ framework in the corporate setting. See Shackelford and Shevlin (2001) for a comprehensive review of empirical research in taxation, much of which is based on the Scholes and Wolfson (now Scholes et al., 2005) framework. 5. An interesting corollary to these propositions is that whenever it is preferable for the association to pay the lobby tax, it will also be more efficient to pass along the cost to the members by increasing the dues. The after-tax cost of the dues increase will always be less than the reduction in services that would otherwise occur. Of course, this result makes sense only if members value the services received at more than the after-tax cost of the dues increase. 6. In 1996, 65% of Forms 990-T reporting lobby tax were filed solely for that purpose (Riley, 2000). 7. The amount of lobbying expenditures is always disclosed on Form 990, which is subject to public disclosure, and thereby available to anyone who requests it. Political contributions and lobbying expenditures are also tracked by organizations such as the Center for Responsive Politics, and this information is made available to the public. See their website at http://www.opensecrets.org. 8. When the dependent variable is limited to two discrete choices, pay (Y ¼ 1) or notify (Y ¼ 0), ordinary least squares regression is inefficient (Greene, 1997, pp. 873–874). An alternative approach is to use a probit or logit model. These binary choice models assume an unobservable underlying response variably, y*, which is continuous, and for which y* ¼ b0 x + u, where b is the set of parameters that reflect the impact of changes in the independent variables (x). When y* exceeds some threshold, Y ¼ 1. The probability that Y ¼ 1 is equal to the cumulative distribution function of (b0 x) (Maddala, 1983, pp. 22–27). The probit model uses the standard normal distribution function while the logit model uses the logistic cumulative distribution function. Maximum likelihood estimation produces coefficient estimates that are unbiased and consistent (Greene, 1997, p. 871). In situations like the lobby tax decision, where there is a small proportion of Y ¼ 1 responses, logit seems to result in a better fitting model (Greene, 1997, p. 875). 9. In fact, organizations that can provide evidence that at least 90% of their membership is unable to deduct dues as a business/employment expense are exempt from the Section 6033 reporting requirements and/or lobby tax. 10. A large number of firms had zero current liabilities, so the traditional current ratio was unworkable. The ratio of cash to total assets and the ratio of current liabilities to current assets both gave results similar to those using CURRENT. 11. Twelve firms reported zero dues revenue, and thus would face no lobby tax consequences. Three firms answered ‘‘Yes’’ to both questions on lines 85g and 85h (see Fig. 3), and another five firms answered ‘‘No’’ to both questions. These choices,


59

to pay the lobby tax on taxable lobby expenditures or to add such expenditures to next year’s dues notices, are mutually exclusive; thus, it is not clear what the firms’ choices are. 12. The lobby tax issue was part of a larger study of taxation issues affecting trade, labor, and agricultural associations. 13. Because Form 990 is subject to public disclosure, the names and partial addresses of the firms are included in the SOI microdata records. 14. Yetman (2001) had a 30% response rate when requesting copies of Form 990T from charitable nonprofits. 15. Results for probit specifications (not shown) were qualitatively similar but had reduced predictive ability. 16. McFadden’s Pseudo R2 is computed as 1 – L1/L0, where L1 is the log likelihood of the full model, and L0 is the log likelihood of an alternative model, which contains only a constant. 17. Many associations have a range of dues charges for various levels of membership, and some actually charge dues on a sliding scale based on the member’s gross receipts; thus it was impossible to determine whether a change in total dues revenues was a result of increased charges per member or changes in the distribution (or income) of members. 18. As shown in Fig. 2, six out of 10 possible combinations of income tax bracket and FICA tax bracket result in a CMTR greater than 35%. Granted, some of these combinations are more likely than others, but considering filing status, other sources of income/loss (including a spouse’s income/loss), itemized deductions, etc., are well within the realm of possibility. 19. It would be interesting to explore this issue further, but the current data do not provide any basis for estimating demand elasticity for individual associations. The average change in membership numbers from 1995 to 2000 does not differ significantly between firms who paid the lobby tax and those who passed it along to their members.

REFERENCES Greene, W. (1997). Econometric analysis (3rd ed.). Upper Saddle River, NJ: Prentice-Hall. Hofmann, M. (2006). Tax-motivated earnings management by associations. Unpublished working paper, Andrews University. Hopkins, B., & Tesdahl, D. (1995). Legal affairs. Association Management, 47(2), 27. Hudson Institute. (1990). The value of associations to American society. Washington, DC: The American Society of Association Executives. Lobbying. (2001–2004). The Columbia encyclopedia (6th ed.). New York: Columbia University Press. Retrieved October 27, 2005 from http://www.bartleby.com/65/. Maddala, G. (1983). Limited-dependent and qualitative variables in econometrics. Cambridge, UK: The Cambridge University Press. Matsunaga, S., Shevlin, T., & Shores, D. (1992). Disqualifying dispositions of incentive stock options: Tax benefits versus financial reporting costs. Journal of Accounting Research, 30(Supplement), 37–68.

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Omer, T., & Yetman, R. (2003). Near zero taxable income reporting by non-profit organizations. Journal of the American Taxation Association, 25(2), 19–34. Riley, M. (2000). Unrelated business income of non-profit organizations, 1996. Statistics of Income Bulletin, 19(4), 123–146. Riley, M. (2002). Unrelated business income tax returns, 1998. Statistics of Income Bulletin, 21(4), 187–215. Sansing, R. (1998). The unrelated business income tax, cost allocation, and productive efficiency. National Tax Journal, 51(2), 291–302. Scholes, M., Wolfson, M., Erickson, M., Maydew, E., & Shevlin, T. (2005). Taxes and business strategy: A planning approach (3rd ed.). Englewood Cliffs, NJ: Prentice-Hall. Shackelford, D., & Shevlin, T. (2001). Empirical tax research in accounting. Journal of Accounting and Economics, 31(1–3), 321–388. Smith, S. (1995). Associations at risk. Association Management, 47(1), 33. Tenenbaum, J. (1994a). Fighting the new lobby tax law. Association Management, 46(2), 36–42. Tenenbaum, J. (1994b). Lobby tax Q & A. Association Management, 46(5), 52–57. Tenenbaum, J. (1995). The new lobby tax rules. Association Management, 47(9), 77–82. Yetman, R. (2001). Tax-motivated expense allocations by non-profit organizations. The Accounting Review, 76(3), 297–311. Weiland, R. (1993). President’s corner. Tax Executive, 45(5), 356–358.

APPENDIX A. CMTR WITH RESPECT TO THE LOSS OF $1 OF DUES DEDUCTION The loss of the deduction increases taxable income, as well as income subject to self-employment tax. For taxpayers whose income subject to FICA tax is less than or equal to $65,400 (in 1997), the self-employment tax rate is 15.3%. For taxpayers whose income subject to FICA tax is greater than 65,400, the marginal self-employment tax rate is 2.9%, which is the Medicare portion of the FICA tax. $1 0:9235 applicable SE tax rate ¼ DSE tax One-half of the SE tax is deductible for AGI, so taxable income is increased by $1 and decreased by the deduction for the increased SE tax. $1 1=2ðDSE TaxÞ ¼ DTaxable Income The increase in taxable income is taxed at the marginal income tax rate (MTR). DTaxable Income MTR ¼ DIncome Tax The CMTR is equal to the sum of the changes in SE tax and income tax, divided by the $1 increase in income. CMTR ¼ ðDSE Tax þ DIncome TaxÞ=$1


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APPENDIX B. OPTIMIZATION OF ALTERNATIVES A, B, AND C Refer to Fig. 1, which describes the three alternatives. Basically, the objective is to minimize the cost among the three alternatives. The costs are measured per dollar of dues spent on lobbying. In Alternative A, where the association notifies the members as to the dues spent on lobbying, the cost is the increase in taxes paid by the members as a result of the loss of the dues deduction. The resulting increase in taxable income is taxed at the members’ marginal tax rate. The derivation of the CMTR is shown in Appendix A. CostA ¼ CMTR $1 In Alternative B, where the association pays the lobby tax and reduces services by an offsetting amount, the cost to the members of the reduced services is measured by the 35% lobby tax levied on the dues spent for lobbying. CostB ¼ 35% $1 In Alternative C, the association pays the lobby tax and increases the amount charged for dues by an offsetting amount. Since in this case the increased dues are deductible, the net cost to the members is the after-tax cost of the dues increase. CostC ¼ ð35% $1Þ ð1 CMTRÞ Proposition 1. Alternative B will have a lower cost than Alternative A whenever the members’ CMTR is greater than 35%. CostBoCost A when ð35% $1ÞoðCMTR $1Þ; or when CMTR435%. Proposition 2. Alternative C will have a lower cost than Alternative B whenever the members’ CMTR is greater than zero. CostCoCostB when ½ð35% $1Þ ð1 CMTRÞoð35% $1Þ ð1 CMTRÞo1 CMTR40

62

MARY ANN HOFMANN

Proposition 3. Alternative C will have a lower cost than Alternative A whenever the members’ CMTR is greater than 26%. CostCoCostA when ½ð35% $1Þ ð1 CMTRÞoðCMTR $1Þ ½35% ð35% CMTRÞoCMTR 35%o1:35 CMTR 26%oCMTR; or CMTR426

APPENDIX C. RELEVANT EXCERPTS FROM THE SURVEY INSTRUMENT 10. Membership Information:

1995

2000

Number of Members Estimate the approximate proportion of your membership that consists of the following:

Employed Individuals (wage-earners) Self-employed Individuals (proprietors, partners) Corporations Non-profit Organizations

% % % %

Total

100%

Part III: Lobby Tax – complete if you made lobbying expenditures in any year from 1994 to 1997 15. The 1993 ‘‘Lobby Tax’’ law made lobbying expenditures taxable to the organization, unless members were notified as to the non-deductibility of their dues. Indicate how this law affected your organization’s lobbying activities and tax compliance costs over subsequent years by


63

circling the number corresponding to the following scale: 1 – Large decrease 2 – Moderate decrease 3 – Small decrease

4 5 6 7

– – – –

No change Small increase Moderate increase Large increase

(a) Amount spent for lobbying activities:

1234567

(b) Amount spent for record-keeping and tax return preparation:

1234567

16. Choose from the list below the three most significant factors that were considered in deciding whether to pay the lobby tax or to disclose lobbying activity to the members. Write a 1, 2, and 3 next to those factors, in their order of importance (1 ¼ most important). _____Administrative costs of filing the 990-T _____Administrative costs of notifying members _____Cash flow considerations _____Convenience of the members _____Convenience of the organization _____Desire to maintain confidentiality regarding lobbying activity _____Minimizing the tax liability of the members _____Minimizing the tax liability of the organization _____Organization is exempt from lobby tax, or members pay no dues _____Other________________________________________________ _____Other________________________________________________

SOCIAL SECURITY REFORM: EXPLORING THE GENERATIONAL AND RACIAL DIVIDE Cynthia M. Jackson, James J. Maroney and Timothy J. Rupert ABSTRACT Increased life expectancies and decreased birthrates have placed enormous financial pressure on the Social Security system. Because significant reforms are needed to ensure its financial solvency, our study examines the acceptability of proposals to reform the system. Given the potentially divergent views suggested by prior research, we selected participants from the following four groups (1) younger black taxpayers, (2) younger white taxpayers, (3) older black taxpayers, and (4) older white taxpayers. While there was agreement among the groups on several of the proposals, in general, the differences between the generations were more pronounced than the differences between the racial groups.

INTRODUCTION Maintaining the solvency of the Social Security system has been identified as one of the greatest challenges facing tax policy makers (Gravelle, 2002; Pollack, 2002). The Trustees of the Social Security Fund confirm the magnitude of the problem in their 2005 annual report by suggesting that it would Advances in Taxation, Volume 17, 65–94 Copyright r 2007 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1058-7497/doi:10.1016/S1058-7497(06)17003-9

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CYNTHIA M. JACKSON ET AL.

take an immediate increase in program revenues of 15% or an immediate reduction in benefits of 13% to ensure the system’s solvency for the next 75 years1 (Social Security and Medicare Boards of Trustees, 2005). Further compounding the funding problem with the Social Security system is the fact that the Medicare system also has significant funding problems. In fact, the Trustees indicate in their 2005 annual report that ‘‘Medicare’s financial difficulties come sooner – and are much more severe – than those confronting Social Security’’ (Social Security and Medicare Boards of Trustees, 2005). Thus, it appears that substantial reforms to both the Social Security and Medicare systems are required. The primary cause of these funding problems is the changing age demographic in American society. For example, in 1960 there were 5.1 workers per beneficiary in the Social Security system, with this ratio falling to about 3.3 workers per beneficiary currently (Concord Coalition, 2005). As the baby boomer generation begins to retire starting in 2008, this ratio will continue to decrease until it stabilizes at around 2.0 workers per beneficiary around 2030 (Concord Coalition, 2005; Kotlikoff & Burns, 2004). Given that both the Social Security and Medicare systems are essentially on a payas-you-go-basis,2 this changing age demographic will likely require substantial reforms to both systems. Former Federal Reserve Board Chairman Alan Greenspan acknowledged this changing age demographic, as well as the need for significant reforms to both Social Security and Medicare, in recent testimony to Congress. Chairman Greenspan indicates ‘‘this dramatic demographic change is certain to place enormous demands on our nation’s resources – demands we almost surely will be unable to meet unless action is taken. For a variety of reasons, that action is better taken as soon as possible’’ (Federal Reserve Board, 2004). Given this demographic change, along with the current financial status of the Social Security and Medicare funds, reforms are urgently needed for both the Social Security and Medicare systems. Thus, the purpose of this research study is to examine some of the reform proposals that are currently being discussed. Although the focus of our study is on the Social Security system, we also discuss implications of our findings for reform of the Medicare system. In general, the proposals that have been advanced to reform the Social Security system either increase fund revenues or decrease fund expenditures (see, e.g., Ball & Bethell, 1998 or Aaron & Reischauer, 2001, for a discussion of these proposals). Further, many of the recent reform proposals are designed so that, in general, benefits for current retirees and those near retirement age are not changed. In fact, President Bush has recently indicated that any reforms to the Social Security system should not affect benefits for

Social Security Reform

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those taxpayers 55 or older (Bush, 2005). Thus, the increased Social Security taxes and/or benefit reductions from most of the proposals may be primarily borne by future retirees, particularly younger adults. As the preceding discussion suggests, the proposals that are adopted to address the solvency of the Social Security Trust Fund may result in very different outcomes for current and future retirees. The present research examines preferences for these various possible outcomes by presenting four samples of taxpayers with descriptions of the most commonly proposed alternatives for revising the Social Security system and ensuring its solvency. Recruiting from university classes and several organizations in urban areas of the East coast, we developed samples of participants representing the following four groups (1) younger black taxpayers, (2) younger white taxpayers, (3) older black taxpayers, and (4) older white taxpayers. Participants in each group were asked to rate their agreement with each proposal. The results suggest that significant differences in the agreement of the groups exist for some proposals that would increase revenues, decrease benefits, or establish private accounts. In general, the differences between generations were more pronounced than the differences between racial groups. By understanding differences in these views, as well as potential areas of agreement, policy makers may be able to design a reform plan for Social Security that is acceptable to more Americans.

LITERATURE REVIEW AND RESEARCH QUESTIONS Social Security and Generational Differences As discussed earlier, American society is rapidly aging. One concern is that this changing age demographic may lead to new intergenerational conflicts that we have not previously experienced. For example, researchers have examined the effect of the aging population on funding support for public education (Brunner & Balsdon, 2004; Ladd & Murray, 2001; Kenmitz, 2000) and the public policy for long-term health care support (Tabata, 2005). However, the potential for intergenerational conflict is perhaps greatest with Social Security. Over the last several decades, the burden of the Social Security system on the working population has increased, with the ratio of workers to beneficiary dropping from 5.1 to 3.3 over the last four decades. Further, the value of lifetime benefits received by the average elderly couple has increased dramatically over the same time period, from $195,000 to $710,000

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(Steuerle, 2005). Despite these trends, there is some debate over the urgency of the need for Social Security reform. For example, both the U.S. Congressional Budget Office (1995) and Gokhale and Kotlikoff (2001) suggest that based on their analyses, prevailing policies for Social Security and Medicare are not sustainable. Others (Baker & Weisbrot, 1999) have argued that these analyses are based on assumptions that are too conservative and unrealistic, so the need for reform is not as urgent as might be suggested. Despite the debate over the urgency of reform, the likelihood of reform has grown in recent years as politicians have increasingly called for significant reform to the Social Security system. While a variety of reforms have been proposed, essentially these proposals either increase revenues credited to the Social Security Fund and/or decrease expenditures.3 However, the costs of these proposals are not borne equally across generations. For example, any proposal that increases revenues to the Social Security fund through an increase to the payroll tax rate or through an increase in the maximum wage base subject to taxation will primarily be borne by working taxpayers. Thus, current retirees will bear little, if any, of these costs. Conversely, a decrease in current retirement payments would be most directly felt by current retirees, since they are currently receiving benefits. Historically, reforms to the Social Security system have typically passed most of the cost of reform onto the next generation (Kotlikoff & Burns, 2004). However, due to the impending demographic changes in the United States, a strategy of passing the reform costs of Social Security and Medicare onto the next generation may place an unconscionable tax burden on that generation (Kotlikoff & Burns, 2004). Thus, a reasonable question to ask is how can these systems be changed in a manner that is fair across generations? A failure to address this question raises the potential for significant conflict between generations over the reform of the Social Security system. Given this potential conflict between generations, we examine the following research question: Research Question 1. Do senior citizen taxpayers differ from young taxpayers in their agreement with proposals to reform the Social Security system? Social Security and Racial Differences Social Security has proved to be of great importance for elders from all backgrounds. For example, using data from 1997, Porter, Larin, and Primus (1999) indicate that, before considering Social Security payments, the poverty rate among elders is 47.6%. When Social Security payments are


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considered, this rate drops to just 11.9%. While this drop in poverty rate is dramatic, further analysis indicates that not all racial groups benefit equally from Social Security programs. For example, before considering Social Security, 46.3 percent of elderly whites are considered to live in poverty; this number decreases to just 9.1 percent when Social Security programs are considered. In contrast, 59.9% of elderly blacks fell into the poverty category before considering Social Security; the number fell to 29.1 percent when Social Security was considered (Porter et al., 1999, pp. 17–18). To further underscore the differential impact of Social Security along racial lines, the Social Security Administration (2004) found that threefourths of blacks in comparison to two-thirds of whites depend on Social Security for at least half of their retirement income. Additionally, Social Security is the only source of retirement income for 40 percent of blacks while just 16 percent of whites count it as their only source of retirement income (Hendley & Bilimoria, 1999, p. 60). In reforming Social Security, considerable debate has arisen about the relative effects of Social Security on whites and minority groups. For example, several studies have suggested that because of the effect of shorter life expectancy on the returns received from Social Security, blacks would benefit greatly from reforming the system to allow for private accounts because of the ownership rights associated with the accounts (Tanner, 2001; Beach & Davis, 1998). Others have argued that higher disability rates, a greater number of survivors and lower average wages are important factors overlooked in many of these analyses and when these are taken into account, the impact of reform on the relative benefits received by minorities may not be so clear (Rockeymoore, 2001; Wasow, 2002; Kijakazi, 1998; General Accounting Office (GAO), 2003). Given the importance of Social Security in reducing poverty among the elderly and the differential impact that reforms may have on elders of different racial backgrounds, all taxpayers may not view potential reforms in the same light. In fact, previous researchers have documented substantial ‘‘gaps’’ in the opinions of whites versus other racial groups. For example, Smith and Seltzer (2000) report substantial differences between white and black survey participants on a series of questions designed to gather attitudes on government spending on a variety of programs, including Social Security. Given these previous findings, we examine differences between different racial groups with the following research question: Research Question 2. Do white taxpayers differ from black taxpayers in their agreement with proposals to reform the Social Security system?

70


In summary, the previous literature suggests that different generational and racial groups may have different preferences for the specific reforms that are implemented to strengthen the Social Security system. However, the direction of differences (if any) in these preferences is not clear. Thus, the present study investigates potential differences in terms of acceptance of the various reform proposals with research questions, rather than research hypotheses, through the use of a survey described in the following section.

METHODS Participants In order to examine potential differences in preferences for revisions in the Social Security system for taxpayers of different ages and different races, we recruited participants from four different groups of taxpayers during 2002 and the beginning of 2003. Given that the survey instrument took a relatively short time to complete, none of the participants were compensated for their participation. We recruited two groups of young taxpayers. The first group, Black Youth,4 consisted of 21 members of an organization for young urban professionals from the black community in a large city on the East coast. One of the researchers attended a meeting of the group and administered the instrument at the start of the meeting. The second group, White Youth, consisted of 39 students from two classes at a university in the same city. The classes included a senior level accounting class and a firstsemester class in an MBA program. The survey was administered by one of the researchers at the beginning of class. The students received no credit for their participation. In addition to yielding the 39 students for the White Youth group, the classes also included five black students who we included as part of the Black Youth group. This raised the total number of participants for the Black Youth group to 26.5 In order to compare the responses of the young taxpayers with those of elderly taxpayers, we also recruited two groups of senior citizens. The first elder group, Black Senior, included 24 members of a housing concerns group for black elders, which was sponsored by one of the city’s centers for aging. One of the researchers distributed the instruments at the start of one of the group’s meetings. Finally, the second elder group, White Senior, consisted of 25 senior citizens who were members of a professional group at a senior center. The director of the senior center administered the instrument.6


71

One drawback of recruiting participants from specific groups as we did, compared with other survey methods like a national survey, is that the resulting samples are not representative of the population as a whole. For example, the geographic focus of the groups is probably the most apparent way in which we are limited in generalizing from our results. However, this method of gathering our samples also offers some clear benefits. We were able to gain 100 percent participation from the participants in each group, thereby effectively eliminating the limitation of non-response bias that is often present in other survey methods. In addition, because two of the participant groups involved older participants, we were better able to ensure that they were able to adequately understand and process the survey materials. Recent studies have shown that 30 percent of senior citizens develop dementia by age 80. By gathering responses from participants who were part of an active senior group, we help to limit the measurement error that may be associated with broader survey techniques of this age group. Procedures We created a survey instrument that included nine frequently suggested proposals for revising the Social Security system to ensure its solvency.7 For each of the alternatives, we provided a brief description of how the action would change the Social Security system.8 Exhibit 1 includes the proposals and their descriptions.9 After reading each alternative, participants indicated their agreement with the proposal using a 7-point Likert scale (1 ¼ strongly agree and 7 ¼ strongly disagree). On average, participants were able to complete the instrument in about 20 min. After rating their agreement with each of the proposals, participants then provided background information, including their gender, age, educational background, political orientation, and experience as a recipient of Social Security benefits. Table 1 reports the results from these demographic questions. As this table indicates, the youth samples were fairly evenly split on gender. However, the senior samples were not as evenly divided between the genders. The Black Senior group consisted almost entirely of women. While we would have preferred to have a more similar split in gender representation for the two senior groups, previous researchers have not found gender differences on Social Security issues for either blacks or whites (Smith & Seltzer, 2000).

72


Exhibit 1.

Proposals to Reform the Social Security System.

Allow Social Security Surpluses to be Invested in Debt and Equity Securities. The surplus in the Social Security Trust Fund is currently invested in United States Treasury bonds. If surpluses in the fund were invested in debt and equity securities from private companies instead, these investments may provide higher returns than the interest credited to the fund from treasury bonds. However, there is a risk that the investment return from the debt and equity securities may be less than the Treasury bonds Increase Maximum Amount of Wages Subject to Social Security Tax. The maximum amount of wages subject to the Social Security tax is $80,400 for the year 2001. An increase in the maximum amount of wages subject to taxes would help to expand the size of the Social Security tax base and thereby increase revenues Increase Social Security Tax Rate. Currently the Social Security tax rate paid on wages and salary by both the employee and the employer is 6.2%. An increase in the tax rate would provide an increase in revenues Tax Social Security Benefits the Same as Private Pensions. Any Social Security benefits a retiree receives, beyond what he or she contributed to the system as a worker, would be taxed as ordinary income. Currently, only beneficiaries with incomes above certain annual thresholds owe taxes on their benefits, and just a portion of their benefits is subject to the tax. This change would have a favorable effect due to the increase in income taxes paid on retirement benefits, which are credited to the Social Security fund Use Budget Surpluses from Social Security Fund to Repay National Debt. If the projected surpluses from the Social Security Fund are used to repay the national debt, both the Congressional Budget Office and private economists project that the entire national debt would be repaid by 2016. Therefore, the interest that the United States government must pay on the national debt would be eliminated. These interest savings could be credited to the Social Security Fund, thereby increasing fund revenues Adjust CPI to Obtain a More Accurate Measure of Inflation. Social Security benefits are currently adjusted for inflation based on changes in the CPI. Many economists believe that the current CPI overstates the actual inflation rate. If adjustments were made to CPI to obtain a more accurate measure of inflation, the growth in future Social Security benefits would decline Reduce Future Retirement Benefits by Increasing Retirement Age. Since life expectancies for Americans have been increasing, an alternative approach to trimming benefits would be to increase the retirement age. For taxpayers born 1960 and later, the current retirement age is 67. If the life expectancy of individuals born after 1960 continues to increase, the normal retirement age could be adjusted to reflect the longer life expectancy Reduce Future Retirement Benefits by Trimming Monthly Benefits. Since the life expectancy for Americans has been increasing, a reduction in monthly benefit payments for younger taxpayers would still provide total benefit payments equal to older taxpayers due to the increased life expectancies Allow Workers to Invest in Individual Investment Accounts. Currently workers do not have the opportunity to invest any of their Social Security payments into individual investment accounts. If workers were allowed to establish such accounts, these individual accounts may provide higher investment returns than those received by the Social Security Fund. These higher investment returns may result in higher benefit payments. However, there is a risk that these investment accounts may earn less, resulting in lower benefit payments


73

Table 1. Demographic Data for Sample. Percentage of Participantsa

Gender Male Female No response Age Under 30 30–40 40–55 Over 55 Receive social security Yes No No response

Black youth

White youth

Black senior

White senior

40 60

49 51

4 96

63 29 8

76 24

90 10 100

100

87 13

96 4

100

100

Attend college Yes No No response

96 4

100

61 35

38 62

Candidates supported: Democratic Republican Neither more than other No response

81 4 15

44 31 23 3

61 4 21 13

21 21 54 4

a

Total may not add to 100 percent due to rounding.

In further comparing the backgrounds of the senior groups, more of the black seniors have attended college than the white seniors. Over 60 percent of the black seniors have attended college while slightly less than 40 percent of the white seniors have attended college. However, both groups are generally well educated and should be able to analyze and understand the various Social Security reform proposals that were presented to them. Finally, more of the black participants are likely to affiliate themselves with Democratic candidates than the white participants. For the black youths, over 80 percent support Democratic candidates as compared to less than 50 percent of the white youths. Similarly, over 60 percent of the black seniors support Democratic candidates as compared to slightly over 20 percent of white seniors.

74


RESULTS Overall Mean Agreement for Reform Proposals To examine the agreement of the entire sample for the various proposals, we divided the proposals into three categories (1) proposals to increase Social Security fund revenues, (2) proposals to decrease Social Security fund benefits, and (3) the proposal to establish individual investment accounts. Table 2 presents key statistics (means and standard deviations) for each of the proposals. As indicated in the Methods section, agreement was based on a 7-point Likert scale, with 1 ¼ strongly agree and 7 ¼ strongly disagree. To examine the extent of agreement for the total sample with the various proposals, we tested the mean agreement for each proposal to see if it differed from the point of indifference (i.e., 4) on the Likert scale. As indicated in the table, six of the proposals had mean agreement scores that were significantly Table 2. Mean Agreement for the Various Social Security Proposals Across All Participant Groups.

Proposals to increase Social Security fund revenues Allow Social Security surpluses to be invested in debt and equity securities Increase maximum amount of wages subject to Social Security tax Increase Social Security tax rate Tax Social Security benefits the same as private pensions Use budget surpluses from Social Security fund to repay national debt Proposals to decrease Social Security fund benefit payments Adjust CPI to obtain a more accurate measure of inflation Reduce future retirement benefits by increasing retirement age Reduce future retirement benefits by trimming monthly benefits Proposals to establish individual investment accounts Allow workers to invest in individual investment accounts

Meana

Standard Deviation

4.93

1.99

3.75

2.15

4.89 5.03 5.39

1.89 1.93 1.90

4.14 4.72

1.94 1.89

5.09

1.80

4.35

2.37

a Participants indicated the extent of their agreement with the proposals in Table 2 by responding on a 7-point Likert scale with 1 ¼ Strongly Agree and 7 ¼ Strongly Disagree. po0.01, two-tailed.


75

different from the point of indifference. Four of these proposals were designed to increase Social Security fund revenues. These include proposals to allow Social Security surpluses to be invested in debt and equity securities (mean ¼ 4.93), to increase the Social Security tax rate (mean ¼ 4.89), to tax Social Security benefits the same as private pensions (mean ¼ 5.03), and to use budget surpluses from the Social Security fund to repay the national debt (mean ¼ 5.39). Two additional proposals from the group designed to decrease Social Security fund benefit payments were also significantly different from the point of indifference. The proposals included reducing future benefits by increasing the retirement age (mean ¼ 4.72) and by trimming monthly benefits (mean ¼ 5.09). It is interesting to note that all six of these proposals have means that are greater than 4 (the point of indifference), indicating that the sample as a whole disagrees with the proposals. In fact, only one of the proposals (to increase the maximum amount of wages subject to Social Security tax) has an average disagreement score that is less than 4.0. Analysis of Research Questions 1 and 2 To examine the research questions related to differences between age groups and racial groups, we ran a MANOVA model with the participants’ agreement with the nine proposals serving as the dependent variables. We included the age group (senior or youth) and racial group (black or white) as the independent variables. Both age and race proved to be significant (Wilks l ¼ 13.88 and 3.12; p ¼ 0.000 and 0.002 for age and race, respectively). As suggested in the literature review, the various proposals may have a quite different appeal to the various age and racial groups. For this reason, in the following sections we look at agreement with the various proposals by subgroup.10 Proposals to Increase Social Security Fund Revenues Table 3 presents key statistics (means and standard deviations) for each participant group for the proposals designed to increase Social Security fund revenues. In addition to reporting the key statistics for the various groups, we also report the results of Scheffe comparisons for tests of differences in the means for the various groups.11 The results reported in Table 3 suggest that several significant differences in the agreement with the various proposals to increase Social Security fund revenues exist among the groups. Specifically, significant differences were found for three of the proposals. For the proposal to allow the government to invest Social Security surpluses in debt and equity securities and the

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Table 3. Means, Standard Deviations, and Scheffe Comparisons for Agreement with Social Security Proposals by Participant Group – Proposals to Increase Social Security Fund Revenues. Group

n

Meana

St. Dev.

