The Congress of the United States O Congressional Budget Office

CBO

Effective Tax Rates: Comparing

Annual and Multiyear Measures

January 2005

A

PAPER
Notes

Numbers in the tables and text of this report may not add up to totals because of rounding.

Unless otherwise specified, all years are calendar years.
Preface

This Congressional Budget Office (CBO) paper, which was prepared at the request of the 

Chairman of the House Committee on Ways and Means, is the first of several papers that 

address methodological issues in distributional analyses. The analysis focuses on the choice of 

period used to assess the distribution of income and taxes and examines the effect of measuring income and taxes over periods longer than one year. It uses data from a panel of income 

tax returns to calculate both annual and multiyear (longitudinal) effective tax rates. But 

because income tax returns lack sufficient information about low-income taxpayers, the study 

also draws on the University of Michigan’s Panel Study of Income Dynamics to extend the 

analysis to lower-income households.

Edward Harris, David Weiner, and Roberton Williams of CBO’s Tax Analysis Division wrote 

the paper under the direction of G. Thomas Woodward. Dean R. Lillard of Cornell University reviewed a draft of the paper and provided valuable comments, as did John Sabelhaus, 

Douglas Hamilton, Paul Cullinan, and Arlene Holen of CBO. (The assistance of external participants implies no responsibility for the final product, which rests solely with CBO.) 

Leah Mazade edited the paper, and Janey Cohen proofread it. Denise Williams typed early 

drafts of the manuscript, and Maureen Costantino both designed the cover and prepared the 

paper for publication. Lenny Skutnik produced the printed copies of the report, and Annette 

Kalicki prepared the electronic versions for CBO's Web site (www.cbo.gov). 

Douglas Holtz-Eakin

Director 

January 2005

Introduction and Summary 1

The Unit of Analysis 2

The Income Measure 2

The Measurement Period 3

The Incidence of Taxes 3

What Is Distributional Analysis? 4

Longitudinal Versus Annual Measures of Effective

Tax Rates 5

The Framework of CBO’s Analysis 6

Sources of Data 6

Unit of Analysis 6

Restrictions on the Sample 7

Weighting 7

Definition of Income 7

Measure of Tax Liability 7

Construction of Multiyear Measures 8

Definition of Income Categories 8

Comparison of Annual and Longitudinal

Distributions 9

Limitations of the Analysis 12

Distribution of Annual and Longitudinal Income

and Taxes 12

Distributional Effects of Illustrative Policy Changes

Under Longitudinal Measures 15

Reduce the Top Two Individual Income Tax Rates 15

Doubling the Child Credit 16

Make the Child Credit Fully Refundable 17

Conclusion 17

Appendix A: Attrition in the Continuous Work History

Sample 29

Appendix B: Alternative Measures of the Distribution of 

Annual and Longitudinal Income and Taxes 33

Appendix C: CBO’s Method for Deriving Income

Quintiles 47

CONTENTS
vi EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Tables

1. Selected Methods for Distributional Analyses 18

2. Annual and Longitudinal Income and Effective Tax Rates,

1993 to 1995 19

3. Annual and Longitudinal Income and Effective Tax Rates,

1991 to 1997 21

4. Annual and Longitudinal Income and Effective Tax Rates,

1987 to 2000 23

5. Distributional Effects of Reducing the Top Two Individual Income

Tax Rates 25

6. Distributional Effects of Doubling the Child Credit 26

7. Distributional Effects of Making the Child Credit Fully Refundable 27

A-1. Causes of Attrition in the Continuous Work History Sample for 1987 30

A-2. Characteristics of Taxpayers in the Continuous Work History Sample

for 1987 31

A-3. Ten-Year Attrition Rates in the Continuous Work History Sample 31

A-4. Annual and Longitudinal Income and Effective Tax Rates,

1986 to 1995 32

B-1. Annual and Longitudinal Income and Tax Rates for Taxpayers in

All Possible Three-Year Periods, 1987 to 2000 34

B-2. Annual and Longitudinal Income and Tax Rates for Taxpayers in

All Possible Seven-Year Periods, 1987 to 2000 36

B-3. Annual and Longitudinal Income and Tax Rates for Taxpayers

in Any Three-Year Period, 1987 to 2000 38

B-4. Annual and Longitudinal Income and Effective Tax Rates Under

Different Sampling Restrictions, 1987 to 2000 40

B-5. Annual and Longitudinal Income and Tax Rates for PSID

Respondents in All Possible Three-Year Periods, 1987 to 1995 42

B-6. Annual and Longitudinal Income and Tax Rates for PSID

Respondents in Any Three-Year Period, 1987 to 1995 44

C-1. Minimum Income by Quintile 47
CONTENTS vii

Boxes

1. Distributional Analyses of Tax Systems 2

2. Sampling Issues Associated with Longitudinal Data 10

3. Distributional Measures 13

4. Measuring Income Longitudinally Using the Panel Study

of Income Dynamics 14

Effective Tax Rates: Comparing 

Annual and Multiyear Measures

Introduction and Summary

The distribution of the economic burden of taxes is central to tax policy. In constructing measures of effective tax 

rates—the share of their income that people pay in 

taxes—analysts must confront a wide range of issues: 

what to include in measuring income, the range of taxes 

to be studied, the shifting and ultimate incidence of taxes 

(that is, on whom the ultimate burden of a tax falls), 

whether to study individuals or households, and the period that the analysis is to cover (see Box 1). This Congressional Budget Office (CBO) paper focuses on how 

the choice of a particular time frame affects distributional 

assessments of the burden of federal taxes.

People pay most federal taxes on the basis of annual accounting; the individual income tax, for example, is generally assessed on taxable income earned during a calendar year.1 Because of that annual accounting period and 

because tax laws may change from one year to the next, 

most analyses of effective tax rates cover individual years. 

(CBO regularly publishes reports showing the annual distribution of income and taxes for specific years.)2 How 

much of their income people pay in taxes fluctuates from 

year to year, in part because a rise or fall in income moves 

them into higher or lower tax brackets; in part because 

tax laws change; and in part because their filing status, 

amount of itemized deductions, or other circumstances 

change. At the same time, variability in people’s income 

alters their capacity to pay taxes over time. In the face of 

such changes, focusing exclusively on the impact of taxes 

on an annual basis may provide a limited view of the relative tax burdens that people bear over time. As a broader 

view, for example, an analysis could compare the present 

value of taxes paid over a person’s lifetime with the 

present value of his or her lifetime income.3

But current data do not allow actual lifetime measures of 

effective tax rates. The longest period for which information is available is that covered by the University of Michigan’s Panel Study of Income Dynamics (PSID). The 

PSID has followed approximately 5,000 families since 

1968, interviewing them almost annually, and that 

5,000-family sample appears to represent roughly the entire population. But the PSID provides only limited information on taxes and covers relatively few individuals at 

the upper end of the income distribution—a segment of 

the population that is central to any analysis of federal tax

revenues.

In contrast, the Internal Revenue Service’s Statistics of Income (SOI) sample of tax returns provides rich detail on 

taxes and an extensive random sample of tax filers that includes those at the top of the income distribution. However, because people, particularly those at the bottom of 

the distribution, move onto and off the tax rolls from 

year to year, SOI data poorly represent the entire population over time and cannot consistently provide information on low-income taxpayers. 

Nevertheless, even with such limitations, the two sources 

of data, especially when examined in concert, offer the 

1. Some exceptions exist, such as the ability to carry unused business 

or capital losses into successive tax years and the ability to average 

income over several years, which was allowed under tax law prior 

to the Tax Reform Act of 1986.

2. See Congressional Budget Office, Effective Federal Tax Rates, 

1979-1997 (October 2001), and Effective Federal Tax Rates, 1997 

to 2000 (August 2003). An update in April 2004, which is available only on CBO’s web site (www.cbo.gov), extends the series 

through 2001.

3. The present value is a single number that expresses a flow of current and future income (or payments) in terms of an equivalent 

lump sum received (or paid) today.
2 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Box 1.

Distributional Analyses of Tax Systems

Distributional analyses of tax systems compare the different tax burdens that people bear, typically focusing on 

how those burdens vary among income groups. For example, in several reports, the Congressional Budget Office (CBO) has estimated how federal taxes are distributed annually among groups of households, which have 

been defined on the basis of their income. CBO’s assessments rely on cross-sectional data covering single years; 

they do not consider how tax burdens may change over 

time with taxpayers’ circumstances. Such longer-term 

measures of tax burdens require panel data—information collected annually, for many years, from the same 

group of people.

CBO's previous reports have presented summary statistics that include each group’s average effective tax rate—

tax liability as a percentage of total income—and the 

share of federal taxes that it paid. In 2001, for example, 

households in the lowest fifth (quintile) of the population paid 5.4 percent of their income in federal taxes and 

about 1 percent of the total federal tax bill. In contrast, 

households in the top quintile faced an average effective 

federal tax rate of 26.8 percent and paid about 65 percent of all federal taxes.

Several factors strongly influence any estimate of the distribution of taxes. They include the unit of analysis, the 

components of income measured, the period covered, 

and assumptions about the incidence of each tax—who 

actually bears the burden of it.

The Unit of Analysis 

Analysts measure tax burdens over one of four kinds of 

units: individuals, taxpaying units (people included on a 

single tax return), families, or households. The key issue 

from an economic perspective is that taxes reduce consumption, so the appropriate unit of analysis should be 

some form of consumer unit—a group of people who 

combine their income to purchase goods and services. 

Yet even that simplification is problematic because the 

makeup of the groups often shifts for different purchasing choices. For example, students who share an apartment compose a single group to purchase housing but 

not necessarily a single group to buy food. Furthermore, 

consumer units are hard to identify. Available data typically report household and family relationships; to measure tax burdens on the basis of consumer units, analysts 

must infer the groups that actually make decisions about 

consumption.

The Income Measure

People typically think of their income as comprising 

their pay for working, returns on their investments (interest, dividends, rents, and capital gains), pension payments, and government transfer payments (such as Social Security benefits). However, researchers often use a 

broader concept, one that also includes the value of 

in-kind benefits, such as health insurance, food stamps, 

and housing assistance; income and payroll tax payments that are made by others (such as an employer) but 

that actually fall on individuals in the form of lower 

wages and salaries or smaller returns on investments; and 

the value of “services” provided by durable goods (for example, owner-occupied housing). In its most broadly 

construed but most difficult-to-measure form, income 

over a particular period equals the value of consumption 

of all kinds, including leisure, plus any change in wealth. 

Some analysts argue that consumption rather than income more accurately represents a person’s well-being, 

even though that measure ignores savings.

Larger households generally consume more goods and 

services than smaller households do, and in distributional studies, many analysts adjust households’ income 

to account for such variation.1 For example, a couple 

needs more income than a single person does to consume at the same level. Measuring income per capita 

(total income divided by number of people) considers increased needs but ignores economies of scale: 

two people may not be able to live as cheaply as one, 

but they can live more cheaply together than they 

can live apart. In general, analysts use various ad1. Ways to adjust income are discussed in Roberton Williams, 

David Weiner, and Frank Sammartino, Equivalence Scales, 

the Income Distribution, and Federal Taxes, Technical Paper 

1999-2 (October 1998), available from CBO’s Tax Analysis 

Division or at www.cbo.gov/Tech.cfm.
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 3

Box 1.

Continued

justed measures of income that fall somewhere between unadjusted and per capita income.

The measure of income that analysts use for a distributional analysis and the adjustments they make for 

different-sized households can influence their results. 

Factors affecting those decisions include the purposes of the analysis, availability of data, and methods at hand for valuing noncash income or consumption. 

The Measurement Period

Distributional analyses typically focus on annual 

measures of income and taxes—because the government generally assesses taxes annually, tax data usually cover a single year, and many taxpayers think 

about their income and taxes on an annual basis. A 

person’s income may vary, however, and a single year 

may not accurately indicate a taxpayer’s well-being. 

A spell of unemployment may temporarily lower income, for example, whereas the sale of a business 

may briefly raise it.

People’s income also changes relative to that of others. Thus, a single year’s assessment of income and 

taxes may be uncharacteristic of experience over 

longer periods. Income mobility stems in part from 

the fact that a person’s income over his or her lifetime tends to follow a common pattern: it rises from 

low levels early in life, peaks during the most productive years, and then falls off during retirement. 

By measuring income over longer periods, perhaps 

over an entire lifetime, analysts take income mobility 

into account, minimize the effects of year-to-year 

fluctuations, and are better able to assess people’s 

economic well-being.

Other factors that change over time affect the taxes 

that people pay. For example, families grow as they 

have children, and they shrink as children grow up 

and leave home. Those fluctuations produce parallel 

changes in both the number of dependent exemptions taxpayers can claim and their income tax liability. Therefore, even if a person’s income is stable over 

time, other factors may lead to differences between 

taxes paid in a given year and average taxes paid over 

a longer period. 

The Incidence of Taxes

Distributional assessments of tax systems require 

analysts to assign the burden of each tax to individuals. (The reason is that the actual burden of taxes 

may not fall on the people or businesses that pay 

them to the government. The burden may instead be 

shifted to others through lower wages, smaller returns on investments, or higher prices.) The assumptions used in assigning tax burdens can determine 

the results of an analysis. But researchers disagree 

about incidence—particularly for the corporate income tax and estate taxes. Furthermore, measuring 

incidence accurately may mean assessing not just 

taxes but rather taxes net of the benefits that the collected revenues pay for. For example, considering the 

distribution of Social Security taxes without accounting for the benefits that the taxpayer will receive in 

retirement may misrepresent the actual burden of the 

tax when the program is considered as a whole. 

Most analysts agree that workers bear both the employee’s and employer’s share of payroll taxes—employees shoulder the latter tax burden through wages 

that are lower than they would be in the taxes’ absence. There is less agreement about who bears other 

federal taxes. Some researchers maintain that the personal income tax falls entirely on the people whose 

income is taxed. Others argue that the portion of the 

tax that falls on income from capital ultimately reduces workers’ income and is thus borne by workers 

rather than by the owners of capital. Experts similarly disagree about the corporate tax, with some asserting that it falls on income from capital, income 

from labor, or foreigners. Analysts’ views also differ 

about who actually pays excise taxes and whether the 

burden of estate taxes falls on the person who dies or 

on his or her heirs.
4 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

best information with which to examine tax burdens longitudinally—that is, over periods longer than a year.

This analysis compared the distribution of income and 

taxes measured on an annual basis with the distribution 

measured longitudinally. Its key findings are as follows:

B Incomes and taxes when measured longitudinally are 

more evenly distributed than they are when measured 

annually. In addition, the distribution becomes more 

equal as the time horizon lengthens.

B When a one-year measure of income is used, incomes 

and tax rates for lower quintiles, or fifths, of the income distribution on average are lower than they are 

when a longer period of measurement is used. Thus, 

income in the second quintile when measured over 

14 years is 26 percent higher than annual income over 

the same period, and the effective income tax rate is 

3.5 percentage points higher. 

B Incomes in the highest quintile are smaller when 

measured over a longer period than when measured 

annually. In the top quintile, income measured over 

14 years is 4 percent below average annual income. 

However, for that quintile, the effective tax rate under 

either measurement period differs by only one-tenth 

of a percentage point.

B The effects of illustrative tax policy changes generally 

appear more evenly distributed when they are measured over multiple years than when they are assessed 

on an annual basis. For example, as measured on an 

annual basis, a doubling of the child credit would affect only 3 percent of taxpayers in the second quintile 

and lower the average tax rate in that quintile by 0.1 

percentage points. Under longitudinal measures, almost 9 percent of taxpayers in that second quintile 

would see an effect, and their effective tax rate would 

be reduced by 0.2 percentage points. In the average 

year, 32 percent of taxpayers would be affected by that 

change, but 52 percent would be affected in at least 

one of 10 years. A policy that reduced the top two income tax rates would lower the effective rate only in 

the top quintile—by 1.0 percentage point when measured annually and by 1.1 percentage points when 

measured longitudinally. In the average year, only

2 percent of taxpayers would be affected by that 

change, but 6 percent would be affected in at least one 

of 10 years.

