The Accuracy of Tax Imputations: Estimating Tax Liabilities and Credits Using Linked Survey and Administrative Data

83 Pages Posted: 23 Dec 2020 Last revised: 18 Feb 2021

See all articles by Bruce Meyer

Bruce Meyer

University of Chicago

Derek Wu

University of Chicago - Harris School of Public Policy

Grace Finley

Harvard University

Patrick Langetieg

Government of the United States of America - Internal Revenue Service (IRS)

Carla Medalia

U.S. Census Bureau

Mark Payne

Government of the United States of America - Internal Revenue Service (IRS)

Alan Plumley

Government of the United States of America - Internal Revenue Service (IRS)

Date Written: December 2020

Abstract

This paper calculates accurate estimates of income and payroll taxes using a groundbreaking set of linked survey and administrative tax data that are part of the Comprehensive Income Dataset (CID). We compare our estimates to survey imputations produced by the Census Bureau and those generated using the TAXSIM calculator from the National Bureau of Economic Research. The administrative data include two sets of Internal Revenue Service (IRS) data: (1) a limited set of tax information for the population of individual income tax returns covering selected line items from Forms 1040, W-2, and 1099-R; and (2) an extensive set of population tax records processed by the IRS in 2011, covering nearly every line item on Form 1040 and most lines on a series of third-party information returns. We link these IRS records to the Current Population Survey Annual Social and Economic Supplement (CPS) for reference year 2010. We describe how we form tax units and estimate various types of tax liabilities and credits using these linked data, providing a roadmap for constructing accurate measures of taxes while preserving the survey family as the sharing unit for distributional analyses. We find that aggregate estimates of various tax components using the limited and extensive tax data estimates are close to each other and much closer to public IRS tabulations than either of the imputations using survey data alone. At the individual level, the absolute errors of survey-only imputations of federal income taxes and total taxes are on average 10% and 13%, respectively, of adjusted gross income. In contrast, the limited tax data imputations yield mean absolute errors for federal income taxes and total taxes that are about 2% and 3% of adjusted gross income, respectively. For the Earned Income Tax Credit, the limited tax data imputation is off by less than $20 on average for a typical family (compared to more than $500 using either of the survey-only imputations).

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Suggested Citation

Meyer, Bruce and Wu, Derek and Finley, Grace and Langetieg, Patrick and Medalia, Carla and Payne, Mark and Plumley, Alan, The Accuracy of Tax Imputations: Estimating Tax Liabilities and Credits Using Linked Survey and Administrative Data (December 2020). NBER Working Paper No. w28229, Available at SSRN: https://ssrn.com/abstract=3753139

Bruce Meyer (Contact Author)

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

Derek Wu

University of Chicago - Harris School of Public Policy ( email )

1155 East 60th Street
Chicago, IL 60637
United States

Grace Finley

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Patrick Langetieg

Government of the United States of America - Internal Revenue Service (IRS) ( email )

1111 Constitution Avenue, NW
Washington, DC 20224
United States

Carla Medalia

U.S. Census Bureau ( email )

4600 Silver Hill Road
D.C., WA 20233
United States

Mark Payne

Government of the United States of America - Internal Revenue Service (IRS) ( email )

1111 Constitution Avenue, NW
Washington, DC 20224
United States

Alan Plumley

Government of the United States of America - Internal Revenue Service (IRS) ( email )

1111 Constitution Avenue, NW
Washington, DC 20224
United States

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