Sign. Diff. (o0.01)

Allow Social Security Surpluses to be Invested in Debt and Equity Securities Black youth (BY) 26 4.19 1.74 BS White youth (WY) 39 3.56 1.76 BS, WS Black senior (BS) 24 6.67 0.92 BY, WY White senior (WS) 25 5.24 1.94 WY Increase Maximum Amount of Wages Black youth (BY) 26 White youth (WY) 39 Black senior (BS) 24 White senior (WS) 25 Increase Social Security Tax Rate Black youth (BY) 26 White youth (WY) 39 Black senior (BS) 24 White senior (WS) 25

(o0.05)

WS BS

Subject to Social Security Tax 3.46 2.00 3.51 2.09 4.21 2.59 3.68 2.01 4.88 4.77 5.50 4.12

1.40 1.61 2.17 2.03

Tax Social Security Benefits the Same as Private Pensions Black youth (BY) 26 4.15 1.62 White youth (WY) 39 4.28 1.76 Black senior (BS) 24 5.96 2.05 White senior (WS) 25 5.08 2.04 Use Budget Surpluses from Social Security Fund to Repay National Black youth (BY) 26 4.54 1.77 White youth (WY) 39 4.00 1.73 Black senior (BS) 24 6.92 0.28 White senior (WS) 25 6.08 1.73

BS BS WY

BY

Debt BS, WS BS, WS BY, WY BY, WY

a

Participants indicated the extent of their agreement with the proposals in Tables 3–5 by responding on a 7-point Likert scale with 1 ¼ Strongly Agree and 7 ¼ Strongly Disagree.

proposal to use budget surpluses from Social Security to repay the national debt, the Scheffe tests indicate significant differences between the youth groups and the senior groups. For the proposal to allow the government to invest Social Security surpluses in debt and equity securities, both the black youth and the white youth groups indicated either indifference or slight agreement with this proposal (means ¼ 4.19 and 3.56, respectively). In contrast, both the black and white senior groups expressed more disagreement


77

with this proposal (means ¼ 6.67 and 5.24). As indicated in Table 3, the difference between the level of agreement of the black seniors and all of the other groups proved to be significant. In addition, the level of agreement by the white seniors was significantly different from the white youths but not from the black youths. However, there was no significant difference between the two youth groups. Similarly, agreement with the proposal to use budget surpluses from Social Security to repay the national debt also differed based on age rather than racial background. Once again, the two youth groups were near the point of indifference on the agreement scale (means ¼ 4.54 and 4.00 for black and white youth, respectively). In contrast, both the senior groups felt a higher level of disagreement with this proposal (means ¼ 6.92 and 6.08 for the black and white seniors, respectively). Finally, for the proposal to tax Social Security benefits the same as private pensions, there were significant differences between the two youth groups and the black seniors. Once again, the two youth groups expressed mean agreement near the point of indifference (means ¼ 4.15 and 4.28 for black and white youths, respectively) while the black seniors expressed a higher degree of disagreement with the proposal (mean ¼ 5.96). Proposals to Decrease Social Security Fund Benefit Payments Table 4 contains the extent of agreement for each of the groups with the proposals to decrease Social Security benefit payments. The greatest disagreement occurred for the proposal to reduce future benefits by trimming monthly benefits. The black seniors strongly disagreed with this proposal (mean ¼ 6.46) while the white seniors also disagreed with the proposal (mean ¼ 5.20). In contrast, the two youth groups were at or near the point of indifference (mean ¼ 4.81 and 4.00, respectively, for black and white youth). The black seniors’ agreement with the proposal was significantly different from both the youth groups (p ¼ 0.01) while the white seniors were significantly different from the white youths (p ¼ 0.05). In addition to the disagreement between the groups on the trimming of monthly benefits, there was also some disagreement between the black seniors and white youths on the proposal to reduce future benefits by increasing the retirement age. The black seniors more strongly disagreed with this proposal than the white youths (means ¼ 5.83 and 4.31, respectively, p ¼ 0.05). Proposals to Establish Individual Investment Accounts Perhaps the most controversial reform for Social Security that has been proposed has been the implementation of individual investment accounts. It

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Table 4. Means, Standard Deviations, and Scheffe Comparisons for Agreement with Social Security Proposals by Participant Group – Proposals to Decrease Social Security Fund Benefit Payments. Group

n

Mean

St. Dev.

Sign. Diff (o0.01)

(o0.05)

Adjust CPI to Obtain a More Accurate Measure of Inflation Black youth (BY) 26 3.73 1.48 White youth (WY) 39 3.74 1.46 Black senior (BS) 24 4.75 2.59 White senior (WS) 25 4.36 2.02 Reduce Future Retirement Benefits by Increasing Retirement Age Black youth (BY) 26 4.46 1.77 White youth (WY) 39 4.31 1.69 Black senior (BS) 24 5.83 1.93 White senior (WS) 25 4.48 2.08 Reduce Future Retirement Benefits by Trimming Monthly Benefits Black youth (BY) 26 4.81 1.47 White youth (WY) 39 4.00 1.54 Black senior (BS) 24 6.46 1.28 White senior (WS) 25 5.20 1.94

BS WY

BS BS BY, WY

WS WY

is not surprising, then, that we find the most disagreement among the various groups about this proposal. As reported in Table 5, the two youth groups tend to demonstrate a fair amount of agreement with this proposal (mean ¼ 3.04 and 2.77, respectively, for the black and white youth groups). In contrast, the white senior group showed slight disagreement with a mean of 4.88 while the black senior group showed strong disagreement with the proposal (mean ¼ 6.46). The level of agreement by both the senior groups was significantly different from the two youth groups (po0.01). Further, the white senior group was also significantly different from the black senior group (po0.05). As discussed earlier and indicated in Table 1, we gathered data from our participants as to their political orientation. Therefore, we compared the participants’ agreement with individual investment accounts based on political orientation. The results indicate that those participants who identified themselves as supporting Republican candidates did not have a significantly greater acceptance of this proposal than those participants who identified themselves as supporting Democratic candidates (t ¼ 1.61, p ¼ 0.11, twotailed test). A similar comparison of the participants’ agreement with


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Table 5. Means, Standard Deviations, and Scheffe Comparisons for Agreement with Social Security Proposals by Participant Group – Proposals to Establish Individual Investment Accounts. Group

n

Mean

St. Dev.

Sign. Diff. (o 0.01)

Allow Workers to Invest in Individual Black youth (BY) 26 White youth (WY) 39 Black senior (BS) 24 White senior (WS) 25

Investment Accounts 3.04 1.56 2.77 1.97 6.46 1.14 4.88 2.45

BS, BS, BY, BY,

WS WS WY WY

(o0.05)

WS BS

individual investment accounts based on race indicate that the white groups had a greater acceptance of this proposal than the black groups (t ¼ 2.49, p ¼ 0.014, two-tailed test). Further, a comparison of the participants’ agreement with individual investment accounts based on generational differences indicates that the youth groups’ acceptance of this proposal was significantly greater than that of the senior citizen groups (t ¼ 7.63, p ¼ 0.000, two-tailed test). Given the significance of the race and age variables, and in order to understand the relative contributions of age and race to differences in the acceptance of the individual investment account proposal, we performed an ANOVA using agreement with individual investment accounts as the dependent variable and race (white or black) and age (youth or senior) as the independent variables. The results of this analysis indicate that age (F ¼ 60.35, p ¼ 0.000) had substantially more explanatory power than race (F ¼ 6.74, p ¼ 0.011). Taken together, the results indicate that generational differences are the more important factor in determining agreement with the individual investment account proposal, not political party or race. Implications of this finding are discussed in the conclusion section. Most and Least Preferred Proposals Given the divergent views between generations as to reforming the Social Security system, it is important to understand if there is some common ground in terms of acceptance of certain proposals. By examining the mean agreement with the nine proposals, the proposal that is most preferred by both the black and white senior citizen groups is increasing the maximum amount of wages subject to the Social Security tax. This proposal is also the second most preferred proposal for both the black and white youth groups.

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As discussed earlier and as indicated by Table 3, there were no differences between the four groups in terms of their agreement with this proposal. Further, Table 2 indicates that the overall mean agreement with this proposal is 3.75. Though this mean agreement rating is not statistically different from the point of indifference (4.00), it is the only proposal with a mean rating in the agreement range. Further, this proposal is only one of the three proposals that are not significantly greater than the point of indifference (indicating disagreement with the proposal). This analysis suggests that there is a fairly strong consensus among the four groups as to their acceptance of this proposal. A further review of means reveals that the proposal to adjust the consumer price index (CPI) to obtain a more accurate measure of inflation is rated second overall by the black seniors and third overall by the white seniors. This proposal is also the third most preferred proposal for the black youth group and fourth most preferred for the white youth group. As discussed earlier and as indicated by Table 4, there were no differences between the four groups in terms of their agreement with this proposal. Further, Table 2 indicates that the overall mean agreement rating of this proposal is 4.14 and that this proposal is also one of the three proposals that are not significantly greater than the point of indifference (indicating disagreement with the proposal). In summary, this analysis suggests that there is consensus among the four groups as to their relative acceptance of this proposal. While there is general consensus for increasing the Social Security wage base and adjusting the CPI, the groups disagree on some of the other proposals. For example, as indicated by the means, the proposal most preferred by both the black and white youth groups is to allow workers to invest in individual investment accounts. As indicated by Table 5, the mean agreement with the proposal for individual investment accounts is 3.04 for the black youth group and 2.77 for the white youth group. These mean agreements are significantly less than the point of indifference for both the black youth group (t ¼ 3.14, p ¼ 0.004, two-tailed test) and the white youth group (t ¼ 3.91, p ¼ 0.000, two-tailed test), indicating significant agreement with this proposal. Further, the mean agreement with this proposal for the youth groups is significantly greater (po0.001) than their agreement with all of the remaining proposals, with the exception of the proposal to raise the maximum amount of wages subject to the Social Security tax where the agreement with individual investment accounts was marginally greater (po0.10). In contrast with the youth groups’ strong agreement with the proposal to establish individual investment accounts, both senior groups disagree with this reform proposal. As indicated earlier by Table 5, the black seniors’


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mean agreement of 6.46 and the white seniors’ mean agreement of 4.88 are both significantly less than the agreement ratings for the black and white youth groups. Further, these mean agreement ratings are significantly greater than the point of indifference for both the black senior group (t ¼ 10.55, p ¼ 0.000, two-tailed test) and the white senior group (t ¼ 1.79, p ¼ 0.086, two-tailed test), indicating strong disagreement with this proposal. Finally, the proposal to increase the Social Security tax rate is ranked third in terms of mean agreement for the black seniors and is ranked second in terms of mean agreement for the white seniors. However, this proposal is one of the least preferred proposals by the youth groups. In fact, the mean agreement rating for the black youths is the lowest of the nine proposals and is the third lowest mean agreement rating for the white youths. Although Table 3 indicates that there are no significant differences among the four groups in terms of their mean agreement with this proposal, that result is partially driven by the low mean agreement ratings for each of the nine proposals by the senior groups. In summary, the analysis presented in this section suggests that there is some consensus between the youth and senior groups in terms of their relative agreement with two of the Social Security reform proposals. However, there are sharply divergent views on some of the other reform proposals. Implications of these convergent and divergent views on the various reform proposals are examined in the conclusion section. Supplemental Analyses In addition to gathering data from the participants as to their agreement with proposed Social Security reforms, we also gathered data on some opinion questions relevant to Social Security. One question asked to the participants, ‘‘In general, how concerned are you that Social Security benefits will be substantially reduced during your retirement?’’ Endpoints were labeled (1) ‘‘Not Concerned’’ and (7) ‘‘Very Concerned.’’ The black seniors were very concerned that their benefits would be reduced (mean ¼ 6.33). The white seniors also exhibited some concern (mean ¼ 5.16), as did the two youth groups (mean ¼ 4.85 for both the black youth and white youth). The black seniors’ level of concern was significantly higher than both of the youth groups (p ¼ 0.027 versus the white youth group and p ¼ 0.051 versus the black youth group). There were no other significant differences between the four groups. We also conducted analyses to examine whether the participants’ concern about a potential reduction in Social Security benefits was correlated with

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their agreement with the nine reform proposals. Pearson Correlation coefficients were calculated between the participants’ agreement with each of the nine proposals and their level of concern about a reduction in their Social Security benefits. The participants’ concern about a benefit reduction was positively correlated with four of the nine reform proposals. These four reform proposals included the proposal to allow Social Security surpluses to be invested in debt and equity securities (Pearson Correlation ¼ 0.331, p ¼ 0.000); the proposal to use budget surpluses from the Social Security fund to repay the national debt (Pearson Correlation ¼ 0.323, p ¼ 0.000); the proposal to allow workers to invest in individual investment accounts (Pearson Correlation ¼ 0.248, p ¼ 0.008); and the proposal to reduce future retirement benefits by increasing the retirement age (Pearson Correlation ¼ 0.33, p ¼ 0.000). The significant positive correlations indicate that as the participants’ concern about a reduction in Social Security benefits increases, their disagreement with the reform proposal also increases. These significant positive correlations, combined with our finding that the black senior citizens exhibited a higher level of concern about benefit reductions than the two youth groups, offers some potential insights to tax policy makers. Of particular interest are the significant correlations between the level of concern about a benefit reduction and the proposal to establish individual investment accounts and the proposal to invest the Social Security surplus in debt and equity securities. These significant correlations may help to explain why the black senior citizens are so strongly opposed to reform proposals that change how Social Security funds are invested. They fear that their own Social Security benefits will be reduced if these investment alternatives are allowed. Thus, to enhance the black senior citizens’ acceptance of individual investment accounts, tax policy makers will need to mitigate their concern that their future benefits will not be safe if these investment proposals are adopted. A second question asked to the participants, ‘‘How important is a candidate’s position on Social Security to your vote?’’ Endpoints were labeled (1) ‘‘Not at all Important’’ and (7) ‘‘Extremely Important.’’ The black seniors indicated that a candidate’s position was very important to their vote (mean ¼ 6.83). The white seniors also indicated that a candidate’s position was important to their vote (mean ¼ 5.56), while the two youth groups indicated a lesser importance (mean ¼ 4.65 for the black youth group and mean ¼ 4.51 for the white youth). Scheffe comparisons indicate that a candidate’s position on Social Security is significantly more important to a voting decision for the black seniors than for both the youth groups (p ¼ 0.000 versus both the white youth group and black youth group) and


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also more important than for the white senior group (p ¼ 0.016). Further, a candidate’s position on Social Security is significantly more important to a voting decision for the white seniors than for the white youth group (p ¼ 0.033). There was no significant difference between the white senior group and the black youth group (p ¼ 0.136). Pearson Correlation coefficients were also calculated between the participants’ assessment of the importance of a candidate’s position on Social Security to their vote and their agreement with each of the nine reform proposals. The importance of a candidate’s position on Social Security was significantly (po0.01) positively correlated with seven of the nine proposals. Only the proposal to increase the Social Security tax rate and the proposal to increase the maximum amount of wages subject to Social Security tax were not significantly correlated with the participants’ assessed importance of a candidate’s position. These significant positive correlations indicate that as the participants’ assessed importance of a candidate’s position on Social Security to their vote increases, their disagreement with the reform proposal also increases. These significant correlations help to explain the difficulty tax policy makers have with Social Security reform, particularly given our additional findings that Social Security is more likely to affect seniors’ voting patterns than younger taxpayers’ voting patterns and that in general the seniors disagreed with most of the reform proposals. The fact that senior citizens represent the age demographic with the highest voting percentage (U.S. Assistance Election Commission, 2000) illustrates why Social Security is often times referred to by politicians as the ‘‘third rail’’ of American politics (try to change it and you will be voted out of Washington, DC). Implications for Social Security reform due to seniors’ voting patterns are also discussed in the conclusions section.

CONCLUSIONS The purpose of this research study was to examine how groups of Americans that differ in age and race view the acceptability of some of the current proposals to modify the Social Security system. We accomplished this purpose by gathering survey data from groups of senior citizens (black and white) and young adults (black and white). Although we find in general that all four groups tended to be indifferent at best to the reform proposals, and in fact disagreed with many of the proposals, we did find some cases where there was agreement among the groups. However, there were also strongly divergent views on some of the proposals. Overall, our results indicate that

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most of the differences among groups were generational differences and not racial differences. As indicated in the Methods section, we gathered the data by presenting specific groups with our survey instrument rather than using other survey techniques, like a national survey. Our survey method helped to ensure that we were reducing the impact of sampling bias that might be caused by nonresponse bias. However, the findings need to be considered in light of the limitations of the methods that we used to gather the data. By its very intent, our survey method was not designed to gather samples that represented the entire population. All the participants were recruited from the East coast; thus, we are unable to address the extent that agreement with the proposals may vary by geographical region. Future research could employ national surveys to examine how preferences for various proposals may vary across geographic regions. Further, the participants were generally more highly educated than the population. While this ensures a greater likelihood that the participants were able to analyze and understand the proposals, we are unable to generalize the results to a population with a greater diversity of educational backgrounds. Future research should examine whether agreement with the Social Security reform proposals varies across educational backgrounds. We also recruited participants from just two racial groups. Other racial groups may have different opinions about proposals to reform Social Security. Thus, further research should examine the acceptance by other minority groups (e.g., Hispanics and Asians) of the proposals to reform the Social Security system. In addition to limitations based on our samples, our findings are also limited by the fact that we gathered our data during 2002 and 2003. Since that time, Social Security has received a great deal of attention in the media and from interested parties and organizations. This attention may have altered the opinions of some taxpayers about the proposals.12 Further, the present study is also limited by the choice of proposals that were included as part of our survey instrument. Recently, several new proposals have been offered to address the Social Security issue.13 Because we did not examine these recent reform proposals as part of our study, we are unable to comment on how these proposals are viewed across generation and race. Finally, we pre-tested the explanations of the proposals that we provided participants to ensure that they were clear and understandable. However, we did not examine potential effects of the framing of the questions by incorporating alternate wording of the explanations or the ordering of the information provided in an explanation. For example, the proposal that explains the possibility of allowing Social Security surpluses to be invested in debt


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and equity securities describes the potential benefit of higher returns and then presents the potential drawback of increased risk. We did not test whether an explanation that provides the potential drawback first and then the potential benefit would result in the same level of agreement with the proposal. Future research could draw on the substantial literature on framing effects in accounting (e.g., Chang, Yen, & Duh, 2002) and tax (e.g., Traub, 1999; Schepanski & Kelsey, 1990; Christensen & Hite, 1997) to examine how the framing of the descriptions for Social Security reform may affect agreement with the proposals. Despite these limitations, the results of the present study provide some important insights. There was a fairly strong consensus between the seniors and young adults on the proposal to increase the maximum amount of wages subject to Social Security tax. Because it is unlikely that the wages of any of the survey participants currently exceed the maximum amount of wages subject to tax ($90,000 in 2005), the fact that there was consensus as to agreement with the proposal is consistent with prior tax research that suggests fairness perceptions and agreement with tax law changes are strongly influenced by self interest (e.g. Maroney, Rupert, & Wartick, 2002; Hite & Roberts, 1991). Though it is unlikely that workers with earnings at or above the maximum would have similar views on this proposal as those of our participants, given the fairly small number of workers (approximately 6%) who currently have earnings at or above the maximum, it is likely that a proposal to increase the maximum wage base for Social Security may eventually become part of a Social Security reform package.14 A second proposal on which there was consensus among the groups was the proposal to adjust the CPI to obtain a more accurate measure of inflation. Robert M. Ball and Bethell (1998) estimate that the CPI that is currently used to index benefits, once a worker retires, overstates the actual rate of inflation for the elderly by 0.20 percentage points. In fact, former Federal Reserve Board Chairman Alan Greenspan shares this belief that the CPI overstates inflation and therefore overcompensates Social Security beneficiaries (Federal Reserve Board, 2004). The participants in our study appeared to have a consensus as to their acceptance of this proposal. Though the participants were essentially indifferent to the proposal, this was unlike many of the other proposals where there was significant disagreement. It is interesting to note that the participants did not disagree with this proposal even though they were told in the survey materials that if the adjustments to the CPI were made, ‘‘the growth in future Social Security benefits would decline.’’ Thus, unlike the proposal to raise the maximum amount of wages subject to Social Security tax, self interest does not appear

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to be guiding their judgment. Ball and Bethell (1998) estimate that this change in itself would reduce the projected 75-year Social Security deficit by approximately 19%. The results of our study suggest that this reform proposal may be acceptable to groups of Americans with very divergent interests (senior citizens and young adults). Although there appears to be relative acceptance of a reduction in Social Security benefits through adjustments to the CPI, there tended to be disagreement, particularly by the senior citizens, with the remaining proposals that would reduce benefits. However, even though benefit reductions may be an unpopular alternative to reforming the Social Security system, a number of economists believe that any Social Security reform package must include some benefit reductions. For example, in his recent testimony to Congress, former Federal Reserve Board Chairman Alan Greenspan clearly indicated his preference for reforms that reduce expenditures, rather than increase revenues (Federal Reserve Board, 2004). Greenspan suggested adjustments to the CPI as a way of reducing outlays and also suggested adjusting the age for eligibility for Social Security and Medicare benefits due to changes in life expectancy (Federal Reserve Board, 2004). Given our finding of the disagreement with proposals to reduce benefits by increasing the retirement age, policy makers who intend to propose this type of reform will need to carefully consider the ‘‘framing’’ of the proposal. The most relevant form of framing may be ‘‘attribute framing.’’ Attribute framing refers to a situation whereby the same objective information is evaluated differently depending on whether it is presented in a positive or negative light (Levin, Gaeth, & Schneider, 1998; Levin, Gaeth, Schneider, & Lauriola, 2002). Therefore, rather than explaining the potential change as an increase in retirement age that reduces benefits (negative light), it can be explained as indexing the retirement age for increases in life expectancy (positive way). Also, because retirees’ life expectancies will have increased, total benefits paid (discounted present-value basis) should still be equivalent to the amounts received by earlier retirees. Future accounting researchers should examine whether this proposal, and other reform proposals to Medicare and Social Security, can be framed in a positive light, thereby making them more attractive. Such framing may be able to increase the acceptance of necessary, yet unpopular changes. We also examined our participants’ acceptance of a proposal to create individual investment accounts. President Bush recently called for the establishment of individual investment accounts in his 2005 State of the Union speech. The initial agreement or disagreement within Congress has closely followed party lines (Bernstein, 2005). Economists also sharply disagree as to the relative advantages and disadvantages of this proposal, with


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some agreeing with (e.g., Hubbard, 2005) and some disagreeing with (e.g., Diamond & Orszag, 2004) the proposal. The purpose of this study was not to enter into the debate as to the conceptual advantages and disadvantages of private accounts, but to understand whether acceptance of this proposal differs by generation and race. The results of our study suggest that generational differences are the most important factor in determining agreement with this proposal and not race or political orientation. Thus, it appears that this reform proposal may have the potential to create significant conflict between generations. Further, because many of the other ideas that have been proposed to reform the Social Security system tend to disadvantage younger adults to a much greater extent than senior citizens, the potential for generational conflict over this issue may be further exacerbated. An encouraging finding from our study relates to our results regarding racial differences between the participants’ agreement and disagreement with the various reform proposals. Though the black seniors tended to exhibit stronger disagreement with the various reform proposals than the white seniors, as evidenced by a significant or marginally significant difference on their agreement ratings for five of the nine proposals,15 there were no such differences between the black and white youth groups. In fact, the agreement or disagreement with the various proposals by the black and white youth groups was remarkably consistent. Our finding of a strong disagreement with many of the reform proposals by the black seniors is consistent with research in sociology which indicates a general mistrust of government held by minorities (Crocker, Luhtanen, Broadnax, & Blaine, 1999; Howell & Fagan, 1988). This finding suggests that almost any Social Security reform proposal may be difficult to sell to this demographic group. Further, our finding of strongly consistent views between the black and white youth groups suggests that the gap between races as to their general view of government may be closing. Despite this positive development, our finding that the views on many of the reform proposals differ across generations still makes Social Security reform very difficult. While the present study focuses on proposals to reform the Social Security system and these proposals are also garnering much of the current attention of policy makers, funding problems for Medicare also loom large. As the Social Security and Medicare Board of Trustees indicated in their 2005 annual report, it would take an immediate increase in program revenues of 107% or an immediate reduction in program outlays of 48% to ensure the system’s solvency for the next 75 years. Given the substantial challenges facing both the Social Security and Medicare systems, what can be done to ensure that we do not face significant conflict between generations as we

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seek to reform both the Social Security and Medicare systems? In other words, how can the burden of reforming these systems be equitably shared between generations? A recently developed method, referred to as ‘‘generational accounting’’ (Auerbach, Gokhale, & Kotlikoff, 1991) may be useful in ensuring that reforms to these systems are equitable across generations. Generational accounting is intended to measure how the government’s fiscal burden is shared between generations. Unlike the Federal Government’s current financial reporting system that focuses on the annual federal deficit or surplus to guide fiscal policy, generational accounting also incorporates government’s implicit liabilities through programs such as Social Security and Medicare (U.S. Congressional Budget Office, 1995; Kotlikoff, 1992; Auerbach, Kotlikoff, & Leibfritz, 1999; Kotlikoff & Burns, 2004). The method can then be used to address questions such as (1) Which generation will pay for government policies with their net taxes? or (2) If a given policy applies to all current generations for the rest of their lives, what would that imply for the net taxes of current and future generations (U.S. Congressional Budget Office, 1995)? Though the Congressional Budget Office (CBO) recognized certain limitations with generational accounting (for example, the difficulty of choosing an appropriate discount rate or predicting the future population growth rate), they concluded that generational accounting is a tool that can be used to inform policy analysis (CBO, 1995). However, the fact that generational accounting has not received widespread use in government reporting is not surprising given the CBO’s (1995) finding, through the use of generational accounting, that the lifetime net tax rate of future generations would have to be about twice the rate of current newborns given existing government programs. Most recently, Gokhale and Kotlikoff (2001) arrived at a very similar calculation. If generational accounting was used to examine the potential effect of reforms to the Social Security and Medicare systems on people of different ages, it may inform policy makers about the fairness of the reform proposals to the various generations. However, given our finding that Social Security issues are more likely to affect the votes of senior citizens than younger taxpayers, and the fact that senior citizens are about twice as likely to vote as younger (aged 18–24) taxpayers (U.S. Assistance Election Commission, 2000), politicians may place more emphasis on the views of senior citizens. This emphasis would be most unfortunate because given the changing age demographic in the United States discussed earlier, it may not be possible to continue fiscal policies that shift the costs of Social Security and Medicare reform onto the younger generation and their descendants without significantly increasing the tax burden of these generations (Kotlikoff & Burns, 2004).


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A final policy recommendation relates to the accounting system currently used in the Trustees’ annual report for the Social Security and Medicare systems. In effect, the Trustees’ annual report uses a cash-basis form of accounting and primarily focuses on the system’s annual cash receipts and cash payments. Although the Trustees’ report does project cash flow figures for the next 75 years, results for the current year focus on the change in net assets on a cash-basis. Jackson (2004) argues that the Social Security system should also be required to include a GAAP-style accrual accounting statement as part of their annual report. Jackson (2004) converted the Trustees’ December 31, 2002 annual report for the Social Security fund into an accrual basis. He found that instead of the $165.4 billion increase in net assets reported by the Trustees on a cash-basis, the Social Security trust fund would have reported a loss of $467.5 billion on a GAAP-style accrual basis and would have also reported an unfunded accrued liability of approximately $12.6 trillion (Jackson, 2004).16 Jackson (2004) suggests that accrual accounting, used in conjunction with the current system, would create a ‘‘clearer picture’’ of the Social Security fund’s finances. Further, he suggests ‘‘accrual accounting would also create political incentives for political leaders to address Social Security’s difficulties in a timely manner, and enhance the quality of public debate over the relative merits of competing reform proposals’’ (Jackson, 2004, p. 59). We concur with this recommendation and also believe the Medicare system could benefit from a similar GAAP-style reporting requirement. Doing so should help create a sense of urgency for Medicare and Social Security reform in both political parties, which tends to be mitigated by the current focus on annual cash flows.

NOTES 1. The use of a 75-year forecast period significantly understates the magnitude of the funding problem since there is also a substantial imbalance between revenues and expenses after the 75-year period (Jackson, 2004). 2. Although there are Social Security and Medicare Trust Funds, as discussed later in the paper, the assets in these funds are substantially less than the total accrued liabilities. Further, there is also disagreement as to the significance of the assets held in these funds. These assets are ‘‘special purpose Treasury securities,’’ and in essence represent a government IOU to itself. Diamond and Orszag (2004) argue that these securities are assets because they can be redeemed to pay benefits and because the accumulation of the fund has allowed the government to reduce their debt. However, Diamond and Orszag (2004) acknowledge that when these securities are used to pay benefits, this will require additional government borrowings or additional tax revenues. As indicated earlier by Schieber and Shoven (1999), ‘‘these

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are the same choices that the government would face if the system didn’t have the bonds and simply asked for a bailout. The point is that the bonds have helped save the system only if they have resulted in greater investment in the economy and hence higher productivity and higher wages for those who are either going to have to pay the taxes or buy the bonds y . All in all, the trust fund balances do not offer much reason to be sanguine about the burden we are passing on to future generations’’ (Schieber & Shoven, 1999, p. 207). 3. Currently revenues credited to the Social Security Fund include the employees’ and employers’ share of the Social Security payroll tax (combined rate of 12.4%), interest credited on the Social Security Trust Fund balance and the income tax revenues received due to the partial taxation of Social Security benefits. 4. Throughout the discussion of our survey, the term ‘‘black’’ is used to describe any participant who designated his or her ethnic background as ‘‘African-American/ other black.’’ 5. The classes used for the survey consisted of 60 students. In addition to the 39 students who were included in the white youth group and the five who were included in the black youth group, an additional 16 were excluded from the sample because they indicated their ethnic background was other than non-Hispanic/white or African-American/other black. 6. We were advised that the participants would feel more at ease if the director of the senior center, rather than one of the researchers, administered the instrument. The director of the senior center indicated to us that the participants appeared to understand the survey instrument and did not have any questions about the survey instrument. 7. We created four different versions of the instrument with the alternatives randomly ordered. There were no significant differences in responses among the different orderings of the alternatives. 8. We tried to create the descriptions so that they would be clear and neutral as well as provide the necessary information without being too lengthy. To determine if we had achieved these goals, we pre-tested the instrument by giving it to colleagues and friends who represented various age and racial groups. While the feedback from the participants in the pre-test generally indicated that the descriptions were clear and understandable, we made several small wording changes to the descriptions based on their comments. 9. For a review of the major proposals that have been offered to address the solvency of the Social Security system, see Steuerle and Bakija (1994), Ball and Bethell (1998), and Aaron and Reischauer (2001). 10. Because we are interested in differences among all four groups, we report the results of Scheffe comparisons from a MANOVA model that used the four sub-groups as the independent variable. However, we did run separate analyses for age and racial group. For the analysis with age group as the independent variable, we found significant differences between the seniors and youths on all of the proposals except the proposal to increase the maximum amount of wages subject to the Social Security tax and the proposal to increase the Social Security tax rate. For the analysis with racial group as the independent variable, we found significant differences between blacks and whites on all proposals except the proposal to adjust the CPI to obtain a more accurate measure of inflation, the proposal to increase the Social Security tax rate, and the proposal to tax Social Security benefits, the same as private pensions.


