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

S-Tier
Journal: American Economic Review
Year: 2017
Volume: 107
Issue: 5
Pages: 471-75

Authors (6)

John Guyton (not in RePEc) Pat Langetieg (not in RePEc) Day Manoli (Georgetown University) Mark Payne (not in RePEc) Brenda Schafer (not in RePEc) Michael Sebastiani (not in RePEc)

Score contribution per author:

1.341 = (α=2.01 / 6 authors) × 4.0x S-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

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.

Technical Details

RePEc Handle
repec:aea:aecrev:v:107:y:2017:i:5:p:471-75
Journal Field
General
Author Count
6
Added to Database
2026-01-25