LIST OF CONTRIBUTORS Susan B . Anders
Department of Accounting, St. Bonaventure University, USA
Christine C. Bauman...
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LIST OF CONTRIBUTORS Susan B . Anders
Department of Accounting, St. Bonaventure University, USA
Christine C. Bauman
School of Business Administration, University of Wisconsin-Milwaukee, USA
B. Anthony Billings
Department of Accounting, Wayne State University, USA
Tonya K. Flesher
Patterson School of Accountancy, University of Mississippi, USA
Sharon K. Ford
Department of Accountancy and Computer Information Systems, Delta State University, USA
Anna C. Fowler
Department of Accounting, University of Texas-Austin, USA
Gregory G. Geisler
Department of Accounting and Information Systems, University of Missouri-St . Louis, USA
Daryl M. Guffey
School of Accountancy and Legal Studies, Clemson University, USA
Philip J. Harmelink
Department of Accounting, University of New Orleans, USA
Peggy A . Hite
Department of Accounting and Information Systems, Indiana University, USA
Angela L . J. Hwang
Department of Accounting and Finance, Eastern Michigan University, USA Vii
LIST OF CONTRIBUTOR
Ernest R. Larkins
School of Accountancy, Georgia State University, USA
Daniel P. Murphy
Department of Acounting and Business Law, University of Tennessee, USA
Buagu Musazi
Department of Accounting, Virginia State University, USA
Claire Y Nash
Department of Accounting, Christian Brothers University, USA
Elizabeth Plummer
Department of Accounting, Southern Methodist University, USA
Dan L . Schisler
Department of Accounting, East Carolina University, USA
Douglas K. Schneider
Department of Accounting, East Carolina University, USA
Morris H. Stocks
Patterson School of Accountancy, University of Mississippi, USA
William M. VanDenburgh
Department of Accounting, Louisiana State University, USA
Ann Boyd Watts
Department of Accounting and Business Law, University of Tennessee, USA
W. Mark Wilder
Patterson School of Accountancy, University of Mississippi, USA
EDITORIAL BOARD EDITOR Thomas M . Porcano Miami University Kenneth Anderson University of Tennessee, USA
Suzanne M . Luttman Santa Clara University, USA
Caroline K . Craig Illinois State University, USA
Gary A . McGill University of Florida, USA
Anthony P . Curatola Drexel University, USA Ted D . Englebrecht Louisiana Tech University, USA Philip J . Harmelink University of New Orleans, USA D . John Hasseldine University of Nottingham, England Peggy A . Hite Indiana University-Bloomington, USA Beth B . Kern Indiana University-South Bend, USA
Daniel P . Murphy University of Tennessee, USA Charles E . Price Auburn University, USA William A. Raabe Capital University, USA Michael L . Roberts University of Alabama, USA David Ryan Temple University, USA Dan L. Schisler East Carolina University, USA Toby Stock Ohio University, USA
AD HOC REVIEWERS Richard C . Hatfield Drexel University, USA
Cherie J . O'Neil Colorado State University, USA
Herbert G . Hunt California State University, USA
Patrick J . Wilkie George Mason University, USA
Janet A . Meade University of Houston, USA
STATEMENT OF PURPOSE Advances in Taxation (AIT) 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, computer usage, education, law, planning, and policy . Interdisciplinary research involving : economics, finance, or other areas is also encouraged . Acceptable research methods include any analytical, behavioral, descriptive, legal, quantitative, survey, or theoretical approach appropriate for the project . Manuscripts should be readable, relevant, and reliable . To be readable, manuscripts must be understandable and concise . To be relevant, manuscripts must be directly related to problems inherent in the system of taxation . To be reliable, conclusions must follow logically from the evidence and arguments presented . Sound research design and execution are critical for empirical studies . Reasonable assumptions and logical development are essential for theoretical manuscripts . AIT welcomes comments from readers . Editorial correspondence pertaining to manuscripts should be forwarded to : Professor Thomas M . Porcano Department of Accountancy Richard T. Farmer School of Business Administration Miami University Oxford, Ohio 45056 Phone : 513 529 6221 Fax : 513 529 4740 E -mail : porcantm@muohio .ed u See http ://www.jaipress .com / for Guidelines and additional information regarding manuscript submissions . Professor Thomas M . Porcano Series Editor
AN EMPIRICAL ANALYSIS OF THE EFFECT OF THE EARNED INCOME TAX CREDIT ON WORK EFFORT Susan B . Anders
ABSTRACT The purpose of this study is to further the examination of the effectiveness of the earned income tax credit (EITC) in meeting one of Congress' major objectives for the credit : increasing work incentives . Economic theory predicts a potential work incentive in the phase-in range of the credit and a potential work disincentive in the phase-out range . This study utilizes empirical analysis of individual tax return data to evaluate EITC participants' and comparable non-participants' wage income cross-sectionally and over time for indications of statistically significant changes . Observations are grouped into income classifications based on the income ranges of the credit : phase-in, plateau, and phase-out . The wages for EITC participants, as well as for non-participants, increased significantly over selected time windows during the 1979 to 1990 time period. Wage growth .for both participants and non-participants was greater in the phase-in range than in the phase-out range- The potential existence of significant differences in income growth between participants and non-participants is only indicated for the time period of the mid-1980s, before the major increase in the credit post-1986. Contrary to theory, the current study estimates a potential disincentive in the mid-1980s in
Advances in Taxation, Volume 14, pages 1-35 . Copyright 0 2002 by Elsevier Science Ltd . All rights of reproduction in any form reserved . ISBN : 0-7623-0889-3
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SUSAN B . ANDERS
the phase-in range, as well as the phase-out range. However, after the post-1986 increase in the credit, the differences between the participants and non-participants are no longer statistically significant and a potential disincentive cannot be inferred.
INTRODUCTION The EITC was first enacted in 1975 to : (1) reduce the burden of the Social Security tax for the working poor, (2) increase the progressivity of the tax system overall, and (3) increase the incentives of low-income individuals to work (Pechman, 1987, pp . 112-113) . The EITC has become the major government support for many low-income families . The Congressional Budget Office (CBO, 2000) estimates for the years 2000 and 2001 predict federal government spending outlays for the EITC will exceed those for family support programs .' Estimated expenditures for 2000 are $23 billion for family support and $25 billion for EITC . For 2001, they are $29 billion for family support and $30 billion for EITC (CBO, 2000) . Welfare reforms that emphasize work requirements over guaranteed entitlements also have increased the importance of, and expenditures on, the ETTC 2 Welfare to work alternatives now place time limits on the receipt of transfer payments . Additionally, as further encouragement for work while receiving assistance, the receipt of EITC refunds no longer reduces transfer payment amounts . The EITC is a refundable credit, which means that eligible taxpayers may receive refunds if the amount of the credit exceeds their tax liability . Appendix A details the historical participation in the credit and average credit amounts from 1975 through 1998 . For 1998, approximately $27 billion was paid out in refunds and 83% of the claimants received a refund (Gish, 2001, p . 4) . Although the EITC has been in existence for more than 25 years, it is still the subject of some controversy, and changes to the credit are regularly proposed by supporters and opponents alike . The Economic Growth and Tax Relief Reconciliation Act of 2001 increases the beginning and ending points of the phase-out range of the EITC for married couples filing joint returns . Also in 2001, the Senate is considering a bill (S . 685) that would expand the credit for families with three or more children . On the other hand, a bill has been proposed in the House of Representatives (H . R . 1652) that would repeal the credit for taxpayers without children and reduce the amount of the credit for those still eligible . The current study adds to the literature examining the impact of tax incentives on the labor supply . Previous studies have examined the effect of a
An Empirical Analysis of the Effect of the Earned Income Tax Credit
3
Negative Income Tax (NIT) on the hours worked by a treatment group, who received a guaranteed grant, versus a control group, who received no grant (Robins, 1985, GAO, 1993) . Other studies have applied parameter estimates from NIT experiments to examine labor supply response, in terms of changes in hours worked or changes in earnings, to changes in the EITC (GAO, 1993 ; Holtzblatt et al ., 1994) . Further studies have simulated the effects of increases or decreases in the credit rate (and phase-out rate) on a "treatment group" only (Browning, 1995) . The most recent empirical studies utilize household survey data to compare changes in employment rates or hours worked by single women (Eissa & Liebman, 1996 ; Meyer & Rosenbaum, 1999 ; Ellwood, 2000) and married couples (Eissa & Hoynes, 1998) with and without children . These studies focus on differences between potential beneficiaries and non-beneficiaries that may be related to the expansion of the EITC, and are discussed in more detail in the literature review section of the paper . This study contributes to a better understanding of the EITC by expanding the research method and by utilizing data from actual filed tax returns, rather than self-reported survey data . Using tax return data focuses the issue on whether the people who actually did claim the credit, rather than those who may have been eligible, were better off .' Additionally, widening the examination from single mothers to all actual claimants is important because of the purported "marriage penalty" effects on low-income married couples whose combined low incomes place them in or above the phase-out range . This study does not address compliance issues (i .e . whether or not taxpayers were eligible for the credit) . 4 Using a different data source provides the opportunity to triangulate the results of this study with other studies . For example, if the results of this study are similar to the simulation or household survey studies, confidence in all of the studies can be increased. On the other hand, if the results of the current study differ from prior studies, the need for additional research could be indicated . This study examines the growth or decline in wages (in constant dollars) over nine time windows which cover the time period 1979 through 1990, for a "treatment group" (i .e . EITC participants) and a "control group" (i .e . non-participants) . The chosen time windows take into account various changes in the credit during that time period . However, the focus is on differences between participants and non-participants that may be associated with an overriding incentive or disincentive of the EITC . This study also expands upon previous empirical studies by separating the tax returns into income groups based on the income ranges of the credit . The
4
SUSAN B . ANDERS
appearance of growth or decline in wages is examined separately for the phase-in, plateau, and phase-out income ranges . Examining the ranges separately is important because of the predicted differing effects on labor supply for each range (described below), which have been the source of much of the controversy surrounding the EITC . EITC participants are facing an upper limit on earnings that reduces their hourly wages in the phase-out range . If the EITC creates a disincentive to work, then participants in the phase-out income range would be expected to have a flatter distribution of earnings over time than non-participants in the phase-out income range . On the other hand, for participants in the phase-in range, the distribution of earnings over time would be expected to be steeper than for non-participants . Comparing the growth rates in earnings of EITC participants and non-participants with similar beginning levels of income allows the examination of differences in growth patterns that may indicate potential incentives or disincentives from the credit . The results of this study do not provide support for the idea that the EITC program influences the work efforts of recipients . In contrast to prior simulation studies, the results indicate that EITC participants exhibited positive wage growth (in constant dollars) in all income ranges, suggesting either that they worked more hours over time, or were more productive, or both . However, wage growth was significantly higher for EITC participants in the phase-in range, where the work incentive is positive, than for participants in the phase-out range, where the work incentive is negative . Importantly, the same pattern of wage growth is also exhibited by low-income workers who did not receive the EITC . This is in contrast to the results of previous empirical studies, which generally report an increased labor measure only for potential beneficiaries and not for potential nonbeneficiaries . The possible existence of significant differences in income growth between participants and non-participants is only indicated for the time period of the mid-1980s, before the major increase in the credit post-1986 . Contrary to theory, the current study estimates a potential disincentive in the mid-1980s in the phase-in range, as well as the phaseout range . However, after the post-1986 increase in the credit, the differences between the participants and non-participants are no longer statistically significant. The remainder of this article is organized as follows . First, the economic theory behind potential disincentives is briefly summarized . Second, a review of the related literature is presented . Third, the research design is developed . Finally, the results are presented, along with a discussion of the limitations of the study and suggestions for future research .
An Empirical Analysis of the Effect of the Earned Income Tax Credit
5
LITERATURE REVIEW Although the earned income tax credit is intended to provide an incentive for low-income taxpayers to work, some theoretical literature suggests that the credit may actually reduce work incentives . The effect on labor supply may depend on whether the taxpayer's income is in the "phase-in," "plateau," or "phase-out" ranges (Scholz, 1994 ; JCT, 1995) . In the "phase-in" range, the amount of credit increases as the taxpayer's earned income increases, so the credit acts as an earnings subsidy (Browning, 1995) . In the "plateau" range, the EITC acts as a lump-sum transfer since the amount of the credit is constant at the maximum amount, with no increase (or decrease) for additional earnings (Browning, 1995) . In the "phase-out" range, taxpayers lose a percentage of the credit for each additional dollar earned, similar to a negative income tax (Browning, 1995) . The operations of the "phase-in," "plateau," and "phase-out" ranges for the years of this study are depicted graphically in Fig . 1 . The overall effect of the EITC on work effort can be separated into a "substitution effect" and an "income effect ." The substitution effect derives from : (1) a positive credit rate, which increases the net wage, versus ; (2) an increase in the marginal tax rate (i.e. phase-out of the credit) which decreases the net wage (Browning, 1995) . In the phase-in range, the substitution effect provides a positive incentive to increase labor supply, because the higher after-tax wage makes leisure more expensive, and individuals may substitute work for leisure (Scholz, 1994 ; JCT, 1995) . In the "plateau" range, there is no substitution effect, since the credit does not increase or decrease . However, in the "phase-out" range, the decreasing after-tax wage makes leisure relatively less expensive, and individuals may choose to substitute leisure for work (Browning, 1995) . The "income effect" describes the potential for individuals to choose to work fewer hours, since their disposable money incomes have increased with receipt of the transfer (credit) (Scholz, 1994) . The negative direction of the income effect holds across all income ranges of the EITC . In the "phase-in" range, the substitution and income effects are in opposition to each other (JCT, 1995), although the positive substitution effect is expected to dominate the negative income effect and result in a net increase in the labor supply (Holtzblatt et al ., 1993 ; Scholz, 1994) . The income effect operates unopposed in the "plateau" range, although the strength of its effect is not clear (Holtzblatt et al ., 1994) . In the "phase-out" range, the substitution effect would be expected to reinforce the income effect for a net reduction in labor supply (JCT, 1995 ; Browning, 1995) . The theoretical development of the EITC has grown out of discussions of the negative income tax (NIT) . However, there are important differences
6
SUSAN B . ANDERS
1979 through 1984 : Maximum Credit $500 Phaseoat
Phasem 10% ooo~l $5,000 $0
s6,000
1985 through 1986 : Maximum Credit $550
1987 : Maximum Credit $851
Fig . 1 .
