EXPLORING ISSUES IN THE DEVELOPMENT 

OF MACROECONOMIC MODELS FOR USE 

IN TAX POLICY ANALYSIS 

Prepared by the Staff 

of the 

JOINT COMMITTEE ON TAXATION 

June 16, 2006 

JCX-19-06
i 

CONTENTS 

Page

INTRODUCTION .......................................................................................................................... 1 

PART I − LESSONS FROM MULTIPLE SIMULATIONS OF THE MACROECONOMIC 

EFFECTS OF A TEN PERCENT CUT IN INDIVIDUAL INCOME TAX RATES.................... 2 

A. Introduction..................................................................................................................... 2 

B. Role of Modeling Assumptions ...................................................................................... 4 

C. Role of Tax Rate Aggregation and Model Calibration................................................... 8 

PART II − THE DEVELOPMENT OF MACROECONOMIC ANALYSIS OF TAX 

LEGISLATION AT THE JOINT COMMITTEE ON TAXATION............................................ 13 

A. Introduction................................................................................................................... 13 

B. Conventional Analysis.................................................................................................. 14 

C. History of Joint Committee on Taxation Involvement in Macroeconomic Analysis ... 16 

D. Recent Exploration and Developments in Macroeconomic Analysis by the Joint 

Committee Staff............................................................................................................ 20 

E. Conclusion .................................................................................................................... 23 
1 

INTRODUCTION 

The Brookings Institution and the Heritage Foundation invited the staff of the Joint 

Committee on Taxation (“Joint Committee staff”) to participate in a seminar on June 16, 2006, 

titled “A Seminar on Dynamic Analysis and a Discussion with the Current and Former Directors 

of the Congressional Budget Office.” The purpose of the seminar is to present to Congressional 

staff and other interested persons a discussion of developments in the use of macroeconomic 

models for the analysis of proposed changes in Federal tax policy. 

This document1

 reproduces the prepared remarks of the Joint Committee staff, in the 

order in which the remarks were delivered at the seminar. Part I of this document reports on 

work of the Joint Committee staff identifying the sensitivity of reported macroeconomic results 

to the type of model being used, assumptions about the sizes of behavioral responses and 

monetary and fiscal policy reactions, and simplifying assumptions with respect to the level of 

aggregation used in modeling changes in tax policy. This report demonstrates the importance of 

the level of disaggregation in the calculation of average and marginal tax rates to the outcome of 

macroeconomic models. 

Part II of this document provides a brief history of Joint Committee staff efforts to 

estimate the macroeconomic effects of tax proposals. It also presents some recent model 

developments and describes some future developments under consideration by the Joint 

Committee staff. 

 1

 This document may be cited as follows: Joint Committee on Taxation, Exploring Issues in the 

Development of Macroeconomic Models for Use in Tax Policy Analysis, (JCX-19-06), June 16, 2006. 
2 

PART I − LESSONS FROM MULTIPLE SIMULATIONS OF THE 

MACROECONOMIC EFFECTS OF A TEN PERCENT CUT 

IN INDIVIDUAL INCOME TAX RATES 

A. Introduction 

The staff of the Joint Committee on Taxation has been actively involved, for about a 

decade, in developing the capability to perform macroeconomic analysis of tax law changes. 

One of the most striking results of this effort has been the significant dependence of simulation 

results on a range of modeling decisions. It is generally recognized that model results will be 

sensitive to the type of model being used and to assumptions about the sizes of behavioral 

responses and monetary and fiscal policy reactions. What is less obvious is that model results can 

vary substantially depending on modeling choices that some might think are insignificant. 

Simplifying assumptions with respect to the level of aggregation used in modeling changes in tax 

policy is one of these lesser known areas. This presentation will discuss both types of sensitivity 

in the modeling of a ten percent cut in tax rates, with a focus on the more often disregarded 

question of tax sector aggregation. 

Effects of tax cuts on individual behavior

A cut in individual income tax rates changes incentives to work through its effect on 

average and marginal tax rates on wages. The reduction in average tax rates on wages decreases 

the amount of work necessary to earn a target amount of after-tax income, thus reducing 

incentives to work. The reduction in marginal rates (i.e., the tax rate on additional increments of 

earned income) increases the value to the worker of additional labor, thus increasing his 

incentive to work. Similarly, the reduction in individual income tax rates reduces marginal and 

average tax rates on income from capital, including dividends, interest, rent, and capital gains, 

which allows individuals to accumulate more wealth for a given level of saving, while at the 

same time increasing the after-tax rate of return on additional savings. In theory, these competing 

effects could cause either a net increase or net decrease in labor supply, savings, and investment, 

depending on the strength of taxpayer responsiveness to each incentive. These types of responses 

are often referred to as “supply side” effects. 
3 

A number of statistical studies have attempted to measure the size of these effects.2

 

While these studies have not yielded a clear consensus on a single set of responses, there is a 

general indication that the marginal effects outweigh the average effects, and thus a cut in taxes 

on wages can be expected to provide some incentive for extra work, and a cut in taxes on income 

from capital can be expected to provide some incentive for additional savings and investment. 

The amount of growth a model predicts from a ten-percent tax cut is fairly sensitive to the size of 

the behavioral responses built into the model. In particular, the assumed responsiveness of labor 

supply can have a large influence on the extent of the short-run supply side effect on the 

economy. 

Fiscal and monetary policy response

A cut in individual income tax rates increases the amount of income available to 

individuals to purchase goods and services in the immediate short-run, thus providing a short-run 

stimulus in demand for the output of producers. Depending on whether the economy is already 

operating at capacity, this increased demand may primarily increase output and employment, or 

it may primarily increase prices. The Federal Reserve Board may react by increasing interest 

rates to combat expected inflation, or it may accommodate the increased demand. In the shortrun, different assumptions about the response of the Federal Reserve Board to the tax cut can 

have a large impact on the outcome of the simulations. 

The way the Federal government finances the reduction in tax revenues due to the tax cut 

can also have a significant effect on the predicted effects of the policy. If the Federal 

government is not operating with a fiscal surplus before the implementation of the tax cut, it will 

either have to borrow to finance the same real level of expenditures, or it will need to reduce 

spending or increase taxes in some other way. These Federal government choices regarding how 

much to borrow for how long, and what type of spending cuts or tax increases should be used to 

offset lost revenues from the tax cut can have significant effects on the size and timing of any 

growth effects resulting from the tax cut. The importance of this assumption depends on the type 

of model framework chosen for analysis.

