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

By Raj Chetty, John N. Friedman, Emmanuel Saez. 2013

559 citations recorded by the source corpus.

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.

Subfields: Accounting, Economics and Econometrics, Gender Studies

View Paper: https://www.semanticscholar.org/paper/43f4aadf2b7f46f3ca49df0c30e6e1ca08648982

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Citations in the corpus

Cycling to School: Increasing Secondary School Enrollment for Girls in India (2013, unknown): “(JEL H42, I21, I28, J16, O15, O18)”
The Long-Term Consequences of Teacher Discretion in Grading of High-Stakes Tests (2016, background): “and/or ends (Saez, 2010; Chetty et al., 2011; Kleven and Waseem, 2012). 2This type of idea has related, although distinct, predecessors in the literature. Chetty et al. (2013) use bunching as an “instrument” (but implemented as a reduced form) for information about tax incentives, and Marx (2015) us”
Failure to Refinance (2016, unknown): “…information that would allow us to determine the exact mechanism for spatial heterogeneity [e.g., we do not observe the originating lender in our data; we also cannot track individuals as they move from one location to another to test for peer effects as in Chetty, Friedman, and Saez (2013) ].”
The Policy Elasticity (2016, background): “54A further defense of this assumption is found in the EITC papers using single women without children as a control group (e.g. Eissa and Liebman (1996); Chetty et al. (2013)).”
Shaming tax delinquents (2015, unknown): “share of self-employed individuals in the 3-digit ZIP code estimated to be mis-reporting income to take advantage of EITC benefits (Chetty et al., 2013).”
The impact of redistributive policies on inequality in OECD countries (2012, unknown): “As recent evidence has shown, the introduction of the EITC in the US, an in-work benefit programme targeted at the bottom of the distribution, has effectively reduced inequality without large disincentive effects (Chetty et al., 2013).”
The interest rate elasticity of mortgage demand: Evidence from bunching at the conforming loan limit (2017, methodology): “For example, Saez (2010), Chetty et al. (2011), Chetty et al. (2013), and Gelber et al. (2013) study labor supply and earnings responses to kinked income tax and social security benefit schedules.”
Social Insurance: Connecting Theory to Data (2012, background): “Coate (1995) demonstrates that the optimal transfer policy therefore involves in-kind transfers of insurance to address the ine¢ cient under-insurance that arises in response to unconditional transfers.”
Inference in Regression Discontinuity Designs with a Discrete Running Variable (2016, unknown): “…economics journals that follow this methodology include Oreopoulos (2006), Card et al. (2008), Urquiola and Verhoogen (2009), Martorell and McFarlin (2011), Fredriksson et al. (2013), Chetty et al. (2013), Clark and Royer (2013), and Hinnerich and Pettersson-Lidbom (2014), among many others.”
Psychological Frictions and the Incomplete Take-Up of Social Benefits: Evidence from an IRS Field Experiment (2015, background): “…programs , these limits imply that the failure to claim may be a consequence of low program awareness (e.g., Chetty, Friedman, and Saez 2013; Chetty and Saez 2013; Smeeding, Phillips, and O'Connor 2000), confusion regarding program rules or incentives (e.g., Liebman and Zeckhauser 2004),…”
The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects (2018, methodology): “an equation analogous to equation (1), including a quadratic term in parental income rank p to account for the nonlinearities in tail outcomes identified in Chetty et al. (2014). We then calculate the predicted probability of being nonemployed πU pcs and being above the 90th percentile π90 pcs using”
Taking State-Capacity Research to the Field: Insights from Collaborations with Tax Authorities (2019, unknown): “Chetty et al. (2013) study the effect of the EITC on wage earnings.”