Earned Income Tax Credit Ranges .
$10,000
An Empirical Analysis of the Ellect of the Earned Income Tax Credit
7
between the EITC and an NIT (Alstott, 1994, p . 609 ; Cataldo, 1995, p. 59) . The NIT provides a guaranteed level of income, subsidizing individuals for the difference between their own incomes (which may be zero) and a minimum amount of income that is guaranteed to all individuals . The NIT subsidy decreases as the individual's own income increases . Thus, an NIT neither requires nor rewards work effort . In contrast, the EITC provides a wage subsidy as a percentage of earnings, which increases as taxpayers' earnings increase . The potential income effects and substitution effects associated with the NIT also apply to the EITC . However, analysis of the EITC cannot transfer directly from the NIT because the structure of the EITC is more complex . The EITC provides potential incentives as well as disincentives, due to the use of a phase-in range, plateau range, and phase-out range of income . The structure of the NIT utilizes only a phase-out range for determining the stipend . Thus, while it does not encourage participants to work, it may well discourage additional work for participants who are in the phase-out range . Prior studies on the effectiveness of the EITC in encouraging low-income individuals to work have produced disparate results . Simulation studies utilizing NIT estimates have supported the economic theory that taxpayers are discouraged from working in the plateau and phase-out ranges of the credit . On the other hand, empirical studies using household survey data have reported that potential beneficiaries of the credit increased their labor supply in comparison to potential non-beneficiaries . These studies are summarized in Tables 1 through 3 as follows . Simulation and empirical studies that have examined changes in hours worked are summarized in Table 1 . Simulation and modeling studies that analyzed changes in earnings are summarized in Table 2 . An empirical study that addressed changes in employment rates is summarized in Table 3 . The U .S . Department of Health and Human Services conducted four NIT experiments between 1968 and 1982 (Robins, 1985, pp . 567-568) . Some simulation studies of the effectiveness of the EITC utilized estimates from the largest and most comprehensive of the four experiments, sometimes referred to as the "Seattle/Denver" experiments, which were conducted between 1971 and 1977 . A treatment group received a guaranteed grant subject to a 50% or 70% phase-out based on income level . A control group received no grant (GAO, 1993) . Labor supply responses in terms of relative changes in hours worked by the treatment group are summarized in Panel A of Table 1, and indicate that husbands would reduce their hours worked by 12 .5%, wives by 23 .4%, and single heads of household by 20 .7% . The Government Accounting Office (1993) simulated the effects of the EITC on labor supply utilizing estimates of changes in hours worked by participants
8 Table 1 .
SUSAN B . ANDERS Summary of Labor Supply Responses : Changes in Hours Worked .
Panel A NIT experiments (GAO, 1993) GAO simulation (1993) Eissa and Liebman (1996) With children Without children Previously in workforce Eissa and Hoynes (1998) With 2 children With I child Without children Meyer and Rosenbaum (1999) With children Without children Panel B GAO simulation (1993)
Husbands -12 .5% -1 .5%
Wives -23.4% -6.5%
Single Head of Household -20 .7% -0 .3% +1 .9% None None
+0 .3% -0 .6% -1 .3%
-2.6% -0.1% +1 .7% +6 .0% -1 .0%
Phase-in +4.1%
Plateau -2 .6%
Phase-out -4 .3%
Overall -2 .1%
in the Seattle/Denver NIT experiments . Regression coefficient estimates of income and substitution effects from the NIT experiments were applied to estimate the labor supply response of low-income workers to the 1988 EITC . The results are summarized in Panel A of Table 1, and indicate that husbands would reduce their hours worked by 1 .5%, wives by 6.5%, and single heads of household by 20 .7% . If analyzed by income ranges of the EITC, as shown in Panel B of Table 1, hours worked increased 4 .1% in the phase-in range, but fell 2 .1% overall . Holtzblatt, McCubbin and Gillette (1994) also simulated the response of eligible workers to changes in the EITC in OBRA90 and OBRA93, using parameters estimated in the Seattle/Denver NIT experiments to determine the change in aggregate labor supply of eligible wage earners already in the workforce . In response to the changes in OBRA90, overall gross earnings fell by 1 .7%, and in response to OBRA93, overall earnings fell an additional 0 .7% . The effects on earnings by credit range are summarized in Table 2 . Browning (1995) modeled the effects of the EITC on labor supply with particular emphasis on the phase-out range . He estimated income and substitution effects at different levels of earnings, utilizing wage elasticities of labor supply and income elasticities from prior studies . Browning calculated that families in the upper end of the phase-out range would reduce earnings (and therefore labor supply) by 0 .73% .
9
An Empirical Analysis of the Effect of the Earned Income Tax Credit Table 2 .
Summary of Labor Supply Responses : Changes in Earnings . Phase-in
Holtzblatt et al. simulation (1994) OBRA90 OBRA93 Browning model (1995)
+1 .1% +1 .6%
Plateau
1 .6%
Phase-out
-2.0%
Overall
-L7% -0 .7%
0 .73%
Several recent studies have utilized data from the Current Population Survey (CPS), which is a monthly self-reported household survey conducted by the Bureau of the Census . The CPS data are collected by personal and telephone interviews of a recurring sample of 60,000 households . The studies utilizing CPS data analyzed changes in hours worked or employment rate, by populations that would potentially benefit from the credit, as an indication of the work incentive effects of the EITC . Eissa and Liebman (1996) utilized data from the March CPS to examine changes in the labor supply of single women with children, following the TRA86 expansions of the EITC . They compared the change in labor supply of single women with children, who were eligible for the EITC, to the change in labor supply of single women without children, who were not eligible for the EITC . They found that single women with children, who were not previously in the workforce, increased their labor force participation by 1 .9% . In contrast, they found no significant change in the number of hours worked by single women with children who were already in the workforce or by single women without children . Eissa and Hoynes (1998) utilized CPS data from 1985 to 1997 to compare labor supply responses of married couples with children and similar married couples without children, during a period of major expansions in the EITC . As summarized in Panel A of Table 1, they found that married men with children increased their labor supply (in terms of hours worked) relative to married men without children . In contrast, married women with children were more likely to decrease labor force participation . Meyer and Rosenbaum (1999) analyzed CPS data from 1985 to 1997 to examine the effect of several social programs (including EITC) on the labor supply of single mothers in comparison to single women without children . They estimated that the EITC was responsible for over 60% of the increase in employment rates of single mothers during the full 1984 to 1996 period . During the 1992 to 1996 period, however, the EITC explained only 37% of the increase in single mothers' employment rates .
10
SUSAN B . ANDERS
Table 3.
Summary of Labor Supply Responses : Changes in Employment Rates .
Ellwood (2000)
First Quartile
Second Quartile
Third Quartile
Fourth Quartile
Median earnings (1998) Women with children Unmarried Married Women without children Unmarried/married
$11,0110°
$15,000h
$20,000,
$30,100`
+21% +5%
+13% +11%
+8% +8%
+4% +6%
-1%/-2%
Notes: (a) Similar to plateau range ; (b) Similar to phase-out range; (c) Beyond phase-out range .
Ellwood (2000) utilized CPS data from 1975 to 1999 to separate women into four equal skill/wage groups . As summarized in Table 3, the employment rates for both married and unmarried women with children increased between 1986 and 1999 in all four wage groups. The greatest increase in employment occurred in the first quartile for unmarried women and in the second quartile for married women . There was no growth in employment for married or unmarried women without children . The current study contributes to the analysis of the work incentive effects of the EITC by using data from actual tax returns and by examining income growth in the different income ranges of the credit, which are predicted to have different incentive/disincentive effects . Using tax return data focuses the issue on whether the people who did claim the credit, rather than those who may have been eligible, were better off . Additionally, widening the examination from single mothers to all actual claimants is important because of the purported "marriage penalty" effects on low-income married couples.
RESEARCH DESIGN This study utilizes empirical analysis of actual individual income tax return data to evaluate EITC participants' and comparable non-participants' wages (in constant dollars) over time for indications of statistically significant increases or decreases . The wages of participants and a comparable sample of nonparticipants also are compared cross-sectionally for evidence of a statistically significant difference between the two groups over time . Comparisons are made over different time windows to take into account the expansion of credit eligibility and the increasing number of claimants between 1979 and 1990 .
An Empirical Analysis of the Effect of the Earned Income Tax Credit
II
Economic theory predicts a potential work incentive in the phase-in range and a potential work disincentive in the phase-out range, which calls for separate analyses by each income classification . This study examines a potential association between income growth (or decline) and the theoretical incentives (or disincentives) of the EITC . As an archival study, cause and effect between the credit and growth (or decline) in income cannot be inferred, and no implication of a causal relationship is intended . However, the use of panel data in this study may provide for the control of some omitted confounding variables if they are constant over time . If the EITC is effective in accomplishing the congressional objective of inducing low-income individuals to earn wages (or self-employment income), the incomes of EITC claimants would increase over a period of time as they enter the work force and develop work skills and experience . "Income" can obviously be defined by many different variables, and combinations of variables, in the tax return data . As a practical matter, the income variables chosen must be important to the EITC concept of income . Wages are used in this study as a proxy for "income," as approximately 93% of EITC claimants reported wages on their tax returns . Wage income also represented approximately 93% of total EITC earnings (IRS, Statistics of Income, 1975-1994) . Self-employment income is also eligible earned income for purposes of calculating the EITC . Out of all EITC claimants, approximately 15% reported self-employment earnings, although the amount of self-employment income accounted for only 7% of total EITC earnings (IRS, Statistics of Income, 1975-1994) . Net self-employment income also is examined as a subsidiary aspect of this study, although in the interest of simplicity, the following discussion focuses on wage income .'
Method
Means tests and regression analysis are used to examine the possible effectiveness of the EITC in encouraging low-income individuals to work . Comparisons of wages (in constant dollars) are made for the same taxpayers between a base year and a later year . Wage growth (decline) is analyzed separately for participants and non-participants . The two groups are then compared for indications of statistically significant differences . The means for wages for the same EITC recipients and a comparable group of the same non-recipients are calculated for each tax year, adjusted for inflation to 1990 dollars, and analyzed for differences over time (between the base year and a later year) . The means are analyzed for differences over time
12
SUSAN B . ANDERS
Table 4. Tax Year 1979-1984 1985-1986 1987 1988 1989 1990
EITC Credit Ranges for 1979 through 1990 .
Credit Rate
Maximum Phase-in Income
Plateau Range
Phase-out Range
Phase-out Rate
10% 11% 14% 14% 14% 14%
$5,000 $5,000 $6,080 $6,240 $6,500 $6,810
$5,001-6,000 $5,001-6,500 $6,081-6,920 $6,241-9,840 $6,501-10,240 $6,811-10,730
$6,001-10,000 $6,501-11,000 $6,921-15,432 $9,841-18,576 $10,241-19,340 $10,731-20,264
12 .5% 12,22% 10% 10% 10% 10%
for all participants and all non-participants over the entire income range, and separately for each credit range group . The comparisons are made over nine different time windows to take into account the expansion of credit eligibility and the increasing number of claimants between 1979 and 1990 . The EITC credit ranges for 1979 through 1990 are detailed in Table 4 . The base years chosen are 1979, 1983, and 1987 . 1979 is the first year available in the data set and is the closest to 1975, the year of inception of the EITC . As the first year available . 1979 also provides the largest time span between a base year and a later year. 1983 was chosen as the second base year as it is approximately mid-way through the nine-year period during which the maximum credit was constant . This was also the period during which inflation was eroding the value of the EITC . The average credit was at its lowest point during the period of 1982 through 1984, as detailed in Appendix A . 1983 was chosen over 1982 or 1984 because of a reduction of the number of tax returns available in the data for 1982 and 1984, due to cost saving measures on the part of the Internal Revenue Service . 1987 was chosen for the third base year as the first major increase since the inception of the credit took effect in 1987 . The percentage of tax returns claiming the credit increased more than two percentage points from 1986, and the dollar value of the credit also increased . The credit was also indexed for inflation beginning in 1987 . The base years were linked to the next year following the base year and also to the later years of 1983, 1987, and 1990 . For example, the same 1979 taxpayers were linked to 1980, to 1983, to 1987, and to 1990 . The years 1983 and 1987 were chosen as later years for the same reasons discussed above, and also to provide for equal multiples of four-year periods . 1990 was chosen as the final base year as it is the last year available in the data set . The time windows are summarized in Table 5 .
