THE EFFECT OF INCOME TAXES 

ON HOUSEHOLD INCOME 

Gerald Auten and Robert Carroll 

U.S. Department of the Treasury 

OTA Working Paper 75 March 1998 

OTA Papers and Briefs are circulated so that the preliminary findings of tax research conductedby 

staff members and others associated with the Office of Tax Analysis may reach a wider audience. 

The views expressed are those of the authors, and do not reflect Treasury policy. Comments are 

invited, but OTA papers and Briefs should not be quoted without permission from the authors. 

Additional copies of this publication may be puchased from the National Technical Information 

Service, 5285 Port Royal Road, Springfield,VA 22161. 

Office of Tax Analysis 

U.S.Treasury Department 

Washington, DC 20220 

* We thank Jim Cilke and Gordon Wilson for their help in the developmentof the data and tax 

calculators, and Pete Sailer for his help in the development of the occupation codes. We are 

grateful to Len Burman, Martin Feldstein, Jonathan Gruber, Douglas Holtz-Eakin, David 

Joulfaian, C. Erik Larson, Karl Scholz, Joel Slemrod, Paul Smith, Jeny Tempalski,Eric Toder, 

and participants of the 1994NBER Summer Institute, the 1995 Tax Policy Research Symposium 

sponsored by the University of Michigan’s Office of Tax Policy Research, and the Hmard-MIT 

Public Finance Seminar for helpful comments. 
ABSTRACT 

Virtually all research on income and wealth distributions during the 1980s has identified a 

trend towards increasing inequality. Some of this research indicates that the increasing inequality 

during the 1980s is the continuation and acceleration of trends spanning several decades. This 

paper explores to what extent behavioral responses to the tax changes during the 1980s may also rl 

explain the rising inequality. The 1986 Tax Reform Act is used as a natural experiment to 

explore the roles played by both taxes and a variety of non-tax factors, including changing returns 

to education. Our principal finding is that both tax rates and non-tax factors appear to have had 

substantial effects on relative income growth during the late 1980s. 

c 
I 

c 

THE EFFECT OF INCOME TAXES ON HOUSEHOLD INCOME 

I. Introduction 

Although income inequality increased dramatically during the 1980~~ the causes of the 

rise in income inequality during this period are unclear. Two views have emerged as possible 

explanations of this rise in income inequality. One view is that it reflects the continuation and 

acceleration of trends spanning several decades. According to this view, a variety of economic 

factors having little to do with taxes explain the trend towards higher income inequality. For 

example, Murphy and Welch (1992) and Katz and Murphy (1992) found that the returns to 

human capital or education increased as a result of increased demand for labor with more 

education and skill. Other explanations include technological change (Bound and Johnson, 

1992), declining union membership (Freeman, 1993), increasing import competition, lessening 

of government pressure to increase minority employment (Bound and Johnson, 1992), increasing 

immigration (Topel, 1994), changing supplies of college educated workers (Katz and Murphy, 

1992), and continuation of the unwinding of wage compression during World War I1 (Goldin and 

Margo 1992). In general, this research has not considered the role played by taxes. 

Another view suggests that the tax rate reductions during the 1980s played an integral 

role in the rise in income inequality during the 1980s.' According to this view, increases in 

reported incomes among high income households were, in large part, the result of tax-induced 

behavioral responses, rather than a more fbndamental change in the shape of the income 

distribution (see, for example, Lindsey (1987) and Feldstein (1995a)). These behavioral 

responses may have taken many different forms including increased labor supply and 

'In the Economic Recovery Tax Act of 1981 (ERTA), the top individual income tax rate was 

reduced from 70 percent to 50 percent. In the TaxReform Act of 1986 (TRA), Congress broadened the 

tax base and further reduced the top statutory tax rate from 50 percent to 28 percent. 
2 

participation, increased savings, altering the timing of income, changes in the form of 

compensation, rearranging of portfolios, reduced tax evasion and avoidance, and changes in 

taxpayer decisions about deductions (e.g., how much to donate to charity and borrow for 

housing).2 This literature, however, has generally incorporated only limited controls for nontax 

factors that may have affected income changes. 

Evaluating the effects of the taxchanges of the 1980s and any appropriate policy 

response to increased inequality will depend on the extent to which these views can explain the 

increase in income inequality during the 1980s. If taxpayers reduce their reported incomes in 

response to higher tax rates, policies that increase tax rates to increase the progressivity of the tax 

system and reduce income inequality may be less effective. In addition, to the extent households 

report higher incomes due to lower tax rates, the U.S. Treasury would receive more revenue than 

otherwise. Moreover, if taxpayers are very responsive to changes in tax rates and go to great 

lengths to remange the way they receive and earn their income, the welfare cost of higher tax 

rates could be large compared to tax revenues collected (Feldstein, 1995b). Indeed, many of 

these behavioral responses might be viewed as favorable outcomes of tax rate reductions to the 

extent that they might also be associated with a smaller welfare loss. 

This paper examines the responsiveness of pre-tax income (net of capital gains) to 

changes in tax rates and a variety of non-tax factors, including proxies for a taxpayer's human 

capital or education, during the late 1980s. By including both taxes and non-tax factors, we are 

able to incorporate both of these views and evaluate the extent to which changes in tax rates can 

2Feldstein(1995a) and Slemrod (1994) discuss the different types of tax-induced changes in 

income reported for tax purposes. 
5 

explain the changes in income during the 1980s. 

We use a panel of taxpayers constructed from the Statistics of Income (SOI) Individual 

Tax Files before and after the Tax Reform Act of 1986 (TRA). The use of panel data allows us 

to control for unobserved heterogeneity by modeling individual-specific and time-specific 

effects. The use of tax return data allows us to measure taxrates accurately. Detailed occupation 

information allows us to develop a proxy of a taxpayer's human capital based on the educational 

content of a taxpayer's job. Information on each taxpayer's age from a match with Social 

Security records allows us to account for life cycle effects. Finally, unlike most previous studies 

of income changes, our sample of tax returns contains many high income taxpayers. 

In many respects, TR4 provides a natural experiment to test whether tax rates or non-tax 

factors, or both, explain changes in income during this period. TRA lowered tax rates for most 

taxpayers, but high income taxpayers had the largest percentage reduction in tax rates. Prior to 

TRA, there were 14 tax brackets with rates ranging from 11 to 50 percent. TRA reduced the 

number of tax brackets to two, a 15 percent rate and a 28 percent rate bracket. A 33 percent tax 

rate (the so-called "bubble") was created by the phase-out of the lower 15 percent rate and 

personal exemptions for higher income taxpayers. Because tax rates changed differently for 

different taxpayers, the change in the tax rate will not only be a hction of income. Moreover, 

the exogenous variation in tax rates due to TRA can be captured by calculating the change in tax 

rates holding income constant. This change in tax rates, which, by construction, is independent 

of the level of income, is the primary source of exogenous variation needed for identification of 
4 

the tax rate re~ponse.~ 

Several researchers have used recent changes in tax policy as a natural experiment to 

predict how taxpayers respond to changes in tax rates. CBO (1986), Lindsey (1987) and Navratil 

(1995) find evidence of tax-induced behavioral responses for ERTA, while Feldstein (1995a), 

Feenberg and Poterba (1993), and Eissa (1995) find evidence of tax-induced responses for TRA. 

These studies, however, must be viewed with some caution. Lindsey (1987), which found very 

large responses, did not use panel data, but instead created a synthetic panel by grouping 

similarly situated taxpayers by income and estimating elasticities based on differences across 

these groups. Studies that assume the level of income that would have been achieved absent the 

taxchanges are suspect because all unexpected income changes are assumed to be due to tax 

changes and the counter factual assumption about income growth influences the estimated 

elasticities (CBO,1986; Lindsey, 1987; and Gravelle, 1993). Two recent studies that use panel 

data av.oid some of these problems, but rely on samples of taxpayers that have relatively few 

high-income returns, and, similar to Lindsey (1987), may not adequately control for non-tax 

factors (Feldstein, 1995a and Navratil, 1995). Using successive cross-sections, Feenberg and 

Poterba (1993) investigate the rising share of income reported on very high-income taxreturns. 