What Is Distributional Analysis?

Equity, or fairness, is a key consideration in evaluating tax 

policy, although there are many views on what “fairness” 

means. Distributional analysis, which shows how income 

and taxes are distributed among individuals, families, or 

households, is one widely used way to inform judgments 

about the fairness of changes in the tax system. Policymakers use such analyses to evaluate the existing distribution of tax burdens, study how the distribution has 

changed over time, and assess proposed changes to tax 

law.

Several governmental organizations, including CBO, periodically estimate the distribution of income earned and 

taxes paid in a given year.4

 The fundamental structure of 

those analyses is similar, although they differ in their details. In general, the approach is to combine information 

from a sample of tax returns for a year with survey data 

for the same year covering people who did not file tax returns. The resulting cross section of data represents the 

entire population for that year. Analysts assign tax payments to each taxpayer under specific assumptions about 

who bears the ultimate burden of each tax. (CBO, for instance, assumes that employees bear the burden of the 

employer’s share of the payroll tax and that all owners of 

capital effectively pay the corporate income tax.) People 

are arrayed in income groups, usually by using a broad 

measure of income from both taxable sources (such as 

wages) and nontaxable sources (such as the health insurance premiums employers pay on behalf of employees). 

The analyses examine a number of indicators of tax policy, including the average income of each income group 

and the taxes each group pays—often expressed as a 

group’s effective tax rate and share of total tax payments.

Those analyses of annual data show that the federal tax 

system is progressive—average effective tax rates increase 

as income rises. The individual income tax is especially 

progressive because its graduated rate structure taxes 

4. See Congressional Budget Office, Effective Federal Tax Rates, 

1979-1997, and Effective Federal Tax Rates, 1997 to 2000, for a 

detailed description of CBO’s methodology. The methodology of 

the Department of the Treasury is described in detail in JulieAnne Cronin, U.S. Treasury Distributional Analysis Methodology, 

OTA Paper 85 (Department of the Treasury, Office of Tax Analysis, September 1999). The Joint Committee on Taxation's methodology is outlined in Joint Committee on Taxation, Distribution 

of Certain Federal Tax Liabilities by Income Class for Calendar Year 

2001, JCX-2-01 (February 27, 2001). 
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 5

larger incomes at higher rates. Corporate income taxes 

also appear progressive under CBO’s assumptions about 

incidence because income from capital is concentrated 

among people in higher-income groups.5

 Payroll taxes 

claim a roughly constant share of income for most groups 

in the income distribution, but that share declines for 

families with the highest income because their earnings 

exceed the maximum amount that is subject to tax. Excise 

taxes—in fact, consumption taxes generally—are regressive because lower-income groups spend a greater proportion of their income than higher-income groups spend on 

goods that are subject to tax.

Longitudinal Versus Annual Measures 

of Effective Tax Rates

Most distributional analyses consider annual measures of 

income and taxes. Federal income and payroll taxes are 

currently levied on income yearly, and annual collection 

periods for those revenues lead to yearly reporting of tax 

data. Many major surveys, such as the Bureau of the Census’s Current Population Survey, also ask respondents 

about their income over the past year. 

A one-year time horizon, however, provides a limited perspective on the distributional impact of federal taxes. 

Measuring income and taxes over a longer period, even 

over a lifetime, may assess overall economic well-being 

more accurately than an annual measure of income does. 

Annual income differs from lifetime income for many 

reasons, some relatively predictable and some transitory. 

Events in a person’s life, such as marriage or divorce, may 

produce some of the differences; other factors relate to 

changes in earnings and savings over people’s lifetimes. 

When individuals enter the workforce, they generally 

earn relatively low wages, but their earnings and other income rise as they gain experience and accumulate assets. 

Once they retire, their wages fall, and they begin to draw 

on their savings. Still other differences are transitory: 

someone may become temporarily unemployed or realize 

a large capital gain. As income fluctuates, tax payments 

change correspondingly. Thus, a person’s income or taxes 

in any given year may not accurately represent that person’s economic well-being over a longer period.

Because of such fluctuations, annual measures of income 

group together people who have different lifetime economic circumstances. For example, the bottom income 

quintile contains many people with a history of low earnings and with limited prospects for earnings in the future. 

But it may also include a medical student who is working 

part-time and borrowing against expected long-term income to defray living expenses. And it may contain retirees who have accumulated a substantial amount of wealth 

but have only limited income. All of those people have 

low annual income for the specific year being measured. 

Over their lifetime, however, some of them would not be 

found in the bottom quintile.

Analyses that use a one-year measure may cause the distribution of income and taxes to appear more unequal than 

it would seem in a comparable assessment that covered a 

longer period. In any one year, some people have a temporarily high level of income, and others have a temporarily low level. Measuring income over a longer time 

frame moderates those temporary effects, and the distribution of income appears more even. Also a factor with 

an annual measure is that if the size of the share of income that is transitory changes over time, the distribution of annual income might shift, even with no alteration in the distribution of longer-term income.

The extent to which the potential drawbacks of using 

cross-sectional (annual) analysis will matter depends on 

the actual pattern of changes in income. If taxpayers’ incomes fluctuate greatly from year to year and people’s lifetime incomes differ substantially from their income in 

any one year, then using distributional results based on 

cross-sectional analysis could lead to very different conclusions than those reached by using a longer-term income measure. However, if effects arising from transitory 

ups and downs in income and a taxpayer’s stage in the life 

cycle are small relative to other differences among taxpayers, the annual distribution of income and taxes may be 

similar to the longer-term distribution. 

Previous studies have examined the effects of measuring 

income and taxes over different periods. The Department 

of the Treasury recently developed a data set for a 10-year 

panel of families to use in analyzing tax proposals.6 Its 

analysis found that income and taxes were somewhat 

5. Some analysts argue that at least part of the burden of corporate 

income taxes falls on workers in the form of lower wages. In that 

view, the labor force has less capital with which to work because 

corporate taxes reduce investment in capital goods—lowering 

workers’ productivity and hence their wages.

6. James Cilke and others, “Distributional Analysis: A Longer-Term 

Perspective,” in National Tax Association, Proceedings of the 93rd 

Annual Conference on Taxation (Washington, D.C.: National Tax 

Association, 2001).
6 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

more evenly distributed when a 10-year measure of income was used in place of an annual measure, but overall, 

income and taxes were distributed similarly under both 

measures. Joel Slemrod, a researcher at the University of 

Michigan, also found that income distributions were similar under the two types of measures. (Slemrod compared 

“time-exposure” income—income measured over the 

multiyear 1979-1985 period—with annual income.)7 He 

determined, however, that the share of income going to 

the bottom group was substantially greater under his longitudinal measure than it was under his annual measure. 

The Framework of CBO’s Analysis

This study followed a group of people over multiple years 

and compared the distribution of their income and taxes 

measured on an annual basis and measured longitudinally. Other facets of the analysis—the people considered, 

the definition of income, and the tax law that was applied 

to that income—were held constant to isolate the effects 

of measuring income and taxes over different periods (see 

Table 1 on page 18).

Sources of Data

The data for CBO’s analysis came from two sources: the 

Internal Revenue Service’s (IRS’s) Continuous Work History Sample (CWHS), which is a random sample of individual income tax returns for the same taxpayers each 

year, and the University of Michigan’s Panel Study of Income Dynamics (PSID).8

 The two data sets have different strengths and weaknesses. The CWHS contains detailed information about income and other tax-related 

characteristics (such as the amount of itemized deductions), which permits analysts to estimate income taxes 

accurately. However, the CWHS includes only people 

who file tax returns, and many lower-income families are 

thus excluded from the CWHS because they are not required to file returns. The CWHS has another drawback: 

it provides no information about untaxed income, such as 

means-tested transfer payments like food stamps or housing assistance. Because such income goes disproportionately to low-income households, its omission may significantly understate those households’ total income and 

economic well-being.

In contrast, the PSID contains less-detailed information 

about income and no information on other tax-related 

characteristics, which reduces the accuracy of tax calculations from it. Furthermore, because the PSID is a survey, 

it is probably less reliable than tax-return data because of 

errors in reporting by the survey’s respondents. In addition, incomes in the PSID are top-coded, or capped at 

certain levels, to preserve confidentiality, a feature that 

limits the survey’s usefulness in examining upper-income 

families. However, the advantages of the PSID are that it 

covers the entire population and captures information 

about income from major cash transfer programs (such as 

the Temporary Assistance for Needy Families, or TANF, 

program).

Because of the relative strengths of the two data sets, 

CBO relied on the PSID in examining lower-income 

families and on the CWHS in considering middle- and 

upper-income taxpayers.

Unit of Analysis

CBO’s study considered the income and taxes of taxpaying units, which are generally either individuals or married couples filing joint tax returns.9 To make results 

from the PSID comparable with those from the CWHS, 

CBO created taxpaying units out of the PSID’s families, 

essentially by including only the income of the head of 

the family and spouse. For families that had several taxpaying units, such as a multigenerational family, CBO 

considered only the primary unit (because the PSID does 

not provide the information necessary to track the income of secondary units). For a substantial majority of 

families, the primary taxpaying unit, the family, and the 

household were identical, so the choice of the unit of 

analysis in this study is unlikely to have a significant impact on its results. 

7. Joel Slemrod, “Taxation and Inequality: A Time-Exposure Perspective,” in James M. Poterba, ed., Tax Policy and the Economy, 

vol. 6 (Cambridge, Mass.: MIT Press, 1992).

8. The CWHS contains all taxpayers whose Social Security number 

ends in certain combinations. (In 2001, for example, each combination, which is a 1-in-10,000 sample of tax returns, contained 

about 13,000 returns.) The IRS has sampled a different number 

of combinations over the years, ranging from one in 1986 to five 

from 1998 to 2001. Its data differ from the Social Security 

Administration’s records of earnings histories, which are also called 

the Continuous Work History Sample.

9. Taxpayers who file their own return but are claimed as a dependent on another return are excluded from the analysis.
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 7

Restrictions on the Sample

In this analysis, multiyear measures of income and taxes 

were compared with annual measures of those variables. 

Multiyear measures can be calculated only for taxpayers 

who appear in every relevant year of data; consequently, 

CBO restricted its analysis to those taxpayers. Yet that approach does not guarantee a representative sample. If taxpayers for whom data are available every year differ systematically from taxpayers for whom data are available 

only intermittently, that method might yield a misleading 

estimate of the experience of taxpayers who dropped out 

of the study (an issue that is discussed in more detail 

later). 

CBO placed no other restrictions on the sample of taxpaying units that it considered. Taxpayers whose family 

structure changed, whether through marriage, divorce, or 

having children, were kept in the sample. Similarly, CBO 

retained taxpayers who reached retirement age and left 

the workforce as well as taxpayers who entered the workforce for the first time. Effectively, life-cycle transitions 

were considered part of a set of events that caused income 

to change over time. As a result, taxpayers who experienced such events were treated no differently than taxpayers who received a pay increase or realized a capital 

gain.10

Weighting

Weighting is a statistical tool that helps ensure that estimates derived from a sample can be “generalized”—

deemed to apply—to an entire population. In the case of 

the CWHS, which is a simple random sample, CBO gave 

each return an equal weight because every tax return has 

an equal chance of being included in the sample. Weighting was more complex for the PSID data because of that 

sample’s design. Families and individuals have different 

probabilities of being included in the PSID sample, so 

the survey includes weights that reflect those probabilities. The weights used in the PSID also adjust for differences in rates of response among the groups; thus, the 

weight for a family is different in every year of the sample. 

For its analysis, CBO applied to every year of a period the 

PSID’s longitudinal weight for a family in the last year of 

that period.11

Definition of Income 

The same definitions of income were used throughout 

the period that CBO examined. The income measure was 

as broad as possible, given the available data, but falls 

short of being comprehensive. For the tax-return data, income consists of wages and salaries, business income, taxable and tax-exempt interest, dividends, realized capital 

gains, unemployment compensation, rent and royalty income, taxable pensions, and other income reported on 

tax returns. The measure excludes Social Security benefits 

(because not all recipients are required to report that income on their tax returns); other untaxed income, such as 

TANF payments (because that information is not captured on a tax return); and in-kind transfers, such as food 

stamps.

CBO applied two definitions of income to the PSID 

data: first, taxable income, which includes wages, business income, interest, dividends, pension income, unemployment compensation, and rental income; and second, 

total income, which equals taxable income plus Social Security benefits and income from several cash transfer programs. Taxable income is the measure most analogous to 

that used for the CWHS sample, so CBO used it for the 

most part to facilitate comparisons between the two data 

sets. Total income is a broader measure that more closely 

approximates overall economic resources.

Measure of Tax Liability

For this analysis, CBO used a narrow measure that focused on federal individual income taxes. (The measure 

was intended to simplify the analysis, but in future studies, CBO may broaden the scope of its analysis to include 

other taxes.) Individual income taxes are the best choice 

for examining multiyear effective tax rates because they 

are the largest source of federal revenues, vary the most 

directly with income, and are most readily attributed to 

10. Taxpayers who go through a major life-cycle change may have 

more-volatile income and tax payments than taxpayers who are 

not undergoing such transitions. As a result, their presence in the 

sample may increase the difference between the results of annual 

and longitudinal income and tax measures. In practice, however, 

their inclusion does not appear to be central to CBO’s results. 

Table B-4 shows how two life-cycle-related restrictions affect the 

sample. The first limits the analysis to taxpayers who neither 

marry nor divorce during the study period. The second constrains 

it to taxpayers aged 25 to 60 during the period. Those restrictions 

had little effect on the differences between the results of annual 

and longitudinal income measures.

11. Applying the longitudinal individual—rather than family—

weight made little qualitative difference to the study’s results. For a 

more detailed discussion of the PSID’s weights, see Martha S. 

Hill, The Panel Study of Income Dynamics: A User’s Guide (Newbury Park, Calif.: Sage Publications, 1992). 
8 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

individual taxpayers. Some other taxes, such as payroll 

taxes, would also be relatively straightforward to study. 

In contrast, excise taxes would be difficult to include in 

CBO’s analytical framework because few data exist on

individuals’ consumption of specific goods over long 

periods.

To better assess changes in income separately from 

changes in tax law, CBO used a constant-law measure of 

tax liability: the liability that a taxpaying unit would have 

incurred if 2000 tax law had applied in the years being 

examined. CBO thus inflated incomes to 2000 levels and 

incorporated in its simulations the assumption that the 

2000 tax code was in place.12 Calculations of taxes using 

data from the PSID are necessarily more approximate because the survey collects no information about itemized 

deductions and capital gains.13

Construction of Multiyear Measures

For each taxpayer in the data, CBO constructed annual 

and multiyear measures of income and taxes. Annual 

measures are simply the values for each year that the data 

covered. Multiyear, or longitudinal, measures apply to 

longer periods of various lengths and are the average of 

annual incomes or taxes over the relevant period. Thus, 

for example, three-year income in CBO’s analysis is onethird of total real (inflation-adjusted) income over a 

three-year period. A taxpayer who had income of 

$30,000 in year one and $60,000 in years two and three 

would have a three-year income of $50,000.