 2

 For example, see Altonji, Joseph, “Intertemporal Substitution in Labor Supply: Evidence from 

Micro Data, Journal of Political Economy, v.94, no.3, 1986, pp. s176-s215; Boskin, Michael J., 

“Taxation, Saving, and the Rate of Interest,” Journal of Political Economy, v.86, no2, April 1978, pp.s3-

s28; Blundell, Richard and Thomas MaCurdy, “Labor Supply: A Review of Alternative Approaches, “ in 

Handbook of Labor Economics, Volume 3A, edited by Orley Ashenfelter and David Card, Amsterdam: 

North Holland, 1999; Congressional Budget Office, “Labor Supply and Taxes,” CBO Memorandum, 

January 1996; Engen, Eric M., William G. Gale, and John Karl Scholz; “Do Savings Incentives Work?’ 

Brookings Papers on Economic Activity, edited by Henry J. Aaron and William G. Gale, Washington, 

D.C. the Brookings Institution, 1996, pp. 83-121; Engen, Eric M., Jane Gravelle, and Kent Smetters, 

“Dynamic Tax Models: Why They Do the Things They Do,” National Tax Journal, v.50, no.3, 

September, 1997, pp. 657-82; Evans, Owen J., “Tax Policy, the Interest Elasticity of Saving, and Capital 

Accumulation: Numerical Analysis of Theoretical Models,” American Economic Review, v.73, no.3, 

June, 1983, pp. 398-410; and Prescott, Edward C., “Why Do Americans Work So Much More than 

Europeans?” Federal Reserve Bank of Minneapolis Quarterly Review, v. 28, no.1, July 2004, pp. 2-13. 
4 

B. Role of Modeling Assumptions 

Simulation results

In the first set of results, the Joint Committee staff used its macroeconomic equilibrium 

growth model3 (referred to as “MEG”) to examine the sensitivity of modeling results to different 

assumptions about labor supply responsiveness and monetary and fiscal policy responses.4 MEG 

models the long-run equilibrium growth path of the economy according to neoclassical growth 

theory, but it is also designed to include the effects of demand stimulus and monetary policy in 

simulating the short-run transition path in response to policy changes. The consumption and 

savings decision is made by a representative household that maximizes its desired consumption 

subject to a budget constraint. The labor supply response used in these simulations is modeled 

separately for four groups of workers: low-income primary earners, low-income secondary 

earners, moderate-and-high income primary earners, and moderate-and-high income secondary 

earners. “Low-income earners” are defined as earners who meet the income requirements for the 

earned income credit. Primary earners are assumed to be less responsive to decreases in 

marginal tax rates than secondary earners. Low-income earners are assumed to be more 

responsive to changes in tax rates than high income earners.5 Because of the sensitivity of 

growth effects to these parameters, these simulations were run with two sets of elasticities. The 

labor supply parameters used in these simulations are shown in Table 1.6

 3

 The Joint Committee on Taxation macroeconomic equilibrium growth model was developed 

for use in macroeconomic revenue analysis in consultation with Macroeconomic Advisers, LLC. 

4

 These simulations and their results are described in more detail in John Diamond and Pamela 

Moomau, “Issues in analyzing the Macroeconomic Effects of Tax Policy,” National Tax Journal, vol. 

LVI, no.3, September 2003, pp. 447-462. 

5

 It is important to note that there is a distinction between labor supply responsiveness and 

taxable income responsiveness. While studies of the responsiveness of taxable income to changes in tax 

rates have indicated that high income taxpayers appear to be more likely to make adjustments in taxable 

income through timing changes, portfolio adjustments, and other shifting behavior, the labor supply 

responsiveness of high income primary earners has been found to be lower than for others. See, for 

example, Emmanuel Saez, “Reported Incomes and Marginal Tax rates, 1960-2000: Evidence and Policy 

Implications,” National Bureau of Economic Research Working Paper 10273, 

www.nber.org/papers/w10273 regarding taxable income elasticities. See Chinhui Juhn, Kevin M. 

Murphy, and Robert H. Topel, “Why Has the Natural Rate of Unemployment Increased over Time? 

Brookings Papers on Economic Activity, 199(2), pp. 75-142 and Robert Moffitt and Mark Wilhelm, 

“Taxation and the Labor Supply Decisions of the Affluent,” Does Atlas Shrug? The Economic 

Consequences of Taxing the Rich, Joel Slemrod, ed., New York: Harvard University Press and Russell 

Sage Foundation, 2000 regarding labor supply responsiveness. 

6

 More detail about both models and their parameters used in these simulations may be found in 

Joint Committee on Taxation, Overview of the Work of the Staff of the Joint Committee on Taxation to 

Model the Macroeconomic Effects of Proposed Tax Legislation to Comply with House Rule XIII.h.2, 

December 22, 2002, JCX-105-03, pp.38-43. 
5 

Table 1.−Labor Supply Parameters 

Macroeconomic Equilibrium Growth Model 

Labor Supply Elasticities in Macroeconomic 

Equilibrium Growth Model 

Income Substitution Low Elasticity 

Substitution 

Low Income Primary -0.1 0.2 0.15 

Other Primary -0.1 0.1 0.1 

Low Income Secondary -0.3 0.8 0.4 

Other Secondary -0.2 0.6 0.3 

In order to test for the sensitivity of simulation results to short-run stimulus effects, these 

simulations are presented assuming two different types of monetary policy. The first assumes 

that the Federal Reserve Board reacts nearly instantaneously to counteract temporary demand 

stimulus, thus returning the economy quickly to equilibrium levels of employment and potential 

Gross Domestic Product. The second assumes that the Federal Reserve Board ignores changes 

in fiscal policy, and adheres to a fixed rate of money growth. 

Table 2 shows the range of results in terms of changes in growth in Gross Domestic 

Product depending on assumed labor supply elasticity, and monetary and fiscal policy reactions. 