An Empirical Analysis of the Effect of the Earned Income Tax Credit Table 5. Window
Time Period
1 2
1979 to 1980 1979 to 1983
3
1979 to 1987
4 5
1979 to 1990 1983 to 1984
6
1983 to 1987
7 8
1983 to 1990 1987 to 1988
9
1987 to 1990
13
Time Windows . Description
The first year available in this data set is 1979. The credit rate and income ranges were constant over this time period, although taxpayers were adversely affected by rising inflation. The first major increase in the credit and income ranges occurred in 1987, as indexing for inflation was incorporated. The last year currently available in this data set is 1990 . Base year 1983 is approximately midway between base year 1979 and the first major increase in the credit in 1987 . The credit rate and income ranges were moderately increased by the 1984 and 1986 tax acts, although probably not sufficiently to offset inflation . The last year currently available in this data set is 1990 . The first major increase in the credit and income ranges occurred in 1987, as indexing for inflation was incorporated. The credit and income ranges were steadily increased during this period . The last year currently available in this data set is 1990.
If the EITC is associated with work incentives, we would expect to find differential rates of growth in earnings over time of taxpayers who claim the credit and those who do not. This result would be expected whether the credit has a positive or negative association with work incentives . To analyze differences over time, the changes in incomes of EITC participants and non-participants are compared over the nine time windows using regression analyses . Data
The data set is selected from the IRS Panel of Individual Income Tax Returns provided by the University of Michigan Center for Tax Policy 6 The data are compiled by tax year and consist of actual individual income tax returns . They currently are available for 1979 through 1990 . The tax returns included in the IRS Panel of Individual Income Tax Returns were selected by a stratified random sample of tax returns filed each year to produce reliable estimates of the entire population of individual income tax returns (Slemrod, 1990) . Each year contains a subset of tax returns from a panel of taxpayers whose tax returns are included year after year, and therefore, can be followed through the study . The percentage of tax returns claiming the EITC in the IRS Panel of Individual
14
SUSAN B . ANDERS Table 6.
IRS Panel of Individual Income Tax Returns . Tax Reurns Claiming the EITC .
Tax Year
Number of Returns in Sample
Returns in Sample with EITC
Percentage of Sample with EITC
Percentage of All Returns with EITC
1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990
45,141 46,214 46,670 9,235 19,120 9,762 20,202 10,120 21,191 21,656 22,352 22,683
3,480 3,460 3,242 595 1,234 554 1,270 590 1,714 2,153 2,348 2,500
7 .71% 7 .49% 6 .95% 6 .43% 6 .45% 5 .68% 6 .29% 5 .83% 8 .09% 9 .94% 10 .50% 11 .02%
7 .70% 7 .41% 7 .04% 6.71% 6.51% 5 .65% 6.38% 5 .99% 8 .23% 9 .96% 10.43% 11 .04%
Income Tax Returns for 1979 through 1990 is representative of the percentage of the total population of tax returns claiming the EITC in those years, and is summarized in Table 6 . The data set used for this study contains variables taken directly from tax returns, as well as some amounts calculated by the IRS . The data are ideal for examining many tax policy issues, particularly when the constructs under analysis can be operationalized with tax return information. The data set does not permit the analysis of demographic factors, however, nor does it include economic and sociological data, such as participation in welfare programs, that are not reported on individual tax returns . Sample Selection From the panel data, all tax returns with EITC were selected for the participant group in each year to be examined . Tax returns were deleted if the returns were filed for the wrong year (e.g . 1978 tax returns filed with 1979 tax returns) . In addition, tax returns where the taxpayers were over the age of 65, or were claimedd as dependents on another return (i .e . children under 18), were deleted since these individuals are not the focus of the incentive policies of the EITC . Tax returns with negative adjusted gross incomes were deleted to make the results more interpretable and to eliminate tax returns with investment losses in excess of earned income. In order to limit the analyses in this study to those
An Empirical Analysis of the Effect of the Earned Income Tar Credit
15
individuals who might appropriately be considered persistent "working poor," tax returns with changes in income of greater than plus or minus $20,000 were deleted from the samples for both the means tests and regression analyses . A non-participant group is used for comparison with EITC participants . The data set is as comparable as possible to the participant group, at least in terms of base year income levels (before EITC) and sources of income . The non-participant group was created by deleting, from the complete sample, those tax returns claiming the EITC . In addition to the adjustments mentioned in the prior paragraphs, tax returns with no earned income or with adjusted gross income in excess of the EITC ceiling were also deleted . Taxpayers who should have claimed the credit, but did not claim it, were properly included in the nonparticipant group, since they did not benefit from the credit .' Thus, the income patterns of the two groups are relatively similar, as portrayed in Fig . 2 . In order to increase the comparability of the participant and non-participant groups, both groups were further reduced by eliminating tax returns with interest income, dividend income, and capital gains or losses . Although low-income taxpayers may legitimately have investment income, Congress indicated its desire to limit EITC eligibility to taxpayers without significant investment income by placing a cap on interest income (in the years following the study period) . Taxpayers with itemized deductions were also deleted to reduce the samples to taxpayers in comparable standard deduction (zero bracket amount) positions .
$12,000 $10,000 $8,000 -
9
5
$6,000
-
$4,000
-
$2,000
-
79
Non-participants
80
81
82
83
84
85
86
87
Year Fig. 2 .
Average Base Year Wages in 1990 Dollars .
88
89
90
16
SUSAN B . ANDERS
Taxpayers who were employed in the base year, but who retired before or during the later comparison year, are outside the scope of policy incentives . These individuals experience a decrease in earned income that is not potentially influenced by EITC policy . In order to control for this situation, observations where the taxpayer is 65 or older in the later comparison year were deleted for both means tests and regression analyses . Another potential source of change in income that is outside the scope of the EITC is a change in marital (or filing) status . In the regression analyses, change in marital status is included as a control variable . For the means tests, observations where the taxpayer's marital (filing) status differed between the base year and the later comparison year were deleted to control for change in marital status . Table 7 details the final sample selection of participants for the means tests and regression analyses . Table 8 details the final sample of comparable non-participants . The EITC participant and non-participant groups were further separated into sub-groups based on the portion of the credit range into which their incomes fall in the base years . For example, in 1979, the phase-in group consists of those with incomes up to $5,000 . The plateau group consists of those with incomes between $5,001 and $6,000 . The phase-out group consists of those with incomes between $6,001 and $10,000 . The EITC credit ranges for 1979 through 1990 are detailed in Table 4 . Hypotheses The first hypothesis compares the mean wages for EITC participants in a base year to the mean wages for the same taxpayers in a later year . If the credit encourages additional work effort among participants, this should be evidenced by increased wages over time . The comparison is made through a paired t-test of the difference between the later year and base year . The first hypothesis (in the null form) is : HI : There is no difference in the means (in constant dollars) of EITC claimants' wages for a base year (e.g . 1979) and a later year (e .g . 1980) . Different results should be observed depending on whether taxpayers are in the phase-in, plateau, or phase-out ranges . Examining wage growth (or decline) in the separate ranges precludes the possibility of disincentives offsetting incentives in the overall picture . The second hypothesis compares the mean growth (or decline) in wages for EITC participants in the phase-in, plateau, and phase-out ranges, between the base year and a later year.
An Empirical Analysis of the Effect of the Earned Income Tax Credit 0
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Investment Company Group Characteristics (1982-1996) .
Mean CG Dist.
Mean Dividend Income
CG Dist. As a % of Total Dist. (CG+ dividends)
Mean Turnover Ratio (%)
Mean Total Net Assets
Meam Net Asset Value
n = 89
0.98
0.28
0 .78
86
0 .90
14 .41
n = 60
0.81
0.46
0 .64
69
1 .26
14 .21
n = 70
0.99
0.41
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83
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16 .96
n=79
0.83
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77
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83
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n=56
0.85
0.31
0 .73
74
0 .12
12 .68
Note : Capital gains distributions, dividend income and net asset values are per share amounts .
Total net assets are in billions .
distributions could have been the result of increased portfolio sales activity necessary to meet shareholder redemption activity which occurred in response to the change in marginal tax rates . The possibility that capital gains resulted from this consumption activity is controlled for in the analysis by including a variable capturing the effect of net redemption activity (on capital gains distributions) .
EMPIRICAL RESULTS Three specifications of equation 5 were estimated using a log functional form and these results are referred to as the "semilog" models . Specifically, the following three regression equations are estimated for each transformation : Model I - a parsimonious model estimating permanent effects alone ; Model II
261
The Effect of Capital Gains Tax Policy Table 4.
Average Annual Capital Gains Distributions and Dividend Income (per share amounts) : 1982-1996 . Entire Sample n=149
Growth Cos . n=89
Growth and Income Cos . n=60
Year
Capital Gains
Income
Capital Gains
Income
Capital Gains
Income
1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996
0.51 0.70 0.92 0.60 2 .03 1 .67 0 .40 0 .82 0 .46 0 .57 0 .76 1 .03 0 .79 0 .97 1 .40
0 .45 0 .39 0 .37 0 .40 0 .37 0 .42 0 .38 0 .44 0 .40 0 .33 0 .34 0 .26 0 .22 0 .27 0 .26
0 .55 0 .69 1 .01 0 .54 2 .14 1 .87 0 .33 0 .83 0 .47 0 .68 0 .84 1 .14 0 .95 1 .06 1 .53
0.37 0 .29 0 .30 0 .32 0 .29 0 .35 0 .30 0 .37 0 .32 0 .27 0 .32 0 .19 0 .14 0 .21 0 .21
0 .46 0 .72 0 .78 0 .69 1 .87 1 .37 0 .50 0 .80 0 .44 0 .42 0 .65 0 .85 0 .57 0 .82 1 .22
0 .59 0 .54 0 .52 0 .52 0.50 0 .53 0 .49 0 .55 0 .53 0 .43 0 .38 0 .36 0 .34 0 .36 0 .34
- a model isolating permanent effects, but also including the transitory effects
of micro-economic variables and fund-specific characteristics ; and, Model III a full model that considers permanent effects and the transitory effects of microand macro-economic variables, as well as fund-specific characteristics .
Model 1 :
g1, = .a,, + /3 IMTR, + u 1 ,
(7)
Model 17:
g„= a,,+ /3 1 MTR±/3,X1,+u 1,,
(8)
where X1, is a characteristics . Model III:
vector of micro-economic variables and fund-specific
g1, = a1 , + f3 1 MTR,+/32X1, + u it
(9)
where X1 , includes the variables in Model II and other macro-economic variables .
262
CLAIRE Y. NASH ET AL. Permanent Effects of Capital Gains Taxation
The semilog model estimates are shown in Table 5 where the restricted model, Model I, is presented first. The coefficients for both of the tax rate dummy variables, MTRI and MTR3, are positive and significantly different from zero in Model I in which transitory effects are not included. The effect of increasing the marginal tax rate from 20% (MTRI, representing pre-TRA 86) to 33% (TRA 86) is a decrease in the mean amount of capital gains distributions of $1 .25 per share." The effect of decreasing the marginal tax rate from 33% (TRA 86) to 28% (MTR3, representing post-TRA86) is an increase in the mean amount of capital gains distributions of $1 .25 . The direction of the permanent effects observed are consistent with evidence presented in empirical studies investigating the responses of individuals to capital gains tax rates (Feldstein et al ., 1980 ; Minarik, 1984 ; Amen & Clotfelter, 1982 ; Burman & Randolph, 1994) . When micro- and macro-economic variables and fund-specific characteristics are introduced into the semilog model to control for transitory effects, the coefficients of the MTRI variable continue to be significant (Model II and Model III) . The effect of introducing transitory effects into the equation is an increase of $1 .72 (Model III= e054) in the mean amount of capital gains distributions during MTRL However, the coefficient for MTR3 becomes insignificantly different from zero . The coefficient for MTR3 declines to $0.11 in Model II before rising to $0.24 in the fully unrestricted model . This rise and decline in the MTR3 coefficient in Model 11 and Model III, respectively, suggests that the variability in investment company capital gains distributions during the postTRA 86 tax regime may be due, in greater part, to transitory effects . Minarik (1981) and Burman and Randolph (1994) found a similar overestimation of permanent effects when transitory effects were ignored . The increases in capital gains distributions observed during MTRI and MTR3 indicate that lower marginal capital gains tax rates not only provide an incentive to individual taxpayers to engage in gains trading, but influence the level of investment company capital gains distributions as well . The increase in capital gains realized by investment companies during periods of relatively low marginal capital gains tax rates adds further credence to the arguments of tax policy makers who advocate preferential taxation of capital gains . Therefore, the null hypothesis that the level of capital gains distributions is not significantly different across tax regimes is rejected . The variability in the significance of the increase in investment company capital gains distributions during MTRI and MTR3 is expected . It suggests that the modest reduction in the marginal tax rate (from 33 to 28) had a much smaller effect on investment company capital gains distributions than the more
263
The Effect of Capital Gains Tax Policy
Table 5.
Semilog Models Estimated Coefficients of Variables Included in Model .