To compute an average effective tax rate, CBO took 

multiyear measures of taxes, averaged people’s tax payments over multiple years, and divided by their average 

income. Suppose that the taxpayer who had a three-year 

income of $50,000 had tax liability of $3,000 in year one 

and $12,000 in years two and three. He or she would 

have a three-year tax liability of $9,000. Dividing that 

three-year average liability ($9,000) by three-year income 

($50,000) yields a three-year effective tax rate of 18 percent. That multiyear rate represents the share of the taxpayer’s total income that he or she would have paid in 

taxes, given the pattern of income, had 2000 law been in 

effect over the entire three-year period.

Other methods would generate different longitudinal effective tax rates. One alternative would compute the longitudinal rate by averaging the rates from each year. That 

method would weight the tax rate in each year equally—

even though the tax rate in years when the person’s income was higher would contribute more to the multiyear 

tax burden. Because of the progressivity of the tax system, 

that alternative method would generally make longitudinal tax rates appear lower than the rates generated by the 

measure used in this analysis.

Another approach would compute the longitudinal rate 

by estimating what taxes would have been had the person 

received his or her average income in every year of the period. Clearly, that method would not capture the interactions between the level of annual income and taxes. Because income taxes are assessed annually and income is 

subject to a schedule of increasing rates, taxpayers whose 

income is volatile generally face higher effective rates 

than those whose income is the same on average but more 

stable. 

Definition of Income Categories

CBO’s analysis assigned taxpayers to quintiles on the 

basis of their income, measured over single years or multiyear periods. The process for the PSID was straightforward because the data represent the entire population. 

Thus, for each year, analysts ranked all taxpaying units in 

the PSID cross section by income and divided the units 

into quintiles of equal size.

Calculating quintiles for the CWHS was more complicated.14 Because the data exclude families who do not file 

12. Incomes were adjusted for inflation through the consumer price 

index research series (CPI-U-RS).

13. Several simplifying assumptions were made to calculate taxes from 

the PSID data. First, the tax base was considered to comprise 

wages, business income, interest, dividends, pensions, unemployment compensation, and rental income. Second, all filers were 

assumed to take the standard deduction. Third, legally married 

couples in general were assumed to file a joint return and unmarried people to file either a single or a head of household return. 

(The exception was unmarried couples who lived together. The 

PSID treats those couples as married and does not report all 

income separately for them, so CBO treated them as filing a joint 

return.) Finally, if a family had children residing with their parents, the children were assumed to be qualifying children for purposes of the dependent exemption, head of household status, the 

earned income credit, and, if they were under 17 years old, the 

child credit. For a more detailed discussion of the issues in estimating taxes from the PSID, see Barbara A. Butrica and Richard V. Burkhauser, Estimating Federal Income Tax Burdens for Panel 

Study of Income Dynamics (PSID) Families Using the National 

Bureau of Economic Research TAXSIM Model, Aging Studies Program Paper No. 12 (Maxwell Center for Demography and Economics of Aging, Syracuse University, December 1997). 
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 9

tax returns and the sample has experienced disproportionate “attrition” (departure from the sample as years 

passed) among lower-income taxpayers, the CWHS does 

not represent the full population (see Box 2). As a result, 

if CBO had constructed quintiles by dividing the CWHS 

sample into fifths of equal size, the income ranges of 

those quintiles would have differed from the ranges of 

quintiles created by dividing a representative sample into 

fifths. (For example, the bottom fifth of people who filed 

tax returns in consecutive years have substantially higher 

incomes than the bottom fifth of the entire population.) 

The misalignment of income ranges between the two sets 

of quintiles would have made it difficult to generalize results from a given CWHS quintile to the same quintile of 

the full population. 

To address the CWHS’s exclusion of families who do not 

file returns, CBO used data from a representative crosssection of the entire population to divide the tax-return 

sample into quintiles. Information from the entire taxfiling population in a given year was first combined with 

data for the same year from the Current Population Survey, forming a cross section that represented the entire 

population. The taxpaying units in the cross section were 

then ranked by income and divided into five equal-sized 

groups. (The ranking incorporated the assumption that 

all nonfilers fell into the lowest income quintile.) CBO 

then used the income range associated with each population quintile to assign members of the CWHS sample to 

income groups (see Appendix C). For example, if the 

lowest population-based quintile had income ranging 

from zero to $15,000, any CWHS taxpaying unit with 

income in that range would be assigned to the lowest 

quintile. The “quintiles” that resulted from that procedure did not each contain one-fifth of the CWHS sample; rather, they contained the members of the sample 

whose level of income put them in that particular population-based fifth. At the same time, the procedure resulted 

in too few taxpaying units to allow meaningful estimates 

for the lowest quintile. Consequently, CBO reports no 

findings for that income category based on the CWHS 

data.

Defining income quintiles based on longitudinal income 

is difficult because multiyear income can only be determined for a subset of the population—taxpayers who appear in every year of the data. That limitation makes it 

impossible to calculate the longitudinal income ranges for 

each fifth of the entire population. Instead, CBO created 

longitudinal quintiles that had the same average number 

of taxpayers as the average of the cross-sectional quintiles 

with which they were being compared (the average annual measure). That procedure ensured that observed differences between annual and longitudinal income and 

taxes for a particular quintile derived solely from changing the measurement period and not from changes in the 

number of taxpayers in each quintile.

Comparison of Annual and Longitudinal

Distributions

CBO averaged values from all the cross sections in a period into a single measure, which it then compared with a 

longitudinal measure of income and taxes over the same 

span. That average cross-sectional measure provides a 

suitable basis for comparison because it covers the same 

period that the longitudinal measure covers, dividing the 

same total income and total taxes among the same group 

of taxpayers. An alternative to the average of annual measures would be to compare the longitudinal results with a 

single cross section. How to choose that comparison year, 

however, is not obvious, and whatever choice was made 

could influence the study’s results. (Differences between 

the longitudinal measure and any one cross section would 

reflect the shifting of the cross-sectional distribution over 

time in addition to the length of time over which income 

and taxes were measured.)

For this analysis, the average annual measure was compared with two different longitudinal measures. The first, 

longitudinal with longitudinal ranking, combined income and taxes over multiple years into one longitudinal 

metric for each taxpaying unit and arrayed those units 

into quintiles on the basis of that metric. Essentially, the 

measure substitutes a multiyear time horizon for a oneyear span, showing distributional results under the longer 

period. 

The second longitudinal measure, longitudinal with 

first-year ranking, also calculates income and taxes on a 

multiyear basis, but it arrays taxpaying units into quin14. In contrast to CBO’s historical cross-sectional method, this analysis ranks taxpayers by their level of income without adjusting for 

the size of the taxpaying unit. Moreover, in this study, income 

quintiles are structured to have equal numbers of taxpaying units 

rather than equal numbers of people. Both of those choices reflect 

the fact that information on tax returns does not allow precise 

identification of the size of an economic unit.
10 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Box 2.

Sampling Issues Associated with Longitudinal Data

Cross-sectional surveys draw a sample of people that 

represents the entire population, and they collect information about those people at a single point in 

time. By comparison, longitudinal, or panel, studies 

begin with a cross-sectional sample and then follow 

those people over an extended period, collecting information about them at regular intervals. On the 

one hand, the multiyear aspect of such research 

makes longitudinal data valuable for examining dynamic processes or discerning cause-and-effect relationships. On the other hand, the extended nature of 

panel studies makes it more difficult to maintain a 

sample that represents the entire population.

One way in which a panel may become unrepresentative is through attrition—the disappearance of 

some people from the panel during some years. If 

participants who drop out differ fundamentally from 

those who do not, their omission may make the 

panel unrepresentative of the full population and 

bias results based on the panel. Statistical procedures 

can lessen the effects of attrition, but the problem always afflicts analyses that use panel data.

The University of Michigan’s Panel Study of Income 

Dynamics (PSID), on which the Congressional Budget Office (CBO) based a substantial portion of this 

analysis of effective tax rates, reflects substantial attrition, even though study staff try to maintain contact 

with all of the families in the sample. About half of 

the original families in the PSID left the survey during its first 20 years—some moved and could not be 

located, others died, and still others declined to participate any longer.

Several studies have evaluated attrition in the PSID 

and found that it is concentrated among lowerincome respondents.1

 Yet despite the loss of people 

from the panel, the distribution of income among 

the PSID’s respondents is similar to the income distribution in the Bureau of the Census’s March Current Population Survey for various years—which 

suggests that the PSID has remained roughly representative. Two factors account for that finding. First, 

the PSID contains attrition-adjusted weights that are 

intended to partially correct for different rates of attrition among the various demographic groups. 

Those adjustments are small but generally improve 

the survey’s representativeness. Second, differences in 

the initial characteristics of the families who leave the 

study and the families who stay have faded over time, 

allowing the survivors on some dimensions to adequately represent those who have left. 

Yet even if cross-sectional data gathered through the 

PSID remain roughly representative of the larger 

population, the pattern of changes in income—the 

focus of CBO’s analysis—may differ systematically 

between those who remained in the sample and 

those who left it. No external benchmark exists 

against which that pattern might be compared. One 

way to measure the possible bias arising from attrition is to compare longitudinal and annual income 

of PSID respondents who remain in the sample for 

different lengths of time. Such a comparison shows 

that patterns are similar whether a respondent is required to be in the sample for nine years or only for 

three and suggests that attrition does not unduly influence results from the PSID (see Tables B-5 and 

B-6). 

Attrition is a bigger problem in the Internal Revenue 

Service’s (IRS’s) tax data than in the PSID. Although 

most Americans file tax returns every year, many 

people move into and out of the tax system as their 

income rises and falls. For example, the proportion 

of taxpayers who appear in data for 1987 from the 

1. John Fitzgerald, Peter Gottschalk, and Robert Moffitt, “An 

Analysis of Sample Attrition in Panel Data: The Michigan 

Panel Study of Income Dynamics,” Journal of Human 

Resources, vol. 33, no. 2 (Spring 1998); Lee A. Lillard and 

Constantijn W. A. Panis, “Panel Attrition from the Panel 

Study of Income Dynamics: Household Income, Marital 

Status, and Mortality,” Journal of Human Resources, vol. 33, 

no. 2 (Spring 1998); and Elena Gouskova and Robert F. 

Schoeni, “Comparing Estimates of Family Income in the 

Panel Study of Income Dynamics and March Current Population Survey, 1968-1999” (2002), available at http://

psidonline.isr.umich.edu/Guide/Quality/psid_vs_cps.pdf.
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 11

Box 2.

Continued

IRS’s Continuous Work History Sample (CWHS) 

and who also appear in the file for each of the subsequent 13 years is just 56 percent. People who are 

missing for one or more years may, among other reasons, have died, married and filed joint returns under 

their spouse’s Social Security number, or had income 

below the level requiring a tax return. (Appendix A 

discusses attrition in the CWHS in more detail.) Regardless of the reason for their absence, those taxpayers are likely to differ in important ways from people 

who file a return every year, and their omission from 

a longitudinal analysis may bias its findings. 

People who have low income are underrepresented in 

the CWHS. Their small numbers imply that conclusions about them that are based on the CWHS data 

may be unreliable—not only because of the small 

samples but also because low-income people who appear in multiple years may show up only because 

they are unique in some ways. (Specifically, their 

low-income status is more likely to be temporary 

than that of people who file intermittently.) The absence of nonfilers in the CWHS further means that 

some people who have the most volatile income may 

not be part of the sample. For example, in a study 

covering a multiyear period, someone who entered 

the workforce during that time would not appear in 

the study’s initial years, when they were not employed. And someone who retired might not appear 

in later years when relying primarily on nontaxable 

benefits from Social Security.

Attrition does appear to affect comparisons of longitudinal and cross-sectional measures based on the 

CWHS, especially comparisons for the second quintile, or fifth, of the income distribution (see Tables 

B-1 and B-3). CBO’s analysis covered 1987 to 2000. 

Restricting the study to returns that appear in each 

year’s data over the period results in three-year longitudinal income, measured using the CWHS data, 

that is approximately 7 percent to 9 percent above 

average annual income; restricting the analysis to returns that appear in any three-year period leads to 

three-year longitudinal income that is 3 percent to 

4 percent higher. Effective tax rates follow a similar 

pattern: the difference between longitudinal and 

cross-sectional rates appears greater when the 

CWHS is restricted to returns that appear in each of 

the 14 years. Thus, if an analysis requires that sample 

members’ returns appear in every year of the data, 

the study’s results for the second quintile may overstate the differences between longitudinal and annual income and tax rates.

However, comparisons of annual and longitudinal 

income that use the tax data are qualitatively similar 

to comparisons that use the PSID. That similarity 

suggests that conclusions drawn from the tax data 

may be generally valid, despite the attrition it sustains, if the PSID has in fact remained representative. 

To further test how attrition might be biasing results, 

CBO simulated in the PSID the attrition that occurs 

in the CWHS (see Appendix A for details). For likely 

filers, differences between cross-sectional and longitudinal income and taxes were comparable for the 

full population, which suggests that results outside of 

the lowest quintile might not be driven by attrition 

and that conclusions drawn from the tax data may be 

generally valid.

Another reason that a sample panel may become unrepresentative is that the underlying population 

changes over time while the panel remains constant. 

The sampling design of the CWHS—a simple random sample based on Social Security numbers—ensures that as new people enter the filing population, 

they will automatically be included in the panel so 

that the CWHS will reflect that population. The 

PSID’s design requires that it follow all descendants 

of its initial sample, thus automatically capturing 

many aspects of shifts in population. The PSID’s 

original design, however, did not include a method 

to account for new immigrants, and people who 

came to the United States after the initial sample was 

drawn in 1968 are not included. As a result, the 

PSID over time has become less and less representative of the entire population, although changes in the 

late 1990s added a sample of recent immigrants.
12 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

tiles on the basis of their income in the first year of the 

measurement period. This second metric shows the income and taxes that accrue to a fixed cross-sectional quintile over multiple years, as taxpayers’ income and associated taxes change from one year to the next. By keeping 

taxpayers in their initial quintile, the measure provides a 

rough indicator of how likely taxpayers are to be “misclassified” in a cross section.

Limitations of the Analysis

Several shortcomings in the available data limit the conclusions that can be drawn from CBO’s analysis. Most 

important is the issue of attrition. Both the CWHS and 

the PSID have suffered substantial attrition over time, 

which may bias results based on them in unknown ways. 

However, prior research has shown that despite attrition, 

the PSID remains representative at the cross-sectional 

level, and CBO’s results from the tax data are similar to 

those from the PSID. Together, that evidence suggests 

that the attrition bias might not be severe.

A second major limitation involves the length of time 

that the analysis covered. The longest period over which 

income was measured was 14 years, a span that CBO 

considered long enough to mitigate the effects of transitory changes in people’s income (such as realized capital 

gains or spells of unemployment). Even a 14-year period, 

however, does not fully capture income and tax liabilities 

over a person’s lifetime. The youngest taxpayers will appear in the data only for their middle years, when their 

income is relatively low. Middle-aged taxpayers will generally show high earnings because they are in their peak 

income years. Other taxpayers may only appear during 

their retirement years, and their pensions and income 

may greatly understate their lifetime income. Unfortunately, no better measures currently exist.

A final cautionary note applies. The distributional methodology used in this analysis differs in some important respects from the methodology that CBO has used in other 

analyses of effective tax rates (see Table 1 on page 18). 

That earlier methodology, which remains CBO’s primary 

approach to distributional analysis, relies on a combination of detailed income and tax data from tax returns 

and, from the Current Population Survey, information 

about the family relationships of different taxpaying units 

and the extent of their nontaxable income. No source of 

longitudinal data contains the same range of information, 

so this analysis cannot replicate the kind of results CBO’s 

usual methodology provides. The findings reported below are thus not fully comparable with those from CBO’s 

other distributional analyses. Within the limitations discussed above, however, the general conclusions should be 

valid.

