Estimating Adjustment Frictions Using Nonlinear Budget Sets: Method and Evidence from the Earnings Test

• 成果类型: Article
• 署名作者: Gelber, Alexander M.; Jones, Damon; Sacks, Daniel W.
• 署名单位: University of California System; University of California San Diego; National Bureau of Economic Research; University of Chicago; Indiana University System; IU Kelley School of Business; Indiana University Bloomington
• 刊物名称: AMERICAN ECONOMIC JOURNAL-APPLIED ECONOMICS
• ISSN/ISSBN: 1945-7782
• DOI: 10.1257/app.20170717
• 发表日期: 2020
• 页码: 1-31
• 关键词: Optimization frictions; taxable income; LABOR; elasticities; COSTS; uncover; CHOICE; micro; MODEL

摘要

We introduce a method for estimating the cost of adjusting earnings, as well as the earnings elasticity with respect to the net-of-tax share. Our method uses information on bunching in the earnings distribution at convex budget set kinks before and after policy-induced changes in the magnitude of the kinks: the larger is the adjustment cost, the smaller is the absolute change in bunching from before to after the policy change. In the context of the Social Security Earnings Test, our results demonstrate that the short-run impact of changes in the effective marginal tax rate can be substantially attenuated.