Are Sufficient Statistics Necessary? Nonparametric Measurement of Deadweight Loss from Unemployment Insurance

• 成果类型: Article
• 署名作者: Lee, David S.; Leung, Pauline; O'Leary, Christopher J.; Pei, Zhuan; Quach, Simon
• 署名单位: Princeton University; National Bureau of Economic Research; Cornell University; W.E. Upjohn Institute for Employment Research
• 刊物名称: JOURNAL OF LABOR ECONOMICS
• ISSN/ISSBN: 0734-306X
• DOI: 10.1086/711594
• 发表日期: 2021
• 页码: S455-S506
• 关键词: marginal tax rates; taxable income; benefits; incentives; duration; DESIGN; takeup; wages

摘要

Central to the welfare analysis of income transfer programs is the deadweight loss associated with possible reforms. To aid analytical tractability, its measurement typically requires specifying a simplified model of behavior. We employ a complementary decomposition approach that compares the behavioral and mechanical components of a policy's total impact on the government budget to study the deadweight loss of two unemployment insurance policies. Experimental and quasi-experimental estimates using state administrative data show that increasing the weekly benefit is more efficient (with a fiscal externality of 53 cents per dollar of mechanical transferred income) than reducing the program's implicit earnings tax.