They find sharp increases in this group's share of reported income in 1987 and 1988 and 

conclude that at least part of the increase was due to the reduction in tax rates in TRA. Their 

3Hausmanand Poterba (1987) estimate that 40 percent of taxpayers faced either the same or 

higher tax rates under TRA, and 11 percent of taxpayers had their marginal tax rates lowered by 10 

percentage points or more. 

Other sources of independent variation that help identify the tax rate effect include state tax rates 

and the uneven effects of base broadening under TRA including the repeal of the sales tax deduction, 

higher floors under medical and miscellaneous deductions, and restrictions on deductions for IRA and 

Keogh contributions. 
5 

conclusion is subject to qualification, however, because they do not adjust the definition of 

income for statutory changes. Using Current Population Survey data, Eissa (1995) found 

evidence that the labor supply of high-income married women increased hue to TU. 

The next section briefly outlines the empirical model. The third section presents the data 

and describes the construction of the variables used in the empirical model. The fourth section 

presents our estimation results, robustness checks, and an estimate of the revenue maximizing 

tax rate. The fifth section concludes the paper. Both taxes and non-tax factors are found to 

explain income changes during the late 1980s. 

11. The Model 

Taxpayers' incomes are influenced by many factors, some of which are within their 

control. First, taxpayers can decide how much labor to supply. Second, taxpayers can change 

the form of their compensation to affect the amount of income subject to tax. High tax rates may 

induce some taxpayers to shiftmore compensation to tax-favored sources, such as fringe benefits 

or stock options. Third, taxpayers can alter how much they save and in what types of assets they 

invest. If taxes are high on income from assets that yield ordinary income, taxpayers can 

purchase assets that yield capital gains. Fourth, taxpayers can reduce income by making 

purchases that receive favorable tax treatment. Taxpayers can choose to contribute more 

generously to charity or to increase home mortgage debt. Fifth, taxpayers can simply reduce 

compliance with the tax law. Taxpayers' incomes are also influenced by factors beyond their 

control, such as business cycles, changes in interest rates, demographic changes, and the growth 

or decline in different industries, occupations, and regions. 

Our empirical model assumes that a taxpayer's income, Yit' ,is explained by four factors 
6 

that attempt to capture these influences: (1) an individual specific effect, ti,(2) a time specific 

effect, yo (3) individual characteristics that do not change over time, but whose relationship to 

income may change over time, Xi, and (4)the marginal tax rate, Tit, which varies across both 

individuals and across time. Income for the ith individual in time period t is given by, 

As is widely known,the individual effect reflects individual specific characteristics such 

as tastes, physical characteristics, geographic location and skills that do not vary over time and 

whose relationship to income do not change over time (Hsiao, 1986). The individual effect is 

eliminated from the model by first differencing. The estimating model becomes, 

where A denotes the change in a variable between period t and period t-1 . The time effect 

controls for factors that affect all individuals in the same fashion at each point in 

time. Although the time effect remains in the model, it is embedded in the constant term. A 

taxpayer's marginal tax rate, zit,plus the individual Characteristics that remain constant over time, 

but whose relationship to income may have changed, Xi, comprise OUT set of independent 

variables. 

Although taxpayer characteristics such as wealth, region or skill level may have remained 

constant between 1985 and 1989,the relationship of these variables to income may have 

changed. Earnings potential in many cases may be linked to regional labor markets (Topel, 
L 

7 

1994). If a region or industry were in decline (e.g., the Texas oil market during the 1980s), 

earnings potential for those employed or withbusinesses within this region or industry would 

likely fall. In addition, earnings of highly skilled workers would likely grow more rapidly than 

the earnings of low skilled workers if their skills become relatively more valuable, even though 

their education level remained constant. Understanding how these factors influence the 

estimated elasticity for the taxvariable or “tax price” will not only allow us to evaluate previous 

research, but also allow us to evaluate the role non-tax factors, such as changes in the demand for 

highly educated workers, played during the 1980s. 

111. The Data 

We use a panel of individual Federal income taxreturns that consists of the same 

taxpayers for years both before and after the Tax Refom Act of 1986. In addition to detailed tax 

return data, the panel over samples high income taxpayers and includes the age and occupation of 

each tax~ayer.~The panel of taxreturns was constructed by matching taxpayers present on both 

the 1985 and 1989 Statistics of Income (SOI) Individual Tax Files5 Tax returns from 1985 

should precede any tax-induced behavior in response to anticipated tax rate changes. Tax return 

data for 1989were used because 1989 is the first year in which the rate changes and most other 

features of TR4 were fully phased in6 Most temporary tax-induced responses to the tax rate 

4Thetax return data are supplementedwith the age of the taxpayer using an exact match with 

data provided by the Social Security Administration. The occupation classifications are based on the 

taxpayer-provided occupation description on the signature line of Form 1040and the industry of a 

taxpayer’s employer from W-2 Forms. 

5TheSO1 Individual Income Tax Files are annual stratified random samples of over 100,000 

individual tax returns filed in each year. See IRS (1989)for a description of the 1989sample procedure. 

6Notall provisions, however, were fully phased-in by 1989. For example, the repeal of the 

deduction of consumer interest for itemizers was not fully phased-in until 1990. 
8 

changes, such as shifting of income and of portfolios, likely occurred prior to 1989.7 

Consequently, a comparison of 1985 and 1989 should exclude most of the transitory effects of 

TRA on taxpayer incomes.8 

We exclude some taxreturns from our panel because of data limitations and to abstract 

from taxpayer characteristicsthat are not likely to be related to tax-induced behavioral responses, 

but affect a taxpayer's reported in~ome.~For example, taxpayers other than single or joint filers 

with the same marital status in both years are excluded to avoid fluctuations in income related to 

changes in household composition due to marriage, divorce, or death of spouse.'O To abstract 

from the effect of TU on retirement decisions, taxpayers who are over age 55 in 1985 are 

excluded." We also exclude all taxpayers who are under age 25 in 1985, since income changes 

for many of these taxpayers reflect the completion of schooling. Tax returns with low taxable 

incomes are excluded because many low income taxpayers drop out of the sample over time and 

certain types of income (e.g., Social Security benefits) may not be reported. We exclude all 

'Most of the transitory shifting of income around TRA occurred in 1986, 1987 and 1988. In 

1986, taxpayers had an incentive to accelerate capital gains and deductions, and defer ordinary income. 

In 1987, ordinary income was increased by 1986 deferrals, but decreased by taxpayers desiring the still 

lower rates in 1988. Income in 1988 was increased by deferrals from 1987. 

*Wemay not capture effects that are fully long-run because the effects of the tax rate changes on 

capital formation and other slowly changing factors are not likely to be fully realized by 1989. 

'These sample exclusions are similar, but less restrictive than those imposed by Feldstein 

(1995a) and Navratil(l995). 

''We also exclude tax returns with a change in their secondary Social Security number because 

the household is no longer composed of the same individuals, which may indicate the taxpayer divorced 

and remarried between 1985 and 1989. 

"We also exclude taxpayers who are identified as deceased or retired based on information from 

each taxpayer's self-described 1989 occupation. The construction of the occupation codes is discussed in 

greater detail below. 

c 
9 

taxpayers with incomes below the income threshold for the 22 percent marginal tax rate in 1985 

@.e.,$21,020 for joint filers and $15,610 for single filers). Taxpayers who are on the altemative 

minimum tax (AMT) in 1985 are also excluded. Although these taxpayers have relatively low 

marginal tax rates (in 1985the AMT rate was 20 percent), their average tax rates are high relative 

to other taxpayers. Deleting AMT taxpayers avoids the difficulty of distinguishingbetween 

differencesin the effect of marginal tax rate changes and average tax rate changes. Finally, we 

exclude taxpayers who report S corporation income after TRA, but not before. Many business 

owners elected S corporation status for their businesses after 1986. For taxpayers who converted 

businesses fiom C corporationsto S corporations,we can observe their post-TRA S corporation 

income, but not their pre-TRA C corporation income. After these adjustments, 15,348 

observationsremain in our sample.” We examine the sensitivity of our results to these sample 

criteria be10w.l~ 

As a result of the stratified sampling procedure used for SO1 Individual Tax Files, 

which over samplestax returns with high incomes and/or tax returns accompanied by particular 

tax schedules, our panel includes a large number of high income tax returns and allows us to 

‘*Inmost cases, the sample restrictions are based on 1985 characteristics because the 1989 

characteristics can be affected by how a taxpayer responded to TRA and, therefore, can be endogenous. 