Table 2.−Percent Change in Real GDP Due to Ten Percent Cut 

in Individual Income Tax Rates 

Using Macroeconomic Equilibrium Growth Model 

First 

Five 

Years 

Second 

Five 

Years 

Long 

Run 

First 

Five 

Years 

Second 

Five 

Years 

Long 

Run 

Modeling Assumptions Fed Targets Potential GDP Fed Targets Fixed Money Growth 

(a) Debt-Financed Cut 0.21 -0.50 -0.94 0.29 0.03 -0.87 

(b) Debt-Financed Cut, Low 

 Labor Elasticity 0.17 -0.07 -0.99 

0.29 0.03 -0.87 

(c) Concurrent G Decrease 0.33 0.30 0.64 0.26 0.28 0.64 

(d) Offsetting Tax Increase 

 After Ten Years 0.21 -0.05 -0.46 

0.32 0.05 -0.38 

Predictably, the growth effects of the tax cut are lower when lower labor responsiveness 

is assumed (row (b) of table), when monetary policy is conducted to counteract the demand 

stimulus of the tax cut (left half of table), and when the tax cut is financed through increasing 

government debt (all but row (c) on table). Within the first five years, the slightly lower labor 
6 

supply elasticity in the second simulation results in a nearly 25 percent reduction in forecast 

GDP growth than the higher elasticity projects. Less restrictive monetary policy results in 

almost one-third more GDP growth in the first five years. 

In the long run, the amount of growth predicted by the tax cut is crucially dependent on 

whether the cut is debt-financed, or financed by a cut in spending or future increase in taxes. 

Because decision-making in the MEG model is myopic, and thus individuals don’t see or react to 

coming fiscal crises, these alternate government finance simulations are of limited interest. They 

do produce the familiar result that tax cuts result in more growth when they are accompanied by 

simultaneous reductions in spending. 

More simulations using an overlapping generations lifecycle model7

 (referred to as 

“OLG”) provide additional information about the sensitivity of outcomes to fiscal policy 

response assumptions. In this model, consumption, savings, and labor supply are determined by 

utility-maximizing individuals represented by 55 cohorts of individuals who maximize 

consumption subject to a lifetime budget constraint (as opposed to the single period budget 

constraint in the MEG model). The labor supply choice is determined through the preference for 

leisure in the utility function. Results from these simulations are summarized on Table 3. 

Table 3.−Percent Change in Real GDP to Ten Percent Cut in Individual Rates 

Using Overlapping Generations Model 

Finance Assumption First Five 

Years 

Second Five 

Years 

Long 

Run 

(a) Cut in non-valued government 

 spending after ten years 0.17 0.02 -0.04 

(b) Cut in government transfer payments 

 after ten years 0.21 0.14 0.10 

(c) Increase in tax rate on labor income 

 after ten years 0.20 0.14 -0.10 

(d) Increase in tax rate on capital 

 income after fifteen years 0.18 0.05 -0.43 

(e) Cut in government transfer payments

 after twenty years 0.19 0.10 -0.21 

In contrast to behavior in the MEG model, in the OLG simulations, individuals can 

foresee changes in government spending or taxation after the ten-year tax cut policy period, and 

adjust their behavior immediately in response to these changes. In the OLG model anticipated 

cuts in future “non-valued” government spending will result in less growth over the first ten 

years relative to anticipated cuts in “valued” government transfer payments or anticipated 

 7

 The Joint Committee staff contracts with Tax Policy Advisers for the use of this OLG model, 

and works collaboratively with TPA on adapting it for Joint Committee needs. 
7 

increases in taxes on labor.8

 People work and save more over the first ten years in anticipation of 

a future loss of valued spending or tax increases, because they recognize the need to accumulate 

more assets against the anticipated lean period later in their life cycle. The farther in the future 

these increases are the longer the timeframe that individuals have to accumulate extra wealth, 

and the more muted these effects are on current labor supply and savings. 

Modeling extension

The range of results due to modeling assumptions presented above do not represent the 

entire spectrum of possible models or the entire range of assumptions about economic reactions 

to a tax cut. Another important model feature that has been shown to affect the results of 

macroeconomic tax policy simulations is whether or not the model includes international capital 

flows.9

 The more responsive savings are to changes in the after-tax return to capital, the more 

capital deepening and growth are likely to occur, even in the presence of debt financing of the 

tax cut. Alternatively, if the model includes an international sector, then rising interest rates in 

the U.S. attract foreign capital and there is an increase in investment, resulting in capital 

deepening and faster growth. The MEG model includes a simple international sector in the form 

of a second “rest of the world” economy, which reacts to simulated changes in the U.S. 

economy. Foreign capital is attracted to the U.S. when U.S. interest rates increase, and imports 

are stimulated by increasing consumption and prices in the U.S. Exchange rates adjust to bring 

the U.S. economy and the “rest of world” economy into purchasing power parity.

10

The OLG model used in the simulations above is a closed economy, relying on increases 

in savings to finance increased investments. A more recent version of the OLG model used by 

the Joint Committee staff includes a fairly rudimentary modeling of international capital, with 

international capital flowing into the U.S. economy in response to rising interest rates. However, 

in contrast to the MEG model, there is not a complimentary goods market in the OLG model. 

Unlike many “small, open economy” models with an interest-rate driven international capital 

flow, this module in OLG is not implemented by setting the after-tax interest rate equal to its prepolicy level. Instead, an interest rate elasticity determines foreign capital flows in an attempt to 

simulate a “large, open economy.” The Joint Committee staff is continuing to make further 

refinements of the international sector. Ideally, the OLG model would also include an 

international goods market as well as the capital market. 

 8

 “Non-valued” government spending is government spending that consumers don’t include in 

their calculation of personal utility. “Valued” government spending is modeled as directly increasing 

individuals’ disposable income - equivalent to transfer payments. 

9

 The role of international capital flows is explored in some detail in Joint Committee on 

Taxation, Joint Committee on Taxation Tax Modeling Project and 1997 Tax Symposium Papers, JCS-21-

97; see summary Table 5, pp. 32-33. 