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11. The Scheffe comparisons were conducted through a MANOVA model that used the four sub-groups as the independent variable and the nine reform proposals as the dependent variables. The overall MANOVA results indicate a highly significant effect for the independent variable (Wilks l ¼ 4.77, p ¼ 0.000). 12. Although we acknowledge the time period over which the data were gathered as a possible limitation, the data collection period might also be considered a strength of our study. Currently, the issue of Social Security reform has become highly politicized. Thus, there are numerous messages being issued by both major political parties and various special interest groups regarding Social Security reform. Because the participants in our study were not exposed to these messages, it is more likely that their opinions were based on their acceptance of the various reform proposals, rather than their support of a political party or a special interest group. Further, because many of the messages currently being provided are intended to persuade rather than inform, our data may provide an unbiased measure of the participants’ agreement with the various reform proposals. 13. One recent suggestion is to expand the Social Security system to include state and local government workers hired after 2008 (Diamond & Orszag, 2004). Currently, ‘‘about 4 million state and local government workers are not covered by Social Security’’ (Diamond & Orszag, 2004, p. 90). Diamond and Orszag estimate that the extension of Social Security coverage to new state and local government workers would reduce the 75-year actuarial deficit by 10 percent. A second recent reform proposal is a proposed change to the method by which retirees’ future Social Security benefits are indexed. Currently, during retirees’ working years, their future benefits are indexed based on the change in average wages in the United States. Once a worker retires, benefits are indexed based on the change in prices (CPI). Because the increase in wages has outpaced the increase in prices over the long term by approximately one percent, some economists (e.g., Hubbard, 2005) suggest that benefits should be indexed based on the changes in the CPI during a retiree’s working years. President Bush also mentioned this as a possible reform to Social Security during his 2005 State of the Union Message (Bush, 2005). 14. Very few economists, if any, propose a situation similar to the Medicare tax whereby all wages would be subject to the Social Security tax. For example, some economists have proposed revising the method through which the maximum wage base is indexed. Currently, the maximum wage base is indexed based on the percentage increase in average wages in the United States (workers’ benefits are indexed on this same basis during their working years). Diamond and Orszag (2004) propose increasing the index to add on an additional 0.5 percentage point each year from 2005 to 2063. Though benefits for these workers would also increase under this plan, they estimate that this change would reduce the Social Security deficit by one-eighth (Diamond & Orszag, 2004, p. 86). 15. In addition to the two significant differences that were discussed in the results section (allowing workers to invest in individual accounts and allowing Social Security surpluses to be invested in debt and equity securities), the two senior groups also were marginally different in their agreement with three additional proposals. These include reducing future retirement benefits by trimming monthly benefits (p ¼ 0.055), reducing future retirement benefits by increasing the retirement age (p ¼ 0.09), and increasing the Social Security tax rate (p ¼ 0.07). Also, the black

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senior group and the black youth group were marginally significantly different in their agreement with the proposal to reduce future retirement benefits by increasing the retirement age (p ¼ 0.083). 16. Total accrued liabilities are approximately $14 trillion at the end of 2002. The balance in the Social Security trust fund is approximately $1.4 trillion, thus liabilities are approximately 10 times greater than the system’s current reserves (Jackson, 2004).

ACKNOWLEDGMENTS The authors wish to thank the editor, two anonymous reviewers, as well as Jean Bedard, Diana Falsetta, Carol Fischer, Stacy Wade, and Marty Wartick for helpful comments on previous drafts of the paper.

REFERENCES Aaron, H., & Reischauer, R. (2001). Countdown to reform: The great social security debate. New York: The Century Foundation Press. Auerbach, A., Gokhale, J., & Kotlikoff, L. (1991). Generational accounts: A meaningful alternative to deficit accounting. In: D. Bradford (Ed.), Tax policy and the economy (Vol. 5, pp. 55–110). Cambridge, MA: MIT Press. Auerbach, A., Kotlikoff, L., & Leibfritz, W. (1999). Generational accounting around the world. Chicago, IL: The University of Chicago Press. Baker, D., & Weisbrot, M. (1999). Social security: The phony crisis. Chicago, IL: The University of Chicago Press. Ball, R., & Bethell, T. (1998). Straight talk about social security: An analysis of the issues in the current debate. A Century Foundation/Twentieth Century Fund Report. New York: The Century Foundation Press. Beach, W., & Davis, G. (1998). Social security’s rate of return. Heritage Center for Data Analysis, Report no. 01–98 (January). Bernstein, A. (2005). Social security: Are private accounts a good idea? Business Week, 24(January), 64–70. Brunner, E., & Balsdon, E. (2004). Intergenerational conflict and the political economy of school spending. Journal of Urban Economics, 56, 369–388. Bush, G. (2005). State of the union message. http://www.whitehouse.gov/news/releases/2005/02/ 20050202-11.html. Chang, C., Yen, S., & Duh, R. (2002). An empirical examination of competing theories to explain the framing effect in accounting-related decisions. Behavioral Research in Accounting, 14, 35–64. Christensen, A., & Hite, P. (1997). A study of the effect of taxpayer business risk perceptions on ambiguous compliance decisions. The Journal of the American Taxation Association, 19, 1–18. Concord Coalition. (2005). Statement of Robert L. Bixby. The Future of Social Security. Before the Senate Special Committee on Aging (February 3, 2005).


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Crocker, J., Luhtanen, R., Broadnax, S., & Blaine, B. (1999). Belief in U.S. government conspiracies against blacks among black and white college students: Powerlessness or system blame? Personality and Social Psychology Bulletin, 25, 941–953. Diamond, P., & Orszag, P. (2004). Saving social security. Washington, DC: Brookings Institution Press. Federal Reserve Board. (2004). Testimony of Chairman Alan Greenspan. Economic Outlook and Current Fiscal Issues. Before the Committee on the Budget, U.S. House of Representatives (February 25). General Accounting Office. (2003). Social security and minorities: Earnings, disability incidence, and mortality are key factors that influence taxes paid and benefits received. (GAO-03-387, April). Gokhale, J., & Kotlikoff, L. (2001). Is war between the generations inevitable? National Center for Policy Analysis, Policy Report No. 246 (November). Gravelle, J. (2002). Stormy weather: The forecast for future tax policy. Tax notes 30th anniversary (pp. 59–63). Falls Church, VA: Tax Analysts. Hendley, A., & Bilimoria, N. (1999). Minorities and social security: An analysis of racial and ethnic differences in the current program. Social Security Bulletin, 62, 59–64. Hite, P., & Roberts, M. (1991). An experimental investigation of taxpayer judgments on rate structure in the individual income tax system. Journal of the American Taxation Association, 13, 47–63. Howell, S., & Fagan, D. (1988). Race and trust in government: Testing the political reality model. Public Opinion Quarterly, 52, 343–350. Hubbard, G. (2005). Social security: Pick the best part of every plan. Business Week, (February 14), 22. Jackson, H. (2004). Accounting for social security and its reform. Harvard Journal on Legislation, 41, 59–159. Kenmitz, A. (2000). Social security, public education, and growth in a representative democracy. Journal of Population Economics, 13, 443–462. Kijakazi, K. (1998). African Americans, Hispanic Americans, and social security: The shortcomings of the heritage foundation reports. Center on Budget and Policy Priorities, (October 8). Kotlikoff, L. (1992). Generational accounting. New York, NY: The Free Press. Kotlikoff, L., & Burns, S. (2004). The coming generational storm. Cambridge, MA: MIT Press. Ladd, H., & Murray, S. (2001). Intergenerational conflict reconsidered: County demographic structure and the demand for public education. Economics of Education Review, 20, 343–357. Levin, I., Gaeth, G., & Schneider, J. (1998). All frames are not created equal: A typology and critical analysis of framing effects. Organizational Behavior and Human Decision Processes, 76, 149–188. Levin, I., Gaeth, G., Schneider, J., & Lauriola, M. (2002). A new look at framing effects: Distribution of effect sizes, individual differences and independence of types effects. Organizational Behavior and Human Decision Processes, 88, 411–429. Maroney, J., Rupert, T., & Wartick, M. (2002). The perceived fairness of taxing social security benefits: The effects of explanations based on different dimensions of tax equity. The Journal of the American Taxation Association, 24, 79–92. Pollack, S. (2002). Is there progress in tax policy? Tax notes 30th anniversary (pp. 69–80). Falls Church, VA: Tax Analysts.

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Porter, K., Larin, K., & Primus, W. (1999). Social security and poverty among the elderly: A national and state perspective. Center on Budget and Policy Priorities (April, 1999). Rockeymoore, M. (2001). Social security reform and African-Americans: Debunking the myths. National Urban League, Policy Brief No. 2 (August). Schepanski, A., & Kelsey, D. (1990). Testing for framing effects in taxpayer compliance decisions. The Journal of the American Taxation Association, 12, 60–78. Schieber, S., & Shoven, J. (1999). The real deal. New Haven, CT: Yale University Press. Smith, R., & Seltzer, R. (2000). Contemporary controversies and the American racial divide. Lanham, MD: Rowman & Littlefield Publishers, Inc. Social Security Administration. (2004). African-Americans and social security. http://www.ssa. gov/pressoffice/factsheets/africanamer-alt.htm. Social Security and Medicare Board of Trustees. (2005). Status of the social security and medicare programs. http://www.ssa.gov/OACT/TR/TR05/index.html. Steuerle, C. (2005). Alternatives to strengthen social security. Statement before the Committee on Ways and Means, United States House of Representatives (May 12). Steuerle, C., & Bakija, J. (1994). Retooling social security for the 21st century: Right and wrong approaches to reform. Washington, DC: The Urban Institute Press. Tabata, K. (2005). Population aging, the costs of health care for the elderly and growth. Journal of Macroeconomics, 27, 472–493. Tanner, M. (2001). Disparate impact: Social security and African Americans. CATO Institute Briefing Papers No. 61 (February 5). Traub, S. (1999). Framing effects in taxation. Heidelberg: Physica-Verlag. U.S. Assistance Election Commission. (2000). Voter registration and turnout by age, gender & race. U.S. Congressional Budget Office. (1995). Who pays and when? An assessment of generational accounting? (November). Wasow, B. (2002). Setting the record straight: Two false claims about African Americans and social security. The Century Foundation (March). http://www.socsec.org/facts/Record_ Straight/African_Americans.pdf.

TAX INCENTIVES FOR ECONOMIC GROWTH: CAPITAL INVESTMENT OR RESEARCH Tracy S. Manly, Deborah W. Thomas and Craig T. Schulman ABSTRACT This paper investigates whether tax incentives can effectively promote capital investment and research spending simultaneously. Tax history provides the experimental setting to compare the influences of these tax initiatives. Analysis shows that firms respond to the research tax incentives by increasing R&D spending but do not significantly react to the policies promoting greater capital investment. More importantly, the results indicate that the tax incentives are negatively related to other types of investment with reduced R&D spending in the presence of incentives for capital investment and capital expenditures decreasing when research is encouraged by tax policy.

INTRODUCTION The American Assembly, a non-partisan group affiliated with Columbia University, lists four essential ingredients for sustained and rapid economic growth: ‘‘continued and enhanced investment in plant and equipment, in Advances in Taxation, Volume 17, 95–120 Copyright r 2007 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1058-7497/doi:10.1016/S1058-7497(06)17004-0

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TRACY S. MANLY ET AL.

scientific research and applied technology, in public infrastructure y and y in education and training’’ (American Assembly, 2000, p. 162). This paper focuses on two of these critical areas, capital investment and research spending, by investigating tax incentives designed to promote private investment to enhance economic growth. Tax benefits for research and capital spending have been present in the tax code for decades. Tax history provides the experimental climate for this study. Prior to 1981, the tax laws favored capital investment more than research spending. The Economic Recovery Act (1981) increased tax incentives for both types of investment. In 1986, with the repeal of the Investment Tax Credit (ITC) and modification of depreciation allowances, tax incentives for capital investment were reduced relative to those for research spending. These changes in the law provide three time periods for comparison of investment patterns of individual firms – when capital investment was favored (1976–1980), when research spending was favored (1986–1990), and when both types of investment experienced increased tax incentives (1981–1985). Tax incentives for research and capital investment encourage substantially different investment activities requiring managers to make tradeoff decisions about where to allocate limited funds. Capital investment tax incentives attract additional spending on current technology while the research incentives emphasize creating new technology for future competitiveness. While the tax law allows firms to use tax incentives for both research and capital concurrently, firms face resource constraints that limit their ability to pursue all investment options available. Brozen (1961) states that ‘‘[t]o some extent, R&D spending is a substitute for capital spending as a means of increasing productivity.’’ Thus, firm response to changes in the tax benefits for these investments may not be as strong as predicted or intended due to the overlapping of multiple tax incentives. As policy makers consider tax incentives as a means to increase one investment or the other, the composite effect of both incentives should be considered and not just each separately. A simultaneous regression model for capital and research investment indicates that firms increase R&D spending when a tax credit for research is enacted, but the presence of capital incentives do not significantly increase capital investment, consistent with prior research (Chirinko, Fazzari, & Meyer, 1999; Gravelle, 1993; Clark & Sichel, 1993; Chirinko, 1986; Chirinko & Eisner, 1983). More importantly, the results indicate that the tax incentives negatively impact other types of investment, with reduced R&D spending when capital investment incentives are available and capital expenditures decreasing when research incentives are present.

Tax Incentives for Economic Growth

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Research evaluating the simultaneous influences of these competing tax incentives is important as government intervention to promote economic growth remains a key element of the tax law. Both the Job Creation and Worker Assistance Act (2002) and the Jobs and Growth Tax Relief Reconciliation Act (2003) were widely acknowledged as economic stimulus packages (Bailey, 2002; Curatola, 2002). In each of these Acts, Congress adopted policies intended to spur capital investment through bonus depreciation. During this time period, Congress has also extended the Research & Experimentation Tax Credit (henceforth, R&E credit). We selected the time period 1976–1990 to capture multiple changes in investment tax incentives similar to the current tax environment for businesses. In describing its revenue estimating procedures, the Joint Committee on Taxation highlights the importance of considering behavioral and indirect effects of tax changes, including shifts in consumption or investment (Joint Committee on Taxation (JCT), 2005). Our results reinforce the continued need for legislators to be aware of possible simultaneous effects of alternative tax policies. One tax incentive should not be considered in isolation, but should be viewed as part of a whole. The negative correlation between research and capital spending in the simultaneous model supports the idea that managers’ investment decisions are interdependent and can be influenced by alternative tax initiatives.

BACKGROUND AND PRIOR RESEARCH The ITC was first enacted in 1962 with the basic objective of promoting economic growth by encouraging modernization and expansion of machinery and equipment (American Enterprise Institution (AEI), 1969).1 Further tax law changes to promote capital investment occurred in 1981 as part of the Economic Recovery Tax Act with the adoption of the Accelerated Cost Recovery System (ACRS) and expansion of the immediate expensing election under Section 179.2 The Tax Reform Act (1986) repealed the ITC and replaced ACRS with the Modified Cost Recovery System, reducing capital investment incentives.3 The Economic Recovery Tax Act of 1981 also passed the R&E credit4 to enhance the international competitiveness of the U.S. by encouraging businesses to perform more research (General Accounting Office (GAO), 1995). Prior to this act, a deduction was allowed for qualifying research expenditures. The deduction is still available but must be reduced by the amount of the credit.

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This study focuses on the period from 1976 to 1990. The relevant tax changes during these years are illustrated in appendix. The response of corporate spending on fixed investment to changes in the tax system has been widely investigated. Chirinko (1986) reviews much of this literature and the methods used by researchers to investigate the relationship. The findings are generally mixed; however, Chirinko argues that sufficient empirical evidence has not yet been generated to show a connection between capital investment and changes in tax laws. Chirinko et al. (1999) uphold this general argument by finding a relatively small elasticity of investment with respect to user cost which is reduced through tax benefits. Similarly, Clark and Sichel (1993) focus specifically on changes to the ITC and find that tax stimulus is not a good method for changing the demand for investment in fixed assets. Greater support for firm response to changes in the marginal costs of investment through tax changes are found by Cummins and Hassett (1992) and Cummins, Hassett, and Hubbard (1996). Specifically, Cummins and Hassett (1992) demonstrate that although investment spending continued to increase after the 1986 tax reform, the increase was less than would have been expected if the tax incentives for investment had not been diminished. Similarly, numerous studies have examined the response of firms to the introduction of the R&E tax credit. Several authors (Hall & Reenen, 2000; Leyden & Link, 1993; Cordes, 1989) have reviewed this literature pertaining to the U.S. credit as well as similar incentives in other countries. From their review, Hall and Reenen (2000) conclude that the R&E tax credit produces approximately one additional dollar of R&D spending for each dollar of tax revenue forgone. Further, they suggest that the credit may take several years to reach this elasticity, explaining earlier work that found little or no effect for the credit. Berger (1993) investigates the R&E tax credit and the implicit taxes created for competitive firms. His research design points out the importance of controlling for the non-tax factors that influence firm spending in order to assess the effect of the credit. He finds that the credit created additional R&D spending. Klassen, Pittman, and Reed (2004) compare R&D tax incentives in both the U.S. and Canada and find the U.S. credits to be the more effective in generating additional spending on research activities. Ellis (1994) models the impact of ITCs on R&D spending. He plots the trends for types of spending, expressing concerns that the ITC siphons investment away from other activities. Using a computable general equilibrium model, Russo (2004) simulates the effects of R&D tax incentives, concluding that incremental credits are more effective than comprehensive credits. When ITC is available for capital investment by innovative firms,


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Russo finds adjustments to the cost of investments tend to reduce the incentive for increasing research efforts. This study extends prior research by empirically investigating the interaction of tax incentives on corporate investment utilizing a model which estimates these two spending decisions, research and capital, simultaneously. The model incorporates the competing tax incentives as predictors for both research and capital spending. This is an important extension of prior research, which primarily focuses on determining the effectiveness of the tax incentive on the intended type of investment. This paper adds an examination of the unintended, but yet important, influence of tax incentives on other types of corporate investment.

RESEARCH DESIGN The research design focuses on firms that actively engage in both research and capital spending whose managers could be forced to make tradeoff decisions about where to invest. Changes in the after-tax cost of these investments could attract more funds than would have been allocated otherwise. Simultaneous equations are used to investigate the relationship between tax credits and investment in capital and research. A three-way fixed effects model controlling for firm, year and industry effects is estimated using two-stage least squares.5 The fixed effect model assumes that differences across groups can be captured by differences in the constant term (Greene, 1990). Thus, the three-way fixed effects model allows a separate intercept for each firm, year and industry. The mean research and capital spending for each effect are captured individually and are not creating a bias for the coefficient estimation. Dependent Variables R&D expense (RDX) reported in the annual financial statements is used as a proxy for the unobservable research expenditures recorded for tax purposes. The level of annual expense is used instead of a measure of spending intensity, such as R&D scaled by sales. The focus of the tax legislation is to increase research spending beyond a base level and does not require that research grow at a rate faster than sales to qualify for the credit. Total reported capital expenditures (CAPX) are used as a proxy for purchases qualifying for the preferential tax treatment, primarily machinery and equipment. The impact this proxy might have on the analysis depends on whether these components of capital expenditures are complements or

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substitutes. If they are complements, then it is reasonable to assume that by lowering the after-tax cost on equipment, certain projects at the margin which also include purchases for property and plant might be undertaken. Although the property and plant purchases do not receive the tax credit, they were in part induced by the availability of the tax incentive. While the total capital expenditures overstate the qualifying expenditures, the impact of the tax incentive is not overstated. However, if the two types of expenditures were substitutes, then an incentive to spend on equipment would decrease spending on property and plant. In this case, the relationship between the tax incentive and total capital expenditures depends on the magnitude of the substitution. If the substitution of equipment for property and plant is greater than one for one, the tax credit would show a positive, but understated, correlation to total capital expenditures. If the substitution is less than one for one, a negative correlation would exist between the availability of the credit and total capital expenditures. This substitution option would bias against finding a positive relationship between the credit and capital expenditures. Independent Variables Tax Credit Usability The two dependent variables are regressed on indicator variables (RECRED, ITCRED) that indicate the usability of each of the tax incentives. Each of the tax credits is considered usable during the years enacted when the individual firm also had positive earnings before taxes for the current and prior years.6 The tax incentives under investigation have a history of being changed frequently by Congress (see Notes 1 and 3). If uncertainty about the consistency of the tax benefits influenced managers’ spending decisions, then that creates a bias against finding a relationship between the independent variables and research and capital spending. Control Variables Funds Availability The investment decisions of corporate managers depend on the availability of funds for investment. Prior research documents a positive relationship between internal funds and R&D (Berger, 1993; Shehata, 1991; Grabowski, 1968). However, both internally and externally generated funds can be used for research and capital spending. Thus, both cash from operations (AVGOPCF) and cash from financing (AVGFCF) are included. The twoyear averages of these measures are used because the entire amount of cash


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generated in a period may not be expended in that same period. To further capture the funds availability position of the firm for the current year, the beginning of the year cash balance (CASH) is included. The simultaneous regression model captures the interdependence of these two investment decisions. Funds committed to either research or capital change the level of funds for additional spending on other activities. Therefore, current capital (CAPX) spending is included as a control for R&D spending (RDX) and vice versa. Firm Financial Position In addition to cash considerations, the level of corporate spending depends on the firm-specific financial position. The reported earnings of the firm are an important consideration for managers making investment decisions. Barth, Elliott, and Finn (1999) show that the market rewards firms with a pattern of increasing earnings, providing a powerful motivation for managers to focus on the trend in net income. In addition, Baber, Fairfield, and Haggard (1991) investigate the importance of reported earnings on the decision to invest in R&D. They find that managers decrease R&D spending when that spending would create negative income or a decreasing trend. Therefore, the change in earnings per share (CEPS) is included in the model to capture the earnings trend for each firm-year. Change in earnings per share (CEPS) is excluded from the capital-spending (CAPX) model because these costs are not likely to be used to smooth income since only a portion of the costs through depreciation is recorded in current income. This is consistent with Baber et al. (1991, p. 819), who report that ‘‘managers are more likely to consider current-period income effects when making R&D decisions than when making capital-spending decisions.’’ The current level of earnings of a firm is also an important consideration for managers in making investment decisions. Horwitz and Kolodny (1980, 1981) and Shehata (1991) show that accounting regulations that required immediate expensing of R&D caused a relative decline in R&D outlays. Thus, the financial reporting consequence of investment is not trivial. Current level of earnings before taxes and research spending (EBT) are included to control for the influence of reported income on investment decisions. The prior year R&D expense (LRDX) and capital spending (LCAPX) affect current spending decisions because projects can span more than one year. Klassen et al. (2004), Berger (1993), and Tillinger (1991) find a strong relationship between R&D for the current and previous year. Firm size (SIZE) is also included as a control.7 Klassen et al. (2004) and Shehata (1991) both find evidence that R&D spending is proportionate to firm size.

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External Influences Factors outside the firm also play a role in corporate spending decisions, requiring further control variables in the model. Gross National Product (GNP) accounts for fluctuations in economic health over the sample period. Beyond economic concerns, each firm’s opportunity costs and expected marginal benefits determine its investment decisions. The q-ratio is a measure of the firm’s marginal benefit compared to the marginal cost of an additional unit of new investment. Tillinger (1991) examines firm response to the R&E tax credit through classifying firms by q-ratios. The positive influence of the credit declines the further the ratio is from a value of one. Firms with a q-ratio close to one are most influenced by the credit. The q-ratio is unobservable, thus the ratio of the book value of assets compared to the market value of assets is incorporated as a proxy. Also, Sougiannis (1994) and Lev and Sougiannis (1996) both demonstrate that R&D spending is related to the market value of the firm. Their research shows that the market value of research firms is adjusted to include an asset value for a portion of R&D expense determined to have future benefit for the firm. As previously stated, a three-way fixed effects model incorporating firm, time and industry8 effects is used to estimate the two investment equations simultaneously. Model: RDX ¼ a1 þ b11 RECRED þ b21 ITCRED þ b31 AVGOPCF þ b41 AVGFCF þ b51 CASH þ b61 CAPX þ b71 CEPS þ b81 EBT þ b91 LRDX þ b101 SIZE þ b111 GNP þ b121 B=M þ

ð1Þ

CAPX ¼ a2 þ b12 RECRED þ b22 ITCRED þ b32 AVGOPCF þ b42 AVGFCF þ b52 CASH þ b62 RDX þ b72 EBT þ b82 LCAPX þ b92 SIZE þ b102 GNP þ b112 B=M þ

ð2Þ

where: RDX

¼

CAPX

¼

All costs incurred during the year that relate to the development of new products or services. Cash outflow for additions to the company’s property, plant and equipment.


RECRED

¼

ITCRED

¼

AVGOPCF

¼

AVGFCF

¼

CASH CEPS

¼ ¼

EBT LRDX

¼ ¼

LCAPX SIZE GNP B/M

¼ ¼ ¼ ¼

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1 for observations from years in which the R&E credit was enacted and the company has earnings before taxes that were positive for the current and prior year, 0 otherwise. 1 for observations from years in which the ITC was enacted and the company had earnings before taxes that were positive for the current and prior year, 0 otherwise. Two-year average of cash from operations for the current and prior year. Cash from operations is computed as the sum of income before extraordinary items, depreciation and amortization, deferred taxes, equity in earnings of unconsolidated subsidiaries, discontinued operations, minority interest income and R&D expense.9 Two-year average of cash from financing activities for the current and prior year. Cash from financing is estimated by the sum of the change in long-term debt and the change in stockholders’ equity less the change in retained earnings. Beginning of the year cash balance. Change in earnings per share from prior to current year. Earnings per share is computed as operating income plus research and development expense divided by the number of common shares used to compute primary earnings per share. Earnings before taxes and research spending. Research and development expense for the prior year. Capital expenditures for the prior year. Total sales Gross National Product. Beginning of the year book-to-market ratio. Book value is measured as total common equity. Market value is the closing price multiplied by the number of common shares outstanding.

The coefficients on RECRED and ITCRED address the research question. These variables capture the influence that the usability of the tax

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benefits has on corporate spending decisions. A positive (negative) relationship indicates the benefit is related to higher (lower) levels of spending. Therefore, if the R&E tax credit effectively stimulates research spending by lowering the after-tax cost, a positive coefficient for RECRED is expected in Eq. (1). Similarly, a positive coefficient for ITCRED is expected in Eq. (2). Both the tax credit variables are included in Eqs. (1) and (2) in order to investigate the influence of the opposing incentive on spending. If the ITC detracts from research spending, then a negative relationship exists between ITCRED and RDX in Eq. (1). In the same way, a negative relationship is expected between RECRED and CAPX in Eq. (2).

SAMPLE SELECTION Observations for the sample are selected from the Compustat database from the years 1976–1990. Fifteen years of data are collected that represent a balanced panel of five experimental years when both credits are present (1981–1985), five years when only the ITC was in effect (1976–1980) and five years when only the R&E credit was enacted (1986–1990).10 Each firm was required to have spending on both capital and research in the current year to be included. The sample selection yields 13,162 firm-year observations from 2,023 companies for the estimation procedure.11 Tables 1 and 2 show summary information for research and capital spending by both industries and years. Although the industry fixed effect in the simultaneous regression model is based on two-digit SIC codes, for reporting purposes industries are divided into one-digit SIC codes. Regulated industries are omitted from the sample. The distribution of observations across industries is largely consistent with that of the Compustat population of firms except that manufacturing industries (3000–3999) are over-represented in the sample. Sensitivity analysis, as reported later, shows that this difference between the sample and the population does not significantly drive the primary results of the empirical tests. Descriptive statistics for the variables are shown in Table 3. Means and standard deviations are shown separately for the observations when the tax credits were available and those when the credits were unavailable. Results are shown from the univariate comparisons made between each of the variables between the two categories for both RECRED and ITCRED. As expected, R&D spending is significantly higher for the firms that could take advantage of the R&E tax credit. These observations also related to higher cash flows, earnings, capital spending and size. Interestingly, these firms that

Industry SIC Codes 0–0999 (Agriculture) 1000–1999 (Mining, construction) 2000–2999 (Food, apparel, lumber, paper, chemicals) 3000–3999 (Rubber, leather, metal, machinery, equipment) 4000–4999 (Transportation, communications) 5000–5999 (Wholesalers, retailers) 7000–7999 (Services) 8000–8999 (Health, education)

Total

Descriptive Statistics – R&D Expense (Mean, in millions (standard deviation) sample size). 1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

6.66 (12.06) 5 8.32 (21.05) 13 20.68 (74.92) 169

10.26 (17.28) 4 12.22 (23.14) 11 19.74 (73.09) 166

1987

1988

1989

1990

Total

2.60 (3.70) 3 7.34 (11.30) 13 7.27 (22.80) 139

3.84 (4.26) 3 6.52 (9.91) 20 10.12 (30.42) 174

4.36 (4.98) 3 7.12 (11.86) 22 9.93 (29.05) 179

4.06 (4.34) 4 4.47 (10.36) 16 15.16 (48.24) 168

3.90 (5.72) 4 4.86 (11.68) 18 18.23 (59.06) 168

3.74 (6.14) 5 5.95 (12.97) 17 23.02 (73.15) 165

4.77 (8.01) 5 7.70 (20.50) 15 23.09 (80.45) 159

5.67 (10.29) 5 7.58 (19.02) 14 19.77 (70.34) 159

1.70 0.94 (0.65) – 3 1 14.53 10.98 (21.59) (17.85) 9 12 27.62 31.27 (87.74) (104.39) 159 169

0 0 – – – – 9.86 16.00 (26.70) (36.89) 9 8 35.88 39.72 (124.46) (132.32) 170 139

0 – – 19.15 (41.97) 7 54.04 (185.89) 130

4.79 (7.96) 45 8.43 (18.55) 204 23.15 (88.09) 2413

11.13 (70.54) 448

13.33 (78.18) 539

16.75 (92.34) 563

15.03 (79.31) 526

14.46 (65.81) 531

15.19 (70.78) 531

17.14 (84.99) 616

17.15 19.77 23.17 26.58 30.21 (84.01) (112.42) (140.89) (162.15) (194.51) 629 682 682 658 664

22.32 29.25 (138.50) (190.35) 652 576

34.84 (232.76) 510

20.71 (131.73) 8838

21.2 (41.55) 4 1.33 (2.48) 27 6.51 (21.52) 28 0.80 (0.92) 7

43.86 (94.27) 9 2.09 (3.35) 30 7.34 (23.55) 30 1.0315 (1.18) 15

20.34 (47.25) 7 1.98 (3.02) 33 7.51 (24.81) 37 1.39 (1.53) 14

0.82 (1.02) 9 3.60 (4.67) 15 5.35 (11.70) 85 1.69 (1.77) 16

0.82 (1.06) 7 3.96 (5.52) 15 8.72 (24.10) 75 1.61 (1.93) 16

58.72 (168.72) 126 1.96 (3.39) 367 6.37 (18.35) 939 1.47 (2.08) 230

9.58 (58.94) 669

11.93 (65.88) 820

13.85 (76.37) 858

23.20 27.17 (127.94) (166.08) 973 848

33.78 (206.06) 760

19.40 (115.85) 13162

47.13 61.72 74.36 111.79 121.88 46.74 57.33 66.99 65.17 93.54 (127.25) (157.52) (166.29) (223.52) (281.65) (136.65) (167.94) (189.51) (214.34) (278.70) 8 7 10 8 10 9 9 9 11 9 2.05 2.14 1.96 1.56 1.08 1.30 1.86 1.97 2.14 2.25 (3.46) (4.17) (3.26) (2.82) (1.72) (2.20) (3.37) (3.64) (4.03) (3.99) 25 24 21 28 29 29 27 24 21 19 3.65 4.80 3.53 7.37 6.92 5.33 5.60 5.14 6.094 9.44 (9.50) (11.49) (5.25) (30.19) (18.54) (11.44) (12.65) (12.18) (15.48) (26.70) 35 41 35 54 62 82 93 91 94 97 2.02 1.59 0.99 1.10 1.32 1.43 1.56 1.24 1.73 2.09 (2.62) (2.58) (1.06) (1.14) (1.37) (2.02) (2.20) (2.34) (2.76) (3.48) 13 16 14 15 15 17 19 18 18 17 13.99 (69.45) 795

14.28 (61.59) 809

16.14 (69.49) 829

17.47 (81.45) 900

17.08 (81.23) 923

17.93 20.15 23.85 27.12 (98.52) (120.65) (139.49) (166.74) 1006 1011 971 990


Table 1.