Dependent Variable - In g - per share capital gains distributions of an investment company, i, at time t
Variable
Expected Sign
Constant
Model I
0 .0375 (3 .882)****
Model 11
Model III
0 .963 (8 .852)****
-0 .490 -(0 .258)
MTRI(D) Coded I when year is pre-TRA 86
0 .222 (1_799)*
0 .227 (2 .260)**
0.541 (2 .690)***
MTR3 (D) Coded I when year is post TRA 86
0 .221 (1 .723)*
0 .106 (1 .05)
0 .245 (1 .311)
NAV (L) Per share net asset value at end of the previous year
0 .527 (17 .395)****
0.524 (17 .271)****
DIV (L) Per share dividends distributed to shareholders during the year
0 .061 (--1.131)
0 .059 ( 1 .091)
TURN Annual turnover rate of the investment companv
0 .00 (1 .968)**
0.000 (1 .950)**
SIZE (L) Total net assets at the end of the year
-0 .082 ( 3 .780)****
-0 .083 (-3 .80)****
LOAD (D) 0-no-load fund 1=load fund, during time t
0 .140 (4 .858)****
0 .)40 (4 .844)****
MGR (D) Change in Fund Manager 0=no change 7=change, during time t
0 .036 (1 .910)*
0.036 (1 .893)*
DMA change in the Dow Jones industrial Average stock market index during time t
0 .000 (0 .256)
REDM - redemption rate An industry measure of the% of investment company shares redeemed (bought hack) during time t by growth and growth-and-income investment companies
.035 0 (0 .997)
264
CLAIRE Y . NASH ET AL .
Table 5.
Continued .
Dependent Variable - In g - per share capital gains distributions of an investment company, i, at time t Expected Model I
Model II
Variable
Model Ill
Sign
SHARE an industry measure of the percentage ? of investment company assets held in taxable accounts of individuals during time t by growth and growth-and-income investment companies COMP A measure of competition calculated as the percentage change in the number of open-end stock and bondand-income investment companies during time t. MSE df R2
-0.016 (-0.763)
-0.006) (-0.752)
0 .113 2,232 0 .00
0 .099 2,226 0 .14
0 .099 2,222 0 .14
Note : t-statistics are in parentheses . * significant at the 0 .10 level; ** significant at the 0 .05 level ; *** significant at the 0 .01 level ; **** significant at the 0 .001 level. Logarithmic variables are indicated by "(L)" ; dummy variables are indicated by "(D) ."
dramatic 65% increase from 20% to 33% . The MTR1 effect is significant across all models specified in the analysis . The significance of this structural change suggests a significant lock-in by investment companies during TRA 86 . While investment company capital gains distributions rose during MTR3, the effect of unlocking capital gains is less significant during this period and its significance does not hold across the less restrictive models . The less significant effects of MTR3 provide evidence that the lock-in effect is larger when marginal tax rates on capital gains are high . Transitory Effects
Transitory effects are introduced into the model to reduce the possibility that the permanent effects of changing marginal tax rates are overstated . Table 5,
The Effect of Capital Gains Tax Policy
265
Model II and Model III, captures the effects of variations in investment company gains distributions that are due to other temporary variations and fund characteristics . The positive relationship between NAV, i and g provides evidence that, on average, investment companies with large baskets of unrealized capital gains distribute higher levels of capital gains . Burman and Randolph (1994) found a similar wealth effect, The DIV variable is not statistically significant . However, the inverse relationship observed is consistent with the theory that investment company portfolio managers increase trading activity to reposition securities portfolios when the return from income and unrealized capital gains has not met fund objectives (Jeffery & Arnett, 1993) . The expected positive relationship between TURN and capital gains distributions was tenuous at best . The turnover variable explains little of the variability in capital gains realized . This result does not support the relationship argued to exist by Jeffery and Amott (1993) . Capital gains distributions decrease as the size of an investment company increases . The SIZE relationship suggests that smaller funds engage in portfolio activity to a greater extent for rebalancing and consumption . Larger investment companies generally experience positive net cash flows and therefore are able to adjust their portfolios using uninvested cash . Absent sufficient positive cash flows, smaller funds must engage in portfolio transactions to meet redemptions and to reposition their portfolios . Investment companies that charge a sales fee (LOAD) distribute more capital gains to shareholders . The load policy adopted by a fund can serve as a cash flow management tool . Investment companies implement or switch to a load policy for a number of reasons . Smaller funds use LOAD to encourage investors to be longer term . Increasing the transaction costs of acquiring or selling investment company shares encourages investors to lock-in to an investment company and thus slows down the flow of cash out of a fund . Larger funds can use LOAD to control cash inflows . Investment company shares selling at a price above NAV may appear less attractive to investors . As the size of an investment company increases, a fund will switch to a load policy to slow down the flow of cash into the investment company . This change in fee policy also causes existing shareholders to lock-in . The lock-in by investors to LOAD funds provides portfolio managers with more discretion in implementing fund portfolio strategies . A change in portfolio manager, MGR, does signal an increase in investment company capital gains distributions . The repositioning that occurs as a result of the change in the investment strategies used to meet portfolio objectives generates capital gains distributions above what would otherwise be expected .
266
CLAIRE Y . NASH ET AL .
The macro-economic variables introduced in the model have little explanatory power. The insignificant coefficients of DJIA show that the increases in capital gains distributions observed was not simply the result of the strong economic growth that occurred during the period . Consumption activity, measured by redeeming investment company shares presented on demand (REDM), has little explanatory power. Having a greater percentage of investment company assets owned by individuals who are subject to taxation on an annual basis does not have an important effect on capital gains distributions . While the phenomenal growth in investment companies, captured by COMP, increased the choices for investors and competition among investment companies, no significant change in the level of capital gains distributions can be attributed to the competitive pressure of this growth . Alternative Model Specifications Various alternative specifications of the models were performed to test the robustness of the results . All specifications produced the same conclusions as the primary analysis . First, a set of estimations using the specifications of equation 5 were calculated using inflation-adjusted measures . This inflation-adjusted version of the model is comparable to the analysis conducted by Lindsay (1987) in which capital gains are adjusted using GNP . The magnitude of the inflation-adjusted effects is larger, relative to the semilog effects, across each model . The consistent relationships noted are further evidence of the robustness of the semilog results . Next, the model was estimated with OLS regression without the natural log transformation . The relationships are consistent using this estimation . A third specification of the model excluded the turnover variable from the analysis . Again, the findings were unchanged . Finally, we included a variable to determine whether the potential excise tax of 4% (as enacted in the Tax Reform Act of 1986) affected the conclusions of our analysis . Recall that the excise tax is assessed (on the undistributed portion) when funds distribute less than 98% of ordinary income and capital gains . As with prior alternative specifications, inclusion of the excise tax variable produced the same results as the primary analysis .
SUMMARY AND CONCLUSIONS Although a preferential tax rate on capital gains is enacted to induce individual investors to unlock gains on appreciated assets, it appears to also be effective
The Effect of Capital Gains Tax Policy
267
in unlocking investment company capital gains . Investment company portfolio managers are not evaluated on after-tax returns, yet the results of this study indicate that portfolio decisions are not entirely insensitive to capital gains tax rates . When the capital gains distributions of investment companies are examined across tax regimes, there is evidence that investment company capital gains distributions are significantly higher during tax regimes with lower marginal capital gains tax rates . Taxable individual accounts still hold the largest percentage of investment company shares and an increase in capital gains distributions during periods of lower capital gains tax rates suggests that portfolio managers consider the tax consequences to these investors . The observed increase in capital gains distributions during periods of lower marginal tax rates also should alleviate concerns that a tax policy aimed primarily at individuals will not have the intended effects . Portfolio managers have replaced individuals as dominant participants in the equity capital markets, but their trading behavior with respect to capital gains realizations is consistent with the realization response targeted by legislators . The unlocking effects of lower marginal capital gains tax rates observed in this study show that investment company growth has not had a negative impact on capital gains tax policy . The objectives of capital gains tax policy can still be achieved even though the decisions of many individual investors are concentrated in the trading activities of a comparatively few portfolio managers . While it would appear that tax minimizing strategies would conflict with a portfolio manager's objective of maximizing the return to shareholders, this study provides evidence that investment companies are more tax efficient than Jeffery and Arnott (1993) suggest . These observed structural shifts in the level of investment company capital gains distributions benefit short-term investors, and investors who hold shares across tax regimes . Other variables that influence the tax efficiency of an investment company include its size, beginning net asset value, turnover ratio, sales fee policy, and changes in portfolio managers . High net asset values indicate a high percentage of unrealized capital gains . A build-up in unrealized gains suggests an increased potential for current capital gains distributions . The turnover ratio of a fund accounts for little or none of the variation in capital gains distributed . As with all research, there are limitations on the generalizability of the results of the study . The independent factors included in the model are not an exhaustive list of possible determinants of realization behavior . In addition, the sample selection technique imposes a clear survivor bias . However, the analysis is concerned with investment company response to capital gains tax rate changes and not with quantifying capital gains distributions of a representative fund over
CLAIRE Y. NASH ET AL .
268
a particular period . There is no reason to believe that the non-survivors would have had a different capital gains distribution strategy than the 149 companies included in the sample . There is also no reason to believe that the non-survivors would have reacted differently to changes in capital gains tax rates .
NOTES l . Mutual funds are either open-end or closed-end . Open-end funds can always issue more shares . Investors are continuously buying (and redeeming) shares from open-end funds when adding (or withdrawing) money from the fund . In general, open-end fund shares are bought and sold directly through the fund itself, or its agents . In contrast, closed-end funds have a finite number of shares which are publicly traded. Investors can buy closed-end fund shares either in a stock offering or in the secondary market . 2 . We recognize that mutual funds may be considered conduits . However, they are not subject to direct taxation on their capital gains (i .e . capital gains flow through to the investor) . Therefore, changes in the marginal capital gains tax rate may have a lesser impact on mutual funds than on direct individual investors . 3 . Investment companies are not allowed to pass through capital losses to shareholders, but are allowed to carry forward these capital losses to offset future capital gains. 4 . The example assumes investment company turnover of 100% or greater and that the fund realizes all capital gains during the period . 5 . This finding is not surprising given that portfolio turnover indicates buying and selling of shares . As selling of shares occurs, capital gains are realized (for shares which have appreciated), which results in lower after-tax returns . 6 . Porcano and Shull (1997) considered the effects of changes in capital gains tax rates on a variety of entities (such as individuals, corporations, and private foundations) . Their findings indicate that the capital gains realization behavior of individuals and corporations (around tax law changes) generally was consistent with expectations . Of particular note was the result that entities such as private foundations also increase their capital gains-taking upon the enactment of lower capital gains tax rates . 7 . Prior to TRA 86, mutual funds were required to distribute at least 90% of the fund's ordinary income and realized capital gains to avoid taxation (if all income and capital gains were not distributed, the fund would be taxed on the undistributed portion) . Additionally, TRA 86 required that if funds did not distribute at least 98% of their capital gains and ordinary income, they would be subject to an excise tax of 4% of the undistributed portion . 8 . A relatively recent phenomenon has been the growth of tax-efficient mutual funds which are marketed to taxable individual investors . While these funds have enjoyed modest growth rates, as of the end of 1999 they represented a small fraction (less than one percent) of mutual fund equity assets . 9 . The taxable status of the shareholder impacts that shareholder's interest in the tax efficiency of the fund. Accordingly, the percentage of the fund held in individual taxable accounts may provide explanatory information about capital gains distributions of that fund . However, our data sources do not provide information on the percentage of each individual fund held in individual taxable accounts . Further evidence that such data are
The Effect of Capital Gains Tax Policy
269
widely unavailable is noted by Bergstresser and Poterba (2000), "we would like to measure the fund inflows attributable to taxable individual investors and to study how those flows are related to various factors . However, we are not aware of any data source that provides the requisite information on fund flows ." Therefore, in the current research we have attempted to consider the taxable status of funds by including the variable (SHARE) in the analysis. 10 . The possibility of family fund concentrations among the investment companies included in the sample was investigated . By referring to the fund family relationships identified in the Morningstar database, it was determined that there are no investment company family concentrations of 5% or more in the sample . 11 . Consistent with our findings, the Kraft and Weiss (1998) measure of capital gains (capital gains yield), is also highest in 1986 and 1987 . 12 . Taking the antilog of the estimated coefficient of MTRI (i .e . e""= 1 .25) .
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Feldstein, M . S ., Slemrod, J ., & Yitzhaki, S . (1980) . The effects of taxation on the selling of corporate stock and the realization of capital gains . Quarterly Journal of Economics, 94, 777-791 . Fuller, W . A., & Battese, G . E. (1974) . Estimation of linear models with crossed-error structure . Journal of Econometrics, 2, 67-78 . Investment Company Institute (Various years) . Mutual Fund Fact Book . Jeffrey, R . H ., & Arnott, R . D . (1993) . Is your alpha big enough to cover its taxes? Journal of Portfolio Management, (Spring), 15-25 . Kraft, A., & Weiss, 1 . (1998) . Tax planning by mutual funds . Unpublished working paper . Lindsey, L. B . (1987) . Capital gains rates, realizations, and revenues . In : M . Felstein (Ed .), The Effects of Taxation on Capital Accumulation . Chicago, IL : The University of Chicago Press . Minarik, J . J . (1981) . Capital Gains . In : H . J. Aaron & J. A . Pechman (Eds), How taxes affect economic Behavior . Washington, D.C . : Brookings Institution . Minarik, J . J . (1984). The effects of taxation on the selling of corporate stock and the realization of capital gains : Comment . The Quarterly Journal of Economics, (February), 118-119 . Myers, M . M ., Poterba, J ., Shackelford, D ., & Shoven, J. (2001) . Copycat Funds : Information Disclosure Regulation and the Returns to Active Management in the Mutual Fund Industry . Working Paper . Porcano, T . M., & Shull, D . M . (1997) . A Comparative Analysis of Capital Gains-Taking . Advances in Taxation, 14. 137-151 . U.S . Congress. Committee on Energy and Commerce (1994) . Mutual fund industry : Hearing before the Committee on Energy and Commerce . 22 July 1993, 146 . GPO: Washington, D .C. U.S . Congree . Committee on Commerce (1996) . Capital markets deregulation and liberalization act of 1995: Hearing before the Committee on Commerce . 14 November 1995, 283 . GPO : Washington, D.C . U.S . Congress (1996). Senator D'Amato of New York speaking on introduced bills and joint resolutions. D'Amato, Alfonse . Congressional Daily Record, (23 May).