10 Purchasing power parity is achieved when exchange rates between currencies allow for goods 

and services to be purchased at essentially the same price in each country. 
8 

C. Role of Tax Rate Aggregation and Model Calibration 

Simulation results

A perhaps little-known source of variation in macroeconomic simulation results is the 

way changes in effective tax rates are measured and translated into macroeconomic simulation 

models. The next set of simulation results will show that predicted growth and revenue feedback 

in models can change depending on how detailed the modeling of taxable income flows is within 

a model. 

The U.S. individual income tax is extremely complex, with a progressive rate structure, a 

plethora of deductions and tax credits targeted at large and small subsets of taxpayers, different 

tax rates on dividends and capital gains than on other sources of income, and the alternative 

minimum tax. Thus even the seemingly straightforward ten percent cut in all individual income 

tax rates can change effective tax rates for different individuals in different ways. 

The Joint Committee staff uses large microsimulation models based on a statistically 

matched sample of individual income tax returns and survey information from the Current 

Population Survey to simulate tax policy changes for individuals. For the ten-percent tax cut, it 

is a fairly simple exercise to obtain the change in marginal and average tax rates for each of the 

280,000 records on the merged tax and Current Population Survey microsimulation file, 

including changes in rates on business income that is taxed as flow-through to individuals.11 

This is in contrast to tax sectors in many macroeconomic simulation models, which are generally 

quite simple and stylized. Tax policy changes are implemented in macroeconomic models by 

determining how the policy changes tax rates in the model. Fewer different tax rates (more 

aggregation) in a model mean that fewer distinct tax sectors are separately modeled. 

Aggregation of tax rates into a single tax sector effectively uses an underlying assumption that 

all agents subject to that aggregate tax react in the same way to tax policy changes. 

However, there is a substantial amount of research that suggests individuals in different 

circumstances are likely to react differently to tax policy changes. In order to explore the 

importance of this concern in the modeling of tax policy, the Joint Committee staff uses the 

MEG model to simulate the ten-percent tax cut assuming different levels of tax rate 

aggregation.12 In contrast to the simulations presented above, all of the simulations presented in 

this portion of the paper assume the same set of labor supply elasticities, monetary policy and 

 11 Joint Committee staff makes use of a similar data base and tax calculator based on a large 

sample of corporate income tax returns to obtain marginal and effective tax rate changes from tax policy 

initiatives affecting corporations. This data set allows us to take account of the impact of net operating 

losses, special business credits, and the corporate alternative minimum tax in calculating effective 

corporate tax rates under specific proposals. 

12 These simulations and their results first appeared in Altshuler, Rosanne, Nicholas Bull, John 

Diamond, Timothy Dowd, and Pamela Moomau, “The Role of Dynamic Scoring in the Federal Budget 

Process,” American Economic Review: Papers and Proceedings, 95, no.2, May 2005. 
9 

government finance, so that the only source of variation in the results is the level of aggregation 

of tax rates in the model.13 

While the level of tax rate aggregation does affect the results of the ten-percent acrossthe-board tax cut, the relative simplicity of this proposal masks the importance the aggregation 

effect can have on proposals that affect only portions of income, or that have significantly 

different effects on average and marginal tax rates of people in different parts of the income 

distribution. For this reason, this analysis includes simulations of a ten-percent cut in wage taxes 

only, as well as of an increase in the personal exemption, which reduces tax liability without 

changing the marginal tax rate of most people. 

In the first set of simulations, there is only one average tax rate (“ATR”) in the model, 

determined by dividing taxable income in the initial period by receipts in the starting model 

period, which is usually the most recent time period for which historical data exist. This rate is 

used to represent the changes in tax rates in both the labor and investment behavioral equations, 

and in a single equation that determines total tax receipts. This single rate, single tax sector 

approach has been commonly used in econometric models that focus on modeling the effects of 

tax policy on short-run fluctuations in demand. It is not well-suited to simulating supply side 

effects because it fails to examine the effects of changes in marginal tax rates. 

In the second set of simulations, the change in average and marginal rates is separately 

calculated, allowing the simulation to account for possibly differential effects of the tax policy 

on after-tax income versus after-tax rate of return on income. But these simulations still require 

averaging of these effects across all taxpayers and sources of income for both behavioral effects 

and the determination of tax receipts. 

In the third set of simulations, there are separately calculated average and marginal tax 

rates (“MTRs”) for each of the seven income sources and four labor supply groups in the MEG 

model’s behavioral equations, but as in the first two simulations, a single average tax rate is 

applied to an aggregated, single measure of taxable income to determine tax receipts. For the 

two sets of primary and secondary workers that make up the four labor supply groups, the same 

average tax rate applies to the primary and secondary worker in each category, reflecting the fact 

that primary and secondary workers experience average tax rates as a family. The potential 

wages of the secondary workers are assumed to be added to the wages for the primary worker; 

thus marginal tax rates for secondary workers are somewhat higher than those for the primary 

workers. 

The aggregation of a single average tax rate for determining revenues is a simplifying 

assumption that is sometimes used in macroeconomic models because it allows for a relatively 

easy calibration between the income measures in the National Income and Product Account 

 13 Labor supply elasticities used in these simulations are those in the first two columns of Table 

1. It is assumed that the Federal Reserve Board targets fixed GDP and the Federal government debtfinances the tax cuts. 
10 

(“NIPA”) data used in most macroeconomic simulation models and taxable income as reported 

on income tax returns. 

In the fourth set of simulations, in addition to the separately calculated average and 

marginal tax rates for each income source and labor supply group in the MEG model’s 

behavioral equations, there are separate average tax rates for each income source in the revenue 

equations. This last step can have an important effect on projected changes in tax receipts. 