For example, whether a taxpayer is subject to the AMT in 1989will, in part, depend on how the taxpayer 

responded to TRA. Nevertheless, in robustness tests presented below we relax many of these sampl’e 

restrictions or apply them symmetrically based on both 1985and 1989characteristics to test the 

sensitivity of our results. 

l3Thesample exclusions reduce the size of the panel fiom 56,003tax returns to 15,348.The 

most significant sample exclusions are: (1) low income taxpayers (19,191taxpayers), (2)age 55 or over 

(13,493taxpayers), (3)age 25 or less (5,808taxpayers), (4)taxpayers subject to the AMT in 1985(4,022 

taxpayers), and (5)non-single and non-joint taxpayers (3,609taxpayers). Applying these five sample 

exclusions simultaneouslyreduces the panel to 21,903taxpayers. The remaining sample exclusions 

reduce the panel to 15,348taxpayers. 
10 

avoids the problems inherent in small samples. For example, the panel includes 3,633 returns 

(24 percent) in the 50 percent rate bracket in 1985 and another 628 (4 percent) in the 49 percent 

rate bracket. The selection of tax returns for the panel, however, depends on whether a tax return 

is sampled for both the 1985 and 1989 SO1 Individual Tax Files. The selection of tax returns for 

our panel is endogenous because the annual SO1 Individual Tax Files are stratified by income, 

the dependent variable in our model. 

Following Hausman and Wise (198 1) and Imbens and Lancaster (1996), we use a 

weighting procedure to correct for endogenous sample selection. The sampling procedure used 

for the SO1 Individual Tax Files has the effect of including in the panel with certainty all 

taxpayers who remain in the same sample strata or move to a sample strata with a higher 

sampling rate between 1985 and 1989. Taxpayers who move to a sample strata with a lower 

sampling rate have a lower probability of remaining in the 1989 SO1 Individual Tax File and 

being included in the panel. Therefore, taxpayers with declines in income between 1985 and 

1989 are underrepresented in our panel. The weights are designed to compensate for this 

underrepresentation. Weighting the data by the maximum weight from the 1985 and 1989 SO1 

Individual Tax Files compensates for the underrepresentation of taxpayers with income declines 

and extrapolates our sample of tax returns to the population. Weighted least squares is used for 

estimation and both weighted and unweighted estimates are reported. A description of the 

weighting procedure is provided in the Appendix. 

Dependent Variable 

Two income concepts are used in our analysis: (1) constant law gross income, and (2) 

constant law taxable income, which is a variant of a taxpayer's taxable income. The gross 
11 

income concept defines income broadly and is useful for analyzing to what extent changes in tax 

rates may explain changes in reported incomes and the income distribution. The taxable income 

concept is less useful for analyzing changes in the income distribution, but is more useful for 

analyzing the overall behavioral response of taxpayers and the revenue maximizing tax rate, 

because adjustments to income, personal exemptions, and the standard deductioditemized 

deductions, are included. Both the gross income and taxable income measures reflect income as 

reported by taxpayers and are adjusted for inflation. 

We define both income concepts on a post-TRA, constant law basis to remove the 

statutory differences in the income measures before and after TR4. We incorporate as many of 

the statutory changes in TR4 as our data allow. The largest adjustment is to subtract capital 

gains realizations from taxable income in both years. Including capital gains would cause 

several problems. First, long-term capital gains were taxed at a different rate than other income 

in 1985, making it difficult to define a single tax rate appropriate for total 1985 income. Second, 

TRA increased effective tax rates for capital gains by repealing the 60-percent exclusion, while 

decreasing rates for other income. Thus, total income including capital gains is subject to two 

offsetting rate effects. 

Because TRA disallowed certain passive losses, post-TR4 taxable income reflects 

smaller losses. Failure to control for the change in passive loss rules would tend to overstate 

income growth and mistakenly attribute this portion of the income change to the tax rate 

response. Because of the lack of the data necessary to construct post-TRA losses absent this 

statutory change and to abstract from the effect of this statutory change on our results, we add all 
12 

losses back to income both before and after TRA.I4 Other adjustmentsto gross income include 

adding back excluded dividends and unemployment compensation. 

Additional adjustments are required to calculate constant law taxable income. The twoearner deduction and non-itemizer deduction for charitable contributions are added back. 

Adjustments are made for the increase in the floor under medical expenses, the new 2 percent 

floor under miscellaneousdeductions, and the repeal of the deduction of sales taxes. 

Adjustments are made for changing the deductions for moving expenses and employee business 

expenses from above-the-linedeductions to deductions available only to itemizers. The 

deduction for IUSis put on a post-TRA basis by limiting it to lower income taxpayers. We also 

adjust for increases in the real value of the standard deductions and personal exemptions in TRA. 

We control for these statutory changes by adjusting 1985 taxable income by the increase in the 

real value of the standard deductions and personal exemptions in 1989. 

Tax Price 

Combined federal-state marginal tax rates were calculated using detailed tax calculators 

to compute each taxpayer's net-of-tax rate (Le., 1-T)or "tax price.".I5 The tax price used for 

estimation is the difference in the natural logarithms of the tax prices in 1985 and 1989. 

A taxpayer's actual tax price, however, is likely to be endogenous with respect to the 

amount of income reported. As taxable income rises, a taxpayer's tax rate may also rise despite 

14Theassumptionthat all changes in reported losses were caused by statutory changestends to 

understate tax-induced behavioral effects. We have not, however, controlled for changes in depreciation 

rules and for statutory changes limiting contributionsfor 401(k) and other similar retirement saving 

plans. Failing to control for these other statutory changes could bias the estimated effects of taxrates 

upward. 

15Thetax calculators were adapted for use with panel data from the US.Treasury 

Department's Individual Tax SimulationModel. 
13 

the rate reductions under TRA. An instrumentalvariable procedure is used to overcome this 

problem.I6 The instrument is constructedby first computing a taxpayer’s 1989 tax rate using 

1985 income inflated to 1989 levels. The instrumental variable is then calculated as the 

differencebetween a taxpayer’s “synthetic” tax price for 1989 and the actual 1985 tax price. 

Two stage least squares estimates are obtained by first regressing the change in the actual tax 

price against the change in the synthetic tax price and the other exogenousvariables. Consistent 

estimates are obtained in the second stage by replacing the change in the actual tax price with 

fitted values from the first stage.17 

By construction,the instrument eliminates the effect of income changes attributable to 

tax-induced behavioral responses on the change in the tax price and only reflects the exogenous 

statutory change in tax rates due to TRA. It is this exogenouschange in tax rates due to TRA 

that is the primary source of identification of the tax price in our model. 

A taxpayer’stax price includes both state and federal marginal tax rates, allowing for the 

deductibilityof state income taxes for taxpayers who itemize deductions. Variation in state tax 

rates that are independentof taxpayers’ income also helps to identify the tax price.’* The means 

and standard deviations for the combined federal-statetax price and the separate federal and state 

I6FollowingHausman (1978), we tested for the possibility of endogeneityof the actual tax price 

and rejected the null hypothesis of exogeneity. 

”Feldstein (1996) uses a somewhat different approach than described above. By distinguishing 

between taxpayers based on their 1985 actual tax rates, Feldstein (1996) omits the first stage in 

procedure described above. This has the effect of ignoring the coefficient on the change in the synthetic 

taxprice in the first stage equation. We considered the effect ignoring thefirst stage equation by 

estimating a reduced form equation that simply includes the synthetictax price, and found the estimated 

tax price elasticity to be somewhat lower than the results reported below. 

’*Feenberg(1987) and Burman and Randolph (1994) use cross-sectionaldifferences in state 

income tax rates to identify tax rate effects. 
14 

tax prices are provided in Table 1. 

Non-Tax Factors 

Differencing controls for many non-tax factors by eliminating individual effects. The tax 

data also allow us to identify taxpayer characteristics whose relationship to income may have 

changed over time. Taxpayer wealth is likely to influence a taxpayer’s ability to alter portfolios 

and labor arrangements in response to tax changes. Tax return data, however, provide no direct 

measure of a taxpayer’s wealth. Instead, the sum of a taxpayer’s dividend and interest income in 

1985 is used as a proxy for an individual’s financial wealth. l9 

Age and age squared (in 1985) are included to control for life cycle effects. We include 

the number of children in 1985 (up to a maximum of 6) and a dummy variable indicating 

whether a taxpayer has any children away from home but still claimed as dependents in 1985. 