Distribution of Annual and

Longitudinal Income and Taxes

In this analysis, CBO examined income distributions and 

tax rates over several periods of varying lengths. A major 

finding is that longitudinal measures over such periods 

show that income and taxes are more evenly distributed 

among taxpaying units than annual measures show them 

to be. The largest difference between the two measures 

appears in the lower-income quintiles. Moreover, the 

longer the time frame used in longitudinal measurement, 

the more even the income distribution becomes.

During the three-year period from 1993 to 1995, the distribution of income and taxes as measured annually 

changed little (see Table 2 on page 19). For the middle 

three quintiles, incomes fluctuated around their respective averages over the three years. Income in the highest 

quintile was flat from 1993 to 1994; then, in 1995, it 

jumped by more than 5 percent—which pulled up the 

overall average. Also fluctuating within a fairly narrow 

range were effective tax rates for the middle three quintiles during the period. And in 1995, when income in the 

top quintile rose, the effective tax rate increased as well. 

As a result, the average annual distribution of income and 

taxes over the period looked much like the distribution in 

any one year. (Box 3 discusses the income measures used 

in Table 2 on page 19.)

At the bottom of the income distribution, income measured longitudinally was higher than average annual income; by comparison, in the highest quintile, longitudinal income was lower. For example, longitudinal income 

for the second quintile (the lowest quintile was excluded 

from the analysis) over the three years was $13,650—

7 percent higher than the annual average of $12,750 over 

the same three years. In contrast, longitudinal income for 

the top quintile—$115,550—was 1 percent below the 

annual average of $116,750. In each yearly cross section, 

the lower income quintiles contained people with temporarily low income, and the top quintile contained some 

individuals with temporarily high income. Measuring income over three years moderates those temporary effects, 

raising incomes at the bottom and paring them back at 

the top. 
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 13

Changes in the share of pretax income for each quintile 

when measured longitudinally mirrored changes in income levels, rising in the lower quintiles and falling in the 

top. Even though longitudinal income is noticeably 

higher at the bottom of the distribution, that quintile’s 

small share of it means that a large percentage increase in 

income has little effect on overall income shares. For example, the second quintile received 2.3 percent of average 

annual income and 2.5 percent of longitudinal income. 

By contrast, the share of longitudinal income received by 

the highest quintile was close to 1 percentage point 

smaller than its share of average annual income.

The pattern of effective individual income tax rates was 

related to that of income. The biggest difference between 

average annual and longitudinal rates was in the second 

quintile, for which the changes in income were largest. 

Because longitudinal income for that group was higher 

and progressive income tax rates rise as income increases, 

the associated taxes were also higher. 

Extending the analysis over a longer period revealed similar but larger effects (see Table 3 on page 21 and Table 4 

on page 23). Over the seven years from 1991 to 1997, 

longitudinal income for the second quintile was 16 percent higher than the average of annual incomes over the 

same period. Measuring income over the 14 years (1987 

to 2000) for which data were available showed longitudinal income exceeding the average annual measure by 

26 percent in the second quintile. The differences were 

smaller for the middle and fourth quintiles; for the highest quintile, longitudinal income was less than average 

annual income. Again, differences in the shares of income 

under the two measures mirrored the differences in levels 

of income. The major effect of lengthening the measurement period was to further narrow the differences between quintiles in levels of income.

Tax rates for the middle three quintiles were higher under 

the longitudinal measures than under the annual measures, reflecting the quintiles’ higher levels of income. In 

the top income group, longitudinal tax rates were either 

unchanged from or slightly higher than annually measured rates, despite the lower longitudinal income for that 

group. Under the annual measures, capital gains for the 

top quintile made up a larger share of income than they 

accounted for under the longitudinal measure. Since 

gains are taxed at lower rates than those that apply to ordinary income, they reduce the overall effective tax rate to 

a greater extent under the annual measures than under 

the longitudinal ones.

Analysis of income and taxes using data from the Panel 

Study of Income Dynamics also found that distributions 

were more even under longitudinal measures than under 

annual measures (see Box 4). Examining different periods 

Box 3.

Distributional Measures

This analysis uses several different metrics to show 

the distribution of income and taxes.

Annual, or cross-sectional, measures are one-year snapshots of the distribution of income and taxes. Families are grouped into quintiles (fifths of the distribution) on the basis of that one year’s income.

Average annual measures combine several annual 

snapshots into one measure. For each quintile, annual income and taxes over several years are averaged 

together, even though the quintiles may contain different people in each year.

Longitudinal measures cover multiple years. Income 

and taxes over the multiyear period are averaged together into one longitudinal metric for each family, 

which is then used to rank families into quintiles. 

The longitudinal measure essentially substitutes a 

multiyear measurement period for a one-year period. 

Longitudinal measures with first-year ranking are a hybrid of the cross-sectional and longitudinal measures. 

Such metrics rank taxpayers by their income in the 

first year (to define quintiles) but then average each 

taxpayer’s income and taxes over the multiyear period. The measure thus shows the income and taxes 

that accrue to a particular cross-sectional quintile 

over the period.
14 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Box 4.

Measuring Income Longitudinally Using the 

Panel Study of Income Dynamics

The Internal Revenue Service’s Continuous Work 

History Sample (CWHS) is not well suited to examining the income of lower-income families, many of 

whom are not required to file tax returns in some 

years. By comparison, the University of Michigan’s 

Panel Study of Income Dynamics (PSID) avoids 

some of the pitfalls inherent in the tax data, making 

it a superior source of information for examining the 

financial well-being of lower-income families.

As part of its analysis, the Congressional Budget Office (CBO) compared annual and longitudinal income from 1987 to 1995, using a measure of taxable 

income based on the CWHS and measures of taxable 

income and total income based on the PSID. The 

same general pattern appeared in both the CWHS 

and PSID measures: income measured longitudinally 

was more evenly distributed among quintiles than 

was income measured annually. Longitudinal income was substantially higher than annual income 

among families in the lower quintiles and slightly 

lower than annual income for families in the highest 

quintile (see the figure below).

Varying the definition of income produced substantially different results in the lowest quintile. Taxable 

income is very volatile for that income group; consequently, when measured longitudinally, it is almost 

double the amount of average annual taxable income. In contrast, total income measured longitudinally is only 25 percent higher than total income 

measured on an annual basis. Average annual taxable 

income among families in the bottom quintile is very 

low, averaging $1,650 over the nine-year period, so 

small changes in the dollar value of taxable income 

for that group produce large percentage changes. Because the bottom quintile relies more heavily on income from nontaxable sources, total income for that 

group varies less than does taxable income.

For the upper four quintiles, the three measures 

show similar differences between annual and longitudinal income regardless of whether data from the 

CWHS or PSID are used and whether total or taxable income is examined. Upper-income families are 

fully represented in both data sets, and they receive 

relatively little income from nontaxable sources. As a 

result, the choice of data set and income measure has 

little effect on the relationship between annual and 

longitudinal income and taxes for such families.

Difference Between Annual and Longitudinal Income

Under Different Definitions of Income, 1987 to 1995 (Percent)

Lowest Quintile Second Quintile Middle Quintile Fourth Quintile Highest Quintile

-20

0

20

40

60

80

100

CWHS Data PSID Taxable Income PSID Total Income
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 15

or varying the restrictions applied to the sample yielded 

similar conclusions about the relative distribution of annual and longitudinal income and taxes.15

Distributional Effects of

Illustrative Policy Changes

Under Longitudinal Measures

Changes in tax law affect taxpayers at different points in 

the income distribution in varying ways. Because people’s 

financial circumstances fluctuate from year to year, 

changes in policy will affect a particular taxpaying unit 

differently over time. The distributional impact of a policy measured longitudinally will look somewhat different 

from the policy’s effect as measured on an annual basis. 

CBO’s analysis examined the distributional effects of 

three illustrative policy changes: reducing the top two individual income tax rates, doubling the value of the child 

credit, and making the child credit fully refundable. The 

effects of the first two policies were simulated using data 

from the CWHS because those policies would primarily 

affect middle- to high-income families.16 The third policy would affect mainly low-income families; therefore, 

CBO used data from the PSID for that simulation.

To assess the impact of the changes in policy over 10 

years, CBO used three different measures of the distribution of income: average annual, longitudinal, and longitudinal with annual, or first-year, ranking (see Box 3 on 

page 13). For each policy, CBO compared the tax liabilities that each measure generated with a fixed base that reflected tax law in 2000. Comparing the results of the 

three measures demonstrated the effect of moving from 

an annual to a longitudinal assessment.

B The average annual measure combined the distributional effects for 10 different years measured separately. For each year, CBO ranked taxpayers into 

quintiles on the basis of that year’s income; the effects 

of the illustrative policy change were then simulated 

and allocated to those cross-sectional quintiles. (That 

method is similar to approaches that are currently used 

to estimate the distributional effects of changes in tax 

policy.)

B The longitudinal measure showed the 10-year change 

in taxes, assigning taxpayers to their multiyear income 

quintile. That approach substituted a 10-year time 

frame for the annual period that is currently used and 

showed how tax changes affect the tax burdens of each 

income class.

B The third method, a longitudinal measure with firstyear ranking, arrayed taxpayers into quintiles by their 

income in the first year but calculated their income 

and taxes for the full 10-year period. That approach 

measures how the policy changes affect a fixed crosssectional income quintile over 10 years.

Reduce the Top Two Individual Income Tax Rates

The first illustrative scenario would reduce the top two 

tax rates under 2000 law—36 percent and 39.6 percent—to 31 percent. Those top rates, which were created 

by the Omnibus Budget Reconciliation Act of 1993 

(OBRA-93), apply to the highest-income taxpayers. In 

2000, the 36 percent rate applied to taxable income 

above $132,600 for single taxpayers and above $161,450 

for married taxpayers filing a joint return. The 39.6 percent rate applied to both single and joint filers who had 

income above $288,350. This scenario would undo the 

changes made by OBRA-93, taxing income previously 

taxed at 36 percent or 39.6 percent at the new maximum 

rate of 31 percent.

The cross-sectional analysis of that change shows that all 

of its effects are concentrated in the top of the income 

distribution (see Table 5 on page 25). According to the 

average annual measure, the effective tax rate would 

change only for the highest quintile, dropping by 1 percentage point over 10 years. Taxpayers in the top 1 percent of the income distribution would see a reduction of 

3.2 percentage points in their effective tax rate.

If taxpayers are ranked by their income in the first year of 

the measurement period and then income and tax 

changes are measured longitudinally, a somewhat differ15. Appendix B compares longitudinal and average annual distributions for each three- and seven-year period from 1987 to 2000 for 

taxpayers who appear in all 14 years of the data. Results are quite 

similar for all of those periods. The appendix also presents results 

for each three-year period when the restriction that a taxpayer 

appear in every year of the 14-year period is dropped. The differences between longitudinal and average annual income and taxes 

appear similar; for the lower quintiles, however, the difference in 

income between the measures is smaller.

16. In a separate analysis, the PSID data were used in simulating the 

first two policies and produced qualitatively similar results.
16 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

ent picture emerges (see the second column in the table). 

The scenario’s effects would still be highly concentrated 

but at the same time slightly more dispersed. Again, the 

effective tax rate would change only for taxpayers in the 

highest quintile in the first year, but some people in the 

lower quintiles also would be affected by the lower 

rates—for example, 0.4 percent of taxpayers in the fourth 

quintile would face a lower tax rate. In addition, some 

people who had lower income in the base year would 

have higher income in subsequent years and benefit from 

the tax change at that point.

Measuring the tax scenario’s effects longitudinally would 

result in no change in effective rates outside of the top 

quintile (see the third column in the table), although a 

few taxpayers outside of that income group would face reduced rates. Relative to the cross-sectional measure, a 

smaller share of taxpayers in the top percentile would be 

affected by this rate reduction policy under the longitudinal measure. But there is little difference between the two 

measures in the share of filers in the top 5 percent who 

would feel an effect, implying movement within the distribution’s top few percentiles.

Many more people would be affected by the reduction in 

rates in any one year than would be affected in the average year. Over the 10-year period, the reduction would 

affect an average of 2.4 percent of taxpayers. But 6 percent would see a drop in their effective tax rate in at least 

one year, implying significant movement the falling rates. 

At the same time, the overall distribution of effects, measured by the change in the effective tax rate, would show 

smaller changes. That lesser impact would largely result 

because people who moved briefly into the affected income range would generally see a smaller drop in rates 

than those who were more permanently in that range. 

Doubling the Child Credit

A second tax policy scenario would increase the child 

credit from $500 to $1,000 for each child aged 17 or 

younger in a family. As under 2000 law, the credit would 

begin to phase out when a single taxpayer’s income exceeded $75,000 and a married taxpayer’s income exceeded $110,000. The credit would not be refundable—

that is, its value could be no greater than the taxpayer’s income tax liability. Thus, taxpayers who owed little or no 

income tax before applying the credit would be little affected by it.

Under an average annual measure, the distributional effects of doubling the child credit would be concentrated 

in the top three quintiles (see Table 6 on page 26). Taxpayers at either end of the income distribution (that is, 

the bottom two quintiles and the top percentiles) would 

be less likely to be affected by the change than would taxpayers in the middle of the distribution. Taxpayers with 

lower income do not owe enough income tax to take full 

advantage of the credit, whereas taxpayers with the highest income fall above the phaseout range and hence cannot claim the credit.

Measuring the policy’s impact longitudinally shows a distribution of effects that is similar to the distribution under annual measures, with the biggest change in rates in 

the middle and fourth quintiles. Under the longitudinal 

measures, the policy change would affect more taxpayers 

at the top and bottom of the income distribution than 

would be affected under the cross-sectional measure. For 

example, under the average annual measure, only 3.2 percent of taxpayers in the second quintile would receive the 

higher credit, compared with 8.6 percent under the longitudinal measure. As their income rose and fell, both 

low-income and the highest-income taxpayers would 

move into and out of the income range in which they 

could receive the credit. The effects of the illustrative policy appear most dispersed when measured longitudinally 

with first-year ranking.

Many more taxpayers would receive the credit in at least 

one year of the period than would receive it in the average 

year. Just under one-third of filers would get the credit in 

the average year; by contrast, more than half would receive it in at least one year. Income dynamics partially explain that outcome. In any given year, many taxpayers 

would have income that was too high or too low to receive the credit. But over a multiyear period, fluctuations 

in income would move them into the range in which the 

credit would affect their tax liability. Demographic 

changes would also contribute to the credit’s being more 

widely distributed among the quintiles. Over the 10-year 

window, some families would have newborn children, 

making them newly eligible for the credit, whereas other 

families would see their children turn 18 and thus no 

longer qualify for it.

Under the average annual measure, only 3 percent of taxpayers in the second quintile would receive the higher 

credit, compared with 31 percent who would receive it in 

at least one year under the longitudinal measure. Yet that 
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 17

difference may overstate the degree to which those taxpayers would experience a lower effective tax rate, because 

they would benefit only in years in which their income 

was high enough that they would owe income tax. Only 

9 percent of taxpayers in the second longitudinal quintile 

would receive the credit in the average year, which implies that the average recipient in that quintile would get 

the credit in only three of the 10 years possible. In contrast, recipients in the third longitudinal quintile would 

receive the credit on average in five of the 10 years, while 

those in the fourth and fifth quintiles would get the credit 

in nearly seven years of the period.