The effects of different levels of tax rate aggregation on projected economic growth are 

shown in Figure 1: 

Figure 1.−Percent Change in Real GDP Under Different Levels 

of Tax Rate Aggregation 

0.00%

0.05%

0.10%

0.15%

0.20%

0.25%

0.30%

0.35%

0.40%

Increase in Personal Exemption Ten Percent Cut in Wage Taxes Ten Percent Cut in Individual Income taxes

One ATR One ATR One MTR Multiple MTRs, one ATR for revenue Multiple ATRs and MTRs

The comparison of interest here is the influence of the level of tax rate aggregation on the 

results for each proposal. The GDP growth rate for the single tax average tax rate (the first bar in 

each group) differs the most from the other levels of aggregation for all three proposals. This is 

because of the inability of the single average tax rate to account for most likely supply side 

effects. For the increase in the personal exemption, which does not significantly affect marginal 

tax rates and therefore is where demand stimulus is the most likely engine of growth, the more 

aggregated measure produces more growth than the more detailed tax sectors. 
11 

Interestingly, for the ten-percent wage rate cut and the ten-percent across the board tax 

cut, the one average rate, one marginal rate aggregation produces more growth than the more 

detailed versions with multiple average and marginal tax rates. When the tax rate change is 

represented as a weighted average change that applies to the whole universe of taxpayers, it 

effectively attributes the incentive effects of the tax cut equally to all taxpayers, thus producing a 

phantom response from taxpayers that are not actually experiencing the tax cut being attributed 

to them. 

One of the major interests in dynamic analysis is in determining how much of the 

estimated revenue cost of a tax cut proposal might be offset by induced revenue growth due to 

GDP growth, often referred to as “revenue feedback.” The effects of different levels of tax rate 

aggregation on the estimated revenue feedback of the tax cuts are shown in Figure 2: 

Figure 2.−Percent Revenue Feedback Under Different Levels 

of Tax Rate Aggregation 

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

Increase in Personal Exemption Ten Percent Cut in Wage Taxes Ten Percent Cut in Individual Income

taxes

One ATR One ATR One MTR Multiple MTRs, one ATR for revenue Multiple MTRs and ATRs

The variation in revenue feedback between the different simulations by and large reflects 

the variation in GDP growth in the different simulations; those simulations producing more GDP 

growth generally also produce more revenue feedback. However, the most interesting contrast 

here is between the third and fourth simulations. For all the proposals, the GDP effects of the 

third and fourth simulations were virtually the same, as would be expected because they have the 

same tax rates in the behavioral equations. However, the revenue feedback varies depending on 

how detailed the revenue equations are. For the two proposals that affect some income sources 

more than others, the exemption increase and the wage tax cut, the revenue feedback from the 
12 

simulation with only one revenue equation is greater than the revenue feedback from the 

simulation with multiple revenue equations. The single aggregate revenue equation falsely 

attributes a change in the average tax rate to all sources of income, rather than the sources of 

income specifically affected by the proposal. In contrast, for the ten-percent across-the-board tax 

cut, the disaggregation of the revenue equation results in more revenue feedback than the single 

equations. 

Modeling extensions

For the variation in results that arise from different modeling assumptions described 

earlier in Part I.B, , there is no general agreement as to which of the various behavioral 

assumptions and modeling frameworks are more or less correct for use in analyzing tax policy. 

There is much less uncertainty as to which of the approaches to modeling tax sectors (described 

in this section) is the “correct approach.” The more disaggregation of tax sectors in a 

macrosimulation model, the more accurately the model is able to represent the change in tax 

policy that is being analyzed. Unfortunately, the more detail there is in an equilibrium 

macrosimulation model, the more difficult it is to develop a set of parameters and a solution 

algorithm that result in the model converging to the steady-state equilibrium that is necessary to 

produce simulation results. Typically, models that have multiple business sectors have only one 

household sector, and models with multiple household sectors have very simple business sectors. 

Thus, although the modeler might be reasonably certain about how the tax sector would be 

modeled ideally, it is still necessary to make choices as to which sectors to model separately, and 

many macroeconomic simulation models currently in use have sacrificed detail in tax modeling 

in order to incorporate detail about other aspects of the economy. 

The Joint Committee staff has disaggregated the tax equations in the macroeconomic 

simulation models we use, particularly the MEG model. Most recently, this effort has extended 

to improving the long-run forecast in the MEG model by iterating between the Joint Committee 

staff’s individual microsimulation model and the MEG model to allow long-run average and 

marginal tax rates to be determined by the interaction between present law tax policy and the 

expected path of income growth as projected by MEG. Because average and marginal tax rates 

affect the rate of growth in MEG, and the rate of growth affects average and marginal tax rates, it 

is necessary to iterate back and forth between the two models until there is convergence in the 

rates produced by each model. The models’ income flows are calibrated so that they are 

consistent with short- and long-run demographic forecasts from the Department of the Census. 

The analysis of cuts in the individual income tax presented above demonstrates that it is 

desirable to have models with more detail in the tax sectors for taxes on individuals. It is 

similarly desirable to have as much disaggregation as possible in the modeling of taxes on 

business. Currently both the MEG model and the OLG model have separate business, owneroccupied housing, and rental housing sectors. OLG also has fully separate corporate and noncorporate sectors, while MEG incorporates a portion of proprietors’ income into its cost of 

capital equations. One of the major planned modeling improvements will increase the number of 

business sectors in MEG, in order to allow analysis of a tax proposal that treats different business 

sectors differently. The simulations above showing the role tax rate aggregation plays in the 

analysis of individual income tax proposals demonstrates the importance of such an 

improvement.
13 

PART II − THE DEVELOPMENT OF MACROECONOMIC ANALYSIS OF 

TAX LEGISLATION AT THE JOINT COMMITTEE ON TAXATION 

A. Introduction 

This presentation discusses the development of macroeconomic analysis of tax legislation 

at the Joint Committee on Taxation. First, it provides background on revenue estimating. Next, 

it provides some history of the Joint Committee staff’s efforts to estimate the macroeconomic 

effects of tax proposals. And finally, it discusses some recent model developments and give a 

sense of some future developments the Joint Committee staff are considering or are working on. 

The Joint Committee staff is nonpartisan and serves the entire Congress. One of the JCT 

staff’s key responsibilities is to provide revenue estimates: These are estimates of the change in 

Federal receipts that would result from proposed tax legislation. The Joint Committee staff’s 

objective is to produce accurate, consistent, and impartial revenue estimates that can be relied 

upon by Members of Congress in making legislative decisions. For budget purposes, the 

Congressional Budget Act of 1974 (“the Budget Act”) stipulates that revenue estimates provided 

by the Joint Committee staff will be the official estimates for all tax legislation considered by the 

Congress. 
14 

B. Conventional Analysis 

What is a revenue estimate? 