Dependent children away from home are typically in college, which may limit the ability of a 

taxpayer to respond to lower tax rates. We also include an “entrepreneurship” dummy variable 

indicating whether a taxpayer reports income in 1985 from a sole proprietorship, partnership, or 

subchapter S corporation. This variable may reflect business ownership and entrepreneurship 

skills, and the propensity for risk-taking. 

Some taxpayers with very low (high) transitory incomes in 1985 are likely to have large 

increases (decreases) in income between 1985 and 1989, many of which would likely occur even 

absent the changes in tax rates under The exclusion of low income taxpayers (i.e., 

19Bothcapital gains and tax-exempt interest are excluded from this variable. The tax return data 

only contain a taxpayers capital gains when realized, not accrued, and contain no information in 1985 on 

tax-exempt interest income. 

20Transitoryincome is somewhat reduced because the income variable excludes capital gains 

income and business losses, which are often large components of transitory income. 
15 

taxpayers below the threshold for the 22 percent rate brackets) from the sample was intended to 

help limit mean reversion bias. Taxpayers with temporarily high incomes, however, may 

experience large declines in income that would be associated with their large declines in tax 

rates, biasing the estimated tax price elasticity downward. In order to control for reversion-tothe-mean effects, a taxpayer's 1985 income is included as an independent variable. 

During the 1980s, some regions of the United States grew quickly, while others 

experienced stagnant economies or recessions. Based on the tax return data, income growth from 

1985to 1989 was about three times higher in the Mid-Atlantic and Northeast regions (27 

percent) than in the West South Central region (9 percent). Dummy variables for Census regions 

based on state of residence in 1985 are included to capture the different opportunities for income 

growth that existed in different regions during this period. 

To explore the view that increasing returns to human capital also play a role in the 

increased inequality in the reported income distribution during the 1980~~ we add dummy 

variables reflecting a taxpayer's occupation in 1989 to our model.21These variables allow us to 

consider whether the relationshipbetween income and returns to human capital may have 

changed between 1985 and 1989. Returns to human capital may have increased because 

individuals in certain occupationsmay have experiencedrelative increases in labor productivity 

due to technological advances or may have been in higher demand perhaps due to increasing 

21Taxpayereported occupation descriptionswere classified using the Standard Occupation 

Classification(SOC) system (see Clark, Reilly, and Sailer, 1989). Nearly 60 percent of the returns in our 

panel were classified by the Statistics of Income Division of the IRS using information from both a 

taxpayer's occupation description in 1989 and the industry classificationof a taxpayer's employer 

obtained from W-2 Forms. We classified an additional 25 percent through detailed examination of 

taxpayer reported occupation and sources of income. SOC classificationswere aggregated into 

occupational groups reflecting education and skill levels, and, in some cases, type of employer 

(government)and industry (doctors and other health related services). 

c 
16 

international competitiveness or technological change. Income growth, however, could also vary 

across occupation categories because some occupations may offer greater flexibility to alter work 

effort or the mix of compensation than others. For example, doctors and lawyers, the occupation 

groups exhibiting the greatest income growth during this period, also have considerable 

flexibility to alter their work schedules and compensation arrangements in response to the tax 

rate changes. If the occupation variables are highly correlated with this tax-related effect, 

inclusion of these variables could bias the estimated elasticity for the tax variable downwards 

(Feldstein, 1996). In recognition of this measurement issue, we present sets of estimates with 

and without the occupation variables in the model. 

IV. Results 

Estimates of equation (2) for constant law gross income are shown in Table 2. 

Unweighted and weighted estimates are shown for three variants of the model: (1) “taxes-only” 

(columns 1 and 2), (2) taxes plus non-tax factors, excluding occupation (columns 3 and 4), and 

(3) taxes plus non-tax factors including occupation (columns 5 and 6). The “taxes only” 

specification includes only a constant term, the tax price (Le., 1-T), and income. This equation is 

most comparable to the earlier research that excludes non-tax factors from the model (for 

example, see Feldstein 1995a, Navratil 1994, and Lindsey, 1987). For this specification, the 

estimated “tax price” elasticity is 1.10 with a standard error (s.e.) of 0.13. The estimates using 

weighted least squares account for the endogenous sample selection and extrapolate OUT results to 

the population of taxpayers. Because the endogenous sample selection results in 

underrepresentation in our panel of taxpayers with income declines and sampling rates are the 

highest for high income taxpayers (i.e., taxpayers with the largest decline in tax rates under 
17 

TU), we expect the elasticities using weighted least squares to be smaller than the unweighted 

results. Using weighted least squares lowers the estimated tax price elasticity to 0.77 with a 

standard error of 0.16. Only the unweighted results are within the range of the taxprice 

elasticities reported by Feldstein (1995a), who reports elasticities between 1.04 and 3.05. The 

weighted results are similar to those reported by Navratil(l995), who reports elasticities around 

0.8. The substantial difference between the estimated tax price elasticities obtained from the 

weighted and unweighted specifications, however, suggests that the unweighted results are likely 

biased upwards due to endogenous sample selection. 

Columns 3 and 4show results for the second specification of the model, which includes 

all of the non-tax factors except a taxpayer's occupation. The coefficient for the proxy for 

financial wealth is positive and significant implying that income grew more rapidly for those 

with greater wealth. The signs of the coefficients for age and age squared are jointly significant 

and imply that income growth declines with age. 

The number of children is positively related to income growth. The dummy variable for 

college age children is negative (but is statistically different from zero only in the unweighted 

regression). The negative sign is consistent with the view that taxpayers with college age 

children may have already been realizing income at a high level in 1985. The coefficient for the 

entrepreneurship dummy is positive, but only significantly different from zero in the unweighted 

regression. The results for the regional dummy variables are consistent with the view that a 

taxpayer's income growth is influenced by regional economic performance. Four of the eight 

. regional dummy variables are statistically significant, with the greatest income growth in the 

northeast and midatlantic states. 
18 

Compared to the taxes only model, the tax price elasticity falls by 15 percent to 0.64 with 

a standard error of 0.16 in the weighted model (column 4). The results for this specification 

suggest that both non-tax-factors (excluding occupation) and changes in .the tax price are 

important determinants of income growth and that failure to control for non-tax factors may 

result in an overstated tax price elasticity. 

The third specification (column 5 and 6) adds the occupation dummies to the model. The 

results for most of the non-tax factors are similar to the results reported in columns (3) and (4). 

Most of the coefficients for the occupation dummies are statistically different from zero. Our 

results for the occupation dummies suggest that changes in returns to human capital were an 

important factor explaining the changes in the income distribution during the 1980s. Taxpayers 

in occupations with high educational content experienced the greatest income growth during this 

period, while taxpayers in occupations with relatively less educational content did not fare as 

well. Lawyers, doctors, and executives and managers, have the largest positive coefficients. The 

effects of occupation, however, must be interpreted with care. In addition to a taxpayer's human 

capital, occupation may also reflect taxpayers' flexibility for rearranging affairs in response to 

changes in tax rates. 

After controlling for occupation, the tax price elasticity remains virtually unchanged at 

0.66 (s.e.=O. 16) in the weighted regression. Even though occupation is an important factor 

explaining income growth, including occupation in the model has little measurable effect on the 

estimated tax price elasticity in our preferred (Le., weighted) model. Although the tax price 

elasticities are well below those reported by Lindsey (1987) and Feldstein (1995a), the results 

reported in Table 2 suggest that both non-tax factors and the tax rate reductions of the 1980s help 

i 
19 

explain the increase in measured income inequality during the 1980s. 

Robustness Checks 

In Table 3 we report a number of robustness checks to consider the sensitivity of the 

results to sample restrictions and variable definitions. The robustness checks also help evaluate 

to what extent the estimated tax price elasticity might vary for different taxpayer groups. These 

robustness checks are based on the model using weighted least squares and includes occupation 

along with the other non-tax factors (i.e., column 6 in Table 2). 