105

106

Table 2. Industry SIC Codes 0–0999 (Agriculture)

Descriptive Statistics-Capital Expenditures (Mean, in millions (standard deviation) sample size). 1976 6.82 (5.99) 3 109.96 (169.59) 13 45.48 (187.39) 139

1977

1978

9.18 7.34 (11.75) (8.10) 3 3 91.14 109.84 (159.09) (190.33) 20 22 67.24 52.45 (316.92) (195.32) 174 179

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

9.76 14.62 17.51 25.44 18.47 22.07 30.53 13.76 1.21 0 0 (8.68) (8.63) (19.84) (26.05) (16.45) (21.43) (23.42) (11.32) – – – 4 4 5 5 5 5 4 3 1 – – 91.61 54.54 60.58 51.30 28.26 34.19 177.54 139.68 86.14 31.41 56.34 (168.26) (102.46) (125.79) (124.15) (65.63) (73.59) (300.72) (257.40) (171.29) (58.16) (69.72) 16 18 17 15 14 13 11 9 12 9 8 110.46 139.30 167.62 163.07 154.66 157.47 170.80 147.12 150.23 168.93 139 (522.15) (655.44) (837.72) (873.63) (780.99) (811.88) (900.40) (666.21) (692.35) (778.09) (173.97) 168 168 165 159 159 169 166 159 169 170 139

Total

30.72 (153.57) 669

54.21 42.61 (455.51) (206.00) 820 858

70.98 73.02 81.75 71.09 62.64 51.49 56.15 49.74 50.94 50.89 59.60 (643.50) (676.77) (734.82) (672.19) (569.77) (373.21) (412.94) (317.12) (336.86) (361.49) (402.82) 795 809 829 900 923 1006 1011 971 990 973 848

Total

0 – – 81.71 (120.11) 7 233.26 (888.83) 130

16.66 (16.89) 45 79.93 (156.60) 204 138.63 (692.19) 2413

43.30 (360.09) 510

32.52 (206.86) 8838

1.84 (1.45) 7 6.04 (8.16) 15 4.97 (19.50) 75 1.82 (3.69) 16

893.08 (3322.5) 126 16.85 (62.70) 367 9.60 (36.05) 939 3.34 (5.70) 230

70.37 (476.51) 760

58.31 (480.16) 13162


1000–1999 (Mining, construction) 2000–2999 (Food, apparel, lumber, paper, chemicals) 3000–3999 24.58 31.46 39.44 36.45 31.12 33.02 28.79 26.06 31.88 33.77 30.16 30.12 25.65 44.13 (Rubber, leather, (144.45) (179.69) (221.29) (275.39) (127.10) (149.75) (134.84) (131.34) (189.62) (214.91) (176.86) (183.81) (141.69) (330.27) metal, 448 539 563 526 531 562 616 629 682 682 658 664 652 576 machinery, equipment) 4000–4999 271.37 1408.33 160.09 2019.92 2459.76 1954.84 2255.74 1524.54 184.51 206.44 246.46 240.75 332.57 4.25 (Transportation, (504.73) (3834.6) (371.63) (5494.9) (6424.9) (5588.6) (5767.2) (4320.4) (489.26) (573.94) (658.76) (776.77) (987.34) (6.95) communications) 4 9 7 8 7 10 8 10 9 9 9 11 9 9 5000–5999 8.91 21.71 16.83 11.55 10.24 10.07 9.12 13.92 17.72 25.38 37.62 41.08 7.15 9.40 (Wholesalers, (24.90) (42.64) (32.89) (23.00) (21.72) (20.66) (24.52) (62.11) (77.99) (89.45) (140.05) (124.13) (9.80) (13.64) retailers) 27 30 33 25 24 21 28 29 29 27 24 21 19 15 7000–7999 14.29 18.16 20.42 19.07 13.15 17.59 19.35 10.64 8.01 7.97 6.71 5.13 6.43 3.53 (Services) (50.07) (49.85) (65.16) (55.35) (27.43) (43.54) (87.73) (34.55) (24.96) (25.51) (16.12) (13.29) (18.43) (10.30) 28 30 37 35 41 35 54 62 82 93 91 94 97 85 8000–8999 4.55 5.16 7.34 6.34 6.42 4.20 4.75 2.18 3.26 1.01 1.77 1.21 2.03 0.95 (Health, education) (5.56) (5.96) (9.13) (7.04) (10.47) (6.30) (8.11) (2.80) (4.26) (1.22) (3.20) (1.24) (2.97) (1.08) 7 15 14 13 16 14 15 15 17 19 18 18 17 16

1990


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Table 3. Descriptive Statistics (Mean, in millions (standard deviation)).

RDX R&D expense CAPX Capital expenditures AVGOPCF Average operating cash flows AVGFCF Average financing cash flows CASH Cash balance, beginning of year CEPS Change in earnings per share EBT Earnings before tax and R&D LRDX Lagged R&D expense LCAPX Lagged capital expenditures SIZE Total sales B/M Ratio of book value to market value

RECRED Not Usable (0) (n ¼ 7213)

RECRED Usable (1) (n ¼ 5949)

ITCRED Not Usable (0) (n ¼ 6387)

ITCRED Usable (1) (n ¼ 6775)

Total (13162)

8.85 (51.39) 33.66 (360.39)

32.17 (161.86) 88.20 (592.47)

19.92 (136.57) 41.93 (319.78)

18.91 (92.15) 73.75 (592.49)

19.40 (115.85) 58.31 (480.16)

46.05 (390.01)

141.66 (808.99)

70.30 (507.92)

107.15 (705.08)

89.27 (617.57)

6.91 (101.98)

21.77 (328.03)

15.05 (287.77)

12.28 (166.11)

13.63 (233.21)

30.02 (220.16)

85.11 (472.44)

49.45 (377.55)

60.07 (338.55)

54.92 (358.03)

0.25 (69.36)

0.52 (66.26)

0.50 (76.22)

0.26 (59.16)

0.38 (67.97)

36.77 (365.25)

129.06 (676.32)

59.57 (448.24)

96.31 (598.08)

78.48 (530.98)

7.97 (45.85)

28.06 (142.18)

17.56 (119.78)

16.56 (81.59)

17.05 (101.92)

30.63 (316.79)

83.69 (594.41)

39.96 (309.28)

68.44 (572.60)

54.62 (464.08)

42.33 (2733.9) 0.94 (0.77)

1111.97 (5994.01) 0.69 (0.51)

589.51 (4135.17) 0.74 (0.67)

870.29 (4855.39) 0.91 (0.68)

734.04 (4522.26) 0.83 (0.68)

Notes: T-tests were performed for each variable between the two RECRED groups and the two ITCRED groups. Means that are statistically different (po0.05) are shown in bold italics. RECRED, R&E tax credit usability. This indicator variable equals 1 for observations from years in which the R&E credit was enacted and the company has earnings before taxes that were positive, 0 otherwise; ITCRED, ITC usability. This indicator variable equals 1 for observations from years in which the ITC was enacted and the company had earnings before taxes that were positive, 0 otherwise.

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spend more on research have a significantly lower average book-to-market ratio. This most likely represents the fact that the intangible assets created from the research are not capitalized in the financial statements. The average capital spending is also larger when firms can utilize the capital incentives including the ITC. Usability of capital investment incentives is related to higher operating cash flows, earnings and size, but it is related to slightly lower, but insignificant, levels of research spending. A correlation matrix of the variables is presented in Table 4.

RESULTS The results from the simultaneous regression equation are shown in Table 5. The variables of interest are the two tax credit usability variables, RECRED and ITCRED. In Eq. (1) for research spending (RDX), the coefficient for the RECRED is both positive and significant. This finding supports prior research that reports the credit is related to increased research spending. In addition, the coefficient for ITCRED is negative and significant in Eq. (1). Thus, the presence of the tax benefits for capital is related to lower amounts of spending on research. The Eq. (2) results for capital spending (CAPX) show that the ITCRED is not significantly related to the dependent variable. Thus, the ITC cannot be clearly associated with increased capital spending by firms that engage in both types of investment. However, the coefficient for RECRED in Eq. (2) is negative and significant, suggesting that this alternative tax incentive serves to decrease the level of capital spending. These findings illustrate that corporate spending decisions incorporate a number of factors including the presence of alternative tax incentives. Each of these tax initiatives influences investment decisions beyond those targeted by legislators. Of the funds availability variables, operating cash flows (AVGOPCF) are positively related to R&D expenses while financing cash flows (AVGFCF) are positively related to capital outlays. These results support prior arguments that R&D funds are generated internally because external funding may be difficult and expensive for these types of projects (Grabowski, 1968; Kamien & Schwartz, 1978). On the other hand, financing appears to be more readily available for capital expenditures that can be used as collateral. The beginning of the year cash balance (CASH) is negatively related to both research and capital spending. It appears that keeping larger amounts of cash on hand does not lead to increased investment by firms. The CAPX and RDX control variables are each significantly negative in the simultaneous equation model, reinforcing the conclusion that these decisions are

RDX CAPX 0.506 RECRED 0.100 ITCRED 0.004 AVGOPCF 0.634 AVGFCF 0.405 CASH 0.719 CEPS 0.001 EBT 0.623 LRDX 0.973 LCAPX 0.471 SIZE 0.364 GNP 0.051 B/M 0.003

CAPX RECRED ITCRED AVGOPCF AVGFCF CASH

CEPS

EBT LRDX LCAPX

0.056 0.033 0.961 0.432 0.612 0.001 0.872 0.500 0.979 0.309 0.002 0.020

0.002 0.001 0.001 0.006 0.002 0.007

0.613 0.842 0.365 0.017 0.005

0.064 0.077 0.031 0.077 0.002 0.087 0.098 0.057 0.174 0.417 0.184

0.030 0.006 0.015 0.002 0.035 0.005 0.031 0.244 0.691 0.129

0.414 0.724 0.001 0.930 0.635 0.954 0.361 0.013 0.016

0.299 0.003 0.315 0.399 0.406 0.124 0.016 0.001

0.001 0.773 0.726 0.588 0.367 0.022 0.002

0.482 0.373 0.050 0.004

0.308 0.001 0.025

SIZE

GNP


Table 4. Correlation Matrix.

0.150 0.183 0.268

Note: Bold and italicized if Pearson Correlation is significant at the 5% level. RDX, R&D expense; CAPX, Capital expenditures; RECRED, Indicator for R&E tax credit; ITCRED, Indicator for investment tax credit; AVGOPCF, Average operating cash flows; AVGFCF, Average financing cash flows; CASH, Cash balance, beginning of year; CEPS, Change in earnings per share; EBT, Earnings before tax and R&D expense; LRDX, Lagged R&D expense; LCAPX, Lagged capital expenditures; SIZE, Log of total sales; GNP, Gross National Product; B/M, Book/Market.

109

110


Table 5. Simultaneous Regression Model (Observations: 13162). RDX Model (1) Adj. R2 0.82

CAPX Model (2) Adj. R2 0.92

Expected sign

Expected sign

Intercept RECRED Indicator for R&E credit ITCRED Indicator for investment tax credit AVGOPCF Average operating cash flows AVGFCF Average financing cash flows CASH Cash balance, beginning of year RDX R&D expense CAPX Capital expenditures CEPS Change in earnings per share EBT Earnings before taxes and R&D expense LRDX Lagged R&D expense LCAPX Lagged capital expenditures SIZE Total sales GNP Gross National Product B/M Ratio of book value to market value

+ –

Coefficient (p-value) 8.70 (o0.01) 2.24 (o0.01) 3.63 (o0.01) 0.033 (0.03) 0.019 (0.12) 0.026 (0.08)

0.110 (o0.01) 0.002 (0.03) 0.024 (0.06)

– +

Coefficient (p-value) 16.51 (0.05) 3.13 (0.02) 1.05 (0.34) 0.050 (0.70) 0.066 (o0.01) 0.048 (0.05) 0.314 (0.02)

0.145 (0.08)

0.880 (o0.01) 0.557 0.007 (o0.01) 0.0003 (0.05) 1.52 (0.07)

0.025(.03) 0.0005 (0.26) 6.34 (o0.01)

Notes: Tests on the coefficients are one-tail for RECRED and ITCRED. All other tests are twotail. p-values are reported using White’s corrected standard errors. GNP is positively related to CAPX when transportation firms are omitted from the sample (see explanation beginning on p. 16).

interdependent. The funds committed to one area of spending are dependent on spending decisions elsewhere. CAPX is negatively related to R&D spending, which suggests that investments in property, plant and equipment detract from funds for research. Similarly, RDX is negatively correlated


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with capital spending. Therefore, higher levels of research spending must also detract from additional investment in capital.12 The change in earnings per share (CEPS) is positively related to R&D expense. This supports the line of reasoning that suggests managers are more likely to make additional research investments when earnings are increasing. This allows them to continue the investment while still showing a smooth stream of income. The level of current earnings (EBT) is positively related to both current R&D and capital spending. Together, these two variables indicate that managers consider financial reporting results as well as the availability of funds in making investment decisions (Table 5). In each equation the lagged dependent variable (LRDX, LCAPX) is positive and highly significant. This is consistent with the idea that these projects extend over more than one time period and that firms make current investment decisions with consideration of prior spending. Firm size (SIZE) is directly related to both R&D and capital spending. Therefore, relatively larger firms tend to be the leaders in investment. These results support the positive relation found between R&D and size by Klassen, et al. (2004). The external influence variable for general economic well-being (GNP) is negatively related to research spending. Thus, firms look to additional innovation in times of economic downturn. However, GNP is not related to capital spending. As an alternative measurement of economic health, we incorporated the change in GNP in both real and constant terms. The results for this variable and the independent variables of interest were not changed. Further investigation shows that the insignificant result for this control variable is driven by the extensive capital spending by the transportation industry during the economic downturn of the early 1980s. When the transportation industry observations are removed from the sample, GNP is positively related to CAPX. The book-to-market ratio is negatively related to both the dependent variables. For firms in this sample, higher level of investment coincides with expectations for growing and expanding firms. These firms are most likely to have market values that well exceed their book values and produce a lower q-ratio. Sensitivity Analysis Manufacturing Industries The manufacturing firms (SIC 3000–3999) make up a substantial portion of the sample. Even though industry effects are controlled for by the fixed

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effects in the original model, an additional test was performed to investigate whether firms from this industry group significantly influenced the results. The observations from the manufacturing industries were separated from the other observations and the simultaneous regression was estimated on the two groups. First, the estimation for the non-manufacturing firms shows the same general pattern of results for the independent variables (RECRED, ITCRED). The one exception is that although the RECRED variable remains negative in the capital-spending model, it is no longer significant at conventional levels. The inferences from the control variables are the same as those from the original model, although the level of significance changes for a few variables. Second, the estimation of the regression for only the manufacturing firms also resembles the results for the full sample, with one exception. The RECRED variable is no longer significantly related to RDX. Thus, the research tax incentives appear to have a stronger influence for firms outside the manufacturing industries. Although some differences do exist, when taken together, the influence of the credits on spending patterns is similar between manufacturing and non-manufacturing firms. Transition Years The R&E credit began in 1981; however, the legislation was enacted in the third quarter of the year and applied retroactively to the start of the year. The statistical tests include 1981 as a year that the R&E credit was available. Since the incentive was not as strong in that year, the tests are repeated removing observations from 1981.13 The primary conclusions are unchanged as the variables of interest retain similar coefficients and significance. For the RDX equation, the RECRED variable is positive and significant and the ITCRED variable is negative and significant. For the CAPX equation, the RECRED variable is negative and significant and the ITCRED variable is not significant. Similar to the transition in 1981, the repeal of the ITC was passed late in 1986 and was made retroactive to the beginning of the year. The model treats the variable ITCRED as being unavailable in the year 1986, but this is known only with the benefit of hindsight. It is possible that firms could have been undertaking capital expenditures in the early months of 1986 with the expectation of receiving tax benefits. The model is estimated without the observations from 1986. Again, the pattern of findings on the variables of interest remains constant. The RECRED variable is significant and positively related to research spending while marginally significant and negatively related to capital spending. The ITCRED variable is negatively related to the dependent variable RDX and unrelated to the dependent


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variable CAPX. Finally, both the transition years were removed jointly and the model was tested. The results showed the same pattern of sign and significance for the coefficients of the tax credit variables as the previous model excluding only 1986. The main inferences from the control variables remain constant throughout the tests, although the level of significance changes on some of the control variables. Tradeoff Effects for Investment Leaders The original model and sample selection address the impact of the two tax incentives on a cross-section of firms engaged in both capital and research spending to test the overall impact of the policies. However, there is another closely related question that addresses how the presence of both credits influences the decisions of firms that invest heavily in both types of spending. The median level of R&D and capital spending was identified for each year included in the sample. Observations were retained if the level of firm investment in research and capital exceeded the median spending in both the categories for the year. This subset of the original sample contains 5,066 observations, and the results of the estimation of the research model are shown in Table 6. The sign and significance of the independent variables are the same as that of the original estimation. Thus, the above inferences hold for the smaller group of firms that are the investment leaders in each category. The sign and significance of the control variables are also similar to the original estimation with one exception. The cash variable is no longer significantly related to R&D spending. As might be expected, this group of firms is significantly larger (as measured by sales and assets) than the sample of firms included in the primary analysis. This shows that the larger firms also face tradeoff decisions that can be influenced by changes in the after-tax costs of investments. One might expect that larger firms would be less influenced because of their increased ability to generate financing, but this does not seem to be the case.

LIMITATIONS When investigating the effects of tax law changes, researchers are constrained by the practice of Congress to pass many provisions as a part of one tax act. In addition to the repeal of the ITC and the adoption of the R&E Tax Credit, the tax reform packages enacted from 1976 to 1990 contained other provisions targeting corporate investment, summarized in appendix. The direct effects of the tax credit changes in 1981 and 1986 cannot be isolated. Our

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Table 6. Simultaneous Regression Model Above Median Spending on R&D and Capital Expenditures (Observations: 5066). RDX Model (1) Adj. R2 0.88

CAPX Model (2) Adj. R2 0.93

Expected sign

Expected sign

Intercept RECRED Indicator for R&E credit ITCRED Indicator for investment tax credit AVGOPCF Average operating cash flows AVGFCF Average financing cash flows CASH Cash balance, beginning of year RDX R&D expense CAPX Capital expenditures CEPS Change in earnings per share EBT Earnings before taxes and R&D expense LRDX Lagged R&D expense LCAPX Lagged capital expenditures SIZE Total sales GNP Gross National Product Book/Market

+ –

Coefficient (p-value) 23.8 (o0.01) 3.59 (o0.01) 7.41 (o0.01) 0.035 (o0.01) 0.012 (0.29) 0.012 (0.34)

0.067 (o0.01) 0.002 (o0.01) 0.014 (0.09)

– +

Coefficient (p-value) 58.04 (0.04) 10.38 (0.03) 5.14 (0.28) 0.104 (0.44) 0.070 (o0.01) 0.041 (0.10) 0.315 (o0.01)

0.137 (0.14)

0.949 (o0.01)

0.02 (0.08) 0.0009 (0.01) 3.90 (0.15)

0.636 (o0.01) 0.014 (0.03) 0.002 (0.21) 20.02 (o0.01)

Notes: Tests on the coefficients are one-tail for RECRED and ITCRED. All other tests are twotail. p-values are reported using White’s corrected standard errors.

results compound the effects of both the changes to depreciation and the ITC, and should be considered in light of this limitation. However, note that during the time periods of interest, Congressional policy was consistent in each act – incentives for capital and research either both increased or decreased, which would bias against our finding significant results.


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CONCLUSION Our research provides support to prior research that tax incentives can induce firms to increase R&D spending (Hall & Reenen, 2000), but are not as effective in encouraging capital investment (Gravelle, 1993; Chirinko, 1986). Investment in plant and equipment would likely occur without tax incentives. Not only may tax incentives for capital investment be ineffective, but they may also be counterproductive by reducing beneficial research spending. Our research indicates that when an ITC is available, firms reduce their investment in research. While both research spending and capital investment contribute to economic growth, it is more important that governments provide support for research. Absent government intervention, it is expected that businesses will invest less than the desirable amount in research because they are not able to fully capture all the benefits due to spillover effects. Governments can remedy this problem by providing protection for research benefits (e.g., patents, copyrights), awarding grants for specific R&D projects, and by reducing the cost of the research through tax incentives (Guinet & Kamata, 1996). The use of tax incentives involves less government interference and allows market signals to play a greater role in the research performed. Even though our research indicates that R&E tax credits may cause a reduction in capital spending, these tax incentives play an important role in the economy. In recent years, policy makers have relied on deductions rather than credits to promote capital spending. The Job Creation and Worker Assistance Act (2002) provided for an additional 30 percent first-year depreciation for new capital investment. The Jobs and Growth Tax Relief Reconciliation Act (2003) increased this enhanced deduction to 50 percent for first-year depreciation. This additional expense deduction was temporary, ending in 2005. The JGTRR also increased the amount of the Section 179 expense election to $100,000 annually, indexed through 2007 and scheduled to fall back to $25,000 in 2008. The current R&E credit is also temporary but Congress has routinely renewed it as it expires, most recently as a part of the Working Families Tax Relief Act of 2004, which extended the credit through 2005. As Congress considers readopting tax incentives for capital investment and research spending, legislators should be aware that the amount firms invest in research is sensitive to tax incentives for capital investment. An emphasis on investment in current technology may cause a reduction in the creation of new technology for competitiveness.

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NOTES 1. The credit required an eight-year useful life for the full cost of the equipment to qualify. Eligible property included primarily tangible property used for manufacturing, production or extraction. The credit equaled seven percent of qualified investments although yearly limits applied. In 1966, President Johnson suspended the ITC due to excessive demands for funds, but then reinstated it five months later in 1967. In 1969, the ITC was repealed. After two years, the credit was reenacted in 1971. The ITC remained in effect until its final repeal in 1986 although adjustments were made in 1975, 1976, 1981 and 1982. 2. See Appendix. The 1981 legislation enacting Section 179 provided the expense election for property placed in service after 1981. Hence, the effective date of Section 179 expensing was January 1, 1982. The later effective date was a mistake and once found, Congress decided not to revisit the issue. Therefore, some investment in 1981 was likely made with the assumption that the expensing election would be available. 3. The 1986 Act also expanded the expense election under Section 179, phasing out the deduction for businesses with total capital investments of over $200,000. This change benefited small businesses investing in plant and equipment. Taken together, however, the provisions of the 1986 Act reduced the incentives for capital investment, particularly for most of the firms included in this study, which are relatively large in size. This and other changes are summarized in appendix. 4. The original provisions allowed firms a tax credit of 25 percent of R&D spending above a certain base amount of spending, the average of the previous three years’ eligible spending. Eligible activities included R&D performed in ‘‘carrying on’’ the firm’s existing trade or business. Purchases of R&D plant and equipment do not apply. The credit was initially designed to terminate in 1986 but has been extended eight times. In 1986, the credit rate dropped to 20 percent. The rules for computing the base amount of R&D changed in 1986, 1990 and 1996. Throughout its life, the credit has remained an incremental credit designed to encourage private R&D spending beyond a base level that would occur without incentives. 5. Two-stage least squares corrects for correlated error terms between the two equations by introducing instrumental variables for research and capital spending when incorporated as predictors. 6. The requirement of positive earnings in the current and prior years identifies companies most likely to be in a tax-paying position and to benefit from the incentives being investigated. Firms with losses in either the current or prior years are labeled as unable to use the credit. Given the provision of NOL carryforwards and carrybackwards, some firms may be misclassified. To the extent this occurs, they should be labeled as being able to use the credit when, in fact, they were not. This misclassification would bias against finding a significant relationship between the independent and dependent variables. Sensitivity analysis was performed which redefined RECRED by requiring positive earnings in the current and prior two years. The results were not qualitatively different than those reported in the paper. 7. Following the recommendation of Barth and Kallapur (1996), size is added as a control variable and White’s correction for standard errors is used. They find that ‘‘deflation has unpredictable effects on coefficient bias, heteroscedasticity, and


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estimation efficiency.’’ Subsequent tests do not indicate a problem with heteroscedasticity that influences the final results. 8. Industries are defined by two-digit SIC codes. 9. For the later years in the sample period, the cash flow variables (AVGOPCF, AVGFCF) could be collected directly from the cash flow statement. When the analysis is performed using this data, substantially more observations are available for years after 1988. However, the results for the test variables (RECRED, ITCRED) remain unchanged. Thus, the computed cash flow variables are used for the entire sample to maintain consistency. These results are shown. 10. Restricting the sample to only those firms with complete data for the 15-year estimation period would impart considerable survivorship bias into the sample selection. The intent and theoretical impact of the credits is to stimulate the level of the targeted activity throughout the economy, not just among those firms that are particularly long-lived. Therefore, each firm must have complete data for only a minimum of three years to be included in the sample. 11. The Compustat population yielded 17,069 observations over the sample period based on the requirement that each firm engage in both research and capital spending. Insufficient data for all the research variables reduced the sample to 15,380. The final sample was reduced to 13,162 by the requirement that each firm have a minimum of three observation years so that the fixed effect by firm could be estimated. 12. The two dependent variables (RDX and CAPX) are modeled as endogenous to the system. Empirical tests show this assumption to be correct. The null of exogeneity is rejected for both CAPX in the RDX model (p-valueo0.01) and RDX in the CAPX model (p-valueo0.01). 13. Section 179 expensing, also enacted in the 1981 legislation, was not retroactive and became effective for property placed in service beginning in 1982 (see Note 2).

ACKNOWLEDGMENTS We would like to thank Karen Pincus and Robert Walsh for comments on an earlier version of this paper, as well as workshop participants at the University of Arkansas, Louisiana State University, University of Tulsa and the American Accounting Association annual meeting.

REFERENCES American Assembly. (2000). Final Report of the Ninety-Fifth American Assembly. Reprinted in Penner, R. G, Sawhill, I. V., & Taylor, T. (2000). Updating America’s social contract: Economic growth and opportunity in the new century. New York: W.W. Norton & Company. American Enterprise Institute (AEI) for Public Policy Research. (1969). The investment tax credit: Should it be repealed? Washington, DC: AEI.

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Baber, W. R., Fairfield, P. M., & Haggard, J. A. (1991). The effect of concern about reported income on discretionary spending decisions: The case of research and development. The Accounting Review, 66(October), 818–829. Bailey, J. (2002). Stimulus plan offers some firms tax windfall. The Wall Street Journal, 219(April 9), B6. Barth, M., & Kallapur, S. (1996). The effects of cross-sectional scale differences on regressions results in empirical accounting research. Contemporary Accounting Research, 13(Fall), 527–567. Barth, M. E., Elliott, J. A., & Finn, M. W. (1999). Market rewards associated with patterns of increasing earnings. Journal of Accounting Research, 37, 387–413. Berger, P. G. (1993). Explicit and implicit tax effects of the R&D tax credit. Journal of Accounting Research, 31(Autumn), 131–171. Brozen, Y. (1961). The future of industrial research. Journal of Business, 34(October), 434–441. Chirinko, R. S. (1986). Business investment and tax policy: A perspective on existing models and empirical results. National Tax Journal, 39, 137–155. Chirinko, R. S., & Eisner, R. (1983). Tax policy and investment in major U.S. macroeconomic econometric models. Journal of Public Economics, 2(March), 138–167. Chirinko, R. S., Fazzari, S. M., & Meyer, A. P. (1999). How responsive is business capital formation to its user cost? An exploration with micro data. Journal of Public Economics, 74(October), 53–80. Clark, P. K., & Sichel, D. E. (1993). Tax incentives and equipment investment. Brookings Papers on Economic Activity, 1, 317–340. Cordes, J. J. (1989). Tax incentives and R&D spending: A review of the evidence. Research Policy, 18, 119–133. Cummins, J. G., & Hassett, K. A. (1992). The effects of taxation on investment: New evidence from firm level panel data. National Tax Journal, 45, 243–251. Cummins, J. G., Hassett, K. A., & Hubbard, R. G. (1996). Tax reforms and investment: A cross-country comparison. Journal of Public Economics, 62, 237–273. Curatola, A. P. (2002). Economic stimulus bill. Strategic Finance, 83(May), 17–18. Economic Recovery Act. (1981). Public Law 97-34 (August 13). Ellis, L. W. (1994). The effect of an investment tax credit on R&D spending. IEEE Transactions on Engineering Management, 41(May), 208–210. General Accounting Office (GAO). (1995). Tax policy: Additional information on the research tax credit, (May), Doc. No. T-GGD-95-161: Washington, DC. Grabowski, H. (1968). The determinants of industrial research and development: A study of the chemical, drug, and petroleum industries. Journal of Political Economy, 82(November/ December), 1119–1143. Gravelle, J. G. (1993). What can private investment accomplish? The case of the investment tax credit. National Tax Journal, 46(September), 276–291. Greene, W. H. (1990). Econometric analysis. New York: Macmillan Publishing Company. Guinet, J., & Kamata, H. (1996). Do tax incentives promote innovation? The OECD Observer, 202(Oct/Nov), 22–25. Hall, B., & Reenen, J. V. (2000). How effective are the fiscal incentives for R&D? A review of the evidence. Research Policy, 29, 449–469. Horwitz, B., & Kolodny, R. (1981). The FASB, the SEC and R&D. Bell Journal of Economics, 12(Spring), 249–262.


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Horwitz, B. N., & Kolodny, R. (1980). The economic effects of involuntary uniformity in the financial reporting of R&D expenditures. Journal of Accounting Research, 18, 38–74. Job Creation and Worker Assistance Act. (2002). Public Law 107-147 (March 8). Jobs and Growth Tax Relief Reconciliation Act. (2003). Public Law 108-27 (May 23). Joint Committee on Taxation (JCT). (2005). Overview of revenue estimating procedures and methodologies used by the staff of the Joint Committee on Taxation, (February 2). Kamien, M., & Schwartz, N. (1978). Self-financing of an R&D project. American Economic Review, 68(June), 252–261. Klassen, K. J., Pittman, J. A., & Reed, M. P. (2004). A cross-national comparison of R&D expenditure decisions: Tax incentives and financial constraints. Contemporary Accounting Research, 21(Fall), 639–680. Lev, B., & Sougiannis, T. (1996). The capitalization, amortization and value-relevance of R&D. Journal of Accounting and Economics, 21(February), 107–138. Leyden, D. P., & Link, A. N. (1993). Tax policies affecting R&D: An international comparison. Technovation, 13, 17–25. Russo, B. (2004). A cots-benefit analysis of R&D tax incentives. Canadian Journal of Economics, 37(May), 313–335. Shehata, M. (1991). Self-selection bias and the economic consequences of accounting regulation: An application of two-stage switching regression to SFAS No. 2. The Accounting Review, 66(October), 768–787. Sougiannis, T. (1994). The accounting based valuation of R&D. The Accounting Review, 69(January), 44–68. Tax Reform Act. (1986). Public Law 94-455 (October 4). Tillinger, J. W. (1991). An analysis of the effectiveness of the research and experimentation tax credit in a q model of valuation. Journal of the American Taxation Association, 13(Fall), 1–29.

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APPENDIX. TAXES AND INVESTMENT INCENTIVES: A SUMMARY OF SIGNIFICANT TAX CHANGES Climate

Years

Capital investment favored

1976–1980

Tax changes favorable to both capital and research spending

1981

1982–1985 1986–1990

Investment tax credit (ITC) available for purchases of tangible personal property Various methods of depreciation were allowed 20% bonus depreciation allowed Accelerated Cost Recovery System (ACRS) adopted Bonus depreciation disallowed Section 179 expense election of up to $5,000 ITC repealed ACRS replaced with modified ACRS Section 179 expensing increased to $10,000, phased out for total expenditures of over $200,000

Research Spending Research deduction allowed

Research and Experimentation (R&E) credit enacted R&E credit rate reduced

Notes: For both types of expenditures an election is required. Any amount taken as a credit is not available as a deduction.


Research investment favored

Capital Spending

SELF-EFFICACY AND TAX RESEARCH PERFORMANCE Dennis Schmidt and Rex Karsten ABSTRACT This study investigates the influence of tax research self-efficacy on tax research performance for a group of novice tax accountants. Tax research self-efficacy is a judgment of one’s ability to perform the specific tasks necessary to solve tax problems. Theory predicts that self-efficacy will be positively associated with task performance and people’s ability to cope with task difficulty. We tested this notion using a computer-based experimental approach to determine if novices with different levels of tax research selfefficacy perform differently when conducting a series of tax research tasks under difficult conditions. Our results, after controlling for certain performance-influencing factors, indicate that tax research self-efficacy is a significant predictor of tax research performance for novice tax accountants. This finding provides evidence of the construct validity of the tax research selfefficacy scale developed by Schmidt and Karsten (2000) and adds to our understanding of the factors that influence tax research performance.

