Author:
Bertanha Marinho, ,McCallum Andrew H.,Seegert Nathan, ,
Abstract
We study the bunching identification strategy for an elasticity parameter that summarizes agents' response to changes in slope (kink) or intercept (notch) of a schedule of incentives. A notch identifies the elasticity but a kink does not, when the distribution of agents is fully flexible. We propose new non-parametric and semi-parametric identification assumptions on the distribution of agents that are weaker than assumptions currently made in the literature. We revisit the original empirical application of the bunching estimator and find that our weaker identification assumptions result in meaningfully different estimates. We provide the Stata package bunching to implement our procedures.
Publisher
Board of Governors of the Federal Reserve System
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A maximum likelihood bunching estimator of the elasticity of taxable income;Journal of Applied Econometrics;2024-01
2. Correcting for Endogeneity in Models with Bunching;Journal of Business & Economic Statistics;2023-09-05
3. Bunching estimation of elasticities using Stata;The Stata Journal: Promoting communications on statistics and Stata;2022-09
4. The quality of the estimators of the ETI;Journal of Public Economics;2022-08