Make the Child Credit Fully Refundable

Under the tax laws prevailing in 2000, the child credit is 

not refundable, so families that have no income tax liability cannot receive it. This third policy scenario would 

make the $500 child credit fully refundable, allowing 

such families—those with no earnings or income tax liability—to claim the full credit.17

Analysis of that policy using an average annual measure 

showed that the policy’s effects would be heavily concentrated in the bottom of the income distribution (see Table 

7 on page 27). The change would lower the effective tax 

rate in the bottom quintile by 2.8 percentage points; it 

would cut the effective rate in the second and middle 

quintiles by 0.6 and 0.1 percentage points, respectively. 

Some families in the fourth quintile who had very low 

levels of taxable income compared with their total income 

would also be affected by the change, although not by 

enough to change the quintile’s effective tax rate.

Under the longitudinal measures, the distribution of the 

policy change’s effects among the quintiles was similar to 

that under the average annual measure but somewhat 

more dispersed. The effective rate as measured using any 

of the three methods would change by more than a percentage point in the bottom quintile, by about half a percentage point in the second quintile, by one-tenth of a 

percentage point in the middle quintile, and not at all in 

the fourth and fifth quintiles. Under the longitudinal 

measures, some families in the fourth and highest quintiles would be affected by the policy because they may experience spells of unemployment, businesses losses, or 

some other decline in their income. Those circumstances 

might push their income below the level at which they 

would owe federal income taxes, allowing them to claim 

the credit because of its refundability.

The change in the effective rate for the lowest quintile is 

smaller when measured longitudinally than when measured annually. Lower-income families would receive 

about the same amount of credit under both longitudinal 

measures. However, because their longitudinal income 

would be much higher than their annual income, the tax 

reduction would represent a smaller percentage of their 

income under the longitudinal measures.

Many more families (over 16 percent) would receive the 

credit in at least one year than would receive it in the average year (fewer than 7 percent). As with the previous 

policy scenario, both fluctuations in income and changes 

in the families’ composition would cause different families to benefit from the credit over time.

Conclusion

For each of the illustrative tax policy scenarios, the effects 

of the change were distributed more broadly when they 

were assessed under the longitudinal measures than when 

evaluated under an annual metric. CBO’s results showed 

that income quintiles that were unaffected by a change in 

tax policy in a single year might be affected over longer 

periods, as income rose and fell. However, the choice of 

either a longitudinal or an annual metric to measure a potential policy’s effects would not dramatically shift the 

overall distribution of any of the changes CBO examined. 

Policies that when measured annually would primarily affect the upper or lower portions of the income distribution showed roughly similar patterns in the longitudinal 

distributions.

17. CBO used data from the PSID for this part of its analysis because 

the policy change would primarily affect low-income families.
18 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table 1.

Selected Methods for Distributional Analyses

Source: Congressional Budget Office.

a. Households are people who share a single housing unit, regardless of the relationships among them. Taxpayers who file dependent 

returns are considered part of the primary taxpaying unit and are not counted separately.

b. Includes Medicare and Medicaid benefits, employer-paid health insurance premiums, food stamps, school lunches and breakfasts, housing assistance, and energy assistance.

c. Social insurance taxes finance Social Security, Medicare, and federal unemployment insurance.

d. Adjusted by dividing by the square root of the household's size.

Source of the Data

(Internal Revenue Service) (University of Michigan) (Census Bureau)

Revenue Service)

Unit of Analysisa

Restrictions on the 

Sample in every year in every year

(Employer's share of social 

insurance taxes and corporate

income taxes)c

retirement plans

Taxes Included and 

Assumptions About 2000 tax law, borne by payers tax law, borne by payers law in each year, borne by payers

Their Incidence

owners of capital

employeesc

Time Horizon

Computing Income 

Quintiles taxpaying unit taxpaying unit for purposes of rankingd

numbers of taxpaying units numbers of taxpaying units numbers of people

on cross section of the on cross section of the on cross section of the

entire population entire population entire population

Quintile break points computed Quintile break points computed Quintile break points computed

No adjustments for size of the No adjustments for size of the Incomes adjusted by household size 

Income quintiles have equal Income quintiles have equal Income quintiles have equal 

Corporate income tax, borne by 

Social insurance taxes, borne by 

Excise taxes, borne by consumers

Multiyear periods up to 14 years Multiyear periods up to 10 years One year

In-kind benefitsb

Taxes paid by businesses 

Employee's contributions to 401(k)

Individual income tax under Individual income tax under 2000 Individual income tax under the

Retirement benefits Retirement benefits Cash transfer payments

Retirement benefits

Interest and dividends Interest and dividends Interest and dividends

Realized capital gains Cash transfer payments Realized capital gains

Income Definition Wages and salaries Wages and salaries Wages and salaries

Self-employment income Self-employment income Self-employment income

Rental income Rental income Rental income

Taxpaying unit Taxpaying unit Household

Taxpaying unit must appear Taxpaying unit must appear None

Continuous Work History Sample Panel Study of Income Dynamics Current Population Survey 

Statistics of Income (Internal 

Method Used in Prior CBO

Based on Tax Data Based on Survey Data Cross-Sectional Analyses

Methods Used in This Longitudinal/Cross-Sectional Analysis
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 19

Table 2.

Annual and Longitudinal Income and Effective Tax Rates, 1993 to 1995

Continued

1993 1994 1995

n.a. n.a. n.a. n.a. n.a. n.a.

12,650 12,600 12,950 12,750 13,650 7

24,200 24,200 24,600 24,350 25,050 3

41,800 42,050 42,600 42,150 42,550 1

114,150 114,600 121,500 116,750 115,550 -1

All Quintiles 60,400 60,900 64,100 61,800 61,800 0

n.a. n.a. n.a. n.a. n.a. n.a.

2.3 2.3 2.2 2.3 2.5 0.2

8.0 7.9 7.5 7.8 8.0 0.2

20.3 20.1 19.4 19.9 20.1 0.2

70.0 70.2 71.4 70.6 69.8 -0.8 ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 100.0 100.0 100.0 0

n.a. n.a. n.a. n.a. n.a. n.a.

-2.9 -3.1 -2.4 -2.8 -1.5 1.3

4.9 5.2 5.3 5.1 5.6 0.5

9.0 9.1 9.3 9.2 9.3 0.1

17.5 17.5 18.5 17.9 17.9 *

All Quintiles 14.4 14.5 15.4 14.8 14.8 0

n.a. n.a. n.a. n.a. n.a. n.a.

-0.5 -0.5 -0.4 -0.4 -0.3 0.1

2.7 2.8 2.6 2.7 3.1 0.4

12.7 12.7 11.7 12.4 12.7 0.3

85.1 85.0 86.1 85.4 84.6 -0.8 ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 100.0 100.0 100.0 0

Annual Measure Multiyear Measures, 1993 to 1995

Income Group Average Annual Longitudinal Differencea

Average Pretax Income (2000 dollars)

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Share of Pretax Income (Percent)

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Effective Individual Income Tax Rate (Percent)c

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Share of Individual Income Tax Liabilities (Percent)c

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile
20 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table 2.

Continued

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Notes: The analysis is limited to taxpaying units that appear in the CWHS in every year from 1987 to 2000. “Share” refers to a portion of the 

sample, not the overall population. Quintiles are defined using income ranges from the entire population, including nonfilers, in the 

applicable period and may not contain one-fifth of taxpaying units that appear in multiple years. Table C-1 shows the income ranges 

associated with each quintile. For the longitudinal measure, each quintile contains the same number of taxpayers that it does under 

the average annual measure with which it is being compared.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

Shares of income received and taxes paid by upper-income quintiles will appear higher in the sample than in the population because 

in the sample, lower-income families are underrepresented.

n.a. = not applicable; * = between -0.05 and 0.05.

a. The difference (longitudinal minus average annual) is calculated as a percentage for income and as percentage points for effective tax 

rates and for shares of pretax income, individual income tax liabilities, and taxpaying units.

b. Values are not shown (because of the small size of the sample) but are included in the totals.

c. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

1993 1994 1995

s

n.a. n.a. n.a. n.a. n.a. n.a.

11.0 11.1 11.1 11.1 11.1 0

20.1 19.8 19.6 19.8 19.8 0

29.4 29.2 29.1 29.2 29.2 0

37.0 37.3 37.7 37.3 37.3 0 ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 100.0 100.0 100.0 0

Annual Measure Multiyear Measures, 1993 to 1995

Income Group Average Annual Longitudinal Differencea

Share of Taxpaying Units (Percent)

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 21

Table 3.

Annual and Longitudinal Income and Effective Tax Rates, 1991 to 1997

Continued

Annual Measure

1991 1994 1997

n.a. n.a. n.a. n.a. n.a. n.a.

13,450 12,600 13,500 13,100 15,150 16

24,800 24,200 25,450 24,650 26,300 7

42,150 42,050 44,150 42,600 43,350 2

111,800 114,600 136,200 120,500 117,600 -2

All Quintiles 59,000 60,900 70,900 63,300 63,300 -1

n.a. n.a. n.a. n.a. n.a. n.a.

2.6 2.3 2.1 2.3 2.7 0.4

8.6 7.9 7.1 7.8 8.2 0.4

20.8 20.1 17.8 19.6 19.8 0.2

69.0 70.2 73.4 71.0 69.5 -1.5 ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 100.0 100.0 100.0 0

n.a. n.a. n.a. n.a. n.a. n.a.

-2.8 -3.1 -1.5 -2.5 * 2.5

5.2 5.2 5.9 5.3 6.1 0.8

9.0 9.1 9.7 9.3 9.5 0.2

17.3 17.5 18.8 18.0 18.0 *

All Quintiles 14.2 14.5 15.9 14.9 14.9 0

n.a. n.a. n.a. n.a. n.a. n.a.

-0.5 -0.5 -0.2 -0.4 * 0.4

3.1 2.8 2.6 2.7 3.3 0.6

13.3 12.7 10.8 12.2 12.6 0.4

84.2 85.0 86.8 85.5 84.0 -1.5 ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 100.0 100.0 100.0 0

Multiyear Measures, 1991 to 1997

Income Group Average Annual Longitudinal Differencea

Average Pretax Income (2000 dollars)

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Share of Pretax Income (Percent)

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Effective Individual Income Tax Rate (Percent)c

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Share of Individual Income Tax Liabilities (Percent)c

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile
22 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table 3.

Continued

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Notes: The analysis is limited to taxpaying units that appear in the CWHS in every year from 1987 to 2000. “Share” refers to a portion of the 

sample, not the overall population. Quintiles are defined using income ranges from the entire population, including nonfilers, in the 

applicable period and may not contain one-fifth of taxpaying units that appear in multiple years. Table C-1 shows the income ranges 

associated with each quintile. For the longitudinal measure, each quintile contains the same number of taxpayers that it does under 

the average annual measure with which it is being compared.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

Shares of income received and taxes paid by upper-income quintiles will appear higher in the sample than in the population because 

in the sample, lower-income families are underrepresented.

n.a. = not applicable; * = between -0.05 and 0.05.

a. The difference (longitudinal minus average annual) is calculated as a percentage for income and as percentage points for effective tax 

rates and for shares of pretax income, individual income tax liabilities, and taxpaying units.

b. Values are not shown (because of the small size of the sample) but are included in the totals.

c. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

Annual Measure

1991 1994 1997

n.a. n.a. n.a. . n.a. n.a. n.a.

11.2 11.1 11.2 11.1 11.1 0

20.3 19.8 19.7 20.0 20.0 0

29.2 29.2 28.6 29.1 29.1 0

36.4 37.3 38.2 37.3 37.3 0 ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 100.0 100.0 100.0 0

Multiyear Measures, 1991 to 1997

Income Group Average Annual Longitudinal Differencea

Share of Taxpaying Units (Percent)

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 23

Table 4.

Annual and Longitudinal Income and Effective Tax Rates, 1987 to 2000

Continued

Annual Measure

1987 1994 2000

n.a. n.a. n.a. n.a. n.a. n.a.

12,700 12,600 14,400 13,450 17,000 26

24,900 24,200 27,300 25,300 28,250 11

42,950 42,050 47,200 43,600 44,850 3

106,500 114,600 160,100 126,000 121,150 -4

All Quintiles 54,750 60,900 77,950 64,850 64,850 0

n.a. n.a. n.a. n.a. n.a. n.a.

3.3 2.3 2.4 2.4 3.1 0.7

9.4 7.9 6.8 7.9 8.8 0.9

21.9 20.1 16.8 19.3 19.9 0.6

65.8 70.2 74.8 71.0 68.3 -2.7 ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 100.0 100.0 100.0 0

n.a. n.a. n.a. n.a. n.a. n.a.

-1.6 -3.1 0.2 -1.7 1.8 3.5

5.5 5.2 6.8 5.6 7.0 1.4

8.9 9.1 10.2 9.4 9.8 0.4

16.5 17.5 19.9 18.1 18.2 0.1

All Quintiles 13.3 14.5 17.1 15.1 15.1 0

n.a. n.a. n.a. n.a. n.a. n.a.

-0.4 -0.5 * -0.3 0.4 0.7

3.9 2.8 2.7 2.9 4.1 1.2

14.6 12.7 10.0 12.0 13.0 1.0

81.7 85.0 87.2 85.3 82.6 -2.7 ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 100.0 100.0 100.0 0

Multiyear Measures, 1987 to 2000

Income Group Average Annual Longitudinal Differencea

Average Pretax Income (2000 dollars)

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Share of Pretax Income (Percent)

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Effective Individual Income Tax Rate (Percent)c

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Share of Individual Income Tax Liabilities (Percent)c

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile
24 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table 4.

Continued

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Notes: The analysis is limited to taxpaying units that appear in the CWHS in every year from 1987 to 2000. “Share” refers to a portion of the 

sample, not the overall population. Quintiles are defined using income ranges from the entire population, including nonfilers, in the 

applicable period and may not contain one-fifth of taxpaying units that appear in multiple years. Table C-1 shows the income ranges 

associated with each quintile. For the longitudinal measure, each quintile contains the same number of taxpayers that it does under 

the average annual measure with which it is being compared.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

Shares of income received and taxes paid by upper-income quintiles will appear higher in the sample than in the population because 

in the sample, lower-income families are underrepresented.

n.a. = not applicable; * = between -0.05 and 0.05.

a. The difference (longitudinal minus average annual) is calculated as a percentage for income and as percentage points for effective tax 

rates and for shares of pretax income, individual income tax liabilities, and taxpaying units.

b. Values are not shown (because of the small size of the sample) but are included in the totals.

c. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

Annual Measure

1987 1994 2000

n.a. n.a. n.a. n.a. n.a. n.a.

14.1 11.1 13.0 11.8 11.8 0

20.7 19.8 19.3 20.1 20.1 0

27.9 29.2 27.8 28.7 28.7 0

33.8 37.3 36.4 36.5 36.5 0 ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 100.0 100.0 100.0 0

Multiyear Measures, 1987 to 2000

Income Group Average Annual Longitudinal Differencea

Share of Taxpaying Units (Percent)

Lowest Quintileb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 25

Table 5.

Distributional Effects of Reducing the Top Two Individual Income Tax Rates 

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Notes: The analysis is limited to taxpaying units that appear in the CWHS in every year from 1991 to 2000. Annual quintiles are defined using 

income ranges from the entire population, including nonfilers, in the applicable period and may not contain one-fifth of taxpaying 

units that appear in multiple years. Table C-1 shows the income ranges associated with each quintile. For the measure with longitudinal ranking, each quintile contains the same number of taxpayers that it does under the average annual measure.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

n.a. = not applicable; * = between -0.05 and 0.05.

a. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

b. Values are not shown (because of the small size of the sample) but are included in the totals.

n.a. n.a. n.a.

* **

* **

* **

-1.0 -1.1 -1.1

All Quintiles -0.7 -0.7 -0.7

-1.4 -1.5 -1.4

-1.8 -2.0 -1.9

-3.2 -3.0 -3.2

n.a. n.a. n.a.