INTRODUCTION Studies from accountants in both practice and academia advocate a major restructuring of accounting education, away from a content-driven focus and toward a skill-based curriculum (e.g., AECC, 1990; AICPA, 1999a, b; Advances in Taxation, Volume 17, 121–140 Copyright r 2007 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1058-7497/doi:10.1016/S1058-7497(06)17005-2

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DENNIS SCHMIDT AND REX KARSTEN

Albrect & Sack, 2000). These studies often stress the importance of developing novice accountants’ research skills. For example, the AICPA lists having strong research skills as a core functional competency for individuals entering the accounting profession (AICPA, 1999a), and it emphasizes the importance of research skills in its Model Tax Curriculum (AICPA, 1999b). Under the new computer-based CPA exam (see www.cpa-exam.org), candidates must do online searches of professional literature databases for some of the simulation testlets. For the Regulation section of the exam, candidates are expected to know how to solve simulation problems by searching the Internal Revenue Code and IRS Publication 17, with more databases (e.g., Treasury regulations) possibly to be added in the future. To be successful in practice, individuals must develop tax research skills that will enable them to deal with the complexity of the tax law. They must learn how to search efficiently through the morass of statutory, administrative, and judicial sources that make up the body of tax law, and must be able to evaluate this information critically. Because of the emphasis placed on novice accountants’ research skills by various accounting profession stakeholders, it is important to investigate factors that may influence novices’ tax research performance. This study investigates the influence of tax research self-efficacy on tax research performance for a group of novice accountants. Self-efficacy, a key element in social cognitive theory, is defined as a comprehensive appraisal of one’s perceived capability to perform a specific task (Bandura, 1997). Correspondingly, tax research self-efficacy is a judgment of one’s ability to perform the specific tasks necessary to solve tax problems. This investigation is an extension of a study by Schmidt and Karsten (2000), who developed a reliable, 32-item, tax research self-efficacy scale (see Exhibit 1). In the earlier study, the authors demonstrated the usefulness of a self-efficacy scale for training and outcomes assessment, but they did not test the scale’s predictive ability. The current study assesses the tax research self-efficacy scale’s predictive ability and concludes that it serves as a strong predictor of performance. This result provides evidence of the scale’s construct validity and makes a positive contribution to both the self-efficacy and tax research task literature. This paper is organized in the following fashion. We first review several empirical studies that have investigated the tax research task. The next section describes the self-efficacy construct and its link to performance. We then discuss tax research self-efficacy and state our hypothesis. The following two sections describe the research methods and discuss the results. In the final section of the paper, we state our conclusions, discuss implications and limitations, and make suggestions for future research.

Self-Efficacy and Tax Research Performance

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Exhibit 1. Tax Research Self-Efficacy Scale (Scale Items are Arranged by Skill Category). Establish Facts and Identify Issues I can identify all tax issues related to a set of facts I can identify which facts are necessary to resolve a tax issue I can distinguish between relevant facts and irrelevant facts when researching a tax issue I can determine if additional facts are necessary to resolve a tax issue Locate Relevant Authority I can locate Internal Revenue Code provisions that are relevant to a tax issue I can locate congressional committee reports that relate to statutory tax law I can locate regulations, rulings, and other administrative pronouncements that are relevant to a tax issue I can locate court cases that are relevant to a tax issue I can locate secondary tax authority that is relevant to a tax issue I can locate relevant tax authority using the index or table of contents of a commercial tax service I can locate relevant tax authority using the electronic search function of a commercial tax service Evaluate Authority I can evaluate the authoritative weight of Internal Revenue Code provisions I can evaluate the authoritative weight of congressional committee reports I can evaluate the authoritative weight of regulations, rulings, and other administrative pronouncements I can evaluate the authoritative weight of tax-related court cases I can evaluate the authoritative weight of secondary tax authority I can use a citator to ensure the reliability of tax-related court cases and revenue rulings Develop Conclusions and Recommendations I can develop defensible conclusions after researching a tax issue I can make appropriate recommendations after researching a tax issue Communicate Research Results I can communicate tax research results to a client I can communicate tax research results in a legal memorandum I can communicate tax research results in a protest letter to the IRS Demonstrate Knowledge of Tax Law Structure I can identify the sources of federal tax law I can distinguish between primary and secondary tax authority I can describe how statutory tax law is created I can distinguish between proposed, temporary, and final tax regulations I can describe the structure of the federal court system as it relates to tax cases I can describe how the Internal Revenue Code is organized I can trace the history of changes to the Internal Revenue Code Cite Authority I can provide the proper citation for Internal Revenue Code provisions I can provide the proper citation for regulations, rulings, and other administrative pronouncements I can provide the proper citation for tax-related court cases

Source: Schmidt and Karsten (2000).

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PRIOR TAX RESEARCH TASK STUDIES Tax research is the process of finding and communicating answers to specific tax issues by applying relevant tax authorities to a set of facts. Several prior studies have investigated the tax research task, each using a computer-based experimental approach. Cloyd (1995) examined the effects of prior knowledge on the information search and evaluation behaviors of tax professionals performing a complex tax research task. He found that prior knowledge affected the information search strategies used, the amount of relevant information located, and the ability to discriminate between relevant and nonrelevant information. Spilker (1995) investigated how time pressure and knowledge affect tax researchers’ ability to locate relevant key words from a commercial tax service’s index. He found that knowledge enhanced tax researchers’ ability to select relevant key words in a time-restricted task. Subjects with procedural knowledge responded more positively to time pressure than subjects without such knowledge. Cloyd (1997) investigated the joint effects of prior knowledge and accountability on performance in the information search phase of a tax research task. His results indicated that increases in effort duration improved search effectiveness regardless of prior knowledge. He also found that accountability had a positive influence on search effectiveness for the more knowledgeable subjects. Barrick (2001) examined the effect of Internal Revenue Code knowledge on tax research performance. His results indicated that experienced subjects were better able to use Code section knowledge in tax research than inexperienced subjects. He also found that subjects using a Code section search method (vis-a`-vis a topical method) retrieved more relevant authority than other subject groups. Roberts and Ashton (2003) demonstrated that tax research performance could be improved by exposure to declarative knowledge alone rather than via procedural knowledge acquired from practice and feedback. Subjects improved both their efficiency and effectiveness in tax research tasks following simple declarative knowledge intervention. The current study is consistent with the above studies in that it utilizes a computer-interactive experimental approach to investigate tax research performance. It extends prior research by investigating the influence of self-efficacy on tax research performance. This is the first study to explore the self-efficacy/performance link within the tax research domain. As such, it makes a positive contribution to both the self-efficacy and tax research task literature.


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SELF-EFFICACY AND PERFORMANCE Self-efficacy refers to the belief one has of the capability to perform specific tasks (Bandura, 1997). It is a well-researched and oft-validated construct with its origins in Social Cognitive Theory (Bandura, 1986). Self-efficacy is similar to self-confidence. Both constructs relate to the belief one has of one’s abilities. Self-efficacy is more situational in nature than self-confidence and could be described as task-specific self-confidence. Self-efficacy is a domain-specific, dynamic construct that changes over time as people acquire new information and experiences (Gist & Mitchell, 1992). It involves people’s belief in their capability to mobilize the motivation, cognitive resources, and courses of action needed to orchestrate performance on specific tasks (Wood & Bandura, 1989). Self-efficacy influences the choices people make, the effort they put forth, how long they persist, and how they feel (Pajares, 2004). Research indicates that self-efficacy is positively associated with people’s willingness to participate in tasks, expectations of success in such tasks, and persistence or effective coping behaviors when faced with task-related difficulties (Bandura, 1997). Social cognitive theorists and researchers have identified four sources of information that influence self-efficacy (see Bandura, 1997, for more extensive discussion and support). The cognitive appraisal and integration of the data provided by these information cues ultimately determines self-efficacy (Bandura, 1997; Gist, 1987). In decreasing order of value these include enactive mastery, vicarious experience, persuasion, and emotional or physical reactions. Enactive mastery is defined as repeated performance accomplishments. An individual’s own performances are the most reliable guides for assessing selfefficacy and have been shown to influence self-efficacy more than other information cues. In general, successes raise self-efficacy, and failures lower it. Vicarious experience (i.e., observational learning) is also beneficial, though slightly less influential, than actual performance. Individuals frequently acquire efficacy information by observing the performances of others. People who are similar (e.g., peers) offer the best basis for comparison (Schunk, 1987). Individuals who observe similar persons perform a task are likely to believe that they are capable of accomplishing it as well. Persuasion can also influence efficacy perceptions in some situations, though it is viewed as less effective than enactive mastery or observing others. For example, individuals often receive encouraging information from parents, teachers, and peers that they are capable of performing a task.

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Positive persuasive information raises self-efficacy, although this increase will be temporary if individuals subsequently perform poorly. Finally, individual perceptions of emotional or physiological reactions may also be used to assess performance capability. Strong emotional reaction to a task may provide information about anticipated success or failure. For example, high anxiety may reflect anticipated failure, while low anxiety may be interpreted as a sign of anticipated success. Individuals weigh, integrate, and evaluate information about their capabilities and then regulate their behavior accordingly (Gist, 1987). Previous studies have demonstrated a strong positive link between self-efficacy and performance – people with high self-efficacy for specific tasks typically outperform those with low self-efficacy (e.g., Wood & Bandura, 1989). In fact, numerous meta-analyses have found self-efficacy to be a powerful construct for predicting behavior ‘‘across diverse spheres of functioning’’ (Bandura & Locke, 2003, p. 87). For example, self-efficacy has been found to be a significant predictor of work-related performance (Stajkovic & Luthans, 1998; Sadri & Robertson, 1993), academic performance and persistence (Robbins, Lauver, Le, & Davis, 2004; Multon, Brown, & Lent, 1991), and athletic performance (Moritz, Feltz, Fahrbach, & Mack, 2000). In their discussion of self-efficacy and causality, Bandura and Locke (2003, p. 87) state that ‘‘[t]he evidence from these meta-analyses is consistent in showing that efficacy beliefs contribute significantly to the level of motivation and performance.’’ In their response to the contention that selfefficacy is merely a reflection of prior performance, Bandura and Locke (2003, p. 89) note that ‘‘[t]his claim has long lost its credibility by evidence from countless studies demonstrating that perceived self-efficacy contributes independently to subsequent performance after controlling for prior performance and indices of ability.’’ In summary, the research studies cited above make a strong case that self-efficacy has a causal impact on performance. Although prior studies have demonstrated that the positive relationship between self-efficacy and performance is robust, certain variables may moderate this relationship. For example, Stajkovic and Luthans (1998), in a meta-analysis of 114 studies, demonstrated that task complexity moderated the relationship – the higher the task complexity, the weaker the relationship between self-efficacy and performance. Tax research is a complex, multifaceted process. Therefore, it is important to investigate if the positive link between self-efficacy and performance applies to the tax research domain. No previous study has addressed this issue. In addition, Bandura (2001) notes that self-efficacy scales must be targeted to factors that have impact on


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the domain of functioning in order to yield a predictive relationship. Thus, it is also important to investigate whether the multidimensional tax research self-efficacy scale developed by Schmidt and Karsten (2000) has predictive ability.

TAX RESEARCH SELF-EFFICACY Tax research self-efficacy is a judgment of one’s ability to perform the specific tasks necessary to solve tax problems. The tax research process involves establishing facts and identifying issues, locating relevant authority, evaluating authority, developing conclusions and recommendations, and communicating research results (Karlin, 2003; Raabe, Whittenburg, Sanders, & Bost, 2003). To be effective, tax researchers must also understand the complex structure of tax law and know how to cite authority properly. These are the skills that are captured in the 32-item tax research self-efficacy scale developed by Schmidt and Karsten (2000). This scale appears in Exhibit 1, with the 32 items arranged by skill category. In their study, Schmidt and Karsten (2000) advocated using a tax research self-efficacy scale as a tool for both training diagnostics and outcomes assessment. They administered the instrument to two groups of students in their second undergraduate tax course, once at the beginning of the semester (pretest) and again six weeks later (posttest). The treatment group received additional training in tax law structure and completed two tax research exercises during the six-week test period. The control group received no additional tax research training and did not conduct any tax research exercises during the test period. All but one of the subjects had completed a tax research project in the first tax course. Mean pretest self-efficacy scores, as expected, were moderate for both groups with no significant difference between the groups. For training diagnostic purposes, the 32 items of the tax research self-efficacy scale were rank ordered based on their relative pretest means. The treatment group instructor used this ranking to determine what topics to highlight in a brief training session and to design some of the questions for the tax research exercises. To assess the outcomes of the treatment intervention, the mean posttest self-efficacy score was compared to the mean pretest score for each group. The posttest score increased significantly for the treatment group, while it decreased insignificantly for the control group. The authors concluded that the scale proved useful in identifying training needs and in assessing the outcomes of the treatment intervention.

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HYPOTHESIS Schmidt and Karsten (2000) demonstrated that their tax research selfefficacy scale had a high reliability coefficient (Cronbach’s a ¼ 94). Factor analysis also indicated that the scale captured the multiple dimensions of the tax research process. They did not, however, directly measure their subjects’ tax research performance. Thus, their study did not test the scale’s predictive ability. Bandura (1997, 2001) stresses that a self-efficacy scale should demonstrate construct validity. He states that construct validation is a process of hypothesis testing, and that substantiation of predicted effects provides evidence of a scale’s construct validity. He further asserts that people with high self-efficacy should differ from those with low self-efficacy in distinct ways. For example, a high (low) level of domain-specific self-efficacy should be associated with a high (low) level of domain-specific task performance. Bandura and Locke (2003, p. 89) underscore the fact that self-efficacy contributes independently to subsequent performance after controlling for prior performance and ability. This principle assumes that a valid and reliable scale is used when measuring domain-specific self-efficacy. The interitem reliability of a scale can be assessed statistically using Cronbach’s a or a similar procedure. The ability of a scale to predict behavior or performance provides evidence of its validity. As noted earlier, researchers have demonstrated that self-efficacy is a significant predictor of performance in a variety of domains (e.g., Robbins et al., 2004; Moritz et al., 2000; Stajkovic & Luthans, 1998; Sadri & Robertson, 1993; Multon et al., 1991). However, no one prior to this study has investigated the predictive ability of self-efficacy within the tax research arena. Heeding Bandura’s call for hypothesis testing of predicted effects and based on prior research in other domains, we experimentally tested the following hypothesis: Hypothesis. Tax research self-efficacy is a significant predictor of tax research performance for novice tax accountants, after controlling for other performance-influencing factors.

RESEARCH METHOD Subjects The subjects for the experiment were 41 seniors and graduate accounting students at a mid-size state university. All 41 subjects had completed an


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introductory income tax course and conducted a tax research project in that course using the Web-based RIA Checkpoint commercial tax service. These students were novice tax accountants with similar course-related tax research experience and little or no professional work experience.1 Twenty-six subjects were enrolled in a Volunteer Income Tax Assistance (VITA) course. The remaining 15 subjects were enrolled in a tax research and planning course. Both courses were held in a computer laboratory, which facilitated the experiment. Participation in the experiment for the VITA students was voluntary, and each volunteer received $5 cash compensation. The students in the tax research and planning course participated in the experiment on the first day of class as an in-class exercise and received points equivalent to a homework assignment. The VITA and tax research and planning students were very comparable. T-tests indicated no significant differences between them on their mean tax research performance measure, self-efficacy score, grade in the introductory tax course, overall GPA, or gender makeup. Self-Efficacy Measure The experiment took place in a computer laboratory. The subjects first completed a questionnaire that contained the 32 items of the tax research self-efficacy scale and some demographic and background questions. Unlike the scale in Exhibit 1, the items appeared in random order on the questionnaire with no headings. The questionnaire instructed the subjects to indicate the extent to which they believed they could perform each of the specified tasks using a 0–10 scale for each task. A graph illustrated the 11-point scale with endpoints of 0 (‘‘cannot do’’) and 10 (‘‘certain can do’’) and a midpoint of 5 (‘‘moderately certain can do’’). This 11-point response scale is consistent with Bandura’s (2001) scale-construction guidelines. The entire questionnaire took most subjects about six minutes to complete. A portion of the selfefficacy measure section of the questionnaire appears in Exhibit 2. Overall, the 32-item self-efficacy scale exhibited a high reliability coefficient (Cronbach’s a ¼ 0.95). Individual scale items ranged from a low of 2.95 (evaluating committee reports) to a high of 6.71 (locating regulations and rulings). For hypothesis testing purposes, we used the mean response across all 32 items of the scale to measure the tax research self-efficacy score for each subject. Thus, self-efficacy scores could have ranged anywhere from 0 to 10. Because of their prior, though limited, experience with the tax research process, we expected the subjects to possess at least moderate levels of tax research self-efficacy. As indicated in Table 1, self-efficacy scores ranged from a low of 2.91 to a high of 8.63 with a (moderate) mean of 5.18.

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Exhibit 2. Tax Research Self-Efficacy Measure. For each of the 32 statements below, indicate the extent to which you believe you can perform the specified task. Use the following 0–10 scale: 0 m Cannot do

1

2

3

4

5 6 m Moderately certain can do

7

8

9

10 m Certain can do

The following statements relate to your ability to conduct tax research: 1. ___I can describe how the Internal Revenue Code is organized 2. ___I can locate secondary tax authority that is relevant to a tax issue 3. ___I can evaluate the authoritative weight of congressional committee reports >>>>>>>>>>(skip to end of statements) 30. ___I can identify all tax issues related to a set of facts 31. ___I can communicate tax research results in a legal memorandum 32. ___I can provide the proper citation for tax-related court cases


For example, if you believe you cannot do the specified task, record a response of 0. If you are 100% certain you can do the specified task, record a response of 10. If your belief is somewhere in-between, record a response of 1–9 based on the strength of your belief. Please indicate your responses on the blank line next to each statement.


Table 1. Variable Continuous Variables Tax research performancea Tax research self-efficacyb Income tax gradec Variable

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Descriptive Statistics (n ¼ 41). Minimum

Maximum

Mean

Standard Deviation

0 2.91 2.00

28 8.63 4.00

13.98 5.18 3.15

5.79 1.36 0.64

Frequency

Percent

Coded

Categorical Variables Gender Male Female

13 28

32% 68%

0 1

Took Advance Tax No Yes

16 25

39% 61%

0 1

a

Number of correct points out of 35 possible points for the tax research exercises. Mean score of the 32-item self-efficacy scale with a response range between 0 and 10. c Grade in the introductory income tax course on a 4-point scale. b

Tax Research Performance Measure After completing and turning in the self-efficacy questionnaire, the subjects next logged on to the Web-based (checkpoint.riag.com) RIA Checkpoint commercial tax service. Each person logged on with a unique username and password. The subjects were then given another handout that contained 12 typed research exercises with room for hand-written responses. The exercises were based on short problems and examples from two popular tax research textbooks (Karlin, 2003; Raabe et al., 2003). Each exercise contained a brief statement of facts followed by multiple questions. For example, one exercise was about a soldier who served for eight months in the Iraqi War at a salary of $1,500 per month. The subjects had to determine how much, if any, of the salary was taxable, and they had to provide a complete citation to an Internal Revenue Code section that supported their conclusion. One point was awarded for locating the relevant statutory authority, another for stating the correct conclusion after evaluating the authority, and the third for providing the proper citation. Thus, for the Iraqi War exercise, 3 points were possible. For the 12 exercises, a total of 35 points was possible, due to the multiple parts of each exercise. Some exercises required the subjects to provide specific supporting authority, such

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as a Code section, regulation, revenue ruling, or court decision. Other exercises allowed the specification of any relevant authority. The subjects also had to use a citator. To avoid awarding points for conclusions based on guessing, points were given for correct conclusions only if relevant authority supported them. The 12 research exercises were individually moderate in difficulty level, but the subjects only had 60 minutes to complete them. They were instructed to answer as many of the 12 exercises that they could in the time allowed, and that they did not have to answer the questions in the order they appeared on the handout. Imposing a 60-minute limit added time-pressure stress to the experiment and significantly increased the difficulty of the experimental task. We did this by design for two reasons. First, theory predicts a positive association between self-efficacy and persistence or effective coping behaviors when faced with task-related difficulty (Bandura, 1997). We wanted to make certain that the experimental task had a high difficulty level. Second, we wanted to avoid uniformly high performance scores and low response variance. The experimental task was designed so that only a highly skilled tax researcher could achieve a high performance score. Less skillful researchers would score lower on the performance spectrum according to their relative skill levels. There were 35 possible points for the 12 exercises. As shown in Table 1, the subjects’ performance scores ranged from 0 to 28 points with a mean of 13.98 and a standard deviation of 5.79.2 These scores reflect the general difficulty of the experimental task and the broad differences in individual performance levels. Control Variables Although the primary objective of this study was to investigate the influence of tax research self-efficacy on tax research performance, we were also interested in looking at other factors that may influence performance and controlling for those factors. As pointed out by Bandura and Locke (2003), prior performance and ability should be controlled for when assessing the influence of self-efficacy on subsequent performance. Accordingly, we asked the subjects to provide their grade in the introductory income tax course, participation in an advanced tax course, and gender.3 Descriptive statistics for the control variables appear in Table 1. All 41 subjects had completed an introductory income tax course, in which they had conducted a tax research project. Their grade in that course provided a measure of general income tax knowledge and ability. Grades for the introductory income tax course ranged from 2.00 to 4.00 on a 4-point scale, with a


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mean of 3.15. We believed that involvement in an advanced tax course would increase subjects’ knowledge of the tax law and possibly their tax research experience. Twenty-five (61%) subjects had taken an advanced tax course that dealt primarily with corporations and partnerships. There was no formal research project in that course, but the subjects were exposed to more tax law and had to prepare both a corporate and partnership tax return. In addition, inconsistent findings regarding the relationship of gender and self-efficacy in prior research studies (Bandura, 1997; Pajares, 2002) compelled us to test for a gender effect. Gender makeup was 13 (32%) males and 28 (68%) females.

RESULTS AND DISCUSSION Table 2 lists the Pearson correlation coefficients for the variables of interest investigated in this study. Self-efficacy, grade in the income tax course, and participation in an advanced tax course were all positively, significantly correlated with tax research performance.4 Gender was not significantly correlated with performance, but it was with self-efficacy. Females generally exhibited higher self-efficacy scores than males. Although grade in the income tax course and participation in an advanced tax course were significantly correlated with performance, neither was significantly correlated with self-efficacy.5 Bandura and Locke (2003) point out that self-efficacy is not merely a reflection of prior performance. It appears that these tax course variables were not significant sources of information that influenced the subjects’ tax research self-efficacy, even though they were associated with performance. This finding supports Bandura and Locke’s (2003) contention that self-efficacy contributes to subsequent performance independently of prior performance and ability. The significant correlation between gender and self-efficacy is interesting. As mentioned previously, prior research into the relationship between gender Table 2.

Self-efficacy Income tax grade Gender Took advanced tax

Correlations.

Performance

Self-Efficacy

Income Tax Grade

Gender

0.42 0.44 0.24 0.38

0.09 0.34 0.06

0.28 0.04

0.12

Significant at the 0.01 level. Significant at the 0.05 level.

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and self-efficacy has provided inconsistent findings, with gender effects ‘‘disappearing’’ after controlling for other factors, such as prior academic achievement (Pajares, 2002). The findings here are in keeping with selfefficacy principles and may reflect trends in college enrollments and hiring. Recent surveys indicate that approximately 57% of accounting majors are female, with that percentage reflected in the employment of accounting graduates as well (AICPA, 2004; Hermanson, Hill, & Ivancevich, 2002). In this study, 68% of the participants were female. Since observation of others’ success (a substantial majority of subjects were female) is a valuable source of self-efficacy information, the findings are supported by theory and research (Bandura, 1997). Even though gender was not significantly correlated with tax research performance, we retained it as a control variable in the regression analysis because of its significant association with self-efficacy in this study. This allowed us to partial out any gender effects when investigating the influence of tax research self-efficacy on tax research performance. We tested the hypothesis that tax research self-efficacy is a significant predictor of tax research performance using hierarchical regression analysis (Cohen & Cohen, 1983). This method facilitates the analysis of the incremental contribution of self-efficacy on performance beyond the level explained by the control variables. The dependent variable for the hierarchical regression analysis was tax research performance. Grade in the introductory income tax course, participation in an advanced tax course, and gender served as control variables. The independent variable of interest was tax research self-efficacy.6 Table 3 reports the results of the hierarchical regression analysis. The three control variables entered the regression model in Step 1. This block of variables explained 31% of the variance associated with tax research performance (p ¼ 0.001). Tax research self-efficacy entered the model in Step 2. This variable, along with the control variables, explained 40% of the variance associated with performance (p ¼ 0.000). The coefficient for the self-efficacy variable was highly significant (t ¼ 2.65; p ¼ 0.012), as was the incremental increase in explanatory power when self-efficacy entered the model (incremental R2 ¼ 0.10; F ¼ 7.03; p ¼ 0.012). The findings of the hierarchical regression analysis strongly support our hypothesis. Tax research self-efficacy is a significant predictor of tax research performance for novice tax accountants, even after controlling for other performance-influencing factors. The subjects’ perceived ability to conduct tax research closely mapped their actual performance, independently of other influences. This finding of strong predictive ability for the tax research self-efficacy scale substantially enhances the scale’s construct


Table 3. Variable

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Hierarchical Regression Analysis (Dependent Variable ¼ Tax Research Performance). b

Std. Error

Step 1: Control Variables Only Constant 1.02 3.92 Control Variables: Income tax grade 3.38 1.24 Took advanced tax 4.56 1.56 Gender 2.28 1.70 R2 ¼ 0.36; Adjusted R2 ¼ 0.31; F ¼ 6.88 (p ¼ 0.001) Step 2: Control Variables and Self-Efficacy Constant 7.52 4.38 Control Variables: Income tax grade 3.42 1.15 Took advanced tax 4.14 1.46 Gender 0.75 1.68 Self-efficacy 1.48 0.56 R2 ¼ 0.46; Adjusted R2 ¼ 0.40; F ¼ 7.76 (p ¼ 0.000) Incremental R2 ¼ 0.10; F ¼ 7.03 (p ¼ 0.012)

Beta

0.37 0.39 0.19

0.38 0.35 0.06 0.35

t

Sig.

0.26

0.796

2.72 2.92 1.34

0.010 0.006 0.187

1.72

0.095

2.97 2.84 0.45 2.65

0.005 0.007 0.657 0.012

validity. Validation of the tax research self-efficacy scale developed by Schmidt and Karsten (2000) is a major contribution of this study. Another contribution this study makes to the general self-efficacy literature is that it provides evidence that self-efficacy for a complex task like tax research can be successfully measured. The results of this study also add to our understanding of factors that influence tax research performance. Prior tax research task studies primarily have investigated the effects of knowledge and experience on tax research performance. Cloyd (1995, 1997) used 18 multiple-choice questions regarding partnerships as his measure of knowledge. Spilker (1995) used 10 true– false and multiple-choice questions regarding partnerships as his measure of declarative tax knowledge. He used tax work and research experience as his measure of procedural tax knowledge. Barrick (2001) did not measure Code section knowledge directly. Instead, he used work experience as a proxy for such knowledge. The current study did not investigate tax work experience as a variable of interest because all the subjects had little or no professional work experience. Participation in an advanced tax course, which did vary across subjects, served as an experience variable in this study. Regarding knowledge, the current study did not directly test the subjects’ knowledge about a particular subject (e.g., partnerships) because the tax research

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performance tasks involved 12 different subject areas. Instead, this study used grade in the introductory income tax course as a measure of general tax knowledge. Subjects who took the advanced tax course also had an opportunity to increase their knowledge of tax law. The significant positive association between the tax course variables and the tax research performance measure support prior research related to the influence of knowledge and experience on performance. Demonstrating that tax research self-efficacy is a significant predictor of tax research performance after controlling for general tax knowledge and experience factors makes an important contribution to the tax research task literature.

CONCLUSIONS, IMPLICATIONS, LIMITATIONS, AND FUTURE RESEARCH The primary purpose of this study was to investigate the influence of tax research self-efficacy on tax research performance for a group of novice accountants. This is the first study to explore the self-efficacy/performance link within the tax research domain. The results indicate that tax research self-efficacy is a strong predictor of tax research performance, even after controlling for other performance-influencing factors. The findings of this study provide evidence of the construct validity of the 32-item tax research self-efficacy scale developed by Schmidt and Karsten (2000) and add to our understanding the factors that influence tax research performance. This study has implications for tax educators. Based on our results, we believe that the tax research self-efficacy scale is a very useful tool for assessing the general tax research skill level of people. Higher (lower) selfefficacy scores are generally related to higher (lower) tax research performance levels. Prior research indicates that well-designed self-efficacy measures offer practical advantages and additional insights beyond the use of direct performance measures alone (Bandura, 1997). The tax research self-efficacy scale can be administered in a few minutes. The scale is also transparent and ‘‘user-friendly,’’ providing individuals with a realistic preview of the skills (via the scale items) necessary to conduct tax research. While a direct performance measure may indicate whether a person succeeds or fails on a given research project, it may provide less information regarding the factors contributing to the performance outcome. By comparison, educators can analyze the 32 individual tax research self-efficacy scale items to determine specific areas of the tax research process where people are struggling or where future training could be improved.


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Administering the scale in different college-level tax courses at various times could be beneficial for both training diagnostic and outcomes assessment purposes. Consider, for example, the first tax course in which students engage in tax research activities. Administering the scale subsequent to the conclusion of those activities would give faculty a sense of the general tax research skill level of their students. The results could also be compared to previous semesters’ results in a benchmarking fashion. For courses in which the students have had prior exposure to the tax research task, instructors can administer the scale early in the semester to determine specific areas where students are weak and in need of additional training. Another approach would be to administer the scale both early (pretest) and late (posttest) in the semester. This would allow faculty to assess improvement during the semester of their students’ (perceived) tax research skills. Recruiters of tax professionals may find the tax research self-efficacy scale to be a useful tool when screening applicants. In addition, instructors who conduct in-house training sessions for their firms may find the scale beneficial for assessing the tax research abilities of novice staff accountants and for identifying training needs. This study also has implications for academic researchers. Prior studies have demonstrated that tax research performance is affected by factors such as knowledge (Cloyd, 1995, 1997; Spilker, 1995) and experience (Spilker, 1995; Barrick, 2001). Given its strong, independent influence on tax research performance, academics should consider including a tax research self-efficacy measure as a predictor or control variable when conducting tax research task studies. This was an exploratory study, and it has some limitations that may affect its generalizability. First, the subjects for the experiment were not randomly selected, and they may not be representative of other novice accountants with basic tax research experience. Second, the subject pool was restricted to students representing novice tax accountants. The results may have been different with other subjects, such as experienced tax practitioners. Third, the experimental task consisted of selected tax research exercises and was time-constrained. The results may not be generalizable to other tax research activities or to tasks with relaxed time constraints. To improve generalizability, we suggest that future studies expand the subject pools and vary the experimental tasks. Another suggestion for future research is to investigate if components of the tax research self-efficacy scale (e.g., ability to locate relevant authority) are correlated to components of actual research performance. We also suggest that future research directly tests tax research

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self-efficacy and task-specific tax knowledge (e.g., tax code knowledge), rather than general tax knowledge. Finally, because of the positive self-efficacy/performance link and the favorable motivational aspects of high self-efficacy, we encourage tax educators to develop teaching and training techniques that will increase people’s tax research self-efficacy. As outlined above, prior self-efficacy research (see Bandura, 1997; Pajares, 2004) has identified the most valuable sources of self-efficacy information (e.g., enactive mastery, vicarious experience, persuasion), as well as the most effective modes of delivery (e.g., planned success, modeled behavior, credible persuader). The challenge is to apply these resources to the tax research domain. This is an area ripe for future academic research studies. Self-efficacy influences the effort people put forth, how long they persist, their expectations of success, and how they cope with difficulties. Discovering ways to increase people’s tax research self-efficacy will make them better tax researchers.