THE EFFECT OF TAX RATE CHANGES ON THE YIELD SPREAD BETWEEN CORPORATE AND MUNICIPAL BONDS Elizabeth Plummer
ABSTRACT This study examines the effects of personal and corporate tax rate changes on the spread between pre-tax corporate bond yields and municipal bond yields, and provides evidence of tax clientele differences across bonds of different maturities and across bonds of different risk levels . Implicit tax theory suggests that the personal and corporate tax rate reductions of ERTA and TRA86 should reduce the yield spread between corporate and municipal bonds . The sample consists of 2,770 newly-issued taxable corporate bonds over the period 1979-1989 . Each corporate bond issue is matched with a similar municipal bond issue . The implicit tax rate (ITR) is used to measure the spread between corporate and municipal bond yields, and is equal to the yield spread divided by the corporate bond yield. For the, full sample, reductions in the personal and corporate tax rates both decrease ITR. However, the results differ across tax regimes . Prior to TRA86, changes in the personal and corporate tax rates have similar effects on ITR . Subsequent to TRA86, changes in the personal tax rate
Advances in Taxation, Volume 14, pages 271-307 . Copyright © 2002 by Elsevier Science Ltd. All rights of reproduction in any form reserved. ISBN : 0-7623-0889-3 271
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ELIZABETH PLUMMER
become more important and have a greater effect on ITR than changes in the corporate tax rate . The sample is also divided across time-to-maturity (short/long) and risk level (low/medium) . Evidence suggests that: (1) prior to TRA86, the marginal investors in medium-risk, short-term bonds were corporations, while the marginal investors in low-risk, short-term bonds were both individuals and corporations ; (2) prior to TRA86, the marginal investors in long-term bonds were both individuals and corporations, regardless of risk level ; and (3) subsequent to TRA86, the marginal investors in both short-term and long-term bonds are individuals, regardless of risk level .
1 . INTRODUCTION This study examines the effects of personal and corporate tax rate changes on the yield differential, or spread, between taxable corporate bonds and nontaxable municipal bonds, and provides evidence of tax clientele differences across bonds of different maturities and across bonds of different risk levels . Economics-based tax research assumes that, in equilibrium, different assets of similar risk have equivalent after-tax returns . This implies that if these assets are subject to different tax rates, then their pre-tax returns must differ . Specifically, the more favorably-taxed asset will have a lower pre-tax return . The difference in the pre-tax rates of return is the implicit tax borne by the favorably-taxed asset (Scholes & Wolfson, 1992) . Implicit tax theory suggests that personal and corporate tax rate reductions should reduce the spread between taxable and municipal bond yields required by investors . Consistent with this hypothesis, prior research finds that tax rate reductions do reduce the spread between U .S . Treasury bonds and municipal bond yields (e .g . Poterba, 1986, 1989) . The current study examines the effects of tax rate reductions on the spread between pre-tax corporate bond yields and municipal bond yields . Specifically, the effects of the personal and corporate tax rate reductions provided by the Economic Recovery Tax Act of 1981 (ERTA) and the Tax Reform Act of 1986 (TRA86) are examined . The results indicate that the ERTA and TRA86 tax rate reductions reduce the spread between corporate and municipal bond yields . This is consistent with prior research that uses treasury bonds . However, this study provides empirical evidence that the results differ across tax regimes . Prior to TRA86, results suggest that changes in the personal and corporate tax rates both reduced the yield spread and their effects were not significantly different from one another . Subsequent to TRA86, changes in the personal tax rate become more important and have a greater effect on the yield spread than
The Effect of Tax Rate Changes on the Yield Spread
273
changes in the corporate rate . The increased importance of personal tax rate changes subsequent to TRA86 is most likely attributable to the changes made by TRA86 that restricted the tax benefits that banks received when investing in municipal bonds . Poterba (1989) conjectures that, because TRA86 largely eliminated the tax incentives for banks to invest in municipal bonds, individuals would play an increasingly important role in municipal bond investment . Accordingly, individual tax rates would likely become the primary determinant of the yield spread between taxable and municipal bonds . The results in this study provide empirical support for this conjecture . This study also examines whether the effects of tax rate reductions on yield spreads vary across bonds of different maturities, and provides evidence on differences in tax clienteles between short-term and long-term bonds . In the early 1980s, over 90% of all tax-exempt debt held by banks had a maturity of five years of less . This concentration of bank ownership suggests that banks will play a relatively larger role in setting short-term bond yields . Consistent with this hypothesis, prior to TRA86, the results indicate that corporate tax rate changes are more important for the yield spreads of short-term bonds, while personal tax rate changes are more important for long-term yield spreads . These results complement and extend those reported in Poterba (1986, 1989) who finds similar evidence using U .S . Treasury bonds . However, like the full sample results, this study provides new evidence that the effects of changes in the personal tax rate increased after enactment of TRA86, and provides empirical evidence that, subsequent to TRA86, the marginal investors in both short-term and long-term bonds are individuals . Lastly, this study provides new evidence that the marginal investor differs across bonds of different risk levels . Scholes and Wolfson (1992) show that the pre-tax yield spread between a taxable and nontaxable investment of equivalent risk increases as risk increases . If the pre-tax yields do not both increase proportionately, this will cause differences in the marginal investor for bonds of different risk levels . Prior studies do not allow for possible differences in the marginal investor across risk level . This study examines whether the effects of the tax rate reductions on yield spreads vary across low-risk and medium-risk bonds, and provides evidence on differences in tax clienteles across bonds of different risk levels . This study makes several contributions to our understanding of the effects of tax rates and tax rate changes on corporate and municipal bond prices . First, few studies examine the effects of tax policy on the corporate bond market . However, the corporate bond market is important because bonds provide large amounts of financing for U .S . companies . During 1991, for example, corporate bonds represented 53% ($263 billion) of the total dollar value of all security
274
ELIZABETH PLUMMER
registrations filed with the U .S . Securities and Exchange Commission (Annual Report of the Securities and Exchange Commission, 1992) . Common stock comprised 34% ($168 billion) . This study provides evidence on the sensitivity of pre-tax bond yields to personal and corporate tax rate changes . The yield spread is modeled as a function of the personal and corporate tax rates, and the coefficient estimates from the model approximate the effect of tax rate changes on the yield spread . Second, this study provides empirical evidence that supports Poterba's (1989) conjecture that, subsequent to TRA86, individual tax rates would become the primary determinant of the yield spread . These findings are important to policymakers who must predict how tax law changes will impact the government's revenues and its cost of borrowing .' Third, this study provides new evidence on differences in tax clienteles across bonds of differing risk levels, and on how the marginal investor differs across maturity level and across time . This increases our understanding of the factors that affect the marginal investor and potential variables one must control for when examining such issues . In addition, this study uses corporate bonds as the taxable benchmark, while prior studies use treasury bonds . Therefore, this study provides additional, validating evidence on the relation between tax rates and pre-tax bond yields across bonds of different maturities . Also, this study provides new evidence on post-TRA86 tax clienteles for short- versus long-term bonds . Lastly, the findings not only increase our understanding of the relative importance of personal and corporate tax rates on bond yields, but also increase the confidence with which the relation between tax rate changes and bond yields can be generalized across different bond markets and bond types . The sample used in this study consists of 2,770 newly-issued taxable corporate bonds over the period 1979-1989 . Each corporate bond issue is matched with a municipal bond issue using criteria such as bond rating, issuance date, and time-to-maturity . Accordingly, there are 2,770 matched pairs . The implicit tax rate (ITR) is used to measure the yield spread between corporate and municipal bonds . ITR is equal to the difference between the corporate and municipal bond yields, divided by the corporate bond yield . ITR provides an estimate of the tax rate of the marginal investor (i .e . the investor who is indifferent between investing in either the corporate or municipal bond because his or her after-tax return will be the same) . ITR across the different years and maturity levels is first estimated . As expected, ITR decreases over the sample period, and is greater for short-term bonds than for longer-term bonds . ITR then is modeled as a function of the personal and corporate tax rates, corporate bond issue-specific variables, and other explanatory variables . For the full sample, results indicate that reductions
The Effect of Tax Rate Changes on the Yield Spread
275
in both the personal tax rate and the corporate tax rate decrease ITR . Prior to TRAM the effects of personal and corporate tax rate reductions on ITR are comparable . After TRA86, changes in the personal tax rate have a greater effect on ITR than changes in the corporate tax rate . As discussed above, the increased importance of personal tax rate changes subsequent to TRA86 is most likely attributable to the changes made by TRA86 that decreased banks' incentives to invest in municipal bonds . The model across maturity groups then is estimated . Prior to TRAM, for the shortest-term bonds (0-5 years), changes in the corporate tax rate had more of an effect on ITR than changes in the personal tax rate . For the three other maturity groups with time-to-maturities greater than five years, prior to TRAM, both personal and corporate tax rate changes affect ITR and their effects are not significantly different from one another . After TRAM, regardless of time-to-maturity, changes in the personal tax rate have a greater effect on ITR than changes in the corporate tax rate . These results are consistent with the hypotheses and suggest that : (I) prior to TRAM, the marginal investors in short-term bonds were corporations, while the marginal investors in longer-term bonds were both individuals and corporations ; and (2) after TRA86, the marginal investors in both short-term and long-term bonds are individuals . Finally, the model across low- and medium-risk bond groups is estimated . Results suggest that, on average : (1) prior to TRAM, the marginal investors in medium-risk, short-term bonds were corporations, while the marginal investors in low-risk, short-term bonds were both individuals and corporations ; (2) prior to TRA86, the marginal investors in long-term bonds were both individuals and corporations, regardless of risk level ; and (3) subsequent to TRAM, the marginal investors in both short-term and long-term bonds are individuals, regardless of risk level . The remainder of this article is as follows . The next section discusses the relation between tax rates and pre-tax returns, and develops the hypotheses . Section 3 discusses the sample and research design, while Section 4 provides the results . Conclusions are provided in Section 5 .