What is a revenue estimate? A revenue estimate is an estimate of the change in projected 

Federal baseline receipts that would result from a change in law. The starting point for a revenue 

estimate prepared by the Joint Committee staff is the Congressional Budget Office (“CBO”) 10-

year projection of Federal receipts, referred to as the “receipts baseline.” The receipts baseline 

serves as the benchmark for measuring the effects of proposed tax law changes. The baseline 

assumes that present law remains unchanged during the 10-year budget period. Thus, the 

receipts baseline is an estimate of the Federal receipts that would be collected over the next 10 

years in the absence of statutory changes. The Joint Committee staff is required to estimate the 

revenue effects of proposals relative to the projected CBO receipts baseline. 

A common misunderstanding that arises in reporting revenue estimates to policy makers 

is the distinction between a revenue estimate and receipts forecast. Generally, when the 

economy is growing, the CBO forecast of baseline receipts is growing. A negative revenue 

estimate of a tax proposal does not mean that the Joint Committee is predicting receipts will fall. 

It means that receipts are predicted to grow more slowly if the proposal is enacted than they are 

projected to grow under present law in the baseline receipts forecast. Receipts would only 

decline if the revenue estimate were for a loss in revenues that was greater than the underlying 

growth in baseline receipts. 

For example, consider the Joint Committee staff’s estimates of the overall revenue effects 

of the Jobs and Growth Tax Relief Reconciliation Act of 2003 (“JGTRRA”). Figure 1 allows a 

comparison of CBO’s January 2003 forecast of receipts (the blue bars), the CBO’s forecasted 

receipts as modified by the Joint Committee staff’s estimates for JGTRRA (the red bars), and 

actual receipts (the green bars) for fiscal years 2002 through 2005. The red bars show that after 

adjusting the CBO’s receipts forecast for the Joint Committee staff’s estimate of JGTRRA, 

receipts were estimated to continue to increase. However, the estimated increase is slower than 

in the CBO’s original baseline forecast (the blue bars). In fact, actual receipts (the green bars) 

for 2003 through 2005 totaled $93 billion less than total receipts estimated by the Joint 

Committee staff (the red bars). 

Enactment of legislation in 2004 makes comparison using 2004 and 2005 receipts 

problematic. However, Figure 3 shows that, while the combined CBO/Joint Committee estimate 

of receipts for 2004 and 2005 is slightly less than actual receipts, it reflects a projected overall 

increase in receipts for these years relative to receipts prior to enactment of the legislation. 
15 

Figure 3.−Fiscal Year Federal Receipts in Billions of Current Dollars 

0.0

500.0

1,000.0

1,500.0

2,000.0

2,500.0

2002 2003 2004 2005 

CBO Forecast CBO plus JCT JGTRRA Estimate Federal Receipts Actual

Conventional analysis includes taxpayer behavior

Another frequently expressed misconception about conventional revenue estimates 

provided by Joint Committee staff is the notion that they assume taxpayers will not change their 

behavior in any way in response to tax policy changes. 

One of the conventions that is followed for both revenue estimates prepared by the Joint 

Committee staff and expenditure estimates prepared by the Congressional Budget Office is that 

they are done against a fixed forecast of aggregate economic activity; the Joint Committee staff 

generally assumes that a proposal will not change total aggregate production and therefore holds 

forecasted Gross National Product (“GNP”) fixed. However, conventional revenue estimates 

prepared by the Joint Committee staff should not be confused with “static” revenue estimates. 

Joint Committee staff revenue estimates always take into account many likely behavioral 

responses by taxpayers to proposed changes in tax law. Such behavioral effects incorporate or 

include shifts in the timing of transactions and income recognition, shifts between business 

sectors and entity form, shifts in portfolio holdings, shifts in consumption, and tax planning and 

avoidance strategies. 

To summarize Joint Committee staff’s conventional revenue estimating methodology: the 

Joint Committee staff provide estimates relative to baseline receipts projected for future years 

under present law, not relative to receipts in years prior to the enactment of the proposal; the 

Joint Committee staff generally assumes a fixed GNP forecast; and the Joint Committee staff 

incorporate many types of microeconomic behavioral responses in Joint Committee staff revenue 

estimates. 
16 

C. History of Joint Committee on Taxation Involvement 

in Macroeconomic Analysis 

The beginning: 1995

In January 1995, the Senate and House Budget Committees held a joint hearing to 

consider the feasibility of including macroeconomic effects in revenue estimates of tax 

legislation. The consensus of most of the speakers at that hearing was that, while in theory 

incorporating macroeconomic feedback effects in revenue estimates would be a good idea, in 

practice, the rudimentary state of macroeconomic modeling of tax policy made it infeasible. 

During the following spring, the Joint Committee staff on Taxation began studying and testing 

macroeconomic models to determine their usefulness in revenue estimation. To further this 

work, the Joint Committee staff hosted symposiums of respected macroeconomic modelers in 

1996 and 1997. 

1997 symposium 

On January 17, 1997, the Joint Committee staff hosted a symposium entitled “Modeling 

the Macroeconomic Consequences of Tax Policy.” This symposium presented the results of a 

year-long modeling experiment to explore the predictions of a variety of models regarding the 

macroeconomic feedback effects of fundamental tax reform, with a focus on evaluating the 

feasibility of using these types of results to enhance the U.S. budgeting process. Eleven 

macroeconomic modelers were invited to the symposium: each was asked to analyze the effects 

of two proposals, a broad-based unified income tax, and a broad-based consumption tax. 

Modelers were asked to calibrate their models to the same starting economic baseline, and to 

simulate similar proposals. 

