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The Urban-Brookings Tax Policy Center Microsimulation Model

Documentation and Methodology for Version 0304

Jeff Rohaly, Adam Carasso, Mohammed Adeel Saleem

Published: January 10, 2005
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The nonpartisan Urban Institute publishes studies, reports, and books on timely topics worthy of public consideration. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders.

Note: This report is available in its entirety in the Portable Document Format (PDF).


A. Introduction

The Urban-Brookings microsimulation tax model is a powerful tool for federal tax policy analysis.1 The model calculates tax liability for a representative sample of households, both under the rules that currently exist (current law) and under alternative scenarios. Based on these calculations, the model produces estimates of the revenue consequences of different tax policy choices, as well as their effects on the distribution of tax liabilities and marginal effective tax rates (which affect incentives to work, save, and shelter income from tax). The model is also a useful input to research on the effects of taxation on economic behavior.

Overview

The Urban-Brookings Tax Policy Center model is a large-scale microsimulation model of the U.S. federal tax system. The model is similar to those used by the Congressional Budget Office (CBO), the Joint Committee on Taxation (JCT), and the Treasury's Office of Tax Analysis (OTA).

As its name suggests, a microsimulation model uses microdata—or data on individual units—rather than aggregate information.2 In general, input data are comprised of detailed information at the individual or household level that may be used to calculate tax liability. The sample includes weights that represent how many units are represented by the individual record.3 Estimates for the entire population may then be derived by multiplying the individual estimates by the sample weights and summing them.

In the case of the tax model, the population is the universe of individuals who file income tax returns as well as those individuals whose incomes are too low to require them to file a return ("nonfilers"). The data are a stratified sample of individual income tax returns augmented by information about nonfilers (see discussion below). The tax-calculator portion of the model then applies applicable tax law to each of the individual records in the microdata file and calculates values for variables such as adjusted gross income (AGI), nonrefundable credits, individual income tax liability, and so on. The values of the variables calculated for each individual record are then multiplied by the weight associated with that record to tabulate aggregate results such as total income tax liability for the entire population.

The tax model is not only able to calculate tax liability under current tax law but is also able to simulate alternative policy proposals. It is therefore straightforward to calculate the change in aggregate tax liability from a tax policy proposal and also to determine which class of individuals would benefit from or bear the burden of the tax change.4

The tax model also has the ability to produce estimates for years beyond the year of the input data file (currently 1999). This is made possible by "aging" the individual records in the microdata file. In the aging process, the information on each record—such as the amount of wages and salaries and other forms of income—as well as the weights associated with each record are adjusted based on forecasts from several sources including CBO and the Bureau of the Census.

History

The TPC produced the first version of its microsimulation tax model in 2002.5 Some of the early research that used estimates produced by the model included an analysis of the effects of the Economic Growth and Tax Relief Reconciliation Act of 2001 (EGTRRA) on low-income families and children as well as a detailed study on the looming problem of the alternative minimum tax (AMT).6

A more comprehensive version of the tax model was put in place in the spring of 2003. This updated version improved the original model and expanded its scope in several ways. First, we updated the input data to incorporate the most recent microdata file available from the IRS. Second, we updated our projections and forecasts using the latest economic data available from CBO. Finally, we added the capability to carry out distributional analysis on the entire population by adding nonfilers for the first time, through a statistical match with the Current Population Survey (CPS).

The most recent version of the model was developed in March 2004 and includes the latest economic forecasts from CBO as well as several model enhancements. First, we added a retirement savings module that, among other things, imputes contributions to tax-deferred savings vehicles such as IRAs (both traditional and Roth) and 401(k) plans. Second, we added an estate tax module to the model that allows us to calculate the expected value of net estate tax liability for each record in the tax model database. We also began distributing the burden of the corporate income tax to individuals. Through these improvements, the distribution tables produced by the TPC now include the following federal taxes that in 2003 accounted for about 93 percent of all federal tax revenues: individual and corporate income; payroll; and estate (CBO 2004). Third, we developed two measures of income for our distribution tables that are broader than adjusted gross income (AGI), the qualifier that we used in tables produced by the first two versions of our model. One measure is similar to the income concepts used by Treasury, JCT, and CBO; the other is a broad measure of economic income similar to the one used at Treasury until 2001.

We are currently producing an education module for the model that will allow us to estimate the revenue and distributional effects of the various education provisions in the tax code. We will also continue to update the model using the latest economic and demographic forecasts and projections, as well as the latest microdata released by the IRS.

Notes from this section

1. This document details the methodology underlying version 0304 of the model, which was developed in March 2004. The Tax Policy Center will publish revised versions of this paper as it updates the model.

2. For a detailed explanation of microsimulation models, see http://trim.urban.org

3. The weights equal the inverse of the sampling probability. Thus, for example, if a record was sampled at a rate of 1 in 1,000 (so the probability equals 0.001), the sample weight would be 1,000. In other words, that record represents 1,000 individuals or households.

4. We note two items here: (1) static versus dynamic estimates and (2) statutory versus economic incidence. First, the revenue estimates produced by the model are purely static in nature. A static revenue change ignores the impact of any change in behavior that a policy proposal could cause and also does not take into account any macroeconomic effects of the proposal. For example, an increase in the top statutory marginal tax rate could cause a shift in compensation away from taxable wages and salaries toward untaxed fringe benefits. A purely static analysis would not capture this effect and would likely overestimate the potential revenue gain. Revenue estimates produced by JCT typically include the effect of behavioral changes but not the macroeconomic feedback effects. Behavioral responses can also change the burden of a tax change. For example, the burden of a tax increase on individuals may be smaller than the static change in tax because taxpayers change their behavior to avoid the tax. Thus, static distributional tables tend to overestimate the economic burden of tax increases and underestimate the burden of tax cuts.

Second, burden estimates reflect the statutory incidence—that is, the direct effect on individuals who pay the tax. The economic incidence of the tax may be different. For example, wage subsidies such as the earned income tax credit (EITC) may partially benefit employers who may be able to pay EITC recipients a lower wage. In that case, the economic incidence of the tax would be shared between the direct recipients (low-wage workers) and the indirect beneficiaries (their employers).

5. John O'Hare and Frank Sammartino were instrumental in developing and programming this first version of the model.

6. See Burman, Maag, and Rohaly (2002) and Burman et al. (2002).


Note: This report is available in its entirety in the Portable Document Format (PDF).