2. BACKGROUND AND HYPOTHESES Examining the relative yields of taxable and nontaxable bonds provides an estimate of the marginal investor's tax rate (t,,) . The marginal investor is the investor who is indifferent between investing in the two bonds because the after-tax returns from both bonds will be equivalent .' The marginal investor's tax rate also is referred to as the implicit tax rate (ITR) and is defined as :
276
ELIZABETH PLUMMER Y,(1-t m) = Y„
(1)
tm = (Y, - Y„) / Y,
(2)
where y, is the taxable bond's pre-tax yield, and y. is the non-taxable bond's yield. The value tm provides evidence on the tax clientele attracted to the taxable bond, and the implicit tax borne by the nontaxable bond . Ceteris paribus, taxpayers with a tax rate greater than tm would prefer to invest in the nontaxable bond because it will result in a higher after-tax return, while taxpayers with a tax rate less than tm would prefer to invest in the taxable bond . Prior studies almost exclusively focus on U .S . Treasury bonds when estimating implicit marginal tax rates and examining yield changes in response to tax rate changes . Guenther (1994) provides evidence that the 1981 and 1986 tax rate reductions reduced one-year U .S . Treasury bill yields . Poterba (1986) examines the implicit tax rate for U .S . Treasury bonds with maturities of one, five, ten, and twenty years for the period 1955-1983 . In each of those years, he finds that the implicit tax rate for the one-year bond was greater than that for any of the longer-term bonds . In addition, the implicit tax rate for 20-year bonds, and to a lesser extent for one-year bonds, declined between 1979 and 1982 (i .e . around the time of ERTA) . His results also provide evidence that both personal and corporate tax rate changes affect the relative yields on taxable Treasury bonds and tax-exempt municipal bonds, and some evidence that corporate tax changes are relatively more important for short-term yield spreads while personal tax changes are more important for long-term yield spreads . He attributes his results to the idea that commercial banks are the marginal investor in short-term Treasury bonds, while individuals are the marginal investor in long-term Treasury bonds . Poterba (1986) does not examine tax changes subsequent to 1983 . Poterba (1989) uses an event study method to examine the influence of federal tax policy on the tax-exempt bond market for the period 1969-1988 . He examines news events about Congressional tax policy debates and identifies months in which investors were likely to revise their expectations about future personal and corporate tax rates . His results provide evidence that the yield spread between Treasury and municipal bonds responds to changes in expected individual tax rates . His results also support the idea that, prior to 1986, the municipal bond market was segmented, with corporations being the marginal investor in short-term bonds and individuals being the marginal investor in long-term bonds . Because TRA86 largely eliminated the tax incentives for banks to invest in municipal bonds, Poterba (1989) conjectures that individuals would play an increasingly important role in municipal bond investment . However,
The Effect of Tax Rate Changes on the Yield Spread
2 77
his study does not provide evidence on changes in the marginal investor subsequent to TRA86 3 Fortune (1988) and Feenberg and Poterba (1991) both use representative U .S . Treasury and municipal monthly bond yields to calculate implicit tax rates . Fortune (1988) provides evidence that the implicit tax rate is related to statutory personal income taxes for the period 1976-1985 . Although not the focus of their study, Feenberg and Poterba (1991) report the trend in annual implicit tax rates for one-year and 20-year bonds . For one-year bonds, prior to 1986, the implicit tax rate was very close to the statutory corporate tax rate . After 1986, it more closely tracks the individual tax rate . For 20-year bonds, the ITR shows no clear trend over time . Although it appears to drop in the years immediately following TRA86, it increases again in the late 1980s . Feenberg and Poterba (1991) provide only descriptive evidence on the marginal investor's tax rate (ITR) for one-year and 20-year bonds . They do not examine short-term and long-term bonds for differences in the marginal investor's type (i .e . individual or corporation) and whether that type changes after TRA86 . Ang, Peterson, and Peterson (1985) provide evidence on the average implicit tax rate for 200 corporate bonds over the period 1973-1983 . However, they do not examine whether the implicit tax rate varies across time or across maturities, and provide no evidence on the effects of tax rate changes on corporate bond yields . As discussed earlier, none of these prior studies examine differences in the marginal investor across bonds of varying risk levels . The current study examines the yields for a large sample of newly issued taxable corporate bonds over the period 1979 through 1989 . This period is chosen because it contains two major tax acts that significantly affected both personal and corporate tax rates . ERTA decreased the maximum personal statutory tax rate from 70% to 50%, effective January 1, 1982, but did not change the maximum corporate statutory tax rate . TRA86 reduced the maximum personal statutory tax rate from 50% to 38 .5% in 1987, and from 38 .5% to 28% in 1988 . It reduced the maximum corporate statutory tax rate from 46% to 34%, effective for tax years beginning on or after July 1, 1987 .4 Tax rate reductions will not affect the required rate of return on non-taxable bonds (y), but will reduce the required return on taxable bonds (y,) . Therefore, a reduction in explicit tax rates will reduce the implicit tax rate through its effect on y, Equation (2) above shows that the implicit tax rate is defined as : t,n = (y, - y) / y,
(2)
Therefore, the change in the implicit tax rate due to a change in the explicit tax rate is :
278
ELIZABETH PLUMMER
dtm = [y, / y,2 ] dy,
(3)
It is hypothesized that the implicit tax rate (ITR) will decrease in response to the lower personal and corporate tax rates .' TRA86 largely eliminated the tax incentives for banks to invest in municipal bonds . Until this time, banks were permitted to borrow money, invest the proceeds in municipal bonds, deduct the interest expense payments from their taxable income, and recognize no tax liability from the municipal bond interest income. This contrasted to the general rule that did not allow an interest expense deduction on funds acquired to purchase tax-exempt securities . TRA86 changed the preferential treatment afforded to banks so that, subsequent to TRA86, banks are no longer permitted to deduct interest expense incurred on debt that is used to acquire municipal bonds . Poterba (1989) predicts that, because of this change, individuals would play an increasingly important role in the municipal bond market . Statistics regarding changes in the ownership of municipal bonds over time appear to support this prediction . In 1979, households owned approximately 26% of the outstanding tax-exempt bonds, while commercial banks owned approximately 43% . By 1988, the proportion of tax-exempt debt owned by households had increased to about 45%, while that owned by commercial banks had decreased to approximately 22%' Therefore, consistent with Poterba's (1989) conjecture, changes in the personal tax rate are expected to be relatively more important for explaining changes in ITR after TRA86 . The marginal investor is expected to vary across bonds based on their time-to-maturity . In the early 1980s, 52% of the tax-exempt debt held by banks had a maturity of one year or less, and 92% of banks' tax-exempt investment had a maturity of five years or less (Seek, 1982) . This pattern of ownership suggests that banks will play a relatively more important role in the short-term municipal bond market than in the long-term market . Poterba's (1986) and (1989) results are consistent with this . He finds evidence that, prior to TRA86, corporations are the marginal investor in short-term bonds and individuals are the marginal investor in long-term bonds . Therefore, the sample is divided into four maturity groups : 0-5 years, 6-10 years, 11-20 years, and 21-30 years . If corporations are the marginal investors in short-term bonds and individuals are the marginal investors in long-term bonds, then corporate tax rate changes will be relatively more important for explaining changes in ITR for short-term bonds . In contrast, changes in the personal tax rate will be relatively more important for explaining changes in ITR for longer-term bonds . Lastly, the marginal investor is expected to vary across bonds of different risk levels . Scholes and Wolfson (1992) show that the pre-tax yield spread
The Effect of Tax Rate Changes on the Yield Spread
27 9
between a taxable and nontaxable investment of equivalent risk increases as risk increases because the risk premium on the corporate bond is taxed whereas that on the municipal bond is not . For example, assume that a low-risk corporate and municipal bond have pre-tax yields of 10% and 7%, respectively . For this pair of bonds, the yield spread is 3%, and the marginal investor's tax rate is 30 .0% . Now assume a higher-risk corporate and municipal bond . For the marginal investor's tax rate (and thus ITR) to remain at 30%, each pre-tax yield must rise proportionately . For example, the corporate and municipal bond yields each must rise by 50%, to 15 .0% and 10 .5%, respectively . At this higher level of risk, the yield spread is now 4 .5%, but ITR is still 30 .0% . If the corporate and municipal pre-tax yields do not both rise proportionately, this will cause the marginal investor to differ from the low-risk bond . Therefore, the sample is divided into low-risk and medium-risk bonds, and tests for differences in the marginal investor across the two risk groups are run . This analysis also provides evidence on how the marginal investor changes across time for bonds of different risk. Prior studies do not provide evidence on differences in the marginal investor across bonds of differing risk levels .
3. SAMPLE AND RESEARCH DESIGN Sample The sample consists of all new corporate bond issues on the Fixed Income Database (FIDB)' that meet the following criteria : (1) issued by a corporation over the period 1979 through 1989 ; (2) issued within $3 of $100 ; (3) have a Moody's bond rating of Baa or higher ; and (4) have the variables on the database necessary to estimate the model discussed below . The second criterion assures that the bond is issued close to par in order to minimize potential effects on bond yields of tax-timing options . Tax-option effects arise from taxpayers' abilities to optimally time the recognition of capital gains and losses for tax purposes, potentially causing bond prices to deviate from their hold-to-maturity values (see Constantinides & Ingersoll, 1984) . In addition, the IRC rules regarding amortization of bond discount and premium for corporate bonds differ from the rules for municipal bonds . Therefore, eliminating bonds with substantial discount and premium also helps minimize the possibility that differences in the amortization rules might impact the results ." New bond issues are used for two reasons : this helps to minimize the
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ELIZABETH PLUMMER
potential effects on bond yields of the tax-timing options, and avoids potential problems with out-dated bond ratings . The third criterion is imposed because municipal bond issues, discussed below, are only available for Baa ratings or higher . Because of the relatively small number of corporate bonds with a life greater than 30 years (only 80 bonds over the eleven-year period), they were excluded from the final sample . To obtain estimates of implicit tax rates and to control for differences in rates of return across time, each corporate bond issue is matched with a nontaxable municipal bond issue . Salomon Brothers' Analytical Record of Yields and Yield Spreads is used as the source for municipal bond data. 9 Salomon Brothers provides the average yield-to-maturities for a sample of par value municipal bonds issued at the beginning of each month . They provide the yields for bonds of seven different maturities (1, 2, 5, 10, 15, 20, and 30 years) and three different ratings (prime, good, and medium) . "Prime" is the highest rating awarded to municipal bonds by Moody's and is equivalent to Aaa . "Good" corresponds to An to high A, while "medium" corresponds to A to high Baa . 10 The corporate bond is matched with the representative municipal bond based on bond rating, date of issue, and number of years to maturity . Specifically : (1) the corporate bond and representative municipal bond must be in the same rating class ; (2) the corporate and municipal bond yields must be measured as of the same date ; and (3) the corporate bond is matched with the representative municipal bond that is closest in terms of years-to-maturity . These requirements attempt to ensure that the taxable corporate bond and nontaxable municipal bond are as similar as possible ." Several measures were taken to help control for differences in risk between the corporate bond and its matched municipal counterpart . First, corporate bonds that are subordinated and those with put options are excluded . These features would affect the corporate bond's risk . However, none of the representative municipal bond issues have such features, and these risk differences cannot be controlled for through the matching process . Second, as described in step (1) above, the corporate and municipal bond issues are matched on bond rating . Third, only newly-issued bonds are used . This helps minimize the risk that the bond ratings are outdated and do not reflect an entity's current credit risk ." For purposes of analysis, the sample is divided into two risk groups : low-risk bonds (i .e . rating of Aaa to high A), and medium-risk bonds (i .e. rating of A to high Baa) .
281
The Effect of Tax Rate Changes on the Yield Spread
Table l, panel A, provides information on the sample selection criteria, while panels B and C provide information on the sample breakdown by time-tomaturity, risk level, and industry . The final sample consists of 2,770 new bond issues . The largest group in terms of years-to-maturity is bonds with a 6 to 10 year life (41 .4% of the sample), followed by 21-30 year bonds (26 .4%) and 0-5 year bonds (24 .6%) . In terms of risk level, the sample is almost evenly
Data on corporate bond sample .
Table 1 .
Panel A : Sample selection criteria New corporate bond issues on the FIDB (1979-1989) Less : No yield data Not issued within $3 of $100 No bond rating available
4,877 216 916 57 435 194 80 209
Bond rating lower than Bus Municipal yield data not available Time-to-maturity greater than 30 years Subordinated and/or put option feature Total sample
Panel
B:
2 .770
Sample breakdown
by
bond risk level and by years-to-maturity
0-5 years 6-10 years 11-20 years 21-30 years Total Percentage of sample
Percentage of sample
Low-risk
Medium-risk
Total
468 492 77 326
214 654 135 404
682 1,146 212
24 .6% 41 .4% 7 .7%
730
26 .4%
1,363
1,407
2,770
100 .0%
49 .2%
50 .8%
100 .0%
Panel C : Sample breakdown by industry and by years-to-maturity Industrial
Utility
Financial
Total
Percentage of sample
0-5 years 6-10 years 11-20 years 21-30 years
145 386 64 224
44 314 42 415
493
682
24.6%
446 106 91
1,146 212 730
41 .417, 7 .7 26.4%
Total
819
815
1,136
2,770
100 .0%
29.6%
29 .4%
41 .0%
100.0%
Percentage of sample
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ELIZABETH PLUMMER
divided between low- and medium-risk bonds (49 .2% and 50 .8% of the sample, respectively) . In terms of industry, bonds issued by firms in the financial industry are the most prevalent (41 .0%) . Bonds issued by industrial firms and utility firms make up 29 .6% and 29 .4% of the sample, respectively . Model
The ITR, or variants of it, has been used in several earlier studies (e .g . Peek & Wilcox, 1986 ; Heaton, 1986 ; Buser & Hess, 1986 ; Hochman et al ., 1993) . To estimate the differential effects of the personal and corporate tax rate reductions on the yield spread between corporate and municipal bonds, this study models ITR as a function of the personal and corporate tax rates, corporate bond issue-specific characteristics, and economic-related variables . The equation estimated is : tm„ = (y ;, - y . ;,) / y a = /30 + Ro'D86 + $, tp, + R 2 tc , + 0,T) 86 * tpt + /33CALL, + /34 SINK. + F35ISSUESZ, + /36 YRMATi + /37MEDIUMRTG j + /3 8 1JTILITY. + /3Y FINANCE,
+ P 10RISKGVsP, ,+ /3 11 RISK M " SG, , + /3,2 MUNI_ALL, + error„
(4)
where tma y„ y,, tp, t1t D 86 CALL,
SINK I ISSUES ; YRMAT,
MEDIUMRTG,
= implicit tax rate on municipal bond issue i, measured at time t ; = yield-to-maturity of corporate bond issue i, issued at time t ; = yield-to-maturity of the nontaxable municipal bond issue matched to corporate bond issue i, measured at time t ; = the personal tax rate at time t (defined below) ; = the corporate tax rate at time t (defined below) ; 13 = dummy variable equal to 1 if the year is 1986 or later, and equal to zero otherwise ; = 1 if bond issue i is callable, 0 otherwise ; = I if bond issue i has a sinking fund, 0 otherwise ; = log of issue size of bond issue i, in thousands of dollars ; = years to maturity of bond issue i, defined as number of days from date of issuance date until maturity date, divided by 365 ; = 1 if bond issue i is rated "medium" (A to Baa), and 0 otherwise ;
The Effect of Tax Rate Changes on the Yield Spread UTILITY .
FINANCE ., RISK CWsr
RISK MVyct
MUNt AIL,
2 83
= I if firm issuing bond issue i is in the utility industry, 0
otherwise ; = 1 if firm issuing bond issue i is in the financial industry, 0 otherwise ; = yield spread between newly-issued, one-year good-grade (GI) and prime-grade (P1) municipal debt, divided by PI [i .e . (Gl-Pl)/Pl], measured at time t ; = yield spread between newly-issued, one-year mediumgrade (Ml) and good-grade (Gl) municipal debt, divided by GI [i .e . (Ml-Gl)/Gl], measured at time t ; and = the supply of new municipal debt divided by the supply of new aggregate U .S . market debt, measured at time t .