There were a number of common results from this symposium. First, all of the models 

found that restructuring the U.S. tax system into a consumption-based tax resulted in increased 

economic growth in the long run. However, the size and timing of the increases in economic 

output varied considerably. For example, the increase in GDP after ten years ranged from a 0.7 

percent increase to a 16.4 percent increase. The substantial variation in results arose from 

different assumptions about the responsiveness of the households and producers to the changes 

in taxes, differences in modeling frameworks, and differences in the way the tax changes 

themselves were modeled in each different macro model. To make the results of the symposium 

accessible to Congressional staff and interested parties, the Joint Committee staff published the 

symposium papers and discussions.14 

 14 A complete description of the different models and their results can be found in Joint 

Committee on Taxation, Joint Committee on Taxation Tax Modeling Project and 1997 Tax Symposium 

Papers, JCS-21-97, November 20, 1997. 
17 

Modeling developments since 1997

Since the 1997 symposium, much of the Joint Committee staff’s developmental work has 

focused on enhancing and adapting standard models of the economy for use in the analysis of the 

macroeconomic effects of tax policy changes. Because different types of models have different 

strengths and weaknesses, the Joint Committee staff has worked to become proficient in the use 

of several types of modeling frameworks. 

The Joint Committee staff drew on the results from the symposium and began to 

standardize the methods for translating conventional estimates and tax changes into inputs for 

these macroeconomic models. In order to account for the complexities of the present-law 

Internal Revenue Code, much of the Joint Committee staff’s macroeconomic modeling work has 

involved enhancing and expanding tax-related equations in several types of macroeconomic 

models so that they can make better use of the wealth of information available from the Joint 

Committee microsimulation models. For example, most macroeconomic models start with a 

very rudimentary tax structure, in some cases just a single Federal tax rate. However, the 

microsimulation models, such as those long used by the Joint Committee staff, combine 

individual and business tax return data with tax calculators that provide detailed estimates of tax 

liability under current and proposed tax laws. These detailed microsimulation models allow for 

very specific average and marginal tax rates on different types of taxpayers and different types of 

income, which in turn may be incorporated in each macroeconomic model. In the late 1990’s the 

use of different average and marginal tax rates for different groups of taxpayers generally was 

absent from macroeconomic models. These computations provide the primary tax-related input 

to the macroeconomic models used by the Joint Committee staff. Use of microsimulation 

models to estimate changes in tax rates due to proposed law changes permits incorporating the 

effects of tax proposals in more detail than otherwise possible. A significant amount of variation 

in results can be traced to the way that tax rates are modeled in a macro model.15

Macroeconomic simulation models used by the Joint Committee staff

The most substantial effort with respect to macroeconomic simulation, conducted in 

consultation with a private contractor,16 has resulted in the development of the Joint Committee 

staff’s Macroeconomic Equilibrium Growth (“MEG”) model. In order to explore multiple 

perspectives on the economic modeling of tax policy, the Joint Committee staff has worked with 

several additional macroeconomic models. The most in-depth work involves the use of an 

overlapping generations lifecycle model (“OLG”).17 Key features of the MEG and OLG models 

were described in more detail in the discussion of modeling the effects of a ten-percent tax cut. 

 15 Altshuler, Rosanne, Nicholas Bull, John Diamond, Tim Dowd, and Pamela Moomau, “The 

Role of Dynamic Scoring in the Federal Budget Process: Closing the Gap between Theory and Practice,” 

American Economic Review volume 95, number 2, May 2005: 432-436. 

16 Macroeconomic Advisers, LLC provided initial developmental work for the MEG model. 

17 The OLG model is used pursuant to a contract with Tax Policy Advisers. 
18 

The Joint Committee staff also maintains service contracts with the distributors of two 

commercially available econometric models: the Global Insight model and the Macroeconomic 

Advisers model. 

Macroeconomic analysis of tax bills: information provided to Congress

In 2002, Joint Committee staff presented information about the models they were using 

and the results of numerous sets of simulations from these models to a panel of public finance 

and macro economists during three full-day sessions in June, October, and December. Staff 

from the House and Senate tax writing and budget committees as well as the staff from the Joint 

Economic Committee, the Congressional Budget Office, and the U.S. Treasury Office of Tax 

Analysis attended these sessions as observers. In 2003, the Joint Committee staff published a 

report on the sessions and the models and assumptions.18 

House Rule

A succession of rules passed by the House of Representatives have directed the Joint 

Committee staff to supplement conventional revenue estimates with an analysis of the 

macroeconomic impact of certain tax legislation. In 2003, this resulted in the first official 

macroeconomic analysis of tax legislation, analysis of H.R. 2, The Jobs and Growth Tax Act of 

2003, as reported by the House Ways and Means Committee on May 6, 2003. The 

macroeconomic analysis was inserted into the Congressional Record for Thursday, May 8, 2003 

in compliance with the House rule and in time to be available to Members of Congress for 

deliberation. An expanded version of this analysis is included in a December, 2003, Joint 

Committee on Taxation publication, JCX-105-03. 

Macro analysis of H.R. 2, the Jobs and Growth Tax Reconciliation Act of 2003 (“JGTRA”)

In that report, the Joint Committee staff found that H.R. 2 would likely stimulate the 

economy immediately after enactment by creating temporary incentives to increase work effort, 

business investment, and consumption. The simulations predicted that H.R. 2 would increase 

real GDP over the first six years by between 0.2 percent and 0.9 percent. The report also 

indicated that the anticipated stimulus would be reduced over time because the consumption, 

labor, and investment incentives are temporary, and because the positive business investment 

incentives arising from the tax policy change are eventually likely to be outweighed by the 

reduction in national savings due to increasing Federal government deficits. 

Other official statements Pursuant to the House Rule

Since the analysis of JGTRA, macroeconomic statements have been provided with 

respect to a number of tax bills in accordance with House rules. In general, these have been 

 18 Joint Committee on Taxation, Overview Of Work Of The Staff Of The Joint Committee On 

Taxation To Model The Macroeconomic Effects Of Proposed Tax Legislation To Comply With House 

Rule XIII.3.(h)(2), JCX-105-03, December 22, 2003. 
19 

bills that the Joint Committee staff’s macroeconomic modeling indicated would have an effect 

on the macro economy so small as to be incalculable in the context of a macroeconomic model. 
20 

D. Recent Exploration and Developments in Macroeconomic 

Analysis by the Joint Committee Staff 

Modeling issues explored by the Joint Committee staff

Over the last several years, the Joint Committee staff has completed a number of analyses 

and presented their results both in written reports and in various different forums, both technical 

and non-technical. These presentations and reports have provided a forum for a professional 

dialogue about the Joint Committee staff’s models and provide the staff with technical feedback 

about its methodologies. The following is a description of some of these presentations and 

reports. 