* 0.1 *

* 0.1 *

* 0.4 *

7.3 7.2 7.2

All Quintiles 2.4 2.4 2.4

14.1 13.5 13.9

27.3 24.0 26.2

80.9 63.0 70.2

n.a. n.a. n.a.

n.a. 0.7 0.1

n.a. 0.9 *

n.a. 1.7 0.3

n.a. 16.6 17.8

All Quintiles n.a. 6.0 6.0

n.a. 29.6 33.1

n.a. 48.6 59.0

n.a. 93.0 96.2

Top 10 Percent

Top 5 Percent

Top 1 Percent

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Top 5 Percent

Top 1 Percent

Percentage of Taxpaying Units That Have a Lower Effective Tax Rate in Any Yeara

Lowest Quintileb

Middle Quintile

Fourth Quintile

Highest Quintile

Top 10 Percent

Top 1 Percent

Percentage of Taxpaying Units Yearly That Have a Lower Effective Tax Ratea

Lowest Quintileb

Second Quintile

Fourth Quintile

Highest Quintile

Top 10 Percent

Top 5 Percent

Change in Effective Tax Rate (Percentage points)a

Lowest Quintileb

Second Quintile

Middle Quintile

Income Group Measure With First-Year Ranking With Longitudinal Ranking

Average Annual Longitudinal Measures
26 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table 6.

Distributional Effects of Doubling the Child Credit 

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Notes: The analysis is limited to returns that appear in the CWHS in every year from 1991 to 2000. Annual quintiles are defined using income 

ranges from the entire population, including nonfilers, in the applicable period and may not contain one-fifth of taxpaying units that 

appear in multiple years. Table C-1 shows the income ranges associated with each quintile. For the measure with longitudinal ranking, 

each quintile contains the same number of taxpayers that it does under the average annual measure.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

n.a. = not applicable; * = between -0.05 and 0.05.

a. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

b. Values are not shown (because of the small size of the sample) but are included in the totals.

n.a. n.a. n.a.

-0.1 -0.4 -0.2

-0.5 -0.6 -0.6

-0.8 -0.7 -0.7

-0.3 -0.3 -0.3

All Quintiles -0.4 -0.4 -0.4

-0.2 -0.2 -0.2

-0.1 -0.1 -0.1

* **

n.a. n.a. n.a.

3.2 15.4 8.6

21.9 26.7 23.4

40.4 38.3 39.0

46.2 40.9 44.1

All Quintiles 31.6 31.6 31.6

39.0 34.2 38.2

22.6 22.7 24.1

0.2 4.0 3.1

n.a. n.a. n.a.

n.a. 37.8 30.9

n.a. 49.9 47.8

n.a. 56.9 59.2

n.a. 60.6 63.7

All Quintiles n.a. 52.3 52.3

n.a. 55.4 59.4

n.a. 45.4 48.8

n.a. 14.5 18.0

Top 10 Percent

Top 5 Percent

Top 1 Percent

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Top 5 Percent

Top 1 Percent

Percentage of Taxpaying Units That Have a Lower Effective Tax Rate in Any Yeara

Lowest Quintileb

Middle Quintile

Fourth Quintile

Highest Quintile

Top 10 Percent

Top 1 Percent

Percentage of Taxpaying Units Yearly That Have a Lower Effective Tax Ratea

Lowest Quintileb

Second Quintile

Fourth Quintile

Highest Quintile

Top 10 Percent

Top 5 Percent

Change in Effective Tax Rate (Percentage points)a

Lowest Quintileb

Second Quintile

Middle Quintile

Income Group Measure With First-Year Ranking With Longitudinal Ranking

Average Annual Longitudinal Measures
EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES 27

Table 7.

Distributional Effects of Making the Child Credit Fully Refundable 

Source: Congressional Budget Office based on the University of Michigan's Panel Study of Income Dynamics.

Notes: The analysis is limited to taxpaying units that responded to the study in every year from 1987 to 1996. Annual quintiles are defined 

using income ranges from the entire population, including nonfilers, in the applicable period and may not contain one-fifth of taxpaying units that appear in multiple years. Table C-1 shows the income ranges associated with each quintile. For the measure with longitudinal ranking, each quintile contains the same number of taxpayers that it does under the average annual measure.

The income measure is total income, which comprises wages, business income, interest, dividends, pension income, unemployment 

compensation, rental income, Social Security benefits, and income from several cash transfer programs (such as food stamps).

n.a. = not applicable; * = between -0.05 and 0.05.

a. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

-2.8 -1.6 -2.0

-0.6 -0.4 -0.5

-0.1 -0.1 -0.1

* **

* **

All Quintiles -0.1 -0.1 -0.1

21.7 19.6 19.3

13.2 11.4 11.9

4.1 5.4 4.9

0.4 1.7 1.4

* 0.6 0.4

All Quintiles 6.6 6.6 6.6

n.a. 33.3 31.2

n.a. 28.6 26.9

n.a. 17.3 19.6

n.a. 7.9 8.7

n.a. 4.2 3.2

All Quintiles n.a. 16.3 16.3

Fourth Quintile

Highest Quintile

Percentage of Taxpaying Units That Have a Lower Effective Tax Rate in Any Yeara

Lowest Quintile

Second Quintile

Middle Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Fourth Quintile

Highest Quintile

Percentage of Taxpaying Units Yearly That Have a Lower Effective Tax Ratea

Lowest Quintile

Change in Effective Tax Rate (Percentage points)a

Lowest Quintile

Second Quintile

Middle Quintile

Income Group Measure With First-Year Ranking With Longitudinal Ranking

Average Annual Longitudinal Measures

A

Attrition in the Continuous Work History Sample

The Continuous Work History Sample (CWHS) is a 

longitudinal data set embedded in the Internal Revenue 

Service’s Statistics of Income sample. The CWHS is a 

random sample of tax filers and is generally representative 

of that population. It cannot, however, represent the population that does not file tax returns.

Every year, all tax returns whose primary Social Security 

numbers end in specific four-digit combinations are included in the sample. Two such combinations have been 

included in every year from 1987 to 2000; those returns, 

which potentially cover 14 years of tax filings, form the 

basis of the Congressional Budget Office’s (CBO’s)

analysis.1

Examining income over a multiyear period requires information on a taxpayer’s income for all of the relevant years. 

However, many taxpayers in the CWHS are absent from 

the sample for one or more years, a phenomenon known 

as attrition. Taxpayers may drop out of the sample for 

many reasons, such as if they die, become the secondary 

taxpayer on the return, or fail to file a tax return (either 

because their income is below the filing threshold or because of other factors). Failure to file in fact accounts for 

the most attrition in the CWHS (see Table A-1). Because 

in many instances nonfiling results when a taxpayer’s income drops below the tax threshold, the absence of 

records in the CWHS for nonfilers imparts a bias by excluding many households with low and volatile income.

Because of attrition, taxpayers who remain in the sample 

for a long time differ noticeably from taxpayers who do 

not file a tax return every year (see Table A-2). Long-time 

filers tend to have substantially higher income than nonfilers and are more likely to be married.2

 In fact, of the 

taxpaying units that appear in the data in every year from 

1987 to 2000, only 2 percent have income low enough to 

place them in the bottom quintile of the population. 

Thus, results from the CWHS must be viewed with caution. Because the taxpayers who file over the whole period are demonstrably different from those who do not, 

findings based on the CWHS may not be generalizable to 

the entire population of tax filers. 

Low-income households are clearly underrepresented in 

the CWHS. Indeed, so few returns were available for the 

bottom quintile that CBO does not report results based 

on the CWHS for that income group. However, comparisons of annual and longitudinal income that are based 

on the tax data are qualitatively similar to comparisons 

that use data from the University of Michigan’s Panel 

Study of Income Dynamics (PSID), which is not limited 

to tax filers. For the second quintile, the difference between income measured longitudinally and measured on 

an annual basis is greater when the tax data are used for 

the analysis than when the PSID is used—a difference 

that may reflect the attrition bias in the CWHS. For the 

remaining quintiles, the differences between annual and 

longitudinal income are quite similar regardless of 

whether the CWHS or the PSID is used. The similarity 

suggests that conclusions drawn from the tax data may be 

valid despite the potential attrition bias.

One way to evaluate that possible bias is to use data from 

the PSID to simulate the attrition that occurs in the 

APPENDIX

1. The CWHS actually dates back to 1979. However, in 1984 and 

1986, the Internal Revenue Service sampled only one combination of Social Security numbers. Thus, to examine data on returns 

earlier than 1987 would effectively cut the size of the sample in 

half.

2. Charles W. Christian and Peter J. Firschmann (“Attrition in the 

Statistics of Income Panel of Tax Returns,” National Tax Journal,

vol. 42, no. 4, December 1989) perform formal statistical tests 

that demonstrate that attrition in the CWHS is systematically 

related to a taxpayer’s age, income, and marital status.
30 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table A-1.

Causes of Attrition in the Continuous Work History Sample for 1987

(As a cumulative percentage of records lost)

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

CWHS. The difference between results from a simulation that uses the full PSID and results from a simulation 

that uses the PSID with taxpayers who would not have 

appeared in a panel of tax returns indicates how attrition 

in the CWHS probably affects the results. In analyzing 

those simulations, CBO found that attrition affects results in the bottom quintile but has little effect on the 

other quintiles. 

CBO used a multistep process to simulate the pattern of 

attrition that was expected with the PSID. The starting 

point was all taxpaying units in that data set for a given 

year. Analysts estimated whether each unit would be expected to file a tax return in every year of a 10-year period. They assumed that a PSID unit would not file a return if it had no income from wages or had taxable 

income below the relevant filing threshold for the year.3

Analysts also assumed that when single taxpayers married 

during the period, half would become secondary filers 

who would drop out of the sample.

The rates of attrition from the simulations analysis were 

quite similar to the rates observed in the CWHS (see Table A-3). Over a 10-year period, 38 percent of taxpaying 

units in the CWHS would be absent for at least one year, 

compared with 37 percent in the simulations analysis. 

The magnitude of the various causes of attrition were also 

roughly comparable for the two analyses. In the simulations that used data from the PSID, CBO found that 

22 percent of units that filed in the first year would not 

file a tax return in at least one of the nine successive years 

(because their income would have dropped below the 

level at which they were required to file). In the CWHS, 

22 percent of initial filers dropped out for unknown reasons, presumably because they did not have reason to file 

a tax return in those years.

Differences between annual and longitudinal income and 

taxes that are taken from analyses using the full PSID and 

analyses using only likely filers from that panel exhibit 

comparable patterns (see Table A-4). For the second 

through fifth quintiles, differences between longitudinal 

and annual income and taxes are quite similar for the full 

population and for likely filers. In the lowest quintile, 

however, differences between annual and multiyear measures deviate for the two types of analyses, reflecting the 

disproportionate effect of attrition in that quintile. Those 

findings imply that with the exception of the bottom 

quintile, results from a sample of tax returns, such as the 

CWHS, are likely to provide reasonably unbiased estimates of the differences between annual and longitudinal 

income and taxes.

Individual Became the Taxpayer Became a

Year Secondary Taxpayer Dependent

1987 0 0 0 0 0

1988 1 2 1 4 8

1989 2 3 1 7 12

1990 2 4 1 9 17

1991 3 5 1 11 21

1992 4 6 1 14 25

1993 5 6 1 16 28

1994 6 7 1 17 31

1995 7 7 1 18 34

1996 8 7 1 19 36

1997 9 8 2 20 38

1998 10 8 2 21 40

1999 11 8 2 22 42

2000 12 8 2 23 44

All Reasons Combined

Taxpayer Stopped

Filing for Unknown

Taxpayer Died Reasons

3. People with wages may file tax returns even if they owe no tax so 

that they can have any taxes that were withheld by their employers 

refunded to them. 
APPENDIX A ATTRITION IN THE CONTINUOUS WORK HISTORY SAMPLE 31

Table A-2.

Characteristics of Taxpayers in the 

Continuous Work History Sample

for 1987

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Note: AGI = adjusted gross income.

a. The period covered is 1987 to 2000.

Table A-3.

Ten-Year Attrition Rates in the 

Continuous Work History Sample

(Percent)

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample and the 

University of Michigan's Panel Study of Income Dynamics.

42.6 40.6

17 13

11 6

39 30

49 60

28,984 37,845

who itemized 37 50

income tax rate

(Percent) 13.4 14.5

95,530,000 53,405,000

Size of the Sample 19,106 10,681

Average AGI (Dollars)

Percentage of taxpayers

Average effective 

Population

Memorandum:

Filing Status (Percent)

Single

Married

Tax Information

Age

Average

Percentage under 25

Percentage over 65

Present in Present in

Characteristic 1987 All Yearsa

Taxpayers Taxpayers

8.8 6.2

7.7 7.0

21.8 21.6

___ ___

Total 38.2 34.8

Death

Marriage

Income Dropped Below 

Filing Threshold/Other

Simulate Attrition

Cause of Attrition CWHS in the CWHS

PSID Used to
32 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table A-4.

Annual and Longitudinal Income and Effective Tax Rates, 1986 to 1995

Source: Congressional Budget Office based on the University of Michigan's Panel Study of Income Dynamics.

Notes: The analysis is limited to taxpaying units that responded to the study in every year from 1986 to 1995. Quintiles are defined using 

income ranges from the entire population, including nonfilers, in the applicable period and may not contain one-fifth of taxpaying 

units that appear in multiple years. Table C-1 shows the income ranges associated with each quintile. For the longitudinal measure, 

each quintile contains the same number of taxpayers that it does under the average annual measure with which it is being compared.

Taxable income encompasses what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, 

taxable and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits. Total 

income comprises taxable income plus Social Security benefits and income from cash transfer programs (such as food stamps).

CWHS = Continuous Work History Sample; * = between -0.05 and 0.05.

a. The difference (longitudinal minus average annual) is calculated as a percentage for income and as percentage points for effective tax 

rates.

b. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

1,657 4,032 143 3,770 8,353 122

15,171 18,465 22 16,325 19,877 22

31,286 33,448 7 31,459 33,579 7

52,278 52,674 1 52,476 52,629 *

116,784 110,367 -5 117,812 111,983 -5

All Quintiles 49,424 49,424 0 63,572 63,572 0

-10.3 -4.1 6.2 -22.3 -9.4 13.0

-0.2 4.3 4.5 0.3 3.8 3.5

8.0 8.9 0.9 7.9 8.6 0.7

11.1 11.8 0.8 10.9 11.5 0.6

20.9 20.9 -0.1 21.0 20.8 -0.2

All Quintiles 15.8 15.8 0 16.4 16.4 0

7,847 10,339 32 9,422 12,805 36

20,915 23,695 13 21,808 24,464 12

35,189 37,448 6 35,448 37,814 7

54,981 55,522 1 55,176 55,670 1

119,478 113,294 -5 120,443 115,119 -4

All Quintiles 53,483 53,483 0 66,138 66,138 0

-4.3 -1.4 2.9 -9.8 -4.2 5.6

1.8 3.9 2.1 2.9 5.0 2.1

6.7 7.5 0.8 7.2 7.9 0.6

10.5 11.2 0.7 10.5 11.0 0.5

20.5 20.5 * 20.6 20.5 -0.1

All Quintiles 14.6 14.6 0 15.7 15.7 0

Highest Quintile

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Effective Individual Income Tax Rate (Percent)

b

Total Income

Average Pretax Income (2000 dollars)

Lowest Quintile

Second Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Fourth Quintile

Highest Quintile

Effective Individual Income Tax Rate (Percent)b

Lowest Quintile

Average Pretax Income (2000 dollars)

Lowest Quintile

Second Quintile

Middle Quintile

Measure Measure Differencea

Taxable Income

Income Group Measure Measure Differencea

Average Annual Longitudinal Average Annual Longitudinal

Using Records from the PSID Using PSID Records to Simulate CWHS Attrition
B

Alternative Measures of the Distribution of 

Annual and Longitudinal Income and Taxes

In its analysis, the Congressional Budget Office 

(CBO) tested the sensitivity of its results by comparing 

the longitudinal and annual distributions of income and 

taxes over multiple periods and under different sampling 

restrictions. Annual and longitudinal distributions were 

assessed for each three- and seven-year period from 1987 

to 2000 for taxpayers who appeared in the data in every 

year of the 14-year period (see Tables B-1 and B-2). CBO 

also compared the distributions for each three-year period 

after removing the restriction that a taxpaying unit appear 

in the data every year (see Table B-3). An additional comparison assessed the 14-year longitudinal and crosssectional income and tax distributions under CBO’s current methodology (which includes all taxpaying units 

that appear in multiple years) against the distributions 

from a methodology that limited the sample to taxpaying 

units whose marital status did not change and to filers 

who were aged 25 to 60 over the entire period (see 

Table B-4). Finally, CBO compared longitudinal and annual income and effective tax rates for respondents in the 

Panel Study of Income Dynamics who were in the sample 

for different lengths of time (see Tables B-5 and B-6).