NOTES 1. Only two subjects had any tax-related work experience, both involving a summer internship and the preparation of basic S corporate returns. There was no significant correlation between work experience and tax research performance or between work experience and tax research self-efficacy. 2. Two subjects scored 0 on the performance task (the next lowest score was 5). Their self-efficacy scores were 2.91 and 5.03. Analysis of their search histories indicated that they conducted numerous searches of the RIA Checkpoint databases during the 60-minutes experiment. They did not, however, record any responses on the answer sheet. The results of this study do not change if these two subjects are eliminated from the regression analyses. 3. We also asked the subjects for their overall undergraduate GPA and class standing (undergraduate or graduate). Neither of these variables was significantly correlated with tax research self-efficacy or tax research performance, so we excluded them from the regression analysis. The results of this study do not change if these two variables are included in the analysis. 4. The correlation between self-efficacy and performance (r ¼ 0.42) compares favorably to the results of Stajkovic and Luthans (1998). They conducted a meta-analysis of 114 studies that examined the relationship between self-efficacy and work-related performance. Their results indicated a significant weighted average correlation between self-efficacy and performance of G(r+) ¼ 0.38. 5. Grade in the income tax course and participation in an advanced tax course were not significantly correlated with each other. At the university where the study was conducted, nearly every accounting major takes the advanced tax course, regardless of his/her grade in the introductory class. The reason why only 61% of the subjects had taken the advanced tax course is due exclusively to the timing of when


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we conducted the experiments. By the time they graduated, 100% of the subjects in our study had completed the advanced tax course. 6. We also tested for interaction effects between self-efficacy and the three control variables, but none of the interaction terms was significant.

ACKNOWLEDGMENTS The authors would like to thank the two anonymous reviewers for their helpful comments and the University of Northern Iowa for its financial support.

REFERENCES Accounting Education Change Commission (AECC). (1990). Objectives of education for accountants: Position statement number one. Issues in Accounting Education, 5(2), 307–312. Albrect, S., & Sack, R. (2000). Accounting education: Charting the course through a perilous future. Sarasota, FL: American Accounting Association. American Institute of Certified Public Accountants (AICPA). (1999a). Core competency framework for entry into the accounting profession. New York, NY: AICPA. Available online at http://www.aicpa.org/edu/corecomp.htm. American Institute of Certified Public Accountants (AICPA). (1999b). Model tax curriculum. New York, NY: AICPA. American Institute of Certified Public Accountants (AICPA). (2004). The supply of accounting graduates and the demand for public accounting recruits–2004. New York, NY: AICPA. Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ: Prentice-Hall. Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: WH Freeman. Bandura, A. (2001). Guide for constructing self-efficacy scales. Available from Albert Bandura, Department of Psychology, Stanford University, Stanford, CA 94305–2130. Bandura, A., & Locke, E. A. (2003). Negative self-efficacy and goal effects revisited. Journal of Applied Psychology, 88(1), 87–99. Barrick, J. A. (2001). The effect of Code section knowledge on tax-research performance. Journal of the American Taxation Association, 23(2), 20–34. Cloyd, C. B. (1995). Prior knowledge, information search behaviors, and performance in tax research tasks. Journal of the American Taxation Association, 17(Supplement), 82–107. Cloyd, C. B. (1997). Performance in tax research tasks: The joint effects of knowledge and accountability. The Accounting Review, 72(1), 111–131. Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates. Gist, M. E. (1987). Self-efficacy: Implications for organizational behavior and human resource management. Academy of Management Review, 12(3), 472–485. Gist, M. E., & Mitchell, T. R. (1992). Self-efficacy: A theoretical analysis of its determinants and malleability. Academy of Management Review, 17(2), 183–211.

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Hermanson, H. M., Hill, M. C., & Ivancevich, S. H. (2002). Who are we hiring? Characteristics of entrants to the profession. CPA Journal, 72(8), 67–69. Karlin, B. H. (2003). Tax research (2nd ed.). Upper Saddle River, NJ: Prentice-Hall. Moritz, S. E., Feltz, D. L., Fahrbach, K. R., & Mack, D. E. (2000). The relation of self-efficacy measures to sport performance: A meta-analytic review. Research Quarterly for Exercise and Sport, 71(3), 280–294. Multon, K. D., Brown, S. D., & Lent, R. W. (1991). Relation of self-efficacy beliefs to academic outcomes: A meta-analytic investigation. Journal of Counseling Psychology, 38, 30–38. Pajares, F. (2002). Gender and perceived self-efficacy in self-regulated learning. Theory into Practice, 41(2), 116–125. Pajares, F. (2004). Information on self-efficacy. Available online at http://www.emory.edu/ EDUCATION/mfp/self-efficacy.html. Raabe, W. A., Whittenburg, G. E., Sanders, D. L., & Bost, J. C. (2003). West’s federal tax research (6th ed.). Mason, OH: Thomson South-Western. Robbins, S. B., Lauver, K., Le, H., & Davis, D. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130(2), 261–288. Roberts, M. L., & Ashton, R. H. (2003). Using declarative knowledge to improve information search performance. Journal of the American Taxation Association, 25(1), 21–38. Sadri, G., & Robertson, I. T. (1993). Self-efficacy and work-related behavior: A review and meta-analysis. Applied Psychology: An International Review, 42(2), 139–152. Schmidt, D., & Karsten, R. (2000). Using a self-efficacy scale for training and outcomes assessment: A tax research example. Academy of Educational Leadership Journal, 4(2), 81–95. Schunk, D. H. (1987). Peer models and children’s behavioral change. Review of Educational Research, 57(2), 149–174. Spilker, B. C. (1995). The effects of time pressure and knowledge on key word selection behavior in tax research. The Accounting Review, 70(1), 49–70. Stajkovic, A. D., & Luthans, F. (1998). Self-efficacy and work-related performance: A metaanalysis. Psychological Bulletin, 124(2), 240–261. Wood, R. E., & Bandura, A. (1989). Impact of conceptions of ability on self-regulatory mechanisms and complex decision making. Journal of Personality and Social Psychology, 56(3), 407–415.

DETERMINING INNOCENCE IN INNOCENT-SPOUSE COURT CASES USING LOGIT/PROBIT ANALYSIS Gerald E. Whittenburg, Ira Horowitz and William A. Raabe ABSTRACT This paper examines the decision criteria used by federal courts to adjudicate equitable innocent-spouse relief, when such relief has previously been denied by the Internal Revenue Service (IRS). Empirical logit/ probit regression is used, rather than traditional legal analysis. Specifically, we determine which of the equitable-relief criteria detailed in the innocent-spouse rules did affect judicial decisions during our sample period. We also determine the relative importance of the factors. Using these data, taxpayers and their advisors can better decide whether to pursue further litigation, and how best to tailor the pertinent arguments.

It is generally advantageous for a married couple to file a joint income-tax return, regardless of individual contributions to the family’s taxable income. When the taxable income is underreported, perhaps unintentionally, the result is an underpayment of that year’s income-tax obligation that may eventually be detected in an Internal Revenue Service (IRS) tax audit. The IRS then assesses the couple for the unpaid balance, plus any interest and penalties. Advances in Taxation, Volume 17, 143–165 Copyright r 2007 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1058-7497/doi:10.1016/S1058-7497(06)17006-4

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GERALD E. WHITTENBURG ET AL.

Occasionally, one of the spouses requests ‘‘equitable relief’’ from the additional tax payment, on the grounds that she/he is an ‘‘innocent spouse’’; e.g., because the non-requesting spouse has a legal obligation to pay any additional taxes under a divorce decree, and because the requesting spouse has made a good-faith effort to comply with the income-tax rule. Equitable relief in this context was created in its present form with y6015 of the IRS Restructuring and Reform Act of 1998 (P. L. 105206, July 22, 1998). Should the IRS deny the request, the spouse has recourse to the courts, and the reasons for a court’s final disposition of the matter are spelled out in the written decision. Innocent-spouse cases filed with the courts, however, are rarely black or white, and are seen differently through the eyes of the IRS beholder and those of the requesting spouse filing the case. This paper analyzes innocentspouse cases in an attempt to both isolate the qualifying criteria that, regardless of other considerations, have actually proved to be determinative in the courts’ resolution of those cases, and to estimate the relative importance of those criteria in the courts’ decision processes. In the course of doing so, we can isolate those criteria that have at best played a tangential role in the decision process, even if given a gratuitous voice in a court’s decision. We attack the problem through logit/probit analysis, which has previously been shown to be effective in exploring accounting (e.g., Ohlson, 1980) and taxation (e.g., Stewart, 1982; Ayres, Cloyd, & Robinson, 1996; Cushing & Arguea, 1999) issues, as well as in the determination of the factors that underlie legal decisions (e.g., Conlon & Sullivan, 1999; Steffensmeier & Demuth, 2000; Schneider, 2002). Nonetheless, we acknowledge at the outset that, with Jordan and Holland (1984, p. 75) initiating the debate in reaction to a paper by Englebrecht and Rolfe (1982) that employed the related technique of discriminant analysis in a judicial setting, some would argue that the statistical approach is an inappropriate and ‘‘inadequate substitute for more traditional tax research methods.’’ As Englebrecht and Rolfe (1984, p. 83) counter, however, the statistical approach complements the legal approach insofar as it may ‘‘detect patterns often hidden by the complexities of the tax law’’ and thus can ‘‘aid taxpayers in interpreting relevant judicial positions.’’ Logit/probit analysis, in particular, permits one to estimate the likelihood of a successful outcome, whereas discriminant analysis only produces a separation between success and failure. This paper provides support for Englebrecht and Rolfe’s (1984) position in showing logit/probit analysis to be useful in regard to both pattern detection and interpretation with respect to the important innocent-spouse tax provision, in guiding taxpayers and their advisors, so that the offer of equitable relief can be applied as Congress and the courts intend. Notably, we

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find that only three of the eight criteria that the courts might otherwise be presumed to consider in deciding who is an innocent spouse are actually salient. This important inference has further implications beyond any strategy-setting concerns, because comparable results, elicited through the same research methods employed here, may obtain in other such settings as well.

PRIOR LAW Income tax on a joint return is computed on a married couple’s aggregate income, and the spouses are jointly and severally liable for the tax [y6013(d)(3)]. In general, each spouse is potentially liable for the full tax or any deficiency in tax, penalties, or interest. If, however, one spouse is qualified as an innocent spouse, she/he can be relieved of certain tax liabilities attributable to the other spouse. Prior to July 23, 1998, a spouse could be relieved of a tax liability on a joint return only if each of the following conditions was met. An inability to pay one’s share of the additional tax assessment did not normally qualify a taxpayer for relief as an innocent spouse unless: a joint return is filed; there is a substantial (i.e., in excess of $500) understatement of the tax liability, attributable to grossly erroneous items of one spouse, i.e., there is no basis in the facts or law for the deduction or omission of the item from income [y6013(e)(3), as of December 31, 1997]; the understatement of the tax liability exceeded 25 percent of AGI (10 percent if AGI for the year did not exceed $20,000) [y6013(e)(4), as of December 31, 1997]; the other spouse did not know, and had no reason to know, that there was a substantial understatement of the liability at the time the return was signed; and, it would be inequitable to hold the requesting spouse liable for the deficiency attributable to the substantial understatement, taking into account all facts and circumstances.

CURRENT LAW The IRS Restructuring and Reform Act of 1998 broadened the prospects for relief from joint-and-several liability for a requesting spouse who has filed a joint income-tax return. The old y6013(e) was replaced by a new y6015,

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which extensively revised the innocent-spouse rules for the first time in many years. In general, the new statute brought about the following three changes. (1) All of the AGI thresholds were eliminated. (2) The general requirements for a requesting spouse to qualify for relief were clarified. (3) A new partial-relief election was allowed for taxpayers who no longer are married. General Innocent-Spouse Requirements A requesting spouse can be relieved of a tax liability (including interest, penalties, and other amounts) as an innocent spouse, if the following conditions are met [y6015(b)]. (1) A joint income-tax return is filed for the tax year. (2) There is an understatement of the income-tax liability on the return that is attributable to erroneous items by the other spouse. (3) The requesting spouse establishes that, in signing the return, she/he neither knew nor had reason to know of the understatement. (4) Taking into account all the facts and circumstances, it would be inequitable to hold the requesting spouse liable for the deficiency attributable to the understatement. (5) The requesting spouse elects the benefits of the innocent-spouse provision in the manner that the IRS prescribes on Form 8857, within two years after the date on which the IRS has begun collection activities. This usually happens as part of an IRS audit and does not require a formal assessment. The taxpayer need not exhaust administrative remedies before she/he can request relief as an innocent spouse. The understatement of tax includes all items that would be included on the joint Form 1040, including any self-employment and alternative minimum taxes. There must, however, be an unpaid amount for the innocent-spouse rules to apply; the provisions cannot be used after a tax balance has been paid to reallocate liabilities between the spouses, e.g., in the context of a divorce or death. Effects of community-property laws are ignored for purposes of the innocent-spouse rules [y6015(a)]. The offended spouse can petition for a review by the Tax Court of the results of the relief allowed by the IRS [y6015(e)]. This provision has resulted in a sizable increase in the number of innocent-spouse cases attended to by the Tax Court. A final appeal to the


Exhibit 1.

147

Current and Prior Innocent-Spouse Requirements.

Current Innocent-Spouse Law

Pre-July 23, 1998 Innocent-Spouse Law

The item(s) of the non-requesting spouse are ‘‘erroneous’’ No ‘‘substantial’’ understatement requirement No minimum-liability percentage relative to the requesting spouse’s AGI The requesting spouse must elect relief using a specified form Two-year time limit on seeking relief as an innocent spouse Relief allowed for an unmarried taxpayer

The item(s) of the non-requesting spouse are ‘‘grossly erroneous’’ The understatement is ‘‘substantial’’ The liability exceeds a certain percentage of the requesting spouse’s AGI No specific form required to request relief No specific time limit No provision for an unmarried taxpayer

Treasury can be made if the offended taxpayer is not satisfied with the IRS treatment of the case [y6015(f)]. Unmarried Innocent-Spouse Provisions Equitable relief under the innocent-spouse rules is available by election to a taxpayer who was not married when the return was filed [y6015(c)]. The election is available for income-tax liabilities arising after July 22, 1998. In general, the innocent-spouse items attributable to one spouse are the same as those that would have been allocated to that spouse if the couple had filed individual returns, regardless of their marital status. The election is available to a taxpayer who filed a joint return, but is: (a) no longer married, including that caused by the other spouse’s death; (b) legally separated; or, (c) not a member of the same household with the offending spouse at any time during the 12-month period immediately preceding the election. A y6015(c) election may be made any time after the IRS has asserted a deficiency, but not later than two years after the IRS has begun collection activities against the taxpayer [y6015(c)(3)(B)] (Exhibit 1).

EQUITABLE RELIEF There is a third avenue for a taxpayer to obtain relief, on top of or in lieu of that provided by yy 6015(b) and (c). ‘‘Equitable relief’’ is allowed by the

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Treasury when a requesting spouse establishes that, taking into account all facts and circumstances, it is inequitable for that spouse to be held liable for a portion of an unpaid tax or deficiency. The factors that weigh in favor of the IRS granting equitable relief to a requesting spouse seeking innocent-spouse status include, but are not limited to, the following [Rev. Proc., 2003-61, 2003-2 CB 296]. The same factors are used in applying yy6015 (b) and (c) to show that the tax law leads to an ‘‘inequitable’’ result for the offended spouse. (1) Marital status. The requesting spouse is separated or divorced from the non-requesting spouse. A temporary absence, e.g., due to incarceration, illness, business, vacation, military service, or education, is not considered a separation. (2) Economic hardship. The requesting spouse would suffer economic hardship from not being granted relief. (3) Knowledge or reason to know. The requesting spouse had no knowledge of the liability or deficiency. In determining whether the requesting spouse had reason to know, the IRS considers the spouse’s level of education, any deceit or evasiveness on the part of the non-requesting spouse, the requesting spouse’s degree of involvement in the activity that generated the tax liability, the requesting spouse’s involvement in business and household financial matters, the requesting spouse’s business or financial expertise, and any lavish or unusual expenditures compared with past spending levels. (4) Non-requesting spouse’s legal obligation. The presence of a legal obligation (e.g., under a divorce decree) incurred by the non-requesting spouse to pay any outstanding tax liability. This factor does not weigh in favor of relief if the requesting spouse knew or had reason to know, when entering into the divorce decree or agreement, that the non-requesting spouse would not pay the tax liability. (5) Significant benefit. The requesting spouse did not receive significant benefit (beyond normal support) from the unpaid tax liability or item(s) giving rise to the deficiency. (6) Compliance with the income-tax laws. The requesting spouse has made a good-faith effort to comply with the tax laws in the taxable years following the taxable year or years to which the request for relief relate. (7) Abuse. The non-requesting spouse abused the requesting spouse in some manner. If, however, this factor is not present in a situation, it will not weigh against granting equitable relief.


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(8) Mental or physical health. The requesting spouse was in poor mental or physical health on the date she/he signed the joint return, or at the time the requesting spouse requested relief. The IRS considers the nature, extent, and duration of illness when weighing this factor. Inasmuch as this factor was not cited in any of the cases adjudicated during our sample time period, we do not include it in our statistical analysis. The obverse of each factor usually makes the granting of equitable relief by the IRS less likely, e.g., if the requesting spouse benefited from the understatement of tax, or if, based on his/her education level, the spouse should have known that a tax understatement occurred. Equitable relief is not granted where the joint return was filed with a fraudulent intent, or where prior asset transfers between the spouses are seen as creating the need for the requested relief. When the IRS does not grant equitable relief, the requesting spouse still has recourse to the courts, and the courts will not necessarily see things in the same way as did the IRS personnel, nor will a court’s vision necessarily take in all the same sights. Thus, the problem that we address here is whether, once the IRS has ruled adversely on a requesting spouse’s plea for equitable relief, the court hearing the case will in fact look at all eight of the criteria and, if not, which of the eight criteria, and whether it is deemed to be a positive or negative factor, will impact the court’s decision. We then measure the extent to which each of the salient factors influences the probability that equitable relief will or will not be granted.

RESEARCH METHOD Objectives This study will determine: whether each of the equitable-relief factors has indeed been of probative concern to the courts; which factors have been the most salient factors to affect the courts’ decisions; and, the relative importance of each of the salient factors in determining the probability that equitable relief will be granted or denied. To achieve this end, we use a classic logit/probit analysis as detailed in Greene (2003, Chapter 21).

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In the present context, a tax court processes the data for a set of independent variables xk and parameters bk (k ¼ 0, y, n) to arrive at the unobserved total of y* ¼ Sbkxk+e, where x01 and e is a random-error term. The court grants equitable relief to the requesting spouse whenever y*>0 and denies equitable relief whenever y*r0. Although we do not observe y*, we do observe the binary variable y, which equals unity when equitable relief has been granted to the requesting spouse and is zero otherwise. Hence, y ¼ 1 when y* >0, and y ¼ 0 when y* r0. Probit regression estimates the bk by assuming a normally distributed random error, whereas logit assumes a logistic distribution. Although ‘‘it is difficult to justify the choice of one distribution or another on theoretical grounds y . In most applications, the choice between the two seems not to make much difference’’ (Greene, 2003, p. 667). Either approach yields a set of estimated regression coefficients bk that allow us to assess the probability that a requesting spouse’s plea for equitable relief will be granted. Nonetheless, because of our limited sample size we felt it was imperative to confirm, as we do, that either distribution would lead to an acceptable level of prediction. Therefore, while we present both sets of estimates, we give short shrift to the probit estimates and focus on the logit estimates for our detailed discussion. The estimates and the assessments are based upon a series of ‘‘Yes’’ or ‘‘No’’ answers to questions framed from the factors introduced in Rev. Proc. 2003-61. The parameter estimates also permit one to infer how the courts have, on average, weighted those factors in reaching their decisions. Design We initially identified a set of 62 innocent-spouse cases issued from January 2000 through September 2004. This set includes all the innocent-spouse cases adjudicated in this period. A careful reading of these cases resulted in the elimination of 12 cases as being irrelevant and/or unusable, typically because the decision addressed other procedural or jurisdictional matters, and not the equitable-relief factors of current interest. The 50 cases that were used in this study are shown in Exhibit 2. Three of the 50 cases resulted in split decisions, either because of different circumstances in different tax years, or because different circumstances were judged to warrant relief. The courts decided different aspects of these three cases on different grounds and in essence dealt with each portion of those cases as a stand-alone case with a unique resolution. We do likewise. The final pool of cases thus comprised 54 observations.


Exhibit 2.

Cases Used in the Study.

Alva Cotter Shell IV, T.C. Summary Opinion 2003-136. Andrea J. Vuxta, T.C. Memo. 2004-84. Angela Barriga, T.C. Memo. 2004-102. Ann E. Bartak, T.C. Memo. 2004-83. Arlene C. Ogonoski, T.C. Memo. 2004-52. Brenda Wallace, T.C. Memo. 2003-330. Catherine Rosenthal, T.C. Memo. 2004-89. Cheshire, 89 AFTR 2d 2002-900; 282 F.3d 326 (CA-5, 2002). Connie A. Washington, 120 T.C. 137. Craig A. Penfield, et ux., T.C. Memo. 2002-254. Curtis Earl Moore, T.C. Summary Opinion 2004-86. David J. Price, T.C. Memo. 2003-226. Donna M. Keitz, T.C. Memo. 2004-74. Doyle, 93 AFTR 2d 2004-1864; 94 Fed. Appx. 949 (CA-3, 2004). E. Carolyn Mellen, T.C. Memo. 2002-280. Estate of Barbara J. Jonson, 118 T.C. 106. Fay Dalton, et vir., T.C. Memo. 2002-288. Flores, 88 AFTR 2d 2001-7020; 51 Fed. Cl. 49 (Fed Cl., 2001). Guy Nathaniel Gay, Jr., et al., T.C. Summary Opinion 2003-36. Gwendolyn A. Ewing, 122 T.C. 32. Isaac Baranowicz, et ux., T.C. Memo. 2003-274. Janice L. Cardiff, et vir., T.C. Summary Opinion 2003-142. Jeanine T. Foor, T.C. Memo. 2004-54. Jeanne M. Trent, T.C. Memo. 2002-285. John William Hollis, T.C. Summary Opinion 2004-30. John A. Rowe, et ux., T.C. Memo. 2001-325. Julie C. Nichols, T.C. Memo. 2004-61. Kathleen E. Gilliam, T.C. Summary Opinion 2004-37. Lisa Marie Pierce, T.C. Summary Opinion 2003-126. Louise Demirjian, T.C. Memo. 2004-22. Marc S. Feldman, T.C. Memo. 2003-201. Marianne Hopkins, 121 T.C. 73. Marie-Francine T. Grow, T.C. Summary Opinion 2003-114. Michael B. Butler, et ux., 114 T.C. 276. Nita B. Leissner, T.C. Memo. 2003-191. Pamela J. Ellison, T.C. Memo. 2004-57. Renee Trupin D’Aunay, T.C. Memo. 2004-79. Rosalinda E. Alt, 119 T.C. 306. Ruth Ferrarese, T.C. Memo. 2002-249. Ruthe G. Ohrman, T.C. Memo. 2003-301. Sandra Browda, T.C. Summary Opinion 2004-16. Sandrus L. Collier, T.C. Memo. 2002-144. Sarah J. Barber, T.C. Summary Opinion 2003-110. Shirley Westerhuis, T.C. Summary Opinion 2003-116. Susan L. Castle, T.C. Memo. 2002-142. Teri Geisen Rooks, T.C. Memo. 2004-127. Tracy J. August, T.C. Memo. 2002-201. Verna Doyel, T.C. Memo. 2004-35. Vicki S. Pless, et vir, T.C. Memo. 2004-24. Zenobia E.C. Ziegler, T.C. Memo. 2003-282.

151

152


Each case was analyzed to establish the bases for the court’s decision. Those bases, and some additional aspects of the individual case, were then summarized on the form reproduced here as Exhibit 3. None of our 54 decisions was heard by the Supreme Court; only one case went to the Court of Federal Claims, and only two cases were heard in a Court of Appeals. About 60 percent of the remaining decisions were rendered as a Tax Court Memorandum, and the others were about evenly divided between the Tax Court Small Case and Tax Court Regular. We conduct two w2 tests to see whether (a) the likelihood of a plea being allowed or denied depends upon the level of the court, and (b) whether the amount of the assessment affects the level of the court that hears the case. In the first instance, a w2 statistic of w2 ¼ 0.90 (with two degrees of freedom) fails to reject the hypothesis that whether the requesting spouse’s plea is allowed or denied is independent of which of the latter three courts is rendering the decision. In the second instance, a w2 statistic of w2 ¼ 12.99>9.61 (with two degrees of freedom), rejects the hypothesis (p ¼ 0.01) that the level of the court is independent of the amount of the assessment involved. As one might anticipate, almost half the claims for less than $15,000 were heard in the Small Cases Division. Eleven of the 12 small-case hearings involved less than $15,000, while twice as many cases resolved at each of the two higher levels involved more than $15,000 as opposed to those involving less than $15,000.1 Panel A of Table 1 provides some summary statistics for the distribution of tax assessments that were at issue in the 54 cases. That distribution is (a) highly skewed to the right, as indicated by both the positive skewness coefficient of 6.78, and the fact that the mean of $178,127 dwarfs the median of $17,340, which in turn exceeds the mode of $7,130, and (b) quite peaked, as indicated by the highly positive kurtosis coefficient of 47.87. The broad range of assessments, which exceeds $5 million, also merits mention. Forty-six cases were filed by the female spouse. Panel B of Table 1 completes the sample profile by showing the frequency of mention for the eight factors and whether they were deemed positive or negative by the court. The set of candidate independent variables for inclusion in the vector x0 begins with the natural logarithm of the assessment, denoted A. The use of the natural logarithm is suggested by the highly skewed nature of the distribution of assessments. The second variable in the candidate set is a dummy variable, S ¼ 1 when the filing spouse is a female and S ¼ 0 otherwise. Sixteen additional variables, denoted wji (j ¼ 1, y , 8; i ¼ 1, 2), are introduced to quantify the relative importance of the jth factor in a given case, and whether it was deemed positive, i ¼ 1, or negative, i ¼ 0. Letting Tk


Exhibit 3.

153

Innocent-Spouse Case Analysis Form.

Case Name: Citation: Tax Year?

Decision Year?

Cause of Assessment? (e.g., IRA distribution) Amount of Tax Assessment: $ Court:

Tax Court Small Case Tax Court Memo Tax Court Regular District Court Federal Claims Court of Appeals, Which circuit? Supreme Court

Requesting Spouse's sex: Male

Female

Equitable Relief:

Denied?

Allowed?

1. Would the requesting spouse suffer economic hardship if equitable relief is denied? Yes

No

Not specifically addressed

2. Did the requesting spouse have knowledge of the liability payment or knowledge of items causing the deficiency? Yes

No


3. Did the non-requesting spouse have a legal obligation to pay under a divorce decree? Yes

No


4. Is the unpaid liability solely attributable to the non-requesting spouse? Yes

No


5. Did the requesting spouse significantly benefit from the unpaid liability? Yes

No


6. Was the requesting spouse abused by the non-requesting spouse? Yes

No


7. Is the requesting spouse divorced or separated from the non-requesting spouse? Yes

No

Not determinable

8. Has the requesting spouse made a good-faith effort to comply with tax law in later years? Yes Other

No


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Table 1. A. Tax Assessment Mean: Standard error: Median: Mode: Range: Kurtosis: Skewness

Summary Statistics.

$176.127 $100,776 $17,340 $7,130 $5,365,990 47.87 6.78

B. Frequency of Mention for the Eight Criteria Criteria Economic hardship (j ¼ 1) Knowledge (j ¼ 2) Obligation to pay (j ¼ 3) Sole attribution (j ¼ 4) Significant benefit (j ¼ 5) Spousal abuse (j ¼ 6) Divorce or separation (j ¼ 7) Good-faith compliance (j ¼ 8)

Deemed positive

Deemed negative

Not mentioned

10 39 10 23 15 2 42 11

31 13 41 27 19 44 12 4

13 4 3 4 20 8 0 39

C. Correlation of Criteria Importance Variables (wji) with the Decision Variable (y) Criteria Economic hardship (j ¼ 1) Knowledge (j ¼ 2) Obligation to pay (j ¼ 3) Sole attribution (j ¼ 4) Significant benefit (j ¼ 5) Spousal abuse (j ¼ 6) Divorce or separation (j ¼ 7) Good-faith compliance (j ¼ 8)

Deemed positive (i ¼ 1)

Deemed negative (i ¼ 2)

0.5589 0.6260 0.0061 0.5465 0.4179 0.2654 0.0986 0.4277

0.5091 0.7570 0.1920 0.4533 0.4622 0.1466 0.1836 0.1938

denote the number of factors mentioned in the court’s decision in the kth case, when factor j is one of those factors, then wjik ¼ 1/Tk; otherwise wjik ¼ 0. Thus, when each of the eight issues is addressed either positively or negatively in the court’s decision in the kth case the denominator is Tk ¼ 8 and either wj1k ¼ 1/8 and wj2k ¼ 0, or wj2 ¼ 1/8 and wj1 ¼ 0. When only the jth issue is addressed and is the sole consideration impacting the court’s decision, the denominator is Tk ¼ 1 and either wj1k ¼ 1 and wj2 ¼ 0, or wj2k ¼ 1 and wj1 ¼ 0. When the jth issue is not addressed, both wj1 and wj2 are equal to zero.


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Thus, in principle the import of the jth issue and whether it was an affirmative or a negative consideration in the court’s decision may be assigned any one of nine values ranging from zero, meaning that the issue was ignored by the court, to unity, meaning that this was the only issue that the court deemed relevant. In the latter instance, wj1k ¼ 1 implies that issue was a dispositive positive factor, while wj2k ¼ 1 implies that issue was a dispositive negative factor, in the court’s decision. In practice, however, no fewer than three issues were specifically addressed in any decision in the sample set, so that wj1k and wj2k take on any one of the seven values 0, 1/8, 1/7, y, 1/4, 1/3. For notational convenience, the subscript k to delineate individual cases will henceforth be suppressed. For narrative convenience, the discussion of the statistical results initially focuses solely on the logit approach with the probit procedure to follow.

