CRS has recently begun using two open-source microsimulation tax models to estimate the revenue effects of changes to federal tax law: the Budget Lab at Yale’s (TBL’s) Tax-Simulator and the Policy Simulation Library’s (PSL’s) Tax-Calculator. CRS uses these models to assist congressional offices early in the legislative process during work to inform congressional deliberations on tax policy. Any estimates produced by CRS are not considered official for revenue “scoring” purposes or compliance with budgetary rules. The Joint Committee on Taxation (JCT) is the official tax revenue estimator for Congress. CRS serves as shared staff to congressional committees and Members of Congress. The ability to provide unofficial revenue estimates contributes to the CRS mission of providing timely support to Congress throughout the legislative process. This report first compares the two microsimulation models’ estimates of selected tax expenditures with corresponding tax expenditure estimates published by the JCT. Second, it presents and compares both models’ estimates of 11 hypothetical individual, payroll, and pass-through business tax changes. CRS selected these changes to demonstrate modeling capabilities across a broad range of potential policy options, and they are not intended to represent the estimated cost of any specific legislative proposal that has been introduced. Third, the report discusses how the models’ aggregate baseline projections of individual income tax and payroll tax revenue compare with the Congressional Budget Office’s (CBO’s) projections and why they do not compare directly to one another. The report concludes with a brief discussion of the modeling limitations and considerations. Estimating the revenue effects of changes to the federal tax code is inherently difficult. Microsimulation models like Tax-Simulator and Tax-Calculator combine a representative sample of taxpayer records (typically the IRS’s 2015 Public Use File [PUF], supplemented and aged forward) with detailed tax-law calculators that apply current and alternative tax law scenarios to generate estimates. Differences in estimates across models can arise from differences in the assumptions used to age the data and impute missing data, the revenue baseline against which the estimates are computed, and the behavioral assumptions used to model taxpayer response to tax law changes. Differences between the models’ estimates and the JCT estimates can be attributed to some of these same factors, along with the fact that the JCT has access to more recent confidential taxpayer data. The revenue estimates produced by the TBL and PSL models may be useful to congressional offices as they draft or evaluate tax policy changes, particularly early in the legislative process when JCT estimates may not yet be available. The models are likely to produce results most comparable to potential JCT estimates when analyzing changes to broad features of the tax code, such as the marginal rate structure or income thresholds. The models’ results may differ more substantially from the JCT’s when estimating provisions relying on microdata that require significant data imputation and aging due to the models’ use of a more dated primary data source (the 2015 PUF).
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