Measuring Tax Fairness
The Problems with Tax Distribution Tables
Presentation to the President’s Advisory Panel on
Federal Tax Reform
New Orleans
March 23, 2005
William W. Beach
Director, Center for Data Analysis
The Heritage Foundation
Washington, D.C.
What is tax fairness?
• In many respects, tax fairness is similar to the concept of
fairness in other aspects of U.S. law.
– Equal treatment
– Transparency
– Continuity of rules and practices
• Fairness in the tax realm certainly means that everyone
pays their fair share. That could mean that taxes are
proportional to consumption, to income, or to some other
factor that measures our use of government.
• Fairness also implies “forward equity,” since tax policy
today frequently shapes the future.
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Why consider “forward equity”
• Economists frequently talk about horizontal equity (that equals will be
treated equally) and vertical equity (that, for example, tax burden rises
with income).
• Lawmakers, however, need to recognize that most of their decisions
will affect relatively distant future acts rather than today’s activities or
today’s income or tax distribution.
• That being so, lawmakers should consider whether policy change
facilitates individual economic, social, and personal choices that set in
motion a sequence of activities that lead to goals a person sets for him
or herself.
– For example, do tax policy changes made today raise barriers to
women re-entering the workforce years from now after raising a
family, or to immigrants starting micro-businesses, or to retirees
pursuing part-time work?
– Do policy changes make it more or less difficult for young people
to achieve their goals?
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How would you measure fairness?
• One of the goals of distribution analysis is to show how policy change
affects the economic well-being of taxpayers and non-taxpayers. The
problem, however, is deciding how to measure the relationship
between tax policy and economic well-being.
• Unfortunately, we cannot measure all of the things that affect a
taxpayer’s well-being. Thus, we settle on proxies for those data we
cannot obtain or activities we cannot measure.
– The most common way of measuring fairness is to analyze changes
in income.
– However, what is income?
• What is spent on all goods and services including leisure?
• Net worth?
• Cash and non-cash compensation?
– Even if we settle on a concept, how good are the data?
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The neat classification of taxpayers by income breaks
down when we look at their tax liability in each quintile.
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Why does the neat classification of taxpayers
by income so easily break down?
• The previous chart shows that taxpayers who are
grouped into quintiles by income have vastly
different tax liabilities.
• Millions of taxpayers in the third quintile pay
more in taxes than those in the fourth quintile;
there are millions in the fourth that pay more than
those in the fifth.
• These differences stem from many factors that are
not revealed by simple income distribution: family
businesses, differences in family size, investments,
access to itemized deductions, and so forth.
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What about distributing tax
policy effects by consumption?
• Avoids many of the definitional problems surrounding
“income,” even though short-run and long-run
consumption (housing, education) muddy the data waters.
• Over the course of an individual’s life, consumption tends
to follow income change: incomes are low in youth, rise to
a peak in middle age, and fall again in retirement.
Generally, consumption follows a similar pattern.
– However, hard to study an income tax by looking at
consumption.
– Significant data problems, especially with the
Consumer Expenditure Survey.
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How much can we learn about
the complexity and equity of our tax system
from marginal tax rates ?
• If a primary fairness goal is steadily higher tax rates as
income rises, then looking at marginal tax rates after a
policy change may be a good metric for fairness.
• However, targeting tax policy at specific groups in order to
achieve fairness often frustrates the analysis of whether the
overall tax system is more just.
• As Kevin Hassett of AEI shows in the following dramatic
graphic, current marginal tax rates on the income of a
family of four shows distinctly unequal treatment as their
income rises.*
*Further information can be found at http://www.aei.org/publications/pubID.22160/pub_detail.asp
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Marginal Tax Rates for 2004
(Drawing by Marina Sagona based on graph from Kevin Hassett, American Enterprise Institute)
Is this just?
The marginal tax rates of a family of four
as income rises.
(Graph courtesy of Dr. Kevin Hassett of the American Enterprise Institute)
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Snapshot Analysis
• When economists create a cross-section of taxpayers, they
have grouped these people by income and, usually, family
type at a moment in time. It truly is a snapshot of our tax
system.
• This snapshot analysis is done differently at Congress’s
Joint Committee on Taxation and the Treasury
Department’s Office of Tax Analysis, the two agencies
most responsible for tax policy analysis.
• These two agencies use snapshot analysis of the policy
change implementation using projected historical data.
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Snapshot Analysis
(continued)
• The groupings are based on historical data that have been
changed to reflect the increase in income and taxpayers
that forecasting models predict. But, these groupings
commonly are not affected in all of the ways that tax
policy changes can impact the economy.
• The next three graphs show how JCT and OTA distribute
tax changes across income. JCT uses an income concept
most taxpayers would recognize. OTA used to employ an
income concept that only an economist would appreciate.
It has recently used an income concept more like that of
the JCT.
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The JCT distributes taxes against a measure based on
Adjusted Gross Income (an expanded version of AGI)
Analysis of the Bush 2001 tax cut proposal
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The OTA, however, used to adjust the JCT income concept to
include “imputed income” from things not commonly taxed.
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The new OTA distribution method uses an income concept
closer to the Joint Committee’s
Analysis of the Bush 2001 tax cut proposal
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But, do these approaches tell us what we
really want to know about tax policy change?
• Answering fairness questions by looking at snapshot changes in
tax liability does not tell us what happens to individual
taxpayers living in a society reshaped by tax policy change.
• What we really want to know is how certain types of tax policy
changes affect long-term social and economic outcomes.
• To answer those types of questions, we need “longitudinal” tax
analysis. An example of excellent longitudinal work is the
Congressional Budget Office’s “Effective Tax Rate: Comparing
Annual and Multiyear Measures” (January, 2005).
• In the following graph, the number in bold along the diagonal
represents the percentage of taxpayers who were at that tax rate
in 1987 and remained there ten years later. The chart shows
significant income mobility.
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Follow taxpayers
not classifications over time
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The Center for Data Analysis is taking
longitudinal analysis one step further
• The CDA uses a rich database of taxpayers,
taxpaying families, and households to analyze tax
policy change.
• We employ standard projection techniques to
create a ten-year panel of taxpayers.
• However, we also shape each year’s cross-section
a dynamic simulation of how tax policy affects
those economic factors that shape income, job
creation, and other key indicators.
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Summary
• Fairness questions are natural and inevitable features of tax policy
debate.
• Tax and economic data as well as definitions of income poorly serve
those seeking answers.
• Snapshot analysis probably produces more confusion and bad
information than clarity.
• Following taxpayers over time should provide more insight on fairness
than other analytical approaches. It is important to
– Include more than one year of income in our analysis
– Continue to move beyond snapshot analysis
– And, wherever possible, incorporate the impact of tax policy on the
economy and, thus, on the pool of income and economic decisions that
compose the base from which taxes are drawn.
•
Note: Many of the slides used in this presentation were taken from Jason Fichtner’s excellent essay, “A
Comparison of Tax Distribution Tables: How Missing or Incomplete Information Distorts Perspectives,” The
Heritage Foundation Center for Data Analysis Report CDA04-13, November 9, 2004.
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