THE STATISTICAL ANALYSIS The Logit Estimates With a sample size of N ¼ 54, a logit analysis requires paring down the set of independent variables. Absent theoretical considerations, one way to accomplish this is through a stepwise-regression procedure that allows the computer to make the decision as to which variables to include or omit (Hosmer & Lemeshow, 1989, pp. 106118). In the present instance, the SAS stepwise-regression package informed us that, ‘‘the validity of the model fit is questionable.’’ We therefore adopted a recommended second tack of best subset selection (Hosmer & Lemeshow, 1989, pp. 118126). As Hosmer and Lemeshow (1989, p. 126) point out, ‘‘[n]umerical problems can occur when we overfit a logistic regression model.’’ Thus, in effect we want to look at various combinations of the independent variables to determine the most parsimonious combination that yields a valid model with stable parameter estimates and that provides a reasonably good fit to the data. As a starting point, we considered the simple correlation coefficients of the dependent variable y with each of the 18 independent variables, denoted ry. In particular, ryA ¼ 0.1563 and ryS ¼ 0.0889, suggesting that neither the amount of the tax assessment nor the sex of the filing spouse impacts the court’s decision to any statistically significant extent, which we verified by estimating a logistic regression with these two variables alone. Next, we considered the simple correlation coefficients for y and the factor-importance variables. These are displayed in Panel C of Table 1. On the

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face of it, factors j ¼ 3 and 7, obligation-to-pay and marital-status considerations, respectively, seem destined for relegation to at best secondary roles in the estimation process, with factor j ¼ 6, spousal abuse, joining them. Factor j ¼ 8, good-faith compliance, with ry81 ¼ 0.4277 and ry82 ¼ 0.1938, was also eliminated from consideration at this stage, because of the low frequency of mention, 11 and 4, respectively, seen in Panel B. Similarly, since the significance of benefit, j ¼ 5, was not mentioned in 20 of the cases, this factor, too, was ignored at this stage. We are thus left with three factors, j ¼ 1, 2, and 4economic hardship, knowledge, and sole attribution, respectivelyeach of which might be deemed positive or negative, and each of which has a simple correlation coefficient with y in excess of 9ry429 ¼ 0.4533, which exceeds the comparable correlations for the five factor-importance variables initially eliminated. Once again, however, the SAS stepwise-regression package that considered these six variables produced the ‘‘questionable validity’’ alert. We therefore looked to the frequency-of-mention statistics of Panel B to choose a set of three of these six variables, one for each factor, for the first logit regression: w12, w21, and w42. Since, however, the frequency-of-mention statistic for factor j ¼ 4 was approximately the same, 23 versus 27, for w41 and w42, we contemporaneously estimated the regression with the latter variable replacing the former, which produced a marginally better fit to the data. Specifically, then, suppressing the random-error term, we estimated parameters for the regression: Probability ½Denied ¼ y ¼ 0 ¼ 1=½1 þ expðb0 b1 w12 b2 w21 b3 w41 Þ. (1)

The likelihood ratio w2 statistic of 48.72, with three degrees of freedom, allows us to reject the hypothesis that b1 ¼ b2 ¼ b3 ¼ 0. Indeed, as seen in the first column of estimates of Table 2, wherein the figures in parentheses are the p-values for the Wald w2 statistic (the square of the parameter estimate to its standard error, comparable to the familiar t-ratio in linear regression) all of the estimated slope-determining terms are statistically significant (a ¼ 0.05) as is the intercept-determining term (a ¼ 0.10). That is, the slope of the curve in any dimension is different at every point. For example, taking the partial derivative of the predicted probability with respect to w12 results in @Prob/@w12 ¼ 17.1941exp(2.483517.1941w1231.4807w21+18.5961w41)>0); and b0 ¼ 2.4835 determines the intercept on the vertical axis, but is not equal to it. The Somer’s D and Gamma statistics, which range from 1 to +1 and indicate both direction and strength of degree of association between the predicted values and the observed responses with ordinal measures, equal


157

Table 2. Logit and Probit Regression Results. Parameter

Variable

b0

Constant

b1

Suffer economic hardship Deemed negative Knowledge of the liability Deemed positive Sole attribution Deemed positive

b2 b3

Maximum Likelihood Estimates Logit estimate

Probit estimate

2.4825 (0.0923) 17.1941 (0.0389) 31.4807 (0.0024) 18.5961 (0.0324)

1.3212 (0.0454) 9.5919 (0.0353) 17.5815 (0.0006) 10.7917 (0.0215)

0.956 and 0.967, respectively, indicating a satisfactory fit to the data. In particular, the measures look at ‘‘concordance,’’ or whether the expected result from the regression conforms to the actual result when two observations with different outcomes are paired. In the present instance, there are 35 cases with y ¼ 0 and 19 cases with y ¼ 1, which yields 35 19 pairs. Of these some 97.3 percent are concordant, 1.7 percent discordant, and the remaining are too close to call by SAS standards. The various association measures, including Somer’s D and Gamma, manipulate these concordance data. SAS was not receptive to our attempts to introduce additional variables into the regression, nor were we successful in uncovering an alternative model, incorporating different variables, that produced a better fit. Since qProb/qw12>0, the greater is the import in the court’s decision of the fact that the requesting spouse would not suffer economic hardship, the greater the likelihood that equitable relief will be denied. Similarly, qProb/ qw21>0 so that the greater is the import in the court’s decision of the fact that the requesting spouse had knowledge of the liability payment, the greater is the likelihood that equitable relief will be denied. And, finally, with qProb/qw41o0, the greater is the import in the court’s decision of the fact that the unpaid liability is solely attributable to the non-requesting spouse, the lower is the likelihood that equitable relief will be denied and the greater is the complementary likelihood that equitable relief will be allowed. To put the parameter estimates in proper perspective and gauge their relative import, from Table 2, b1 ¼ 17.1941 and b3 ¼ 18.5961. Thus the fact that a requesting spouse would not suffer economic hardship if equitable relief were to be denied would weigh just about equally in the court’s decision (b1 ¼ 17.1941) as the fact that the unpaid liability is solely attributable to the non-requesting spouse (b3 ¼ 18.5961). The former would

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raise the probability that equitable relief will be denied, whereas the latter would reduce it. In fact, the requesting spouse’s not suffering economic hardship and the non-requesting spouse’s bearing sole responsibility for the liability are virtually perfect offsets. The impact of the knowledge factor, however, is much greater than either of the other two considerations (b3 ¼ 31.4807). That is, if the requesting spouse had knowledge of the liability payment causing the deficiency, even if that liability is solely attributable to the non-requesting spouse, the probability that equitable relief will be denied substantially increases (because b2+b3 ¼ 31.480718.5961 ¼ 12.8846). Indeed, when present in the same case, these two considerations positively affect the probability that equitable relief will be denied, to almost the same extent as does the fact that the requesting spouse would not suffer economic hardship as a result of having the request denied (b2+b3 ¼ 12.8846ob1 ¼ 17.941). The estimated probability that equitable relief will be denied is given by P ¼ 1=½1 þ expð2:4825 17:1941w12 31:4807w21 þ 18:5961w41 Þ.

(2)

In the first observation for the sample set, for example, the decision specifically addressed seven of the factors. For those factors, w12 ¼ 0 (and w11 ¼ 0 as well, so the court ignored the economic-hardship issue), w21 ¼ 1/7 ¼ 0.1429 (so the requesting spouse had knowledge of the liability payment), and w41 ¼ 0 (and here w42 ¼ 0.1429, so the unpaid liability is not solely attributable to the non-requesting spouse). Substituting these values into Eq. (2) yields P ¼ 0.8823 as the estimated probability of equitable relief being denied, and equitable relief was in fact denied in this case. Using a Pd ¼ 0.5 dividing line for classifying whether the estimated model would predict that equitable relief will be denied (PZ0.5) or approved (Po0.5), produces the 2 2 contingency table of Table 3, which provides further insight into how well the estimated model fits the data. The figures in parentheses are the expected number in each cell under the independence assumption, which is rejected at virtually any level of statistical significance by w2 ¼ 27.47. Table 3.

Contingency Table. Predicted

Observed

y¼1 y¼0

y¼1

y¼0

15(6.33) 3(11.66)

4(12.67) 32(23.34)


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Table 3 reveals that the model misses the mark in seven of the 54 cases. It correctly predicts 15 out of the 19 cases of approval and 32 of the 35 cases of denial. Three of the missed predictions were well off the mark. In one case where P ¼ 0.98, equitable relief was allowed, although the court’s rationale is not terribly clear, as the requesting spouse had ‘‘reason to know’’ of the liability item in question. In another case where equitable relief was allowed and P ¼ 0.86, in tandem the legal obligation to pay and solely attributable criteria would seem to have trumped the knowledge issue. In a third instance where P ¼ 0.07 and equitable relief was denied, none of the three criteria was mentioned in the decision, and the non-requesting spouse had a tax to pay. In this case, however, the petitioner’s only claim was that he was forced to file joint returns under duress, which argument was denied. In two cases where equitable relief was allowed, P ¼ 0.52, and in two where equitable relief was denied P ¼ 0.34 and 0.42, which are rather close calls. The Probit Estimates The second column of Table 2 provides the probit estimates for the same set of independent variables. While the two sets of estimates for the slopes look quite different to the naked eye, except in sign, in point of fact their implications are identical. As Greene (2003, p. 676) remarks, one ‘‘might expect to obtain comparable estimates by multiplying the probit coefficients by p/O3E1.8,’’ although the ratio will differ depending upon the balance between 0 and 1 s and might come closer to Amemiya’s (1981) suggested 1.6. In the present case, the ratios for the first two coefficients equal 1.79, which is right on the mark, while for the third coefficient is slightly lower, 1.72. The equations, however, translate quite differently. Again, from the first case, substituting the values of w12 ¼ 0, w21 ¼ 0.1429, and w41 ¼ 0 into the estimated probit equation results in an expected z-value of z ¼ 1.3212+17.5815 0.1429 ¼ 1.1904. Using ‘‘z’’ as the symbol of choice highlights the fact that the probit computation yields a z-value for the cumulative normal density. Referring to a table of the normal distribution, z ¼ 1.1904 translates into an estimated probability of 0.8830 as compared to the logit estimate of 0.8823 that equitable relief will be denied. Proceeding in this manner once again produces contingency Table 3. The lone advantage of the estimated logit regression over the probit regression, then, would seem to be that it permits the direct estimation of the probability that equitable relief will be denied or allowed in any individual case. Insofar as both procedures yield that probability, they have a leg up on discriminant analysis, which does not produce a likelihood but only a separation, as

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observed by Jordan and Holland (1984, p. 75, fn. 1) in a critique of statistical modeling of court behavior.2

OUT-OF-SAMPLE MODEL VERIFICATION To help verify the validity of our model and justify our confidence in the parameter estimates, we took advantage of the approximately eight months that passed between the time that we initially gathered our data and entered into the revise-and-resubmit process to collect an additional out-of-sample set of 11 innocent-spouse cases. These cases comprise what is to the best of our knowledge the population of cases above the Small Cases Division that fall under the purview of this paper in that they were decided under y6015 subsequent to the end of our sample data-collection period. After applying the same analytical procedure to these cases as was done with the original set of fifty, i.e., completing the form of Exhibit 3, we subjected the estimated models to the test of predictive ability. That is, using logit/probit sets of parameter estimates that are based solely on cases decided prior to October 2004, how accurately would the models predict the decisions on all subsequently adjudicated cases? The first column of Table 4 identifies the out-of-sample cases. The second column of Table 4 provides the decision in each case. Finally, the third and fourth columns of the table show the expected logit and probit probabilities, respectively, that equitable relief will be denied under the innocent-spouse rules, given the findings of the court with regard to one or more of the eight Table 4. Out-of-Sample Cases, the Decisions, and the Estimated Models’ Expected Probabilities that Equitable Relief will be Denied. Case and Citation

Decision

Logit Probability

Probit Probability

L. Bussell, T.C. Memo. 2003-77 C. G. Cook, T.C. Memo. 2005-22 M. E. Crahan, 322 F. Supp. 2d 1025 M. A. Durham, T.C. Memo. 2004-184 M. A. George, T. C. Memo. 2004-261 L. K. Haltom, T.C. Memo. 2005-209 P. A. Hendrick, T.C. Memo. 2005-72 E. McClelland, T.C. Memo. 2005-121 W. Payne, T.C. Memo. 2005-130 N. M. O’Neill, T.C. Memo. 2004-183 E. Simon, T.C. Memo. 2005-220

Denied Allowed Allowed Denied Denied Allowed Allowed Allowed Denied Denied Denied

0.9784 0.0020 0.0002 0.9263 0.9964 0.0038 0.0038 0.0008 0.9954 0.9993 0.9735

0.9859 0.0003 0.0000 0.9207 0.9993 0.0009 0.0009 0.0000 0.9999 1.0000 0.9808


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factors, and using the estimated regression results. Thus, for example, equitable relief was denied in Bussell; the expected probability that equitable relief would be denied in this case, given positivity or negativity of the three salient factors, is in fact 0.9784, which is a veritable certainty. Similarly, equitable relief was allowed in Cook where the expected probability that it would be denied is only 0.0020, which again implies a veritable certainty, p (allowed) ¼ 1.00.0020 ¼ 0.998, that equitable relief will be granted. Indeed, either model makes the correct call in each of the six cases in which equitable relief was denied, as well as in each of the five cases in which equitable relief was allowed. Moreover, in the former regard the lowest estimated probability that equitable relief will be denied is 0.9263, while in the latter regard the lowest probability that equitable relief will be allowed is 1.00.0038 ¼ 0.9962. In sum, not only did the estimated models provide perfect predictors, but also they did so in a significant manner.

CONCLUSION Schneider (2002, p. 474) has remarked that in addition to ‘‘traditional legal reasoning where precedent reigns and ‘the law’ develops over time as decision is layered upon decision,’’ there may be other approaches to understanding judges and their rulings. For Schneider, this meant looking into the judges’ backgrounds. For us, this has meant undertaking a statistical analysis of the criteria that the courts have considered in one specific legal setting, that of awarding or denying innocent-spouse equitable relief to a requesting spouse, and through that analysis isolating the factors that affected the courts’ decisions most strongly. The fact that only three of the eight criteria that might qualify one for innocent-spouse equitable relief under the Code are in practice salient, in the sense that they suffice to give an excellent predictor of a court’s decision in an innocent-spouse case, one that failed only 13 percent of the time, came as somewhat of a surprise to us. The overwhelming majority of the time the three-criterion predictor was highly accurate. This is not meant to imply that the other factors, such as legal obligations and spousal abuse, are irrelevant. Rather, the implication is that the economic hardship, knowledge, and attribution factors will generally suffice to give the prospective plaintiff, an excellent handle on how a tax court might decide an innocent-spouse appeal. This principal conclusion leads us to speculate favorably as to whether applications of the logit/probit approach in comparable legal settings might

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yield similar results, especially in cases that involve other largely quantifiable issues. In effective tax planning, knowledge of the key factors that lead to a court granting equitable innocent-spouse relief can be very important. The ability to accurately gauge the likelihood of obtaining such relief can save a taxpayer aspiring to financial relief a considerable amount of time and resources. It can also help a requesting spouse and/or tax advisor to set strategy in preparing the case for equitable relief as an innocent spouse in a manner that is most likely to result in the taxpayer’s prevailing. Several key implications can be seen in our results. The economic-hardship issue presents a strategic challenge. It is not necessary to show that the requesting spouse would suffer economic hardship if equitable relief were to be denied. Rather, it is sufficient not to have the issue brought to the court’s attention in the first place, as indeed was the situation in 13 of the 54 cases, or 24 percent. This is so, because showing economic hardship in the event of denial will not improve the chances of a favorable decision, whereas the absence of economic hardship in the event of denial will substantially raise the likelihood of an unfavorable decision. It is critical, as the most dominant factor, for the court to be unable to ascribe knowledge of the items causing the deficiency to the requesting spouse. Stated differently, economic hardship in defense of innocence is not a virtue, and deniability/ignorance is not a vice. Finally, it is extremely helpful to the requesting spouse’s case if it can be demonstrated that the unpaid liability is solely attributable to the nonrequesting spouse. A set of ‘‘negative’’ implications might also be drawn. Perhaps the most extreme case of a criterion not being used by the court is whether or not the non-requesting spouse had a legal obligation to pay under a divorce decree. Our analysis rejects the hypotheses that a legal obligation to pay will work in favor of the requesting spouse and that the absence of a legal obligation to pay will work in favor of the non-requesting spouse (and against the requesting spouse). Specifically, when either w31 or w32 is introduced into the model alongside w12, w21, and w41, we cannot reject the hypothesis that its regression coefficient, say b4, is statistically different from zero. In point of fact, in six of the ten cases in which there was such a legal obligation the courts did not enforce it and the requesting spouse was denied equitable relief. A further reading of those cases suggests that in five of the latter six, one may infer that the


163

legal obligation was trumped by the knowledge factor. That is, as determined by our model, when the requesting spouse had knowledge of liability payment, as a general rule this substantially increases the likelihood of an unfavorable ruling and any legal obligation is beside the point. Four additional factors that also seem not to contribute to the likelihood that equitable relief will be granted are the couple’s current marital status, whether the requesting spouse significantly benefited from the unpaid liability, whether the requesting spouse was abused, and whether the requesting spouse made a good-faith effort to comply with the tax law in subsequent years. Many reasons might be considered to explain this result, including the relative newness of the pertinent Code section and its language. In any case, our results support the argument that statistical procedures in general, and logit/probit analysis in particular, may indeed be a useful complement to the traditional legal approach in helping to uncover otherwise obscured patterns of judicial reasoning, which in turn can help participants in the judicial process to more accurately interpret the factors, and their weight, that underlie that reasoning even when the daunting complexities of the tax laws are at issue.

NOTES 1. Both w2 statistics are derived from 2 3 contingency tables. In the former instance there are 51 observations; in the latter instance there are only 50 observations. The discrepancy occurs because in one case the amount of the assessment involved could not be determined. In the first of the tables, the number expected in two of the cells was fewer than the usual minimum standard of five for a w2 analysis of a contingency table. Any resulting bias, however, would be in favor of rejecting the null hypothesis. In the second of the tables, the expected number of nine regularcourt cases was just about evenly divided between those involving more than $15,000 and those involving less. 2. Nonetheless, discriminant analysis is indeed a logical alternative to the logit/ probit approach to the problem. Maddala (1991) discusses the application of all three approaches in accounting research and remarks that when the explanatory variables cannot be expected to be normally distributed, as is the case here, ‘‘discriminant analysis gives inconsistent estimates, and one is better off using logit analysis’’ (p. 791). Be that as it may, applying a classic discriminant-analysis approach with the three factors that we have singled out misclassifies only four cases; it denies equitable relief in three cases in which it was allowed and allows it in one case in which it was denied.

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The support-vector-machine approach to discriminant analysis (Hearst et al., 1998) has an advantage over classic discriminant analysis in that it is non-parametric and makes no assumptions as to the underlying distribution of the variables, and the soft-margin formulation is not bound by any minimum-sample-size standards in selecting independent variables. When all 16 of the wji are included, only w82, failure to make a good-faith effort to comply with the tax law in later years, is eliminated as a discriminator, and only one case is misclassified. The implication is that with this single exception upon occasion the courts do pay due obeisance to the other criteria.

ACKNOWLEDGMENT We are grateful for the computational support of Professor Haldun Aytug of the University of Florida with the support-vector-machine approach, and particularly to Ms Jeanette Huntley of San Diego State University for her design and analysis contributions. The comments of the editor and two anonymous reviewers on earlier drafts are also gratefully acknowledged.

REFERENCES Amemiya, T. (1981). Qualitative response models: A survey. Journal of Economic Literature, 19(4), 481–536. Ayres, B. C., Cloyd, C. B., & Robinson, J. R. (1996). Organizational form and taxes: An empirical analysis of small businesses. Journal of the American Taxation Association, 18(Supplement), 49–67. Conlon, D. E., & Sullivan, D. P. (1999). Examining the actions of organizations in conflict: Evidence from the Delaware court of chancery. Academy of Management Journal, 42(3), 319–329. Cushing, W. W., & Arguea, M. (1999). Logit analysis of the employee classification problem for tax purposes. Journal of Financial and Strategic Decisions, 12(2), 95–105. Englebrecht, T. D., & Rolfe, R. J. (1982). An empirical inquiry into the judicial determination of dividend equivalence in stock redemptions. Journal of the American Taxation Association, 4(1), 19–25. Englebrecht, T. D., & Rolfe, R. J. (1984). An empirical inquiry into the determination of dividend equivalence in stock redemptions: A reply. Journal of the American Taxation Association, 5(2), 81–84. Greene, W. H. (2003). Econometric analysis (5th Ed.). Upper Saddle River, NJ: Prentice-Hall. Hearst, M. A., Scho¨lkopf, B., Dumais, S., Osuna, E., & Platt, J. (1998). Support vector machines. IEEE Intelligent Systems, 13(4), 18–28. Hosmer, D. W., Jr., & Lemesho, S. (1989). Applied logistic regression. New York: Wiley. Jordan, W. F., & Holland, R. G. (1984). An empirical inquiry into the determination of dividend equivalence in stock redemptions: A comment. Journal of the American Taxation Association, 5(2), 75–80.


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Maddala, G. S. (1991). A perspective on the use of limited-dependent and qualitative variables models in accounting research. Accounting Review, 66(4), 788–807. Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109–131. Schneider, D. M. (2002). Assessing and predicting who wins federal tax trial decisions. Wake Forest Law Review, 37(2), 473–529. Steffensmeier, D., & Demuth, S. (2000). Ethnicity and sentencing outcomes in U.S. Federal courts. American Sociological Review, 65(5), 705–729. Stewart, D. N. (1982). Use of logit analysis to determine employment status for tax purposes. Journal of the American Taxation Association, 4(1), 5–12.

USING THE SCHOLES AND WOLFSON FRAMEWORK TO COMPARE AN INCOME TAX AND A FORM OF CONSUMPTION TAXATION: A TEACHING NOTE Kenneth E. Anderson ABSTRACT This article uses the Scholes and Wolfson (S&W) framework to describe the fundamental aspects of an income tax and a consumption tax and provides a means to compare these two tax regimes. It thereby gives instructors a structured means to discuss these concepts in a tax policy course and provides an application of the S&W models other than investment decision making. The article also employs the S&W models to compare C corporations and flow-through entities under income tax and consumption tax systems.

INTRODUCTION Scholes and Wolfson (S&W) (1992) published the first edition of their book, Taxes and Business Strategy, to provide a conceptual framework for tax planning. Scholes, Wolfson, Erickson, Maydew, and Shevlin (SWEMS) Advances in Taxation, Volume 17, 169–192 Copyright r 2007 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1058-7497/doi:10.1016/S1058-7497(06)17007-6

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(2005) continue this focus in the third edition of the book. Consequently, most applications of the S&W modeling approach have focused on tax strategies, such as stock versus bond investments, traditional IRA versus Roth IRA decisions, corporate versus partnership organizational form, and deferred versus current compensation. In contrast, this article uses the S&W framework to convey the essential characteristics of an issue covered in most tax policy courses – namely, an income tax versus a consumption tax. This issue is particularly salient in current debates concerning tax reform, such as the President’s Advisory Panel on Federal Tax Reform (Department of the Treasury, 2005). Many features and arguments concerning the income versus consumption tax can be expressed in terms of the S&W models, thereby allowing students to see clearly the basic nature of the two tax regimes. The article first reviews the basic S&W models. It then defines a consumption tax and uses the models to compare various aspects of a consumption tax to an income tax. Following this discussion, the article examines the equity, efficiency, and simplicity aspects of the two tax regimes, and finally it compares various types of business entities under the two types of taxes. When comparing an income tax to a consumption tax, the article assumes a ‘‘pure’’ income tax that does not contain features such as retirement plans and asset expensing even though the current income tax contains these features. In fact, provisions such as retirement plans and asset expensing are consumption tax features, making the current law somewhat of a hybrid of consumption and income taxation.

THE BASIC MODELS Table 1 summarizes the basic S&W models used in this article. Although these models have been developed elsewhere (S&W, 1992; SWEMS, 2005; Stern & Seida, 2004; Pope, Anderson, & Kramer (PA&K), 2007), they are redeveloped here for convenience and then applied to compare income and consumption taxation. S&W employ six vehicles (numbered I–VI), but this article condenses the six vehicles to four models with descriptive names consistent with the PA&K approach. In particular, S&W vehicles I and III are the same except for the applicable tax rates, so this article combines them into the Current Model. For the same reason, S&W vehicles II and IV reduce to the Deferred Model. Finally, this article labels S&W vehicles V and VI as the Exempt and Pension Models, respectively. All four models give the after-tax accumulation of an investment that earns a before-tax rate of return of R. The models differ by the type of

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Table 1.

Basic Models. ATA ¼ AT$[1+R (1t)]n ATA ¼ AT$[(1+R)n (1tn)+tn] ATA ¼ AT$(1+R)n ATA ¼ BT$(1+R)n (1tn) - - or - h i 1 ATA ¼ AT$ ð1t ð1 þ RÞn ð1 tn Þ 0Þ

Current Model Deferred Model Exempt Model Pension Model

Notes: ATA, after-tax accumulation; AT$, after-tax dollars;BT$, before-tax dollars; R, beforetax rate of return; t, applicable marginal tax rate (ordinary tax rate for ordinary income or capital gain tax rate for capital gains or qualified dividends); t0, applicable marginal tax rate in year 0 (year of initial investment); tn, applicable marginal tax rate in year n (year of cashing out); n, investment horizon.

dollars invested (i.e., after-tax versus before-tax dollars) and by the way the investment earnings are explicitly taxed (i.e., currently, later, or never). The term after-tax dollars (AT$) means the taxpayer’s invested amount comes from sources taxed prior to making the investment, e.g., earned income or from borrowings the taxpayer must repay with after-tax amounts. In essence, the taxpayer can invest only after-tax dollars because the tax law does not allow a deduction or exclusion for the investment. Conversely, the term before-tax dollars (BT$) means the taxpayer’s invested amount comes from untaxed sources. The tax law accomplishes this treatment by allowing the taxpayer to deduct or exclude the amount invested. After-tax dollars relate to before-tax dollars as follows: AT$ ¼ BT$ ð1 tÞ

(1)

Current Model The Current Model assumes investment of after-tax dollars and that the investment earnings are taxed currently at a marginal tax rate of t. Consequently, a taxpayer can reinvest only the earnings after taxation, causing the investment to grow at the after-tax rate of return. The variable t in the model denotes the applicable tax rate. For investment vehicles such as taxable bonds and money market funds, t represents the taxpayer’s ordinary marginal tax rate. For vehicles such as mutual funds, t represents the capital gains tax rate. For example, assume a taxpayer having a 25% marginal tax rate earns $10,000 of salary and wishes to invest in a taxable bond yielding a 6% return before taxes for 15 years. Because the taxpayer invests after-tax dollars, he or she can invest only $7,500 [i.e., $10,000 (10.25)]. Thus, the taxpayer’s

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after-tax accumulation will be ATA ¼ $7,500 [1+0.06 (10.25)]15 ¼ $14,515. This model’s key characteristic is that both the taxpayer’s initial investment and the investment’s earnings are taxed currently. Deferred Model The Deferred Model also assumes an after-tax investment, but in this model accrued earnings or gains are taxed at the end of the investment horizon at tax rate tn. Accordingly, taxation of earnings or gains is deferred, and the investment grows at the before-tax rate of return. As with the Current Model, t is the ordinary tax rate for investments yielding ordinary income, such as a non-deductible IRA or a single-premium deferred annuity, and it is the capital gains tax rate for investments yielding long-term capital gains, such as a non-dividend paying stock. The subscript n denotes that the tax rate applies in year n rather than currently. The model in Table 1 derives algebraically from the following intuitive form of the model: AT$ ¼ fð1 þ RÞn ½ð1 þ RÞn 1tn g

(2)

In this form, the first term, (1+R)n, represents the investment’s accumulated growth at the before-tax rate of return. The term [(1+R)n1] represents the earnings or gain on the investment, i.e., the before-tax accumulation less the amount invested (basis). Multiplication by tax rate tn produces the tax on the earnings or gain. The entire expression, therefore, yields the after-tax accumulation on the investment with the earnings or gain taxed at the end of the investment horizon. For example, assume a taxpayer having a 25% ordinary tax rate and a 15% capital gains tax rate earns $10,000 of salary and wishes to invest in a non-dividend paying stock that grows at 6% before taxes for 15 years. Again, because the taxpayer invests after-tax dollars, he or she can invest only $7,500. Thus, the taxpayer’s after-tax proceeds from the stock sale will be ATA ¼ $7,500 [(1+0.06)15 (10.15)+0.15] ¼ $16,403. This model’s key characteristic is that the taxpayer’s initial investment is taxed currently while the earnings or gain are taxed at the end of investment horizon when the taxpayer cashes out. Exempt Model The Exempt Model, as with the previous two models, assumes an after-tax investment. In this case, however, the investment earnings are not explicitly


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taxed at all. This model actually is a special case of the Current Model with t ¼ 0. Examples in current tax law include tax-exempt municipal bonds and Roth IRAs. For example, assume a taxpayer having a 25% marginal tax rate earns $10,000 of salary and wishes to invest in a tax-exempt bond yielding a 6% rate of return for 15 years. As in the previous examples, the taxpayer can invest only $7,500. Thus, the taxpayer’s after-tax accumulation will be ATA ¼ $7,500 (1.06)15 ¼ $17,974. This model’s key characteristic is that the taxpayer’s initial investment is taxed currently, allowing only an after-tax dollar investment, while the earnings are never explicitly taxed. Pension Model Finally, the Pension Model assumes investment of before-tax dollars because the taxpayer either deducts or excludes the amount invested from gross income. In the first form of the Pension Model in Table 1, the expression BT$(1+R)n yields the investment’s accumulated growth before any taxes. At the end of the investment horizon, the entire proceeds, including the initial investment, are taxed at the ordinary tax rate tn. Accordingly, multiplication by (1tn) results in the after-tax accumulation. The second form of the Pension Model in Table 1 substitutes the expression AT$/(1t0) for its equivalent BT$, which allows the expression inside the large brackets to be comparable to the other three models. This model’s key characteristic is that taxation of both the taxpayer’s initial investment and the investment’s earnings is deferred until the end of the investment horizon, thereby providing a double deferral. Examples in current tax law include qualified pension plans, deductible IRAs, 401(k) plans, and 403(b) arrangements. For example, assume a taxpayer having a 25% marginal tax rate earns $10,000 of salary and wishes to invest through a 401(k) plan in an investment yielding a 6% before-tax rate of return for 15 years. Unlike the previous examples, the taxpayer can invest the entire $10,000. Thus, the taxpayer’s after-tax accumulation will be ATA ¼ $10,000(1.06)15 (10.25) ¼ $17,974. Relation of Pension and Exempt Models Although referred to as the Pension Model, this model applies to any situation where a taxpayer deducts or excludes an initial investment, as shown

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later in this article when applied to the cash-flow version of a consumption tax. Also, the Exempt Model applies to any situation where the taxpayer receives no deduction or exclusion for the investment and pays no further tax on investment earnings or withdrawals, as shown later when applied to the prepaid version of a consumption tax. In addition, given equal before-tax rates of returns and a constant tax rate, the Pension Model yields the same after-tax accumulation as the Exempt Model does. To see this equivalency, note that the Pension Model in Table 1 reduces to the same formula as the Exempt Model when t0 ¼ tn. When t0 and tn differ, however, this equivalency breaks down. For example, if the withdrawal year tax rate exceeds the investment year tax rate (i.e., tn>t0), the Exempt Model yields the higher after-tax accumulation, assuming all other variables being equal. Conversely, the Pension Model yields the higher after-tax accumulation if the investment year tax rate exceeds the withdrawal year tax rate (i.e., t0>tn). A later discussion of the cash flow and prepaid methods of implementing a consumption tax will demonstrate the importance of these relationships, particularly the equivalence of the two methods when t 0 ¼ t n.

