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

Author

Listed:
  • Raj Chetty
  • John N. Friedman
  • Emmanuel Saez

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

  • Raj Chetty & John N. Friedman & Emmanuel Saez, 2012. "Using Differences in Knowledge Across Neighborhoods to Uncover the Impacts of the EITC on Earnings," NBER Working Papers 18232, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:18232
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    References listed on IDEAS

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    1. Bises, Bruno, 1990. "Income Tax Perception and Labour Supply in a Sample of Industry Workers," Public Finance = Finances publiques, , vol. 45(1), pages 3-17.
    2. Kopczuk, Wojciech & Pop-Eleches, Cristian, 2007. "Electronic filing, tax preparers and participation in the Earned Income Tax Credit," Journal of Public Economics, Elsevier, vol. 91(7-8), pages 1351-1367, August.
    3. Henrik Jacobsen Kleven & Claus Thustrup Kreiner & Emmanuel Saez, 2016. "Why Can Modern Governments Tax So Much? An Agency Model of Firms as Fiscal Intermediaries," Economica, London School of Economics and Political Science, vol. 83(330), pages 219-246, April.
    4. Raj Chetty, 2012. "Bounds on Elasticities With Optimization Frictions: A Synthesis of Micro and Macro Evidence on Labor Supply," Econometrica, Econometric Society, vol. 80(3), pages 969-1018, May.
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    More about this item

    JEL classification:

    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household

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