In our original sample, we abstract from individual retirement decisions by excluding all 

taxpayers age 55 and above in 1985 (i.e., age 59 and above in 1989). Many individuals, 

however, may not retire until age 62 when they can begin to receive limited Social Security 

benefits or age 65 when they can receive full Social Security benefits. Of course, adding 

additional taxpayers close to typical retirement ages will likely include some taxpayers who 

experience declines in income because of retirement. In addition, the larger personal exemptions 

and standard deductions under TU could have induced middle income taxpayers to retire earlier 

because of higher after-tax incomes in retirement. On the other hand, high-income taxpayers 

have may been induced to postpone retirement because of higher net-of-tax income from 

continuing to work. Relaxation of the age exclusion to 60 and above in 1985 (Le., age 64 and 

above in 1989), adds 1,823 tax returns to our sample (n=17,171) and increases the estimated tax 

price elasticity to 0.84 (s.e.=O.l5) from 0.66 (s.e.=0.16). 

The basic sample eliminates all taxpayers whose 1985 taxable income fell below the 

thresholds for the 22-percent statutory tax rate in 1985. Because 1989 income is affected by a 

taxpayer’s behavioral response, we did not impose a comparable sample criteria based on a 
20 

taxpayer’s 1989 income for our preferred specification (i.e., Table 3). Nevertheless, in Table 4 

we report how such an additional sample criterion affects the estimated tax price elasticity. In 

particular, we inflate the threshold for the 22 percent statutory rate bracket to 1989 levels using 

the Consumer Price Index and exclude the 1,677 taxpayers whose 1989 taxable income fell 

below these income thresholds. Excluding these taxpayers lowers the estimated tax price 

elasticity to 0.47 (s.e.=0.09). 

TRA made S corporations, where business income is passed through to individual owners 

before being taxed, more attractive relative to C corporations that pay income tax at both the 

business entity level and the owner level (see, for example, Carroll and Joulfaian, 1997; Ayers et 

al; 1996; and Plesko, 1994).22 Our basic sample excludes taxpayers who report S corporation 

income in 1989, but not in 1985, to eliminate taxpayers that may have converted their C 

corporation(s) to S corporations in response to TRA. It is possible, however, that some taxpayers 

may have reported S corporation income both before and after TRA, but still converted some 

business activities from the C corporation form to the S corporation form. The growth of total 

income would be overstated for such taxpayers in 1989. To consider this possibility, we examine 

a sample that excludes all taxpayers with any S corporation income in either 1985 or 1989. This 

additional sample restriction eliminates 2,358 taxpayers from our panel, but leaves the estimated 

tax price elasticity virtually unchanged at 0.66 (s.e.=0.17). If we instead include the 4,324 

taxpayers in our panel with S corporation income in either 1985 or 1989, the estimated tax price 

22TRAalso created a similar incentive for C corporations to convert to sole proprietorships and 

partnerships. These other business forms, however, did not receive the same advantages from limited 

liability protection as S and C corporations. Ayers et a1 (1996) find that liability protection may be a 

distinguishing factor between corporate and unincorporated businesses &d in the selection of 

organizational form. 
21 

elasticity rises to 0.79 (s.e.=O. 15), suggesting that income in 1989 and the tax price elasticity 

could be somewhat overstated without controlling for this change in organizational form. 

Taxpayers with AMT in 1985 were excluded from the basic sample. If we exclude 

taxpayers with AMT liability in either year, rather than just in 1985 (excluding an additional 206 

tax returns), the tax price elasticity for the weighted regression remains virtually unchanged 

(coef.=0.67, s.e. = 0.35). If we instead include in our panel the 1,486 taxpayers subject to the 

AMT in either year, the estimated tax price elasticity rises slightly to 0.76 (s.e.=0.15). 

We test whether our results are sensitive to whether a taxpayer reported income from 

capital gains by including a dummy variable for the presence of capital gains in 1985. The repeal 

of the capital gains exclusion combined with the lower tax rates on ordinary income under TRA 

may have induced taxpayers to shift their portfolios from high-capital gain assets to highdividend or high-interest paying assets to take advantage of the relatively lower marginal tax 

rates on ordinary income. Because of this portfolio effect, our dependent variable may overstate 

income in 1989 as compared to income in 1985. 

In order to determine whether our results are sensitive to capital gains portfolio effects 

and to disentangle the effects of capital gains from the AMT, we conduct several experiments. 

First, we include a capital gains dummy variable and find that the estimated tax price is 

unchanged (coef.=0.67, s.e.=0.16) and the dummy variable is not statistically different from zero. 

Since prior to TU excluded capital gains were treated as a preference for the AMT and we 

exclude taxpayers subject to the AMT in 1985 from our basic panel, however, we also likely 

exclude many taxpayers who realize large amounts of capital gains in 1985. Thus, a second 

capital gains test is to include the capital gains dummy variable and also include taxpayers 
22 

subject to the AMT in either year. In this test the estimated tax price elasticity increases to 0.79 

(s.e.=O.15) and the coefficient for the capital gains dummy variable is positive and statistically 

significant. These results suggest that excluding AMT taxpayers may remove some of the 

portfolio effects associated with the change in the relative effective tax rates on capital gains and 

ordinary income under TU. Moreover, the positive and statistically significant coefficient on 

the capital gains dummy variable (coef.=0.055, s.e.=0.029) suggests that some taxpayers who 

realize capital gains in 1985 altered their portfolios in response to the higher effective tax rate on 

capital gains realizations and lower tax rates on income received as ordinary income under TRA. 

We consider whether our results change if we include a dummy variable for itemizers. 

Itemization may help distinguish between taxpayers who own a home rather than rent @e., home 

mortgage interest deduction), live in high tax states (i.e., state and local property, income and 

sales tax deductions), have substantial investment expenses (i.e., interest expense deduction), or 

have above average medical expenses (Le., medical expense deduction). Homeownership may 

serve as a proxy for real estate wealth. Of course, taxpayers who itemize may also have more 

flexibility to rearrange their affairs by changing their decisions about, for example, how much 

equity to hold in their residence and how much to give to charity. Including a dummy variable 

for itemization status in 1985 leaves the tax price elasticity for either model virtually unchanged 

(coef.=0.67, s.e.=O. 17), and the itemization variable is not statistically different fiom zero. 

Most of the independent variables are constructed based on 1985 values. As an 

additional robustness check, some of the variables can be defined symmetrically in both years. 

This may introduce a substantial endogeneity problem in some cases because the 1989 values are 

likely to be influenced by a taxpayer’s tax-induced behavioral response. For example, the 
23 

amount of taxable interest and dividend income reported in 1989 will partly be determined by 

tax-induced changes in the taxpayer’s portfolio. Similarly, changes in housing consumption, 

homeownership, and home equity all may be partly determined by changes in the value of the 

home mortgage interest and property tax deductions due to the lower tax rates and repeal of the 

consumer interest deduction under TRA. In any case, using average financial wealth instead of 

the 1985 value and defining the capital gains and itemizer dummy variables to one if a taxpayer 

reports capital gains income or itemizes in either year increases the estimated tax price elasticity 

somewhat to 0.80 (s.e.=O. 16). 

In another symmetry test, we recompute both constant law gross income and marginal tax 

rates on a pre-TRA basis to the extent the data allow and use 1989 sample exclusions. In our 

preferred specification(i.e., Table 2), we calculated marginal tax rates primarily on post-TRA 

basis because the tax data allow a more complete set of adjustments. For example, TRA limited 

deductible IRA contributionsto taxpayers below certain income thresholds. Because we have no 

information on the IRA contributionsthat would have been made had these IRA contributions 

not been limited by TRA, in OUT preferred specification @e., Table 2) we compute the IRA 

deductions on a post-TRA basis. Computing IRA contributions on a pre-TRA basis would either 

involve imputing which taxpayers above the income thresholds contribute and how much, or 

simply excluding all IRA contributions from income when computing marginal taxrates. 

Similarproblems arise for the medical expense deduction and miscellaneousdeductions above 

the 2 percent floor. When we estimate the tax price elasticity using marginal tax rates and 

income based on the tax law prior to the TU, we find the estimated tax price elasticity to be 

somewhat higher than the results in Table 2 (coef.=0.91, s.e.=O.lO); This rise in the tax price 
24 

elasticity, however, appears to be attributable to the 1989 based sample exclusions, rather than 

basing the income measure and tax rates on pre-TRA tax law. 