THE CONSUMPTION TAX DEFINED Several types of consumption taxes exist in practice and theory with most falling into three categories: a sales taxes, a value added tax (VAT), and a form alternatively called a consumption-based income tax (Anderson, 1994; Nunn & Domenici, 1992), an individual consumption tax (AICPA & Sullivan, 1996), or a consumption-type income tax (McNulty, 2000). Essentially, a consumption tax uses consumption or spending as its base rather than income. Thus, it defers taxation of savings and investment until the taxpayer spends the saved amounts. The tax rate applied to the consumption base can be flat or graduated depending on how progressive lawmakers wish to make the tax structure. The sales tax version of a consumption tax, if applied nationally, would operate similarly to local and state sales taxes. Under such a system, taxpayers pay the tax at the retail level when they purchase goods and services. For example, if the national sales tax rate were 20% and an individual purchased a $1,000 item, he or she would be assessed an additional $200 on the sale. A VAT, on the other hand, applies at each stage of an item’s passage through the production and retail sales process. Here, the value added at each stage is taxed. For example, suppose a company purchases


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raw materials for $400 and manufactures a product that it sells to a distributor for $700. The raw material supplier adds $400 of value, and the manufacturer adds $300 of value. The distributor, in turn, sells it to a retailer for $900 (adding $200 of value), and the retailer sells it to the final consumer for $1,000 (adding $100 of value). If the VAT rate were 20%, the VAT at each stage would be as follows: Raw material supplier (20% $400) Manufacturer (20% $300) Distributor (20% $200) Retailer (20% $100) Total VAT

$80 60 40 20 $200

In practice, an actual VAT would be more complex than this simple example and might entail alternative mechanical approaches to calculating the VAT, such as the credit-invoice method or the subtraction method (U.S. General Accounting Office (GAO), 1989; Price & Porcano, 1992; AICPA & Sullivan, 1996). This article focuses on a consumption-based income tax. In Blueprints for Basic Tax Reform (Blueprints) (Bradford & the U.S. Treasury Tax Policy Staff, 1984), Bradford and the Treasury Department published a major study that thoroughly compared this type of consumption tax with a comprehensive income tax.1 Subsequently, the Center for Strategic and International Studies (CSIS) (Nunn & Domenici, 1992) issued a report that advocated a consumption-based income tax. This article applies the S&W modeling approach to this type of consumption tax in an attempt to make its mechanics and rationale clear and concise. Whether or not the United States moves toward a full consumption tax, this analysis can help students understand the fundamental aspects of a consumption tax and see that some components of current tax law function like a consumption tax, making the current tax somewhat of a hybrid between a pure income tax and pure consumption tax. In its analysis, Blueprints starts with a definition of comprehensive income from which it derives the consumption tax base. Such an approach typically begins with the Haig–Simons concept of income (Haig, 1921; Simons, 1938; Goode, 1976, p. 13; Bradford & the U.S. Treasury Tax Policy Staff, 1984, p. 27), which is I ¼ C þ DW

(3)

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where I is income, C is consumption, and DW is a change in wealth. According to this model, a taxpayer can use his or her income for a combination of spending (consumption) or savings (investment), the latter of which increases wealth. Simple algebra yields the following formula for a consumption base: C ¼ I DW

(4)

Thus, consumption can be measured as income minus changes in wealth. Income in this formula usually is defined broadly to include items such as changes in asset values, gifts, bequests, and inheritances received, as well as the traditional notions of income, such as wages, interest, and dividends (Bradford & the U.S. Treasury Tax Policy Staff, 1984, p. 29). Positive wealth changes (DW) include amounts a taxpayer saves or invests as well as increases in asset values. Negative wealth changes (DW) include spending from previous stores of wealth as well as decreases in asset values. If the recipient of income items does not save or invest them, his or her consumption base (C) will increase because the variable I increases while DW does not change. Conversely, if the recipient saves or invests his or her income, DW increases. This increase leads to a deduction from income (I), which produces an equal reduction in consumption (C). For example, assume a taxpayer earns $100,000 and saves $30,000. Income increases by $100,000, and wealth increases by $30,000. Thus, the taxpayer’s consumption base is $100,000$30,000 ¼ $70,000. If instead the taxpayer takes $30,000 out of accumulated savings (wealth) to make expenditures, his or her consumption base is $100,000(–$30,000) ¼ $130,000. That is, the taxpayer consumes all of his or her current income plus $30,000 of previous savings. As another example, assume a taxpayer’s wealth at the beginning of the year includes stock investments worth $50,000. During the current year, the taxpayer earns $100,000, receives a $30,000 inheritance, experiences a $10,000 stock value increase, and invests $25,000 in a money market fund. The taxpayer’s income is $140,000, computed as follows:

Earnings Inheritance Stock value increase

$100,000 30,000 10,000

Total income

$140,000


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The taxpayer’s increase in wealth is $35,000, computed as follows:

Money market investment Stock value increase

$25,000 10,000

Total wealth increase

$35,000

Thus, the taxpayer’s consumption base in the current year is $140,000 $35,000 ¼ $105,000. Note that the stock value increase appears in both income and the wealth change. If the tax base were more narrowly defined to include only realized income, these value changes would appear in neither place. This article will take the realization approach for pedagogical simplicity and because any enacted tax law most likely would adhere to the realization principle. Cash-Flow and Prepaid Methods To implement a consumption tax, Blueprints proposes two approaches, the cash-flow method and the prepaid method. Under the cash-flow method, the taxpayer deducts or excludes amounts saved or invested. This method produces the consumption base shown in expression 4. When the taxpayer withdraws from the savings or investment account to consume, he or she is taxed at that time. If the taxpayer rolls over the withdrawn amounts to another investment, he or she again deducts or excludes the investment, thereby extending the deferral of taxation. Thus, with respect to investment, the cash-flow method is consistent with the S&W Pension Model. Specifically, as mentioned earlier, a system conforms to the Pension Model if it (1) allows investment of before-tax dollars via a deduction or exclusion of the invested amount, (2) allows the investment to grow at the before-tax rate of return by not taxing earnings currently, and (3) taxes the entire amount of any withdrawals. Because the cash-flow method operates in this fashion, the Pension Model can be used to describe its effects. Examples later in this article will apply the Pension Model to specific types of investments, namely, financial assets. Alternatively, the prepaid method allows no deduction or exclusion for amounts saved or invested, but earnings on investments are exempt from taxation as are amounts withdrawn for consumption. Thus, with the prepaid method, a taxpayer invests after-tax dollars and pays no taxes on the investment after that time. This approach operates exactly like the S&W

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Exempt Model, as later examples will demonstrate when applied to financial assets and consumer durables. Financial Assets Blueprints advocates the cash-flow method for financial assets, including stock investments, purchased through a qualified account. A qualified account is similar to a current-law deductible IRA except it does not limit the amount contributed and does not impose a penalty on early withdrawals. The prepaid method also is acceptable for financial assets, particularly if acquired outside a qualified account, because it results in the same accumulation as the cash-flow method if tax rates are constant. The upper quadrants of Table 2 further demonstrate the two methods of treating financial assets under the assumption that investment year and withdrawal year tax rates are equal (i.e., t0 ¼ tn). Assume a taxpayer earns $10,000 before taxes. Under the cash-flow method (upper left-hand quadrant), the taxpayer deducts the $10,000 investment and Table 2.

Financial Assets Versus Consumer Durables – Cash Flow Versus Prepaid Method. Cash-Flow Method

Financial asset

Consumer durable

Prepaid Method

Earnings Prepaid tax

$10,000 (0)


After-tax earnings invested

$10,000


$10,000 (3,500) $6,500

After-tax liquidation valuea (Pension Model): $10,000 (1.1)2(10.35) ¼ $7,865

After-tax liquidation value (Exempt Model): $6,500 (1.1)2 ¼ $7,865


$10,000 (0)



$10,000


After-tax liquidation value (Modified Model): $10,000 [(1.1)20.35] ¼ $8,600

$10,000 (3,500) $6,500

After-tax liquidation value (Exempt Model): $6,500 (1.1)2 ¼ $7,865

Notes: (1) This table assumes that the investment year and withdrawal year tax rates are equal (i.e., t0 ¼ tn); (2) Variable values are R ¼ 10%, t ¼ 35%, and n ¼ 2. a Liquidation value refers to the after-tax sales proceeds from selling a financial asset or to the after-tax cumulative cash and noncash benefit of a consumer durable.


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pays no current tax. Therefore, the taxpayer can invest the entire $10,000. If the investment earns a 10% annual before-tax rate of return for two years (R ¼ 0.10, n ¼ 2), the taxpayer will have $7,865 upon liquidation of the asset (e.g., by selling or cashing out) and after paying taxes on the proceeds at an assumed 35% tax rate. To see this cash-flow effect another way, observe that the asset grows to $10,000 (1.1)2 ¼ $12,100 before taxes. Because the taxpayer deducted the original investment, the asset has a zero basis. Consequently, upon liquidation of the asset, the taxpayer recognizes a $12,100 gain and pays $4,235 in taxes, thereby leaving $7,865 after taxes, as follows: Before-tax accumulation [$10,000 (1.1)2] Taxes ($12,100 35%) After-tax liquidation value

$12,100 (4,235) $7,865

Under the prepaid method (upper right-hand quadrant), the taxpayer pays the $3,500 consumption tax currently, leaving only $6,500 to invest at the 10% before-tax rate of return.2 Under this method, the asset has a $6,500 basis, the amount of after-tax dollars invested. The taxpayer, however, pays no further taxes, which allows the asset to grow to a value of $7,865. Upon liquidation of the asset, the taxpayer receives $7,865 and recognizes no tax on the $1,365 exempt gain, thereby retaining the entire $7,865 amount, as follows: Before-tax accumulation [$6,500 (1.1)2] Taxes After-tax liquidation value

$7,865 (0) $7,865

Thus, under the given assumptions, the two methods yield equivalent results. Consumer Durables Unlike its acceptance of either method for financial assets, Blueprints recommends only the prepaid method for consumer durables. A consumer durable is a long-term asset from which the owner derives noncash benefits through using the asset. Examples include houses, automobiles, and appliances. The lower quadrants of Table 2 compare the cash flow and prepaid methods applied to a consumer durable and show why the cashflow method is unacceptable. The comparison between these quadrants relies

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on the following assumptions: 1. The value of usage is equivalent to the before-tax rate of return an individual would earn had he or she invested in a financial asset instead of a consumer durable. 2. The value of usage is not taxable under either an income tax or a consumption tax. 3. At the end of the ‘‘investment’’ period, the individual sells the asset for an amount equal to its original cost. The first assumption recognizes the opportunity cost of investing in a consumer durable rather than a financial asset. It also allows for the corollary assumption that the before-tax cumulative value of the consumer durable includes the compounded value of the usage. Accordingly, the before-tax cumulative value equals the cost of the consumer durable times (1+R)n, which, by assumption, equals the cumulative value of financial assets foregone by investing in the consumer durable. The second assumption recognizes that the rental value of personal usage is not taxed under most seriously proposed tax systems. Finally, the third assumption precludes the erosion or appreciation in value of the original investment to make the analysis of consumer durables comparable to that of financial assets. Admittedly, this last assumption is simplistic in that some consumer durables increase in value (e.g., houses) while others decline in value (e.g., automobiles). However, the purpose of the following analysis is to highlight the primary reason for using the prepaid rather than the cash-flow method for consumer durables. Specifically, allowing the cash-flow method for consumer durables would provide the double benefit of an upfront deduction for the asset’s cost and exclusion for the nontax benefits a taxpayer derives from using the asset. An attempt to model value changes in consumer durables would add unnecessary complexity and would obscure the essential pedagogical objective of the analysis. If the cash-flow method were allowed for consumer durables, the individual would deduct the cost of the asset upon purchase and have a zero basis in the asset. Upon a subsequent sale, the individual would recognize a gain equal to the sales price, which also equals the amount of the original purchase price under the third assumption discussed above. Subtracting the tax on this gain from the before-tax cumulative value yields the after-tax cumulative cash and noncash benefits derived from the consumer durable and can be expressed as the following Modified Model: Cost ð1 þ RÞn tn Cost

(5)


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where cost is expressed in before-tax dollars (BT$), and tn equals the individual’s tax rate on the gain. Expression (5) can be simplified to yield the following expression: Cost ½ð1 þ RÞn tn

(6)

If instead the individual used the prepaid method for consumer durables, he or she would not deduct the cost of the asset and would not be taxed on any noncash benefits received from using the consumer durable. Thus, the prepaid method conforms to the Exempt Model. The lower left-hand quadrant of Table 2 shows the results if the individual earns $10,000 and invests the entire amount in a consumer durable. Assuming a 35% tax rate and a two-year investment horizon, the after-tax accumulation is $8,600, which also can be computed as follows: Before-tax accumulation [$10,000 (1.1)2] Taxes ($10,000 35%) After-tax liquidation value

$12,100 (3,500) $8,600

In contrast, the lower right-hand quadrant shows that, with no deduction, the individual has only $6,500 to invest in the consumer durable, resulting in a $7,865 after-tax accumulation. Thus, the prepaid method makes the result of purchasing a consumer durable consistent with the result of investing in a financial asset assuming constant tax rates. The cash-flow method for the consumer durable, on the other hand, leads to an increased accumulation. As noted earlier, this result occurs under the cash-flow method because the individual takes a deduction for the investment and pays no tax on the noncash benefits of using the asset. To prevent this double benefit, Blueprints advocates the prepaid method for consumer durables. Summary This section defined a consumption-based income tax and described two methods, cash-flow and prepaid, suggested by Blueprints for implementing such a tax system. This section also used the S&W modeling approach to compare the two methods and to demonstrate Blueprints’ reasoning for preferring the cash-flow method for financial assets and the prepaid method for consumer durables. A later section shows how the income tax and consumption tax compare when business entities are involved.

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THE EQUITY AND EFFICIENCY ARGUMENTS FOR THE CONSUMPTION TAX DEFINED Proponents of a consumption tax argue their case using three criteria for assessing a tax system: horizontal equity, economic efficiency, and simplicity. The following sections address these criteria in relation to a consumption tax. These sections primarily address the horizontal equity and economic efficiency issues using the S&W models and present a brief discussion of the simplicity issue without relying on the S&W models. Horizontal Equity Issue The traditional definition of horizontal equity holds that taxpayers in equal economic circumstances should pay equal taxes (Bittker, 1980, p. 19; Rosen, 2002, p. 34). Proponents of consumption taxation take a lifetime view of taxation and argue that the income tax is inequitable because it treats current consumers differently than savers while a consumption tax treats them similarly. For the sake of argument, the lifetime view assumes that each taxpayer ultimately will consume what he or she earns. The saver, however, defers consumption to later in life, in contrast to the current consumer who spends as he or she earns. Specifically, over a lifetime, the income tax will cause savers (deferred consumers) to pay more taxes than will a consumption tax or, stated another way, to cause savers to experience a lower future value of consumption. In short, ‘‘the income tax discriminates in favor of those who consume early in life and against those who save and consume later’’ (Anderson, 1994, p. 79). On the other hand, a consumption tax treats consumers and savers similarly regardless of their pattern of spending and saving and therefore ensures horizontal equity. As an example, consider two individuals, one a consumer and the other a saver. Each individual earns $10,000 per year. Consumer spends all after-tax income immediately in the year earned while Saver saves all available earnings in years 1 and 2 and consumes the accumulated amounts at the end of year 2. The before-tax rate of return is 10% (R ¼ 0.10). Table 3 compares these two individuals under an income tax and a consumption tax, each of which imposes a 35% tax rate. (For expediency, this example uses a 2-year rather than a lifetime horizon.) Under the income tax, Consumer faces the Exempt Model because the benefit derived from consumption is not taxed. This result is same as that under the prepaid method of the consumption tax in Table 2 (lower


Table 3.

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Income Tax Versus Consumption Tax – Equity and Efficiency Issues. Income Tax

Consumer

Earnings Income tax After-tax earnings consumed

Saver

Consumption Tax $10,000 (3,500)

Earnings Consumption tax

$10,000 (3,500)

$6,500

After-tax earnings consumed

$6,500

Future value of current consumption (Exempt Model): $6,500 (1.1)2 ¼ $7,865

Future value of current consumption (Exempt Model): $6,500 (1.1)2 ¼ $7,865

Earnings Income tax

$10,000 (3,500)

Earnings Consumption tax

$10,000 (0)

$6,500

After-tax earnings saved

$10,000

After-tax earnings saved

Future value for future consumption (Current Model): $6,500 (1.065)2 ¼ $7,372

Future value for future consumption (Pension Model): $10,000 (1.1)2 (10.35) ¼ $7,865

Notes: (1) This table assumes that the investment year and withdrawal year tax rates are equal (i.e., t0 ¼ tn); (2) Variable values are R ¼ 10%, t ¼ 35%, and n ¼ 2.

right-hand quadrant). Saver, on the other hand, faces the Current Model because the interest earned on invested amounts is taxed currently, thereby allowing the savings to grow at only the after-tax rate of return. At the end of year 2, the future value of Consumer’s consumption exceeds that of Saver. Thus, because the income tax favors early consumption over later consumption, proponents of the consumption tax argue that horizontal inequity exists. (The discussion of efficiency below counters this argument somewhat.) Under the consumption tax, Consumer faces the same Exempt Model. Saver, however, deducts his or her investment using the cash-flow method and excludes interest income from taxation while invested in the savings vehicle. When Saver withdraws the accumulated amount and spends it, he or she is taxed on the consumption. In short, Saver faces the Pension Model. Moreover, because the Pension Model and Exempt Model are equivalent with constant tax rates over time, Consumer and Saver are treated the same and, hence, equitably. As noted earlier, however, this equality does not hold if future tax rates differ from current tax rates. Thus, much of the argument relies on constant tax rates.

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Although not modeled in this article, the income versus consumption tax debate also has a vertical equity component. Opponents of the consumption tax argue that it is regressive because low-income taxpayers do not have the wherewithal to save and invest while high-income taxpayers do. Proponents counter that the consumption tax could be more vertically equitable by using exemptions and a progressive tax rate schedule (Rosen, 2002, p. 452). Note, however, that a progressive tax rate schedule might cause a taxpayer to face different marginal tax rates in different years, thereby introducing some horizontal inequity between consumers and savers. Thus, policymakers may have to accept some horizontal inequity to achieve an acceptable degree of vertical equity. Economic Efficiency Issue Economists view any tax that distorts behavior as being, to some degree, inefficient. For example, a tax on earnings distorts the labor versus leisure decision, a tax on market transactions affects market versus non-market activity, and, according to consumption tax proponents, a tax on savings biases the consumption versus savings decision toward consumption (Bradford & the U.S. Treasury Tax Policy Staff, 1984, pp. 46–47; Rosen, 2002, pp. 451–452). This last tradeoff is particularly pertinent to this article, and the S&W approach can help formalize and clarify the issue. In addition to developing their investment models, S&W also present the concept of implicit taxes. Essentially, if one investment receives more favorable tax treatment than another, the demand and price for the taxfavored investment will increase. Consequently, its before-tax rate of return will decrease until after-tax rates of return reach equilibrium for marginal investors. In Table 3 for example, one could argue that, under the favorable income tax, demand and prices for consumer goods would increase, thereby reducing the before-tax ‘‘return’’ to consumption. If so, the before-tax rate of return to Consumer might fall to 6.5% in equilibrium, and the future value of consumption would fall to $7,372, the same as for Saver. In this event, horizontal inequity would disappear because the decrease in the before-tax rate of return constitutes an implicit tax that negates Consumer’s apparent favorable treatment under the income tax.3 The incentive to consume early, nevertheless, introduces economic inefficiency because the income tax distorts a taxpayer’s consumption versus savings decision. In short, the income tax is not neutral with regard to this tradeoff. On the other hand, the consumption tax is neutral with regard to this decision, and therefore efficient, because under this tax system, a


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taxpayer is indifferent between spending and saving. The two right-hand quadrants of Table 3 demonstrate this neutrality in that the future value of consumption is the same as that for saving. (Although before-tax rates of return might change in the transition from an income tax to consumption tax, neutrality between early and late consumption nevertheless should occur in equilibrium.) Simplicity Issue Proponents of the consumption-based income tax cite its simplicity as another positive feature. Under an income tax, complexity arises, among other things, because taxpayers must account for inventories, depreciation deductions, and other capitalized expenditures. Under a consumption-based income tax, the taxpayer would deduct these items as a form of investment, thereby simplifying the tax system. Some complexities would remain under this type of consumption tax, however. For example, policymakers would have to define precisely what items are included in income and what type of expenditures might not be classified as consumption, such as costs of generating earnings. Summary In this section, the S&W framework demonstrated that, under the income tax, individuals employing different spending patterns face different models while, under the consumption tax, they face equivalent models in that the Pension and Exempt Models are consistent assuming constant tax rates over time (see Table 4). This differential treatment under the income tax indicates Table 4.

Summary of Models under an Income Tax and a Consumption Tax.

Type of Behavior

Current consumption Saving in currently-taxed vehicles Investing in corporate stock

Model under Income Tax Exempt Model Current Model Deferred Model

Model under Consumption Tax

Exempt Model Pension Model (cash-flow method) or Exempt Model (prepaid method) Pension Model (cash-flow method) or Exempt Model (prepaid method)

Note: The treatment of consumption, savings, and investing behavior varies under an income tax but is consistent under a consumption tax. Consistency occurs under the consumption tax because the Exempt and Pension Models are equivalent given constant tax rates over time.

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the potential for horizontal inequity. Horizontal inequity, however, may disappear as before-tax returns adjust to the disparity between tax-favored and non-favored activities, thereby introducing economic inefficiency and implicit taxes. The S&W framework is particularly useful for identifying these inefficient situations because the presence of implicit taxes indicates that taxpayers’ decisions have been influenced by the favorable tax treatment of one activity versus another, thereby causing economic distortions.

BUSINESS ENTITIES AND THE INCOME VERSUS CONSUMPTION TAX Business entities fall into three main categories: sole proprietorships, C corporations, and flow-through entities (e.g., partnerships, limited liability companies, and S corporations). This section demonstrates how the S&W models can be used to describe these entities under an income tax and a consumption tax. Sole Proprietorships Under an income tax, a sole proprietorship’s profit is taxed currently, with assets depreciated over a number of years and inventory costs matched with sales. Essentially, the sole proprietorship conforms to the Current Model because the proprietor’s income is taxed currently, thereby allowing the proprietor to reinvest only after-tax dollars in the business. Under a consumption tax using the cash-flow method, however, the sole proprietorship deducts the entire cost of assets, including inventory, in the year acquired. Later, when the sole proprietorship sells inventory or other assets, the sole proprietor includes the entire sales proceeds in his or her consumption base unless reinvested in other business assets (Bradford & the U.S. Treasury Tax Policy Staff, 1984, p. 107). Thus, the sole proprietorship conforms to the Pension Model under the cash-flow version of a consumption tax. C Corporations Panel A of Table 5 shows how a non-dividend paying C corporation operates under an income tax.4 A shareholder invests in the corporation with after-tax dollars, and the corporation is taxed currently on its profit. Thus, the corporation accumulates its after-tax earnings according to the current model as follows: AT$[1+Rc (1tc)]n. When the corporation liquidates, it


Table 5.

187

Business Entities under an Income Tax.

distributes this accumulated amount to its shareholder (or shareholders). At that time, the shareholder recognizes a gain equal to AT$[1+Rc (1tc)]nAT$, i.e., the liquidation proceeds minus the shareholder’s basis in the corporate stock (AT$ invested). Multiplying this gain by the shareholder’s tax rate (tp) and subtracting the resultant tax from the liquidation proceeds yields the following expression for the shareholder’s after-tax

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accumulation: AT$½1 þ Rc ð1 tc Þn fAT$½1 þ Rc ð1 tc Þn AT$gtp

(7)

After some algebraic manipulation, expression 7 reduces to the Deferred Model in Panel A of Table 5. Note that this form of the Deferred Model has a Current Model embedded in it. Specifically, the corporation is taxed currently on its earnings, but the shareholder’s tax is deferred until the corporation liquidates, given the non-dividend paying assumption of this model. In effect, the corporation’s after-tax rate of return, Rc (1tc), is the shareholder’s before-tax rate of return on his or her stock. This model also reflects the double taxation associated with the corporate form under an income tax.5 Panel A of Table 6, in comparison, shows how the cash-flow method under a consumption tax treats a corporation and its shareholders. First, the shareholder deducts the investment in the corporation and therefore invests before-tax dollars. Second, the corporation is not taxed at the entity level. Finally, the shareholder is taxed on the entire amount of the liquidating distribution.6 Thus, the corporation conforms to the Pension Model under a consumption tax. Alternatively, Blueprints (Bradford & the U.S. Treasury Tax Policy Staff, 1984, p. 121) suggests the prepaid method if the shareholder acquires the stock outside a qualified account. Panel B of Table 6 illustrates this approach, whereby the shareholder takes no deduction for the investment, but neither the corporation nor the shareholder pays taxes on subsequent earnings or liquidating distributions. In this case, the corporate situation conforms to the Exempt Model. As noted earlier in this article, either approach produces an equivalent result given constant tax rates. Flow-Through Entities Panel B of Table 5 shows how a flow-through entity operates under an income tax. Owners invest in the entity with after-tax dollars, but no taxation occurs at the entity level. Instead, the entity’s earnings flow through to the owners in the year earned and are taxed currently at the owner level. The model assumes the entity distributes enough cash for the owner to pay his or her taxes on the flow-through income. Thus, the entity can reinvest only after-tax dollars in its business. The flow-through income increases the owner’s basis in the entity, and the distributions decrease the owner’s basis. At the end of the entity’s life, the owner recognizes no income upon receiving a liquidating distribution because the net increase in the owner’s basis equals the increase in the entity’s value. This feature of flow-through entities maintains taxation only at the owner’s level. The end result is an


Table 6.

189

Business Entities under a Consumption Tax.

investment growing at an after-tax rate of return with current taxation at the owner level. Thus, in the S&W framework, the flow-through entity conforms to the Current Model. Under a consumption tax, on the other hand, a flow-through entity would conform either to the Pension Model shown in Panel A of Table 6 or the Exempt Model shown in Panel B, depending on whether the law prescribes the cash-flow or prepaid method. Blueprints (Bradford & the U.S. Treasury Tax Policy Staff, 1984, p. 122) recommends the cash-flow method for flow-through entities.

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Table 7. Type of Business

Summary of Business Entity Models. Model under Income Tax

Sole proprietorship C Corporation

Current Model Deferred Model

Flow-through entity

Current Model

Model under Consumption Tax

Pension Model (cash-flow method) Pension Model (cash-flow method) or Exempt Model (prepaid method) Pension Model (cash-flow method) or Exempt Model (prepaid method)

Note: The treatment of business entities varies under an income tax but is consistent under a consumption tax. Consistency occurs under the consumption tax because the Exempt and Pension Models are equivalent given constant tax rates over time.

Summary Table 7 summarizes the applicable models for business entities under an income tax and consumption tax. Under the income tax, C corporations receive different treatment than do proprietorships and flow-through entities while, under a consumption tax, all business entities receive equivalent treatment.

CONCLUSION This article has demonstrated how the S&W framework can be used to describe and compare an income tax to a consumption tax. In doing so, it gives instructors in policy courses a structured means to convey these concepts to students. In addition, in a standard S&W type course, it gives instructors another application of the S&W model that contains a policy slant. As pointed out in the Introduction, this article assumes a ‘‘pure’’ income tax in the comparisons to a consumption tax. Current tax law, however, is anything but pure. It contains numerous incentives that deviate from such an income tax, and many of these features resemble a consumption tax. For example, Sec. 179 expensing, 401(k) plans, 403(b) arrangements, and deductible IRAs conform to the Pension Model while Roth IRAs and state and local bonds conform to the Exempt Model. Thus, the current law income tax really is a hybrid of income and consumption tax features, and the S&W approach to conveying the two types of taxes will help students see this aspect of current tax law.


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NOTES 1. McNulty (2000) also provides a good survey of the issues. 2. The examples in this article compute the consumption tax on gross consumption, i.e., a tax-inclusive base of consumption before the tax itself. Thus, for example with $10,000 of gross consumption, the tax at 35% is $3,500, leaving only $6,500 of net consumption after taxes. Alternatively and equivalently, the consumption tax could be computed on net consumption (i.e., a tax-exclusive base) using a net tax rate as follows: tnet ¼

tgross 0:35 ¼ 0:5384612 ¼ 1 tgross 0:65

Thus, the consumption tax again is $3,500, computed as 0.5384612 $6,500. Policy observers should be aware of these two approaches when evaluating alternative proposals so that tax rates and bases are comparable across alternatives. 3. See Bittker (1980) and Feldstein (1976) for a thorough discussion of the concept that inefficiency drives out horizontal inequity in equilibrium, and also see Anderson, Hill, and Murphy (1995) for an empirical demonstration that horizontal inequity disappears when implicit taxes are considered. Feldstein (1976), however, explains that horizontal inequity can occur in the transition from one tax regime to another. 4. This table follows the format used in Chapter 18 of PA&K (2007). 5. The examples in Tables 5 and 6 use a 35% tax rate for the corporation under the income tax and for the owner in all cases. This assumption makes the examples comparable and highlights that the results are driven by the different methods of taxation rather than by differential tax rates. 6. Shareholders also would be taxed on any dividends and the proceeds from the sale of their stock (Bradford & the U.S. Treasury Tax Policy Staff, 1984, pp. 120–121). However, the typical S&W model for the corporation assumes no dividend payments and assumes ultimate liquidation at the end of the investment horizon. Nevertheless, SWEMS (2005) provide a dividend-paying model in footnote 8 on page 92 of their text.

ACKNOWLEDGMENTS I wish to thank the Department of Accounting and Information Management for providing Summer funding for writing this article and the anonymous reviewers for numerous helpful comments.

REFERENCES AICPA, & Sullivan, M. A. (1996). Changing America’s tax system: A guide to the debate. New York, NY: Wiley.

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Anderson, K. E. (1994). The consumption-based income tax. Journal of Accountancy, 177(June), 77–82. Anderson, K. E., Hill, T. J., & Murphy, D. P. (1995). Horizontal equity and implicit taxes. The Journal of the American Taxation Association, 17, 89–100. Bittker, B. I. (1980). Equity, efficiency, and income tax theory: Do misallocations drive out inequities. In: H. J. Aaron & M. J. Boskin (Eds), The economic of taxation (pp. 19–31). Washington, DC: The Brookings Institution. Bradford, D. F. & the U.S. Treasury Tax Policy Staff. (1984). Blueprints for basic tax reform. Arlington, VA: Tax Analysts. Department of the Treasury (2005). President’s advisory panel on federal tax reform-final report, www.taxreformpanel.gov/final-report. Feldstein, M. (1976). Compensation in tax reform. National Tax Journal, 29, 123–130. Goode, R. (1976). The individual income tax. Washington, DC: The Brookings Institution. Haig, R. M. (1921). The concept of income–economic and legal aspects. In: R. M. Haig (Ed.), The federal income tax (pp. 1–28). New York, NY: Columbia University Press. McNulty, J. K. (2000). Flat tax, consumption tax, consumption-type income tax proposals in the United States: A tax policy discussion of fundamental tax reform. California Law Review, 88, 2095–2185. Nunn, S., & Domenici, P. (1992). The CSIS strengthening of America commission. Washington, DC: Center for Strategic and International Studies (CSIS). Pope, T. R., Anderson, K. E., & Kramer, J. L. (PA&K) (2007). Federal taxation 2007: Individuals. Upper Saddle River, NJ: Pearson Prentice-Hall. Price, C. E., & Porcano, T. M. (1992). The value-added tax. Journal of Accountancy, 175(October), 44–48. Rosen, H. S. (2002). Public finance. New York, NY: McGraw-Hill. Scholes, M. S., & Wolfson, M. A. (S&W) (1992). Taxes and business strategy: A planning approach. Englewood Cliffs, NJ: Prentice-Hall. Scholes, M. S., Wolfson, M. A., Erickson, M., Maydew, E. L., & Shevlin, T. (SWEMS) (2005). Taxes and business strategy: A planning approach (3rd ed.). Upper Saddle River, NJ: Prentice-Hall. Simons, H. C. (1938). Personal income taxation: The definition of income as a problem of fiscal policy. Chicago, IL: University of Chicago Press. Stern, J. J., & Seida, J. (2004). Tax concepts and analysis. Bloomington, IN: Stern. U. S. General Accounting Office (GAO). (1989). Tax policy: Tax-credit and subtraction methods of calculating a value-added tax. Washington, DC: U.S. General Accounting Office.

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