The coefficient (3, provides an estimate of the effect on ITR of a change in the personal tax rate, while /3z provides an estimate of the effect on ITR of a change in the corporate tax rate . This estimation decomposes the effects of the personal and corporate tax rates on ITR. A dummy variable (D R6) also is included to examine whether the effects of changes in the personal tax rate differ after enactment of TRA86 . TRA86 significantly affected banks' incentives to purchase municipal bonds . Prior to 1982, banks were permitted a tax deduction for the interest they paid on deposits that were used to purchase municipal bonds . This tax advantage was reduced by TEFRA in 1982, further reduced by DEFRA in 1984, and totally eliminated by TRAM . Accordingly, TRA86 is likely to have affected the marginal investor not only by reducing tax rates but also by reducing banks' participation in the municipal bond market . If bank demand for municipal bonds decreased significantly after TRAM, individuals (and thus personal tax rates) may play a relatively larger role in determining ITR ." Personal and corporate tax rates are estimated using both : (1) the maximum statutory tax rate for the current year (i .e. the year the bond is issued) ; and (2) the maximum statutory tax rate for the next year (i .e. twelve months after the bond is issued) . Table 2 provides the personal and corporate maximum statutory tax rates for the years 1979-1990 . For comparison purposes, Table 2 also provides the maximum effective personal and corporate tax rates for the same period . 15,16 Differences in the non-tax costs of municipal and corporate bonds are controlled for through the matching criteria, and by including issue-specific variables and economic-related variables in the model . The issue-specific variables have been identified by prior research (e .g . Ziebart & Reiter, 1992) as affecting the non-tax cost of corporate bonds (and thus y,) . The economicrelated variables have been identified by prior research (e .g . Buser & Hess,
284
ELIZABETH PLUMMER Table 2.
Maximum statutory tax rates and effective tax rates (in percentages), 1979-1990a .
Year
Max Individual Statutory Rate
Max Corporate Statutory Rate
Effective Individual Rate
Effective Corporate Rate
1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990
70 .0 70 .0 70.0 50.0 50 .0 50 .0 50 .0 50.0 38 .5 28 .0 28 .0 28.0
46 .0 46 .0 46 .0 46 .0 46 .0 46 .0 46 .0 46 .0 46 .0 34 .011, 34 .0 34 .0
64.5 62.9 59 .9 49 .5 49.0 50.6 49 .1 51 .2 34.0 28 .1 27 .9 27 .8
45 .44 45 .43 45 .11 45 .66 45 .57 44 .91 44 .71 42 .52 39 .78 35 .23 35 .33 35 .88
"The maximum statutory rates are taken from the Internal Revenue Code. The effective tax rates are taken from the U .S . Treasury Department's Statistics of Income: Corporate Income Tax Returns and Statistics of Income: Personal Income Tax Returns .
TRA86 reduced the maximum corporate statutory tax rate from 46% to 34%, effective for tax years beginning on or after July 1, 1987 . Corporations having a tax year that straddled July 1, 1987, were subject to a blended rate for that year . b
1986) as affecting the non-tax cost of municipal bonds (and thus yai ) . The predictions made regarding the relation between the issue-specific variables and ITR (a measure of the yield spread) are based on the expected relation of these variables with the corporate bond yield . The coefficients on CALL and SINK are expected to be positive, while the coefficient on ISSUESZ is expected to be negative." A call option (CALL) allows a corporation to retire the bond issue if interest rates drop significantly . Accordingly, the corporation is expected to pay a higher yield for the right to retain this option . Sinking fund agreements (SINK) are undertaken to increase the bondholders' security . Therefore, Sink is expected to be positively associated with corporate bond yields because the necessity of entering into a sinking fund agreement is related to a riskier bond issue . The log of the issue size (ISSUESZ) proxies for the corporate bond issue's marketability and is expected to be associated with lower corporate bond yields . The number of years to the corporate bond's maturity (YRMAT) is expected to be negatively associated with ITR because, as discussed earlier, the implicit tax rate is expected to decrease as Yrmat increases . II To help control for systematic differences across bond risk levels, an indicator variable (MEDIUMRTC) is included if the bonds are rated medium . 19 Industry indicator variables (UTILITY
The Effect of Tax Rate Changes on the Yield Spread
285
and FINANCE) are included to control for any systematic differences in ITR across industry . 20 Three economic-related variables that have been found by prior studies (e.g . Buser & Hess, 1986) to influence yield spreads across time (RISKCV}p, RISKMVSC' and MUNI_ALL) are also included . These variables affect the yield spread because of their effects on the cost of municipal debt (y,,,) . Poterba (1986) and Trczinka (1982) argue that municipal interest rates include a default premium that varies with the level of municipal default risk . They argue that the yield spread between taxable and municipal bonds varies because of variations across time in the perceived riskiness of municipal bonds . To help control for possible changes in the default risk of municipal bonds across time, the yield differential between newly issued, one-year good- and prime-grade municipal bonds (RISK a1`p ), and the yield differential between newly issued, one-year medium- and good-grade municipal bonds (RISKM "SC, ,) are included (see Buser & Hess, 1986) . Both RISK O „ SP , and RISK MVSG increase as municipal bonds' default risk increases . If the perceived riskiness of municipal bonds increases, the municipal yield will increase relative to the taxable yield, thereby decreasing the yield spread . Therefore, if the perceived riskiness of municipal bonds varies across time, there will be a negative relation between ITR and the risk variables (RISK,,,,,,, and RISK MVyo ) . These data are taken from Salomon Brothers' Analytical Record as of the same date as the corporate bond issue . Both risk measures are computed in the same manner as Buser and Hess (1986) . Consistent with prior research, MUNI ALL is included to control for changes in ITR attributable to changes in the relative size of the municipal bond market (see Peek & Wilcox, 1986 ; Poterba, 1986 ; Hochman et al ., 1993) . This is particularly important because of the changes that occurred during the sample period that significantly decreased banks' incentives to invest in municipal bonds (discussed above) . Muni All is expected to be negatively associated with ITR . As the relative supply of municipal debt increases, the municipal yield will increase relative to the taxable yield, thereby decreasing the yield spread . The supply data are taken from the Federal Reserve Bulletin, Flow of Funds accounts . 21 22 Appendix 1 contains a summary of the variables used in the study .
4. RESULTS Descriptive Information
Table 3 contains descriptive statistics regarding the sample's characteristics . The median corporate bond yield is 10.05%, while the median municipal bond
286
ELIZABETH PLUMMER Table 3.
Variable tmii .1 Y y nLt
Issunsz. (in 000s) YRMAT; CALL . $INK .
Descriptive information for selected variables (N = 2,770) . Mean
Median
1st quartile
3rd quartile
30.12% 10.70% 7.43% $134,158 13 .67 yrs
29 .30%
24.34% 9 .04% 6.25% $75,000 6 .01 yrs
35 .72% 12 .03% 8 .40% $150,000 25 .01 yrs
10.05%
7 .10% $100,000 10 .01 yrs
Proportion of sample
64.55% 24 .26%
Note: Variable definitions are in Appendix 1 .
yield is 7 .10% . The median ITR is 29 .30% . The corporate bond issues are large, with a median value of $100 million . The median maturity for all corporate bond issues is a little over 10 years . About 64% of the corporate bonds have call options, while about 24% have sinking fund agreements . Correlation values for the full sample are presented in Table 4 . As hypothesized, ITR (I id is positively correlated with both the personal (t pt) and corporate (tit) tax rates . The Pearson and Spearman correlation values for tmh with tp, are 0 .368 and 0 .311, respectively, and for tmh with t it are 0 .132 and 0 .134, respectively . Also consistent with expectations, ITR is negatively correlated with the number of years to maturity (YRMAT), suggesting that the implicit tax rate decreases as the bonds become longer-term . This is consistent with Poterba's (1986) evidence on the marginal tax rate for U .S . Treasury bonds of differing maturities . As predicted, the size of the corporate bond issue (IssuEsz) is negatively correlated with t mlt , but it is not significant . Contrary to expectations, t mit is negatively correlated with the existence of a call option (CALL) and a sinking fund agreement (SINK) . Recall that predictions regarding the relation of tm¢ and the issue-specific variables are based on the variables' predicted relation with corporate bond yields . The correlations between the corporate bond yield and CALL and SINK, however, are consistent with expectations . As predicted, CALL and SINK are positively correlated with the corporate bond yield .' Marginal Investor in Corporate and Municipal Bonds To provide descriptive evidence on differences in the marginal investor in corporate bonds across tax regimes and across maturities, Table 5 presents the
Effect of Tax Rate Changes on the Yield Spread
r ti O Orn cc N -- w : t~ 080° '0- 08=808
d
SC 5 O
M1 .
J
O p
v
co
0 0 0 0 0 0 0 0 0 0 0
0 fs p p W 0 en Oi p -T p 0 N 0 M O- 0 0 0 0 0 v~ 8 ^~ pI 0 0 0 .J 0 0 0 0 O O C 0
n O'-rn -0 -cc0C 0 0 N 0 00~ 0 00 0O0 00b 00
O O m -O 0 0 00 00 0
II
z~5 v
vet
.d CO N v r L ~_ W ~
i O 4 a L d
7 LO O~ O
m
C 5 S O C O U A m ~ .a v Y p UO L
7,
o
~0-omo O O O O C o
J _8 en 000000
0 O0 VO0-1 0O O0 0O
M8-8-8-8 00000000
N C o 0 0 C 0 6 o O 06c60 N - OG -
.^, 7 - V ^ Vl
288 Table 5.
ELIZABETH PLUMMER Median implicit tax rate by tax regime and by time-to-maturity ."
Bond Group 0-5 Year Maturity 6-10 Year Maturity 11-20 Year Maturity 21-30 Year Maturity Full Sample
Pre-ERTA (1979-1980)
ERTA (1981-1985)
TRA86 (1986-1989)
All Years (1979-1989)
47 .68 (23) 44 .95 (133) 41 .88 (23) 37 .06 (139) 41 .17 (318)
39 .11 (220) 30.34 (499) 25 .57 (82) 23 .42 (244) 29.24 (1,045)
33 .25 (439) 26 .88 (514) 22 .78 (107) 23 .26 (347) 27 .27 (1,407)
34.87 (682) 29.47 (1,146) 25.46 (212) 24.55 (730) 29 .30 (2,770)
"The first number is the median implicit tax rate, while the second number in parentheses is the sample size N. Differences across tax regimes and across time-to-maturity groups are significant at p < 0 .001 by the Jonckheere test of ordered alternatives (Hollander & Wolfe, 1973) .
median ITRs for the years corresponding to pre-ERTA, ERTA, and TRA86 for the full sample and for the four different maturity groups ." For all years combined, the median ITR for the full sample is 29 .30% . Consistent with Poterba's (1986) evidence on U .S . Treasury bonds, the median ITR is highest for the short-term, 0-5 year bonds (34.87%), and is considerably lower for the longer-term bonds (about 25% for bonds with greater than a 10-year life) . In all tax regime periods, the median ITR for the 0-5 year bonds is greater than that for any other maturity group . Generally for each tax regime, the median ITR decreases monotonically as the time-to-maturity increases . For all years combined and for each tax regime period, the ITR differences across time-tomaturity groups are significant at p < 0 .001 by the Jonckheere test of ordered alternatives (Hollander & Wolfe, 1973) 25 For the full sample and within each maturity group, the median ITR decreases monotonically across the three different tax regimes (all differences are significant at p < 0 .001 by the Jonckheere test) . This pattern across tax regimes is consistent with the decreases in the personal and corporate tax rates that occurred over this period . The median ITR for the full sample is 41 .17% for the pre-ERTA period and only 27 .27% for the TRA86 period, a decrease of fourteen percentage points . Across maturity groups, the median ITR decreases from between fourteen to nineteen percentage points .