We include income as an explanatory variable in our preferred model to, at least partially, 

control for mean reversion bias. We find that dropping this variable lowers the estimated tax 

price elasticity to 0.35 (s.e.=0.13), suggesting that a model with no controls for mean reversion 

bias may bias the estimated tax price elasticity downwards. 

After a variety of robustness checks to different sample restrictions and model 

specifications, our basic finding is that the results are somewhat sensitive to changes in 

assumptions, but the estimated tax price elasticity is still significantly above zero, and is 

generally between 0.4 and 0.9. 

Behavioral Response bS Occupation Type 

As discussed above, the tax-induced behavioral responses can be expected to vary by 

occupation not only because of differential changes in the returns to education associated with 

different occupations, but also because some occupations may offer more flexibility to adjust 

compensation packages and labor supply in response to tax law changes. Doctors, lawyers, and 

taxaccountants may have greater control over hours worked than other occupations, and tax 

accountants may have a better understanding of how individual finances can be restructured to 

minimize taxes in the face of a changing tax environment. 

Table 4presents results that interacts the tax price with the occupation dummies to 

separately measure the tax price elasticity across occupations and an F-test of the joint 

significance of the tax price elasticity and the interaction term for each occupation category. The 

dummy variable for government employees and educators is excluded. Only four of the twelve 
25 

occupations listed are jointly statistically different from zero -- executives and managers, 

investors, self-employed and farmers, and sales. It should be noted that the tax price elasticity 

estimates for the occupation groups should be interpreted with some caution because some of the 

occupation classificationstend to be clustered within relatively narrow income ranges. The 

identification of the tax price elasticitiesfor some occupation groups may, therefore, be suspect. 

The highest tax price elasticity is for the investors category (coef.=3.34, F-value=7.32), which 

includes both individuals describingtheir occupations as investors, venture capitalists, or stock 

brokers. The self-employed group has an estimated tax price elasticity of 2.40 (F-value=B.lO). 

Taxpayers in this occupation group, consisting of 127 farmers and 380 other self-employed, are 

likely to have considerableflexibility in how they organize their business affairs, as well as 

control over their labor supply. The taxprice elasticity for taxpayers classified as executives and 

managers, consisting of 2,399 tax returns is 1.08 (F-value=9.47). The tax price elasticity for 

taxpayers classifyingthemselves as having sales-related occupations is 0.98 (F-value=3.06). 

Taxable Income and the Revenue Maximizing Tax Rate. 

One issue of interest for tax policy is what the results imply for the revenue maximizing 

tax rate, the rate at which any further tax rate increases would produce revenues losses. For this 

purpose, it is more appropriateto focus on taxable income rather than the broader income 

concept used in the previous analysis (Feldstein 1995b). Estimation of equation (2) using 

constant law taxable income rather than constant law gross income yields a tax price elasticity of 

0.57 (s.e.=0.226) using weighted least squares and including all of the non-tax factors (Le., 

comparableto column (6) in Table 2). 

The tax price elasticities based on constant law taxable income can be used directly to 
26 

compute the revenue maximizing tax rate. Making the simplifling assumption that the income 

tax is proportional, and following Lindsey (1989, the revenue maximizing tax rate is given by, 

1

r= 

(1 + P,) 

where P5.is the tax price elasticity. Following this formulation, the revenue maximizing tax rate 

for our preferred model (Le., using weighted least squares and including all of the nontax factors) 

would be about 64 percent. Of course, the current tax system is not proportional, but 

progressive. As Lindsey (1985) points out, progressive rates will imply a lower revenue 

maximizing tax rate because inframarginal income will be taxed at a rate unrelated to the top 

marginal tax rate. 

The use of the tax price elasticities reported above to evaluate changes in tax policy 

requires several caveats. First, although the tax price elasticities represent the average response 

of taxpayers to the tax rate changes in TRA, as shown in the previous section some taxpayer 

groups are likely to have different behavioral responses. For example, the response of high 

income taxpayers may be larger than middle income taxpayers because higher income taxpayers 

may have greater flexibility to alter their labor arrangements and portfolios. Second, the 

behavioral response may differ for different types of tax rate changes. For example, the 

behavioral response for rate increases may be different than the response for rate reductions. 

Third, the potential for avoidance and income shifting associated with tax changes will 

vary over time. Taxpayers and their advisors develop new strategies and technologies to 

minimize tax liability. Changes in compliance measures, audit techniques, IRS regulations, and 
27 

court decisions also affect the tax environment over time. All of these factors affect both the 

estimates of behavioral responses and the use of such estimates to predict future taxpayers 

responses. 

V. Conclusion 

Using panel data this paper finds that both tax rates and non-tax factors explain the 

changes in reported income (holding tax law changes constant) following TRA. After 

controlling for nontax factors, we estimate the tax price elasticity to be about 0.66. Including 

nontax factors in the model reduced our estimate of the tax price elasticity by about 15 percent. 

Controllingfor changes in returns to human capital by adding occupation to the model has no 

significant effect on the overall tax price elasticity, but there is some evidence that the tax price 

elasticity varies considerablyacross occupation categories. 

The estimates we present for the model that only includes a taxpayer's tax price and 

controls for endogenous sample selection is lower than the tax price elasticity reported by 

Feldstein (1995a), which relies on a somewhat different empirical approach. Nevertheless, our 

results indicate that tax rate changes are likely to have significant effects on taxpayer behavior, 

reported income, and measured income inequality. 
REFERENCES 

Ayers, Benjamin C, C. Bryan Cloyd, and John R. Robinson, “Organizational Form and Taxes: 

An Empirical Analysis of Small Businesses,”Journal of the American Taxation 

Association, (1996), forthcoming. 

Bound, John and George Johnson, “Changesin the Structure of Wages in the 1980s:An 

Evaluation of Alternative Explanations,”American Economic Review, 82 (June 1992), 

371-392. 

Burman, Leonard E. and William C. Randolph, “Measuring Permanent Responses to CapitalGains Tax Changes in Panel Data,” American Economic Review, 84 (September 1994), 

794-809. 

Carroll, Robert and David Joulfaian. “Taxes and Corporate Choice of OrganizationalForm.” 

U.S. Department of the Treasury, Office of Tax Analysis, Working Paper No. 73, April 

1997. 

Clark, Bobby, Dodie Riley and Peter Sailer, “1979 Occupation Study4979-1983 Mortality 

Study,” In Statistics of Income and Related Administrative Record Research: 1989, 

Internal Revenue Service, 181-187. 

Congressional Budget Office, “Effects of the 1981 Tax Act on the Distributionof Income and 

Taxes Paid,” Staff Working Paper, August 1986. 

Eissa, Nada. “Taxationand Labor Supply of Married Women: The Tax Reform Act of 1986 as a 

Natural Experiment,” NBER Working Paper Series, No. 5023, February 1995. 

Feenberg, Daniel, “Are Tax Price Models Really Identified: The Case of Charitable Giving,” 

National Tax Journal, 40 (December 1987), 629-633. 

Feenberg, Daniel and James Poterba. “Income Inequality and the Incomes of Very High Income 

Taxpayers: Evidence From Tax Returns.” In Tax Policy and the Economy 7 (1993), 145-

177. 

Feldstein, Martin, “The Effect of Marginal Tax Rates on Taxable Income: A Panel Study of the 

1986 Tax Reform Act,” Journal of Political Economy, 103 (June 1995a), 551-572. 

Feldstein, Martin, “How Big Should Government Be?” NBER Working Paper Series, No. 5868, 

December 1996. 

Feldstein, Martin. “Tax Avoidance and the Deadweight Loss of the Income Tax,” NBER 

Working Paper No. 5055, 1995b. 
Freeman, Richard B. “How Much Has De-Unionization Contributed to the Rise in Male Earnings 

Inequality,” In Peter Gottschalk and Sheldon Danziger, eds., Uneven Tides; Rising 

Inequality in America (New York: Russell Sage Foundation, 1993). 

Goldin, Claudia and Robert Margo, “TheGreat Compression: The Wage Structure in the United 

States at Mid-Century,” Quarterly Journal of Economics, 107 (February 1992), 1-34. 

Gravelle, Jane G, “Behavioral Responses to Proposed High Income Tax Rate Increases: An 

Evaluation of the Feldstein-Feenberg Study,” Congressional Research Service Report, 

April 1993. 

