Using Differences in Knowledge Across Neighborhoods to Uncover the Impacts of the EITC on Earnings

77 Pages Posted: 21 Jul 2012

See all articles by Raj Chetty

Raj Chetty

Harvard University

John Friedman

Brown University

John N. Friedman

Harvard University - Harvard Kennedy School (HKS); National Bureau of Economic Research (NBER)

Emmanuel Saez

University of California, Berkeley - Department of Economics; National Bureau of Economic Research (NBER)

Date Written: July 2012

Abstract

We develop a new method of estimating the impacts of tax policies that uses areas with little knowledge about the policy's marginal incentives as counterfactuals for behavior in the absence of the policy. We apply this method to characterize the impacts of the Earned Income Tax Credit (EITC) on earnings using administrative tax records covering all EITC-eligible filers from 1996-2009. We begin by developing a proxy for local knowledge about the EITC schedule -the degree of "sharp bunching"at the exact income level that maximizes EITC refunds by individuals who report self-employment income. The degree of self-employed sharp bunching varies significantly across geographical areas in a manner consistent with differences in knowledge. For instance, individuals who move to higher-bunching areas start to report incomes closer to the refund-maximizing level themselves, while those who move to lower-bunching areas do not. Using this proxy for knowledge, we compare W-2 wage earnings distributions across neighborhoods to uncover the impact of the EITC on real earnings. Areas with high self-employed sharp bunching (i.e., high knowledge) exhibit more mass in their W-2 wage earnings distributions around the EITC plateau. Using a quasi-experimental design that accounts for unobservable differences across neighborhoods, we find that changes in EITC incentives triggered by the birth of a child lead to larger wage earnings responses in higher bunching neighborhoods. The increase in EITC refunds comes primarily from intensive-margin increases in earnings in the phase-in region rather than reductions in earnings in the phase-out region. The increase in EITC refunds is commensurate to a phase-in earnings elasticity of 0.21 on average across the U.S. and 0.58 in high-knowledge neighborhoods.

Suggested Citation

Chetty, Raj and Friedman, John and Friedman, John Norton and Saez, Emmanuel, Using Differences in Knowledge Across Neighborhoods to Uncover the Impacts of the EITC on Earnings (July 2012). NBER Working Paper No. w18232. Available at SSRN: https://ssrn.com/abstract=2114858

Raj Chetty (Contact Author)

Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

John Friedman

Brown University ( email )

Box 1860
Providence, RI 02912
United States

John Norton Friedman

Harvard University - Harvard Kennedy School (HKS) ( email )

79 John F. Kennedy Street
Cambridge, MA 02138
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Emmanuel Saez

University of California, Berkeley - Department of Economics ( email )

549 Evans Hall #3880
Berkeley, CA 94720-3880
United States
510-642-4631 (Phone)
510-642-6615 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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