The Effect of Tax Rate Changes on the Yield Spread
28 9
Full Sample
The pattern of implicit tax rates in Table 5 provides descriptive evidence on the effect of tax rate reductions on the yield spread between corporate and municipal bonds, as well as the tax rates of marginal investors across time and across time-to-maturities . However, it is difficult to discern the type of marginal investor (i .e. individual or corporation) by simply examining the ITR or its trend . That is, the ITR merely tells us the marginal investor's tax rate, not the type of marginal investor . To provide evidence on whether the marginal investor is an individual or a corporation, equation (4) described above is estimated . Equation (4) models t m -, (the ITR) as a function of the personal and corporate tax rates, as well as other explanatory variables . Evidence on the marginal investor's type is provided by examining the relation of ITR with t P and t, (i .e . the (3, and (3, coefficients) . Equation (4) is estimated for the full sample, and results are provided in Table 6 . All t-statistics are computed using White's (1980) covariance matrix . The p-values are one-sided if a directional hypothesis is predicted, and two-sided if no direction is predicted . Poterba (1986), among others, shows that the yield spread between taxable and non-taxable bonds depends upon the market's expectations about tax policy . Therefore, results presented in Table 6 are based on setting t P and t , equal to the maximum statutory tax rates for the year after the bond is issued . This assumes that bond yields are based on investors' expectations about future personal and corporate tax rates, and that the realized maximum statutory tax rates one year after the issuance date provide an unbiased estimate of investors' expectations at time t 17 The adjusted RI for the full sample is 0 .499 . The coefficient /3 i provides an estimate of the effect on ITR of a change in the personal tax rate, while /3, provides an estimate of the effect on ITR of a change in the corporate tax rate . R, and 0, are both hypothesized to be positive, suggesting that reductions in the personal and corporate tax rates both decrease ITR . For the full sample, /3 i = 0.498 and is highly significant (t= 18 .77, with a p-value < 0 .001), while (3 2 = 0 .431 and is also significant (t=7 .04, with a p-value < 0 .001) . Although /3 i is greater than /3,, tests indicate that the difference is not statistically significant . These results are consistent with the hypothesis and suggest that, on average, reductions in the personal and corporate tax rates both decrease ITR . Specifically, a decrease of one percentage point in the personal (corporate) tax rate would reduce the implicit tax rate by 0 .498 (0 .431) percentage points . Also hypothesized is that changes in the personal tax rate will have an increased effect on ITR after TRAM . The coefficient /3' i provides evidence on
290
ELIZABETH PLUMMER
Table 6. Full sample regression results of the marginal investor's tax rate on the personal tax rate, corporate tax rate, and other explanatory variables . [.,~ = a+ u ss+ +)$,CALL,
1Ip1 +
i~,1 +
,
es
I t,
+ /34 S1NK + $ 5 ISSUESZ, + /36 YRMAT .,
+ /37MEDIUMRTG; + /3sUTILITY. + #,FINANCE, + /3 IORISKcvsp, , + /3,,RISK MV,,J ,
Variable
Predicted sign
intercept xe t, *tpi CALL SINK . ISSUESZ. YRMAT MEDIUMRTGI D96
UTILITY.
FINANCE. RISKGvsP,, RIsxMvsG,, MUNI_ALL, Adjusted R2 Sample Size N
? + + + + + 7 7 ? -
+
P 12MUNI-ALL, + error,
Estimated coefficient value 0.826 -1 .793 0 .498 0.431 0 .558 -0.168 0.100 0.002 -0.360 -2 .151 0.918 0 .917 -1 .912 -2 .317 -2 .330
White's t-statistic 0 .14 -1 .96 18 .77 7 .04 11 .48 -5 .74 2 .90 0.01 -22 .31 -4.95 2 .83 3 .04 -2 .50 -0.42 -2.59
p-value" us . (0 .050) (0.001) (0.001) (0 .001) " (0 .002) n.s . (0 .001) (0 .001) (0.005) (0 .002) (0 .006) n .s . (0 .005)
0 .499 2,770
Note : Variable definitions are in Appendix 1 . -p-values are one-sided if a directional hypothesis is predicted, and are two-sided if no direction is predicted . I,' Estimated coefficient is not in the predicted direction and is significant at the p=0 .01 (p=0 .05) level . n .s . Estimated coefficient is not significant at the p=0.10 level .
whether the effect on ITR of changes in the personal tax rate is different after enactment of TRA86. For the full sample, f3' 1 = 0.558 and is highly significant (t = 11,48, with a p-value < 0 .001) . Consistent with the hypothesis, this result suggests that changes in the personal tax rate have had more of an effect on ITR subsequent to TRA86 . The sum of f3, +)3', provides an estimate of the effect on ITR of a change in the personal tax rate after TRA86. The
The Effect of Tax Rate Changes on the Yield Spread
291
coefficient estimates suggest that, after TRAM, a decrease of one percentage point in the personal tax rate reduces ITR by 1 .056 percentage points 2 8 This is consistent with the idea that, after TRAM, the marginal investors in corporate and municipal bonds are individuals . With respect to the issue-specific variables, the coefficient for Sink is significantly positive as expected (t = 2 .90), while Yrmat is negative as expected and highly significant (t = -22 .31) . lssuesz is negative but not significant (t = 0 .01) . Contrary to predictions, Call is significantly negative (t=-5 .74) . Consistent with expectations, implicit tax rates are negatively associated with the size of the issue and are positively associated with the presence of a sinking fund agreement. The estimated coefficient for MEDIUMRTG is significantly negative (t=-4 .95) . This suggests that, after controlling for the other factors in Eq . (4), the ITR for medium-risk bonds is lower than the ITR for low-risk bonds . This suggests that the marginal investors in low- and medium-risk bonds differ . Therefore, a later section of the paper explores the possibility that changes in tax rates have differential effects on the ITRs of low- and medium-risk bonds . The utility and finance industry indicator coefficients are both significantly positive at conventional levels (p-value < 0 .010) . However, in sensitivity analysis (not reported here), there is no evidence that the effects of changes in to and t vary across industry 29 The coefficient on the risk variable RISKCVsp , is significantly negative as predicted (t=-2,50), but the coefficient on RiSK MV C,, , is not significant . These results suggest that variations over time in the perceived riskiness of the lower grade municipal bonds, but not the higher-grade municipal bonds, have had a detectable effect on the ITR . Lastly, the coefficient on MUM-ALL, is significantly negative as predicted (t=-2 .59), suggesting that decreases in the supply of municipal debt decrease ITR . By Time-to-Maturity Groups Corporate tax rate changes are hypothesized to be relatively more important for affecting the yield spread of short-term bonds, while personal tax rate changes are expected to be relatively more important for long-term bonds . To examine this hypothesis, equation (4) is estimated separately for each time-to-maturity group, and results are presented in Table 7 . The adjusted R2 s for the different maturity groups range from 0 .552 to 0 .742 . For the shortest-term bonds (0-5 years), the coefficient on the personal tax rate (/3) has a value of 0 .340, and the coefficient on the corporate tax rate (0 2) has a value of 0 .577 . Both values are significantly greater than zero (p-values < 0 .001) .
292
ELIZABETH PLUMMER
Tests also indicate that t'2 is significantly greater than 6, (p-value < 0 .001) . A decrease of one percentage point in the personal (corporate) tax rate would reduce the implicit tax rate by 0.340 (0.577) percentage points . These results suggest that, prior to TRA86, changes in corporate tax rates were more important than changes in personal tax rates for determining the spread on short-term bonds . However, evidence suggests that the effects on ITR of changes in the personal tax rate increased after enactment of TRA86 . The coefficient /3', has an estimated value of 0 .545 and is significantly greater than zero (p-value < 0 .001) . The sum of /3, +,6', is 0 .885 and implies that a one percentage point decrease in the personal tax rate
Table 7. Regression Results of the Marginal Investor's Tax Rate on the Personal Tax Rate, Corporate Tax Rate, and Other Explanatory Variables, by Time-to-maturity Groups . tmll -
I'O
+ RII DBE+RItp,+R2tn +
I'I
DAfi
tpt
+ #,CALL, + /3,SINK, + $S ISSUESZ, + /36YRMAT. + I37,MEDIUMRTG, + /35UTILITY, + /39FINANCE, +l3, 0RISKey, +(i, RISK,,, ct +$ 12MUNI_ALL, +error,
Variable
Predicted sign
Intercept D86 tr, to D86*tr, CALL SINK. Issuesz, YRMAT. MEDIUMRTC,
?
UTILITY
7
FINANCE , RISKGvsP,, RIsKMvsG, MuNLALL
9
Adjusted R2 Sample Size N
0-5 years: Estimated coefficient White's value t-statistic 0 .217 0 .993 0 .340 0 .577 0 .545 -0 .489 0.882 -0 .783 -1 .755 -2 .559 0.491 0.546 2 .500 2.327 -3 .236 0.552 682
2 .29 1 .25 6.53 7 .00 5 .71 -1 .18 0.79 -3 .20 -12.94 -4.60 0.65 1 .32 1 .17 0.93 -2.90
p-value' (0.022) n .s . (0.001) (0 .001) (0.001) Its.
n.s. (0.001) (0.001) (0.001) Its .
as. n.s. n.s. (0.002)
6-10 years : Estimated coefficient White's value t-statistic 3 .999 0.879 0 .506 0 .534 0 .184 1 .448 -0 .357 -0 .963 -2.162 -2 .802 0 .782 0 .753 -2 .669 1 .077 -2 .937 0 .572 1,146
1 .69 1 .37 14.62 5 .79 10.68 3 .62 -0.57 -3 .40 -17.55 -3 .73 1 .70 1 .88 -2.40 1 .40 -2.39
p-value° (0.090) n .s . (0.001) (0 .001) (0.001) (0.001) ns. (0.001) (0.001) (0.001) (0.090) (0.060) (0.008) n.s. (0.008)
The Effect of Tax Rate Changes on the Yield Spread Table
7.
293
Continued .
tm,,=RF+P DKR+P,tp,+0,t,,+$,'DNR*I,, + R,CALL ., + 0,SINK .. + $, ISSUESZ.. + /3R YRMAT ., + 0,MEDIUMRTG ., + PSUTILITY ., + /3Q FINANCE ., +/3 IO RISK
cvIFI
+(3,,RISK MVSO ,+0, 2MUNI ALL, +error, ,
11-20 years :
21-30 years :
Estimated Variable
Predicted sign
Intercept D86
D86*t ,~ CALL SINK . Issueszs YRMAT . MEDIUMRTa. UTILI Y, FINANCE. RISKGvsP,, RISKMvSG,, MUM Au, Adjusted R'Sample Size N
+ +
s
Estimated
coefficient value
White's t-statistic
-3 .520 -2 .122 0 .900 0 .739 0 .064 -1 .689 0 .609
-1 .45 -1 .59 7 .73 2 .97 3 .68
1 .545 -0 .419 -0 .265 0 .644 1 .197 -2 .809 -1 .031 -3 .317
2.20 -2 .90 -1 .16 1 .71 3 .61 2.23 0 .43 0.90
-1 .20 4 .02
0637 . 212
p-value" as . ns . (0 .001) (0 .002) (0 .001) n .s . (0 .001) c (0 .002) n .s . (0 .088) (0 .001) (0 .013) n .s . n.s .
coefficient value
White's t-statistic
p-value'
3 .936 -2 .399 0 .563
0 .56 .62 1 19 .57
n .s. n.s. (0.001)
0 .617 0 .417 1 .936 0 .516 .419 0 -0.374 -1 .062 2 .136 2 .083 0 .789 1 .870 2 .505
2.59 6 .74 2 .48 .60 1 2 .01 -4 .57 1 .96 5 .84 4 .06
(0.005) (0.001) (0.007) (0.055) c (0.001) (0,050) (0.001) (0 .001) n .s.
-0 .09 -3 .31 -2.16
(0.001) (0 .0t5)
0.742 730
Note: Variable definitions are in Appendix I . 'p-values are one-sided if a directional hypothesis is predicted, and are two-sided if no direction is predicted. s, Estimated coefficient is not in the predicted direction and is significant at the p=0 .01 (p=0 .05) level . n .s . Estimated coefficient is not significant at the p=0.10 level .
reduces ITR by 0 .885 . This suggests that, after TRA86, changes in personal tax rates have had more of an effect on the spread of short-term bond yields than changes in the corporate tax rate . For each of the three other maturity groups with time-to-maturities greater than five years, coefficients on both the personal tax rate (/3) and the corporate tax rate ()3,) are significantly positive . For the 6-10 year maturity
294
ELIZABETH PLUMMER
group, the /3 i and /3Z values are 0 .506 and 0 .534, respectively, and tests indicate the estimated coefficient values are not significantly different from one another. For the 11-20 year maturity group, the estimated values for /3 i and $2 are 0 .900 and 0 .739, respectively, and /3, is marginally greater than /3 z (p < 0.06) . For the longest-term bonds (21-30 years), /3, and /3, are 0 .563 and 0 .617, and are not significantly different from one another. These results suggest that, prior to TRA86, both personal and corporate tax rate changes affected longer-term bond yields and, in general, their effects were not significantly different from one another . For each of these longer-term maturity groups, tests indicate that /3'1 is significantly greater than zero (all p-values < 0 .001) . This suggests that, after TRA86, personal tax rate changes had an increased effect on the spread of these longer-term bond yields . In addition, for each of these maturity groups, tests indicate that the sum of /3 i + 0', is significantly greater than /32 . This is similar to the shortest-term bond group (0-5 years) and suggests that, after TRA86, changes in the personal tax rate have had more of an effect on ITR than changes in the corporate tax rate . In summary, the results are consistent with the hypotheses and suggest that, on average : (1) prior to TRA86, the marginal investors in the shortest-term bonds (0-5 years) were corporations, while the marginal investors in longerterm bonds were both individuals and corporations, and (2) subsequent to TRA86, the marginal investors in both short-term and long-term bonds are individuals . The shift toward individuals being the marginal investors in bonds of all maturities is consistent with Poterba's (1989) hypothesis and with the aggregate statistics showing a relative decrease in bank ownership of tax-exempt securities . Because TRA86 significantly decreased the incentives for banks to purchase municipal bonds, banks will play a relatively smaller role in the municipal bond market, and individuals will play a relatively larger role . As a result, personal tax rates became more important in establishing bond yields . The estimated coefficients on the issue-specific variables vary in magnitude and significance across the maturity groups, but are generally consistent with predictions . For all groups, the estimated coefficients on Call, Sink, and Yrmat are either significant in the predicted direction or insignificant . As expected, IssuESZ is significantly negative for two maturity groups (p