APPENDIX
34 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table B-1.

Annual and Longitudinal Income and Tax Rates for Taxpayers in

All Possible Three-Year Periods, 1987 to 2000

Continued

1987- 1988- 1989- 1990- 1991- 1992- 1993- 1994- 1995- 1996- 1997- 1998-

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

13,350 13,700 13,700 13,500 13,150 12,850 12,750 12,900 13,200 13,650 14,000 14,300

25,300 25,450 25,250 24,950 24,550 24,400 24,350 24,500 24,900 25,550 26,250 26,850

43,350 43,350 42,900 42,500 42,100 42,050 42,150 42,550 43,250 44,350 45,600 46,600

112,250 113,750 111,700 113,050 114,000 114,950 116,750 121,500 128,700 141,150 148,500 156,500

All Quintiles 57,800 59,100 58,750 59,500 60,100 60,750 61,800 64,000 67,350 72,300 75,100 77,450

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

14,450 14,850 14,850 14,650 14,200 13,850 13,650 13,850 14,250 14,700 14,950 15,300

25,950 26,050 25,950 25,650 25,300 25,150 25,050 25,200 25,600 26,300 27,050 27,600

43,650 43,650 43,200 42,800 42,450 42,450 42,550 42,950 43,650 44,850 46,050 47,100

110,850 112,350 110,300 111,650 112,700 113,600 115,550 120,250 127,450 139,700 147,100 155,050

All Quintiles 57,800 59,100 58,750 59,500 60,100 60,750 61,800 64,000 67,350 72,300 75,100 77,450

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

8.1 8.2 8.3 8.6 8.2 7.8 7.3 7.3 8.0 7.7 6.9 7.2

2.5 2.4 2.7 2.8 2.9 3.2 2.9 2.8 2.8 2.9 2.9 2.8

0.7 0.7 0.7 0.7 0.9 0.9 0.9 0.9 0.9 1.1 1.1 1.0

-1.2 -1.2 -1.3 -1.2 -1.2 -1.2 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0

All Quintiles 0 0 0 0 0 0 0 0 0 0 0 0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

-1.6 -1.8 -2.3 -2.7 -2.8 -2.9 -2.8 -2.4 -1.9 -1.1 -0.6 -0.1

5.6 5.6 5.5 5.3 5.1 5.1 5.1 5.2 5.5 5.8 6.2 6.5

8.9 8.9 9.0 9.0 9.0 9.1 9.1 9.3 9.5 9.7 9.9 10.1

17.0 17.0 17.0 17.2 17.5 17.6 17.8 18.0 18.5 18.5 19.0 19.4

All Quintiles 13.8 13.9 13.9 14.2 14.4 14.5 14.8 15.0 15.5 15.7 16.2 16.6

Middle Quintile

Fourth Quintile

Highest Quintile

Highest Quintile

Average Annual Income Tax Rate (Percent)b

Lowest Quintilea

Second Quintile

Lowest Quintilea

Second Quintile

Middle Quintile

Fourth Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Difference (As a percentage of average annual income)

Lowest Quintilea

Second Quintile

Lowest Quintilea

Second Quintile

Longitudinal Income (2000 dollars)

Middle Quintile

Fourth Quintile

Highest Quintile

Average Annual Income (2000 dollars)
APPENDIX B ALTERNATIVE MEASURES OF THE DISTRIBUTION OF ANNUAL AND LONGITUDINAL INCOME AND TAXES 35

Table B-1.

Continued

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Notes: The analysis is limited to taxpaying units that appear in the CWHS in every year from 1987 to 2000. Quintiles are defined using income 

ranges from the entire population, including nonfilers, in the applicable period and may not contain one-fifth of taxpaying units that 

appear in multiple years. Table C-1 shows the income ranges associated with each quintile. For the longitudinal measure, each quintile 

contains the same number of taxpayers that it does under the average annual measure with which it is being compared.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

n.a. = not applicable; * = between -0.05 and 0.05.

a. Values are not shown (because of the small size of the sample) but are included in the totals.

c. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

1987- 1988- 1989- 1990- 1991- 1992- 1993- 1994- 1995- 1996- 1997- 1998-

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

0 0.1 -0.8 -0.8 -1.6 -1.6 -1.5 -1.1 -0.7 0.1 0.7 1.2

6.0 5.8 5.9 5.6 5.6 5.6 5.6 5.8 6.1 6.3 6.6 7.0

9.0 9.1 9.1 9.1 9.2 9.2 9.3 9.4 9.5 9.9 10.1 10.4

17.0 17.0 17.0 17.3 17.6 17.6 17.9 18.1 18.5 18.5 19.0 19.4

All Quintiles 13.8 13.9 13.9 14.2 14.4 14.5 14.8 15.0 15.5 15.7 16.2 16.6

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

1.6 1.9 1.5 1.9 1.2 1.3 1.3 1.3 1.2 1.2 1.3 1.3

0.4 0.2 0.4 0.3 0.5 0.5 0.5 0.6 0.6 0.5 0.4 0.5

0.1 0.2 0.1 0.1 0.2 0.1 0.2 0.1 * 0.2 0.2 0.3

* * * 0.1 0.1 * 0.1 0.1 * * * *

All Quintiles 0 0 0 0 0 0 0 0 0 0 0 0

Highest Quintile

Difference (Percentage points)

Highest Quintile

Lowest Quintilea

Second Quintile

Middle Quintile

Fourth Quintile

Lowest Quintilea

Second Quintile

Middle Quintile

Fourth Quintile

Longitudinal Income Tax Rate (Percent)b
36 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table B-2.

Annual and Longitudinal Income and Tax Rates for Taxpayers in

All Possible Seven-Year Periods, 1987 to 2000

Continued

1987-1993 1988-1994 1989-1995 1990-1996 1991-1997 1992-1998 1993-1999 1994-2000

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

13,300 13,350 13,250 13,100 13,100 13,200 13,350 13,600

25,000 24,900 24,800 24,650 24,650 24,900 25,200 25,650

42,750 42,600 42,500 42,400 42,600 43,100 43,700 44,500

112,850 114,000 114,550 116,900 120,500 127,200 132,050 138,500

All Quintiles 58,900 59,800 60,400 61,550 63,300 66,150 68,250 70,750

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

15,700 15,550 15,350 15,200 15,100 15,200 15,350 15,600

26,650 26,550 26,450 26,300 26,250 26,500 26,700 27,100

43,250 43,200 43,200 43,150 43,400 44,050 44,600 45,400

110,050 111,200 111,750 114,150 117,850 124,500 129,400 135,750

All Quintiles 58,900 59,800 60,400 61,550 63,300 66,150 68,250 70,750

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

15.6 16.6 15.8 14.6 15.4 14.5 12.3 10.3

4.9 6.0 6.0 6.0 6.4 5.6 4.4 3.5

0.6 0.9 1.3 1.4 1.8 1.6 1.3 0.7

-2.6 -2.8 -2.6 -2.5 -2.2 -2.5 -2.4 -3.1

All Quintiles 0 0 0 0 0 0 0 0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

-2.2 -2.4 -2.6 -2.6 -2.5 -2.1 -1.7 -1.2

5.4 5.3 5.3 5.2 5.3 5.4 5.6 5.9

9.0 9.0 9.1 9.1 9.2 9.4 9.5 9.7

17.2 17.3 17.5 17.6 18.0 18.1 18.4 18.8

All Quintiles 14.0 14.2 14.4 14.6 14.9 15.2 15.5 15.9

Highest Quintile

Lowest Quintilea

Second Quintile

Middle Quintile

Fourth Quintile

Lowest Quintilea

Average Annual Income Tax Rate (Percent)b

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Second Quintile

Middle Quintile

Highest Quintile

Difference (As a percentage of average annual income)

Average Annual Income (2000 dollars)

Lowest Quintilea

Fourth Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Longitudinal Income (2000 dollars)

Lowest Quintilea
APPENDIX B ALTERNATIVE MEASURES OF THE DISTRIBUTION OF ANNUAL AND LONGITUDINAL INCOME AND TAXES 37

Table B-2.

Continued

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Notes: The analysis is limited to taxpaying units that appear in the CWHS in every year from 1987 to 2000. Quintiles are defined using income 

ranges from the entire population, including nonfilers, in the applicable period and may not contain one-fifth of taxpaying units that 

appear in multiple years. Table C-1 shows the income ranges associated with each quintile. For the longitudinal measure, each quintile 

contains the same number of taxpayers that it does under the average annual measure with which it is being compared.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

n.a. = not applicable; * = between -0.05 and 0.05.

a. Values are not shown (because of the small size of the sample) but are included in the totals.

b. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

1987-1993 1988-1994 1989-1995 1990-1996 1991-1997 1992-1998 1993-1999 1994-2000

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

0.6 0.6 * -0.2 * 0.4 0.8 1.1

6.3 6.1 6.2 6.0 6.0 6.2 6.5 6.8

9.2 9.3 9.4 9.5 9.5 9.7 9.8 10.0

17.2 17.4 17.5 17.7 18.0 18.2 18.5 18.8

All Quintiles 14.0 14.2 14.4 14.6 14.9 15.2 15.5 15.9

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

2.4 2.9 2.5 2.2 2.5 2.5 2.2 1.9

0.8 0.8 0.8 0.8 0.7 0.8 0.8 0.8

0.2 0.2 0.3 0.4 0.3 0.3 0.3 0.2

* * * 0.1 * 0.1 * *

All Quintiles 0 0 0 0 0 0 0 0

Middle Quintile

Fourth Quintile

Highest Quintile

Difference (Percentage points)

Lowest Quintilea

Second Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Longitudinal Income Tax Rate (Percent)b

Lowest Quintilea
38 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table B-3.

Annual and Longitudinal Income and Tax Rates for Taxpayers in Any 

Three-Year Period, 1987 to 2000

Continued

1987- 1988- 1989- 1990- 1991- 1992- 1993- 1994- 1995- 1996- 1997- 1998-

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

12,800 13,000 12,950 12,700 12,400 12,150 12,100 12,250 12,550 13,000 13,500 13,900

24,950 25,050 24,800 24,500 24,100 23,900 23,850 24,000 24,450 25,050 25,800 26,350

42,950 42,900 42,500 42,050 41,600 41,500 41,550 41,950 42,650 43,700 44,950 45,950

110,600 111,800 110,100 111,000 111,350 112,350 114,000 117,800 124,250 135,050 141,100 145,850

All Quintiles 45,350 44,500 43,700 44,100 44,450 44,850 45,500 46,800 49,100 52,350 54,500 56,900

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

13,350 13,550 13,350 13,250 12,900 12,550 12,500 12,750 13,050 13,450 14,100 14,400

25,200 25,200 24,900 24,750 24,450 24,100 24,050 24,150 24,650 25,250 26,050 26,500

42,950 42,950 42,400 42,000 41,750 41,500 41,600 41,950 42,750 43,600 45,150 46,100

108,850 110,050 108,500 109,250 110,000 110,650 112,550 116,300 122,850 132,900 139,650 143,950

All Quintiles 45,350 44,500 43,700 44,100 44,450 44,850 45,500 46,800 49,100 52,350 54,500 56,900

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

4.3 4.2 3.1 4.3 4.0 3.3 3.3 4.1 4.0 3.5 4.4 3.6

1.0 0.6 0.4 1.0 1.5 0.8 0.8 0.6 0.8 0.8 1.0 0.6

* 0.1 -0.2 -0.1 0.4 * 0.1 * 0.2 -0.2 0.4 0.3

-1.6 -1.6 -1.5 -1.6 -1.2 -1.5 -1.3 -1.3 -1.1 -1.6 -1.0 -1.3

All Quintiles 0 0 0 0 0 0 0 0 0 0 0 0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

-0.4 -0.7 -1.2 -1.8 -2.3 -2.8 -3.0 -3.0 -3.0 -2.9 -2.9 -3.0

5.8 5.8 5.7 5.5 5.3 5.3 5.2 5.3 5.5 5.7 6.1 6.2

9.2 9.2 9.3 9.4 9.4 9.4 9.4 9.5 9.6 9.8 9.9 10.1

16.8 16.9 16.9 17.2 17.3 17.4 17.6 17.8 18.2 18.3 18.6 19.5

All Quintiles 12.8 12.8 12.7 12.9 13.0 13.1 13.3 13.5 13.8 14.1 14.4 15.1

Fourth Quintile

Highest Quintile

Average Annual Income Tax Rate (Percent)b

Lowest Quintilea

Second Quintile

Middle Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Fourth Quintile

Highest Quintile

Difference (As a percentage of average annual income)

Lowest Quintilea

Highest Quintile

Longitudinal Income (2000 dollars)

Second Quintile

Middle Quintile

Lowest Quintilea

Average Annual Income (2000 dollars)

Lowest Quintilea

Second Quintile

Middle Quintile

Fourth Quintile
APPENDIX B ALTERNATIVE MEASURES OF THE DISTRIBUTION OF ANNUAL AND LONGITUDINAL INCOME AND TAXES 39

Table B-3.

Continued

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Notes: The analysis is limited to taxpaying units that appear in the CWHS in any three-year period from 1987 to 2000. Quintiles are defined 

using income ranges from the entire population, including nonfilers, in the applicable period and may not contain one-fifth of taxpaying units that appear in multiple years. Table C-1 shows the income ranges associated with each quintile. For the longitudinal measure, each quintile contains the same number of taxpayers that it does under the average annual measure with which it is being 

compared.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

n.a. = not applicable; * = between -0.05 and 0.05.

a. Values are not shown (because of the small size of the sample) but are included in the totals.

b. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

1987- 1988- 1989- 1990- 1991- 1992- 1993- 1994- 1995- 1996- 1997- 1998-

1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

0.7 0.5 -0.3 -0.6 -1.3 -1.8 -2.1 -1.8 -1.9 -1.6 -1.4 -1.7

6.0 6.0 6.0 5.8 5.7 5.6 5.6 5.6 5.9 6.0 6.3 6.5

9.2 9.3 9.3 9.5 9.4 9.4 9.4 9.5 9.7 9.9 10.1 10.3

16.8 16.9 16.9 17.2 17.4 17.4 17.7 17.8 18.2 18.3 18.7 19.5

All Quintiles 12.8 12.8 12.7 12.9 13.0 13.1 13.3 13.5 13.8 14.1 14.4 15.1

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

1.1 1.2 0.9 1.2 1.0 1.0 0.9 1.2 1.1 1.3 1.5 1.3

0.2 0.2 0.3 0.3 0.4 0.3 0.4 0.3 0.4 0.3 0.2 0.3

* 0.1 * 0.1 * * * * 0.1 0.1 0.2 0.2

0 * * * 0.1 * 0.1 * * * 0.1 *

All Quintiles 0 0 0 0 0 0 0 0 0 0 0 0

Fourth Quintile

Highest Quintile

Difference (Percentage points)

Lowest Quintilea

Second Quintile

Middle Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Longitudinal Income Tax Rate (Percent)b

Lowest Quintilea
40 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table B-4.