Joint Committee staff presented work on analyzing a ten-percent across the board tax cut 

at the spring 2003 meetings of the National Tax Association.19 The analysis found that there is a 

considerable amount of uncertainty about the macroeconomic effects of ten-percent across the 

board rate cut. 

In the fall of 2004 at the National Bureau of Economic Research (“NBER”) working 

group on behavioral effects of tax policy, and at the spring 2005 National Tax Association 

symposium, Joint Committee staff presented work on the feasibility of incorporating a fiscal 

policy reaction function in macro models.20 Often, when analyzing tax policy, macroeconomic 

models need to close the budget gap that results from a tax cut. One potential mechanism that is 

often suggested for closing the budget gap is to econometrically estimate a fiscal policy reaction 

function that reproduces the legislative responses to fiscal gaps. The paper found that fiscal 

policy reaction functions that are consistent with econometrically estimated equations in the 

economics literature, can both return the Federal government to a sustainable fiscal situation and 

can result in a continuation of increasing Federal debt, depending on arbitrary assumptions of 

how to implement the fiscal policy reaction function in the macro model. 

In the spring of 2005 at the NBER working group on behavioral effects of tax policy, 

Joint Committee staff presented work on the dynamic revenue effects of a reduction in capital 

and labor tax rates following the work of a widely reported paper by Mankiw and Weinzierl.21 

 19 Diamond, John W. and Pamela H. Moomau “Issues Analyzing the Macroeconomic Effects of 

Tax Policy,” National Tax Journal Volume LVI, Number 3, September, 2003, 447-462. 

20 Bull, Nicholas, and Timothy Dowd, “Use of Fiscal Policy Reaction Function in Analyzing the 

Macroeconomic Effects of Tax Policy,” National Tax Journal, Volume LVIII, Number 3, September 

2005, 373-390. 

21 Mankiw, N. Gregory, and Mathew Weinzierl, “Dynamic Scoring: A Back of the Envelope 

Guide,” NBER Working Papers, December 2004, No. 11000. In collaboration with Eric Leeper of Indiana 

University, the Joint Committee staff’s work has been circulated as an NBER working paper, Leeper, 

Eric, and Susan Yang, “Dynamic Scoring: Alternative Financing Schemes,” NBER Working Papers, 

February 2006, No. 12103. 
21 

The paper uses a neoclassical growth model to evaluate the effects of bond-financed tax 

reductions that eventually result in adjustments in future government consumption, transfers, 

capital tax rates, or labor tax rates. It finds that Mankiw and Weinzierl’s result can change 

substantially under a different financing mechanism for a tax cut. 

In January of 2005 at the American Economics Association meetings, the Joint 

Committee staff presented work investigating the range of effects from increasing disaggregation 

of tax parameters in macro models.22 

Also in 2005 at the request of Chairman Thomas, in order to provide Congress with 

information about the differential effects on the economy of different types of tax policy, Joint 

Committee staff presented work on estimating the macroeconomic effects of three different 

proposals all with a conventional revenue effect of $500 billion.23 The three proposals are a 

decrease in individual income tax rates, an increase in the personal exemption, and a decrease in 

the corporate income tax rate. Despite the fact that each of these tax cuts reduces revenues by the 

same amount according to conventional revenue estimates, their effects on the economy vary 

greatly, both within the ten-year budget planning horizon and in the longer run. For example, 

using the same model assumptions and assuming contemporaneous reduction in government 

expenditures, the estimated range of effects on real GDP in the long run were from 0.2 for the 

increase in the personal exemption, to 0.4 and 0.9 for the reduction in individual and corporate 

tax rates, respectively. Moreover, the range of results includes negative long-run effects when 

there is not a contemporaneous decrease in government expenditures. 

In this study, the Joint Committee staff experimented with ways to make this comparative 

information easily accessible, presenting the results in a series of graphs showing the different 

growth paths generated by the tax cuts, in addition to providing more precise information in the 

tables than had been provided in previous reports. One of the challenges in the graphic 

presentation is providing both information about the different effects of the different types of 

proposals, and providing information about the sensitivity of the results to differing modeling 

assumptions. The graph below presents the percent change in real GDP from the baseline. As 

can be seen in the graph, the corporate rate cut resulted in more economic growth for a longer 

period of time. 

 22 Altshuler, Rosanne, Nicholas Bull, John Diamond, Tim Dowd, and Pamela Moomau, “The 

Role of Dynamic Scoring in the Federal Budget Process: Closing the Gap between Theory and Practice,” 

American Economic Review volume 95, number 2, May 2005: 432-436. 

23 Joint Committee on Taxation, Macroeconomic Analysis of Various Proposals to Provide $500 

Billion in Tax Relief, (JCX-4-05), March 1, 2005. 
22 

Figure 4.−Percent Change from Baseline in Real GDP: 

No Fiscal Offset; Aggressive Fed Policy 

Areas for Further Development

Recently, the Joint Committee staff has been developing an infinite agent neo-classical 

growth model for tax analysis. It is a dynamic stochastic general equilibrium model with full 

microeconomic foundations. Developmental work on this model is continuing. The Joint 

Committee staff hope to use this new model to address issues relating to anticipation effects and 

distributional effects of tax policy. 

There are a number of other areas for continued research, including, but not limited to, 

the introduction of human capital and imperfect competition into the models. The introduction 

of each of these could have profound impacts on the type of results that the models find from 

different types of tax policies. 
23 

E. Conclusion 

For the past ten years the Joint Committee staff has been investigating the ability to use 

macroeconomic models incorporating sophisticated tax modeling to provide information to 

Members of Congress as part of the tax legislative process. During this time the Joint 

Committee staff has convened respected macroeconomic modelers and public finance experts to 

understand the intricate details of various models; identified, developed, and enhanced models 

that are appropriate for analyzing tax policy; and continued to improve the models and adapt 

them to specific tax policy proposals. In this process the Joint Committee staff has highlighted 

the importance of disaggregated tax policy variables and calibration methods in the modeling of 

tax policy. More recently, under the House rule the Joint Committee has provided 

macroeconomic analysis, including sensitivity analysis, on legislation where there is a sizeable 

macroeconomic effect capable of being modeled.