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Reminders and Recidivism: Using Administrative Data to Characterize Nonfilers and Conduct EITC Outreach

John Guyton, Pat Langetieg, Dayanand Manoli, Mark Payne, Brenda Schafer and Michael Sebastiani

American Economic Review, 2017, vol. 107, issue 5, 471-75

Abstract: This project uses third-party information reporting and population-level administrative tax data to identify the population of nonfilers. This population consists of individuals who do not file a tax return despite having income reported by third parties to the United States Internal Revenue Service. After identifying and characterizing this population, we identified nonfilers who may have been eligible for Earned Income Tax Credit (EITC) benefits. Using an experimental sample drawn from this population of potentially EITC-eligible nonfilers, we conducted two randomized controlled trials to test multiple hypotheses regarding inattention and recency effects in these low-income earners' tax filing decisions.

JEL-codes: D12 H24 H26 I32 K34 (search for similar items in EconPapers)
Date: 2017
Note: DOI: 10.1257/aer.p20171062
References: Add references at CitEc
Citations: View citations in EconPapers (9)

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