Hausman, Jerry, “Specification Test in Econometrics,” Econometrica, 46 (1978), 1251-1272. 

Hausman, Jerry and James Poterba, “Household Behavior and the Tax Reform Act of 1986,” 

Journal of Economic Perspectives, 1 (Summer 1987), 101-119. 

Hausman, Jerry and David Wise, Stratification on Endogenous Variables and Estimation: The 

Gary Income Maintenance Experiment.” In Structural Analysis of Discrete Data with 

Econometric Applications, eds. Charles Manski and Daniel McFadden. (Cambridge 

University Press, 1981). 

Heckman, James, “Sample Selection Bias as a Specification Error,” Econometrica, 47 (January 

1979), 153-161. 

Hsiao, Cheng. Analysis ofpanel Data (New York: Cambridge University Press, 1986). 

Internal Revenue Service, Statistics of Income Division, I989 Individual Income Tax Returns, 

Publication 1034, (Washington, DC: US.Government Printing Office, 1992). 

Imbens, Guido W. and Tony Lancaster, “Efficient Estimation and stratified sampling,” Journal 

of Econometrics 74 (1996), 289-3 18. 

Katz, Lawrence F. and Kevin M. Murphy, “Changesin Relative Wages, 1963-1987: Supply and 

Demand Factors,” Quarterly Journal of Economics, 107 (February 1992), 35-78. 

Lindsey, Lawrence, “Estimatingthe Revenue Maximizing Top Personal Tax Rate,”NBER 

Working Paper Series, No. 1761,October 1985. 

Lindsey, Lawrence, “Individual Taxpayer Response to Tax Cuts: 1982-1984,” Journal of Public 

Economics, 33 (July 1987), 173-206. 

Murphy, Kevin and Finis Welch, “The Structure of Wages,” Quarferly Journal of Economics, 

107 (1) (February 1992), 285-326. 
Navratil, John, “The Economic Recovery Act of 1981,”in Essays on the Impact of Marginal Tax 

Rate Reductions on the Reporting of Taxable Income on Individual Income Tax Returns, 

Ph.D. dissertation, Harvard University, 1995. 

Plesko, George A, “Entity Choice: Financial Characteristicsof S and C Corporations,”Public 

Finance Quarterly, 22 (July 1994), 3 11-334. 

Slemrod, Joel. “On the High-Income Laffer Curve.” In Joel Slemrod, ed., Tax Progressivity and 

Income Equality (Cambridge: Cambridge University Press, 1994), 177-210. 

Topel, Robert J. “Regional Labor Markets and the Determinants of Wage Inequality,”American 

Economic Review, 84 (May 1994), 17-22. 
TABLE 1 

MEANS AND STANDARD DEVIATIONS OF VARIABLES (n=15,348) 

Variables 

A log of Constant Law Gross Income 

A log of Constant Law Taxable Income ~~~ ~ 

A IOg Of (I-TT) 

A log of (I-TF) 

A log of (l-~s) 

Log of Income 

Log of Capital Income 

11 Age 

Age Squared 

Entrepreneur Dummy 

Number of Children 

College Age Children 

Marital Status 

Northeast 

Mid-Atlantic 

West-North Central 

South Atlantic 

East South Central 

West South Central 

Standard 

Mean Deviation 

0.148 0.901 

0.122 1.098 

0.161 0.164 

0.153 0.158 

0.0083 0.0282 

11.601 1.347 

6.894 3.086 

I 40.9 I 8.2 

1,737 

0.514 

1.435 

0.031 

0.875 

0.068 

0.197 

0.063 

0.155 

0.044 

0.101 

668 

0.500 

1.272 

0.174 

0.331 

0.252 

0.398 

0.243 

0.362 

0.205 

0.300 

IFFederal marginal taxrate, zS=State marginal taxrate, TT=combinedFederd-state marginal taxrate. 

I 
?E 

?o 

3 g

sg

E 

8

E

c 

(r 

U 

r

.-

9

2 

c

m 0 w * 

: 4 L .- E 

Y$ %J

P 3 d 
. a 

8

!5 

0
k 

TABLE 3 

Robustness Checks for Complete Model 

Robustness Check 

Include taxpayers age 64 or below in 1989 

Apply income cutoff in both 1985 and 1989 

Exclude taxpayers with any S corporation income 

Include all taxpayers with S corporation income 

Exclude AMT taxpayers in both 1985 and 1989 

Include taxpayers subject to the AMT 

Include capital gains dummy variable 

Include capital gains dummy variable and taxpayers 

subject the AMT 

Other Robustness Checks 

Include itemization dummy variable 

Financial wealth, capital gains, and itemization based 

on both 1985 and 1989 information 

Base marginal tax rates and dependent variable on preTRA law 

Drop income as independentvariable 

Sample Size Tax Price Elasticity 

17,171 0.84' 

(0.15) 

13,671 0.47' 

(0.09) 

12,990 0.66' 

(0.17) 

I 0.79' 17y314 1 (0.15) 

15,142 0.67' 

(0.16) 

16,628 0.76' 

(0.15) 

15,348 0.67' 

(0.16) 

16,628 0.79' 

(0.15) 

15,348 0.67' 

(0.17) 

15,348 0.80' 

(0.16) 

15,089 0.91' 

(0.10) 

15,348 0.35' 

(0.13) 

Estimates are for the complete weighted model, including all non-tax factors. Instrumental 

variables is used with generalized least squares. Standard errors appear in parenthesis. * indicates 

variable is significant at the 95 percent level of confidence. tT= Comblned federal-state marginal 

tax rate. 
TABLE 4 

Tax Price Elasticity By Occupation 

Tax Price 

Elasticity*Occupationi Total Effect 

(Standard Error) (F-Value) 

1 

-0.275 NA 

(0.420) 

1.356' 

(0.480) 1 1.081' (9.470) 

3.612' 3.337' 

(0.976) (7.318) 

0.409 0.134 

Occupation: 

Executives and Managers 

Investors 

Lawyers 

Artists, Journalists, and Athletes 

Doctors and Other Health-Related 

Occupations 

Science, Engineers, and Computers 

(0.640) (0.255) ~~ 

0.783 0.508 

(0.956) (0.392) 

0.780 0.505 

(0.521) (1.45 1) 

0.4 13 0.138 

(0.5 52) (0.292) 

0.256 -0.019 

(0.724) (0.214) 

1.010 0.735 

(0.706) (1.050) 

Supervisors 

Blue Collar 

Farming and Self-Employed 

Sales 

Not Elsewhere Classified 

1 2.399' 2.124' (0.744) 1 (6.091) 

I 1.253' 0.978' (0.581) I (3.061) 

1 0.026 -0.250 (1.307) I (0.233) 

Occupation Information Not Available 0.700 0.425 

(0.596) (0.714) 
Appendix A 

The panel of tax returns used for this paper is constructed by matching taxpayers present in the 

Statistics of Income (SOI) Individual Tax files for both 1985 and 1989. The population of 

individual income tax returns is highly skewed, with a small fraction of individuals accounting 

for a relatively large fraction of income and tax liability. 

The SO1cross-sectional files are stratified by income, business plus farm receipts, and tax 

schedule type to over sample taxpayers with high incomes or business receipts and taxpayers 

who file particular tax schedules (e.g., Schedule C/sole proprietorship and Schedule F/farm 

proprietorship). Income is defined as the greater of a taxpayer’s total income or total loss. 

Taxpayers with very high incomes are selected with certainty. In 1985, 121,480 returns were 

sampled. In 1989, 110,840returns were sampled. 

As noted by Imbens and Lancaster (1996) and Hausman and Wise (1981), if the sampling were 

random or exogenous, estimation would lead to consistent and efficient estimates. However, 

selection of tax returns for the panel used for this paper depends, to a large extent, on the 

dependent variable in our model (i.e., adjusted taxable income less capital gains realizations); 

that is, the sample selection is endogenous. Therefore, without appropriately controlling for 

endogenous sample selection, the estimates of the tax price elasiticity would be likely to suffer 

from sample selection bias. 

The stratification of the sample by income, business receipts, and form type also means our 

sample does not correspond to the true proportions in the population. In order to allow 

inferences to be drawn about how changes in tax rates are likely to affect the population, we also 

need to extrapolate our sample to the population. Below we first describes the construction of the 

panel of tax returns used for this paper and the nature of the sample selection bias. Then we 

outline the weighting approach used to correct for the endogenous sample selection and produce 

population estimates. 

