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

• 成果类型: Article
• 署名作者: Chetty, Raj; Friedman, John N.; Saez, Emmanuel
• 署名单位: Harvard University; National Bureau of Economic Research; Harvard University; University of California System; University of California Berkeley
• 刊物名称: AMERICAN ECONOMIC REVIEW
• ISSN/ISSBN: 0002-8282
• DOI: 10.1257/aer.103.7.2683
• 发表日期: 2013
• 页码: 2683-2721
• 关键词: income-tax credit; optimization frictions; LABOR; elasticities; welfare; micro

摘要

We estimate the impacts of the Earned Income Tax Credit on labor supply using local variation in knowledge about the EITC schedule. We proxy for EITC knowledge in a Zip code with the fraction of individuals who manipulate reported self-employment income to maximize their EITC refund. This measure varies significantly across areas. We exploit changes in EITC eligibility at the birth of a child to estimate labor supply effects. Individuals in high-knowledge areas change wage earnings sharply to obtain larger EITC refunds relative to those in low-knowledge areas. These responses come primarily from intensive-margin earnings increases in the phase-in region.