Annual and Longitudinal Income and Effective Tax Rates Under Different

Sampling Restrictions, 1987 to 2000

Continued

Average Average Average

Annual Longitudinal Annual Longitudinal Annual Longitudinal

Measure Measure Measure Measure Measure Measure

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

13,450 17,000 26 13,450 16,900 25 13,500 17,150 27

25,300 28,250 12 25,300 28,100 11 25,550 28,400 11

43,600 44,850 3 43,650 44,900 3 43,950 45,250 3

126,000 121,150 -4 128,850 124,150 -4 123,050 118,050 -4

All Quintiles 64,850 64,850 0 66,550 66,550 0 70,300 70,300 0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

2.4 3.1 0.7 2.4 3.1 0.7 1.6 2.1 0.5

7.9 8.8 0.9 7.6 8.5 0.9 6.2 6.8 0.6

19.3 19.9 0.6 18.2 17.9 -0.3 18.8 19.0 0.2

71.0 68.3 -2.7 72.3 70.5 -1.8 73.8 72.0 -1.8 ____ ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 0 100.0 100.0 0 100.0 100.0 0

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

-1.7 1.8 3.5 -1.4 2.2 3.6 -4.8 -0.2 4.6

5.6 7.0 1.4 5.8 7.2 1.4 4.7 6.2 1.5

9.4 9.8 0.4 9.4 10.0 0.6 8.6 9.1 0.5

18.1 18.2 0.1 18.3 18.3 * 17.6 17.6 *

All Quintiles 15.1 15.1 0 15.4 15.4 0 14.8 14.8 0

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Income Group

Lowest Quintilec

No Sample Restrictions

Restriction of No Marital 

Restriction of Age Requirementa

Average Pretax Income (2000 dollars)

Differenceb Differenceb Differenceb

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Status Change

Share of Pretax Income (Percent)

Lowest Quintilec

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Effective Individual Income Tax Rate (Percent)d

Lowest Quintilec
APPENDIX B ALTERNATIVE MEASURES OF THE DISTRIBUTION OF ANNUAL AND LONGITUDINAL INCOME AND TAXES 41

Table B-4.

Continued

Source: Congressional Budget Office based on the Internal Revenue Service's Continuous Work History Sample.

Notes: The analysis is limited to taxpaying units that appear in the CWHS in every year from 1987 to 2000. “Share” refers to a portion of the 

sample, not the overall population. Quintiles are defined using income ranges from the entire population, including nonfilers, in the 

applicable period and may not contain one-fifth of taxpaying units that appear in multiple years. Table C-1 shows the income ranges 

associated with each quintile. For the longitudinal measure, each quintile contains the same number of taxpayers that it does under 

the average annual measure with which it is being compared.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

Shares of income received and taxes paid by upper-income quintiles will appear higher in the sample than in the population because 

in the sample, lower-income families are underrepresented.

n.a. = not applicable; * = between -0.05 and 0.05.

a. The sample was restricted to taxpayers who were aged 25 to 60 during the 1987-2000 period.

b. The difference between the average annual and longitudinal measures is calculated as a percentage for income and as percentage points 

for shares of pretax income, effective tax rates, and individual income tax liabilities.

c. Values are not shown (because of the small size of the sample) but are included in the totals.

d. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

Average Average Average

Annual Longitudinal Annual Longitudinal Annual Longitudinal

Measure Measure Measure Measure Measure Measure

n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

-0.3 0.4 0.7 -0.2 0.4 0.6 -0.5 * 0.5

2.9 4.1 1.2 2.9 4.0 1.1 2.0 2.8 0.8

12.0 13.0 1.0 11.2 11.6 0.4 10.9 11.6 0.7

85.3 82.6 -2.7 86.2 84.0 -2.2 87.7 85.7 -2.0 ____ ____ ____ ____ ____ ____

All Quintiles 100.0 100.0 0 100.0 100.0 0 100.0 100.0 0

Fourth Quintile

Highest Quintile

Share of Individual Income Tax Liabilities (Percent)d

Lowest Quintilec

Second Quintile

Middle Quintile

Restriction of No Marital 

No Sample Restrictions Status Change Restriction of Age Requirementa

Income Group Differenceb Differenceb Differenceb
42 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table B-5.

Annual and Longitudinal Income and Tax Rates for PSID Respondents in

All Possible Three-Year Periods, 1987 to 1995

Continued

1987-1989 1988-1990 1989-1991 1990-1992 1991-1993 1992-1994 1993-1995

7,950 8,000 7,800 7,700 7,600 7,700 7,900

20,600 20,250 19,900 20,200 20,750 21,450 21,800

34,700 34,350 33,850 34,450 35,150 36,200 36,500

54,100 53,850 53,150 54,100 55,250 57,050 57,300

114,900 114,500 113,550 115,350 121,300 128,100 131,300

All Quintiles 50,400 50,900 50,700 52,050 53,200 54,650 55,500

8,950 8,950 8,850 8,900 9,100 9,250 9,350

21,350 21,300 21,000 21,550 22,200 23,000 23,300

35,300 35,050 34,500 35,300 36,000 37,100 37,600

54,450 54,050 53,250 54,100 55,600 57,700 57,600

112,450 111,900 111,250 112,650 117,950 124,200 127,650

All Quintiles 50,400 50,900 50,700 52,050 53,200 54,650 55,500

12.6 12.0 13.1 15.3 20.1 20.1 18.5

3.5 5.2 5.5 6.7 7.0 7.2 6.9

1.6 2.1 2.0 2.5 2.5 2.5 3.0

0.6 0.4 0.2 -0.1 0.6 1.2 0.5

-2.2 -2.2 -2.1 -2.3 -2.8 -3.0 -2.8

All Quintiles 0 0 0 0 0 0 0

-3.6 -3.6 -3.6 -3.4 -3.2 -3.0 -2.7

2.7 2.5 2.2 2.5 2.5 2.6 2.7

7.3 7.2 7.0 7.1 7.3 7.3 7.3

11.0 10.9 10.7 10.8 10.9 11.2 11.3

20.6 20.5 20.4 20.4 21.0 21.2 21.4

All Quintiles 14.5 14.6 14.5 14.6 15.0 15.3 15.5

Average Annual Income (2000 dollars)

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Longitudinal Income (2000 dollars)

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Difference (As a percentage of average annual income)

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Highest Quintile

Average Annual Income Tax Rate (Percent)a

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile
APPENDIX B ALTERNATIVE MEASURES OF THE DISTRIBUTION OF ANNUAL AND LONGITUDINAL INCOME AND TAXES 43

Table B-5.

Continued

Source: Congressional Budget Office based on the University of Michigan's Panel Study of Income Dynamics.

Notes: The analysis is limited to taxpaying units that responded to the study in every year from 1987 to 1995. Quintiles are defined using 

income ranges from the entire population, including nonfilers, in the applicable period and may not contain one-fifth of taxpaying 

units that appear in multiple years. Table C-1 shows the income ranges associated with each quintile. For the longitudinal measure, 

each quintile contains the same number of taxpayers that it does under the average annual measure with which it is being compared.

The income measure is total income, which comprises wages, business income, interest, dividends, pension income, unemployment 

compensation, rental income, Social Security benefits, and income from several cash transfer programs (such as food stamps).

* = between -0.05 and 0.05.

a. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

1987-1989 1988-1990 1989-1991 1990-1992 1991-1993 1992-1994 1993-1995

-2.2 -2.6 -2.6 -1.8 -1.5 -1.3 -1.2

3.3 3.3 3.2 3.7 4.0 3.8 3.6

7.5 7.7 7.4 7.6 7.6 7.9 7.8

11.4 11.1 11.0 11.1 11.4 11.5 11.6

20.6 20.5 20.3 20.3 20.9 21.2 21.5

All Quintiles 14.5 14.6 14.5 14.6 15.0 15.3 15.5

1.5 1.0 1.0 1.5 1.7 1.8 1.5

0.6 0.8 1.0 1.2 1.5 1.2 0.9

0.2 0.5 0.4 0.5 0.3 0.6 0.5

0.4 0.2 0.3 0.3 0.4 0.3 0.3

* * * -0.1 * * 0.1

All Quintiles 0 0 0 0 0 0 0

Longitudinal Income Tax Rate (Percent)a

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Fourth Quintile

Highest Quintile

Difference (Percentage points)

Lowest Quintile

Second Quintile

Middle Quintile
44 EFFECTIVE TAX RATES: COMPARING ANNUAL AND MULTIYEAR MEASURES

Table B-6.

Annual and Longitudinal Income and Tax Rates for PSID Respondents in 

Any Three-Year Period, 1987 to 1995

Continued

1987-1989 1988-1990 1989-1991 1990-1992 1991-1993 1992-1994 1993-1995

8,000 7,950 7,750 7,650 7,500 7,650 7,850

20,500 20,150 19,850 20,100 20,600 21,300 21,650

34,750 34,350 33,850 34,400 35,050 36,050 36,350

53,900 53,750 53,000 53,950 55,100 56,900 57,100

114,050 112,850 111,550 113,850 119,900 126,700 129,600

All Quintiles 47,400 47,350 46,750 48,500 49,900 51,150 51,650

8,900 8,950 8,800 8,800 9,050 9,250 9,400

21,200 21,150 20,850 21,350 21,900 22,650 23,050

35,250 34,950 34,350 35,050 35,800 36,900 37,250

54,150 53,750 52,900 53,850 55,350 57,400 57,250

111,500 110,200 109,100 111,050 116,250 122,400 125,550

All Quintiles 47,400 47,350 46,750 48,500 49,900 51,150 51,650

11.6 12.1 13.3 15.4 20.8 21.5 19.8

3.4 4.8 4.9 6.1 6.2 6.5 6.4

1.5 1.8 1.5 1.9 2.2 2.4 2.5

0.4 0.1 -0.1 -0.2 0.5 0.9 0.3

-2.3 -2.4 -2.2 -2.5 -3.0 -3.4 -3.1

All Quintiles 0 0 0 0 0 0 0

-3.4 -3.2 -3.4 -3.4 -3.2 -3.2 -2.9

2.5 2.6 2.5 2.7 2.9 3.0 3.2

7.2 7.1 7.1 7.4 7.7 7.7 7.7

11.0 11.0 10.8 10.9 11.1 11.4 11.5

20.5 20.3 20.2 20.3 20.9 21.1 21.3

All Quintiles 14.1 14.0 13.9 14.2 14.7 14.9 15.0

Average Annual Income (2000 dollars)

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Longitudinal Income (2000 dollars)

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Difference (As a percentage of average annual income)

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Average Annual Income Tax Rate (Percent)a

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile
APPENDIX B ALTERNATIVE MEASURES OF THE DISTRIBUTION OF ANNUAL AND LONGITUDINAL INCOME AND TAXES 45

Table B-6.

Continued

Source: Congressional Budget Office based on the University of Michigan's Panel Study of Income Dynamics.

Notes: The analysis is limited to taxpaying units that responded to the study in any three-year period from 1987 to 1995. Quintiles are defined 

using income ranges from the entire population, including nonfilers, in the applicable period and may not contain one-fifth of taxpaying units that appear in multiple years. Table C-1 shows the income ranges associated with each quintile. For the longitudinal measure, each quintile contains the same number of taxpayers that it does under the average annual measure with which it is being 

compared.

The income measure is total income, which comprises wages, business income, interest, dividends, pension income, unemployment 

compensation, rental income, Social Security benefits, and income from several cash transfer programs (such as food stamps).

* = between -0.05 and 0.05.

a. Taxes were calculated under the law prevailing in 2000 by increasing incomes and deductions to the 2000 level using the rate of inflation.

1987-1989 1988-1990 1989-1991 1990-1992 1991-1993 1992-1994 1993-1995

-2.2 -2.2 -2.4 -1.8 -1.4 -1.3 -1.2

3.2 3.2 3.4 3.8 4.3 4.2 4.1

7.5 7.8 7.5 7.9 7.9 8.3 8.2

11.4 11.1 11.1 11.2 11.6 11.7 11.8

20.5 20.3 20.1 20.2 20.8 21.1 21.4

All Quintiles 14.1 14.0 13.9 14.2 14.7 14.9 15.0

1.2 1.1 1.0 1.5 1.8 1.9 1.7

0.7 0.7 0.9 1.1 1.4 1.2 1.0

0.3 0.6 0.4 0.5 0.2 0.5 0.4

0.3 0.2 0.3 0.3 0.5 0.3 0.3

* * -0.1 -0.1 -0.1 * 0.1

All Quintiles 0 0 0 0 0 0 0

Longitudinal Income Tax Rate (Percent)a

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

Highest Quintile

Difference (Percentage points)

Highest Quintile

Lowest Quintile

Second Quintile

Middle Quintile

Fourth Quintile

C

CBO’s Method for Deriving Income Quintiles

B ecause the Internal Revenue Service’s Continuous 

Work History Sample—the tax-return data that the Congressional Budget Office (CBO) mainly used for this 

analysis—does not represent all taxpayers, CBO relied on 

data from a representative cross section of the entire population to divide the tax-return sample into quintiles (basically fifths of the income distribution). CBO first combined information from the entire tax-filing population 

in a given year with data for the same year from the Census Bureau’s Current Population Survey, forming a cross 

section that represented the full population. The taxpaying units in the cross section were then ranked by income 

and divided into five groups of equal size. (The ranking 

incorporated the assumption that all nonfilers fell into 

the lowest income quintile.) CBO then used the income 

range associated with each population-derived quintile to 

assign members of the tax-return sample to income 

groups. Table C-1 shows the income ranges that were 

used to make that assignment.

Table C-1.

Minimum Income by Quintile

(2000 dollars)

Source: Congressional Budget Office based on data from the Internal Revenue Service’s Statistics of Income data set and the Bureau of the 

Census’s Current Population Survey.

Notes: The minimum income is the lower income boundary for each quintile. Quintiles (fifths of the income distribution) are defined on the 

basis of the full population, including nonfilers, who are assumed to fall into the lowest quintile.

Income includes only what can be consistently measured on a tax return—wages, salaries, self-employment income, rents, taxable 

and nontaxable interest, dividends, realized capital gains, taxable retirement benefits, and unemployment benefits.

APPENDIX

Year Lowest

1987 0 6,376 17,913 32,039 54,901

1988 0 7,220 19,220 33,654 57,568

1989 0 8,272 20,139 35,225 60,324

1990 0 8,539 20,885 36,569 62,313

1991 0 8,735 21,163 37,029 63,432

1992 0 8,546 21,466 37,922 65,708

1993 0 8,185 21,289 38,103 66,358

1994 0 8,081 21,792 38,946 68,576

1995 0 8,755 22,800 40,564 71,337

1996 0 8,742 23,494 41,871 73,967

1997 0 9,413 24,886 44,210 77,654

1998 0 10,561 26,422 46,223 81,688

1999 0 10,652 27,228 47,906 85,392

2000 0 11,421 28,606 50,183 89,092

Second

Quintile

Middle Fourth Highest