Descrbtion of Panel 

The sample strata used for the SO1cross-sectional files are based on the larger of total income or 

total loss, the size of business plus farm receipts, and the presence of particular forms and 

schedules. Returns are then selected from the sample strata from two methods. The first 

method selects all returns with the same two sets of four ending digits of their social security 

number (SSN). Tax returns selected under this first method contribute to a randomly drawn 

sample of tax returns often referred to as the Continuous Work History Survey (CWHS). The 

probability of any tax return being selected for the CWHS sample is roughly equal to 1/5,000.’ 

The second method uses the ending digits of numbers generated by randomly transforming each 

‘The probability of taxpayers’ with the same four ending digits of their SSN being selected is 

1/10,000. Since two sets of four ending digits of a taxpayer’s SSN are used, the sampling probability 

becomes 1/5,000. Tax returns selected under this method constitute about 20 percent of the panel 

observations used for this paper. 
A.2 

tax return's SSN. Tax returns with ending digits below specified values, which define the 

probability of tax returns being drawn within each strata, are selected. In 1985, the sampling 

rates for the various strata ranged from 0.03 percent to 100 percent. From one cross-sectional file 

to another cross-sectional files, the random number for a particular tax return is unchanged 

because the seed value for the random number generator is the same across years. Provided a 

, taxpayer remains in a strata with an equal or greater sampling rate, this sample design guarantees 

that the taxpayer will be selected for future cross-sectional files. This sample design also has the 

effect of maximizing the'overlap of taxpayers sampled in different years. Of the 121,480returns 

sampled in 1985 and 110,840returns sampled in 1989, about 56,003 returns were sampled in 

both years. 

Endogenous Sample Selection 

Taxpayers selected using the SSN transformation described above will generally have an equal or 

greater probability of remaining in subsequent cross-sectional files if their income is unchanged 

or increases because they would either remain in their original sample strata or move to a strata 

with a higher sampling rate. Taxpayers who experience a decline in income are likely to fall into 

a lower sampling strata, and would, therefore, have a probability of being selected for 

subsequent cross-sectional samples of less than one. In fact, the probability that they will be 

sampled in the subsequent cross-section falls to whatever the sampling rate is for their new 

sample strata. The probability that they remain in the cross-section, conditional on being selected 

in a prior year is the ratio of the sampling rate for their new strata to their initial sampling rate 

(Hinkins, Jones, and Scheuren; 1988). 

Tax price elasticities estimated from the sample of tax returns comprising the panel used for this 

paper are likely to suffer from sample selection bias because taxpayers with rising or equal 

incomes are likely to remain in the panel, while taxpayers with falling income are less likely to 

be included in the panel. That is, this paper uses a panel to study the determinants of income 

changes where taxpayers with declines in income are under represented. Moreover, the tax price 

elasticity estimated in our paper is likely to be biased upwards.2 

SamDle Weights to Correct for Sample Selection Bias and Produce PoDulation Estimates 

Figure 1 depicts the 1985 and 1989 SO1files and the panel constructed from the overlap between 

these two files. Tax returns are sampled in 1985 depending on their characteristics (i.e., income, 

business receipts, and form type). The sampling rate for the ith stratum in 1985, P,(85),is 

determined by these characteristics. Whether a tax return is sampled in 1989 will also depend on r- the taxpayer's 1989 characteristics. The taxpayers sampling rate, independent of whether the 

'Although we obtain similar results when only using the randomly selected CWHS returns, we do 

not have a great deal of confidence in these results because the CWHS has few high income taxpayers -- the taxpayers with the greatest reduction in tax rates due to the 1986Tax Reform Act. For example, 

among the CWHS returns in our panel, there are only 50 taxpayers who faced the top 50 percent statutory 

marginal tax rate and 49 taxpayers who faced the 49 percent statutory marginal tax rate in 1985. 

3 
A.3 

taxpayer was sampled in 1985, is Pi(89). 

The panel used for this paper, however, only contains taxpayers that were sampled in both 1985 

and 1989;that is, the overlap between the two cross-sectional files shown on Figure 1 as the 

Figure 1 

Relationship of Panel to Cross Sections of Tax Returns 

1985 Cross Sectional File 1989 Cross Sectional File 

n(85)=121,480 n(89)=110,840 

Population of Tax Returns Filed in 1985 or 1989 

N(85)=101,836,347; N(89)=112,952,035 

intersection between the 1985 and 1989 cross sectional files. 

The probability that a tax return is sampled in both 1985 and 1989, and is, therefore, included in 

our panel of tax returns, can be constructed in two steps depending on whether a taxpayer is 

sampled at all in 1985 and whether the taxpayer is again sampled in 1989. The probability that a 

taxpayer will be sampled in 1985 is given by a tax return’s sampling rate associated with the 

taxpayer characteristics, Pi(85). We can then consider the probability that a taxpayer is sampled 

in 1989 conditional on having already been sampled in 1985. This formulation follows from the 

identity, 

A. 1 
A.4 

where Pi(85 n89) represents our panel of tax returns (as shown in Figure 1) and Pi(89 I 85) 

represents the probability that tax returns are sampled in 1989 conditional on already being 

sampled in 1985. A key feature of this formulation is that the probability that taxpayers are 

selected in 1989 and included in our panel depends on the change in the sampling rates for their 

respective sample strata in each year. In order to correct for the endogenous sample selection, the 

probability of being selected in 1989 and being included in our panel must depend on both 1989 

and 1985 characteristics. 

Recall that because of the sample design of the cross-sectional file, a taxpayer will be selected in 

subsequent cross-sectional files with certainty (i.e., P,(89 185) = 1) if a taxpayer remains in the 

same sample strata or moves to a sample strata with a higher sampling rate. However, if a 

taxpayer moves to a sample strata with a lower sampling rate (e.g., because of a decrease in 

income), the probability that the taxpayer continues to be sampled is less than one. In this case, 

the probability that a taxpayer is selected, conditional on having been selected in 1985, is given 

by Pi(89)/Pi(85). Combining these two possible outcomes, the probability of a taxpayer 

remaining in the panel in 1989 conditional on being sampled in 1985 is given by, 

A.2 

which will be equal to one if a taxpayer remains in the same strata or moves to a strata with a 

higher sampling rate, and less than one otherwise. 

Consider, for example, a taxpayer selected in 1985 with a sampling probability of 1/400 whose 

sampling probability fell to 1/1000 in 1989. The probability that the taxpayer would be selected 

in 1989 and be included in our panel is 4/10. Alternatively, for a taxpayer whose 1985 sampling 

probability was one in 1985,but fell to 1/1000in 1989, would have a probability of 1/1000 of 

being selected in 1989 and being included in our panel. Although the probability of being 

selected in 1989 is the same for these two taxpayers (Le., l/lOOO), the probability that they are 

included in our panel differs because they are sampled at different rates in 1985. Finally, a 

taxpayer who had a sampling probability of 1/1000 in 1985 that increased to 1 in 1989 would 

have a probability of 1 of being included in our panel. 

Substituting equation A. 1 into A.2, the probability that a taxpayer is sampled in both years and 

included in our panel, is given byY3 

30f course, this fokulation does not account for the presence of CWHS returns in our sample. 

Since CWHS returns are sampled with certainty, the probability that they &e selected in 1989conditional 

on being selected in 1985 is one. 
Pi(85) Pi(89185) = Pi(85)[min [ :g:)] A.3 

1, -

= min (P,(85),Pi(89)) 

The weight is simply given by the inverse of the sampling probability, or, 

1 - 1 w. = --

Pi min (Pi(85),Pi(89)) 

= max[ -1 1) A.4 

Pi(85)’Pi(89) 

= max (wi(85),wi(89)) 

where wi(85) and wi(89) are the ith taxpayer’s 1985 and 1989 sampling weights, respectively. 

We then use weighted least squares, which is consistent and asymptotically efficient, to both 

correct for the endogenous sample selection and to extrapolate our sample to the p~pulation.~ 

Both weighted and unweighted results are reported in the paper. 

4Although,with our data some observations may have Pi(85)or Pi(89)equalto zero, but are 

obviously not in our panel, we make no attempt to account for this in our estimation.