Marinho Bertanha, Andrew H. McCallum, Nathan Seegert
arXiv 4 Jan 2021 · Econometrics · publishedJournal of Econometrics (2023) · 23 citations (OpenAlex)
arXiv:2101.01170 · PDF · DOI · OpenAlex · Extracted main text
This paper studies the bunching identification strategy for an elasticity parameter that summarizes agents' responses to changes in slope (kink) or intercept (notch) of a schedule of incentives. We show that current bunching methods may be very sensitive to implicit assumptions in the literature about unobserved individual heterogeneity. We overcome this sensitivity concern with new non- and semi-parametric estimators. Our estimators allow researchers to show how bunching elasticities depend on different identifying assumptions and when elasticities are robust to them. We follow the literature and derive our methods in the context of the iso-elastic utility model and an income tax schedule that creates a piece-wise linear budget constraint. We demonstrate bunching behavior provides robust estimates for self-employed and not-married taxpayers in the context of the U.S. Earned Income Tax Credit. In contrast, estimates for self-employed and married taxpayers depend on specific identifying assumptions, which highlight the value of our approach. We provide the Stata package "bunching" to implement our procedures.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Blomquist, S. and W. Newey (2017, September) (2017) The Bunching Estimator Cannot Identify the Taxable Income Elasticity | 0.950 | 7 | 4 | 86% |
| 2 | Saez, E (2010) Do Taxpayers Bunch at Kink Points? | 0.863 | 14 | 5 | 64% |
| 3 | Cattaneo, M., M. Jansson, X. Ma, and J. Slemrod (2018, March) (2018) Bunching Designs: Estimation and Inference | 0.843 | 3 | 3 | 100% |
| 4 | Chetty, R., J. N. Friedman, T. Olsen, and L. Pistaferri (2011) Adjustment Costs, Firm Responses, and Micro vs. Macro Labor Supply Elasticities: Evidence from Danish Tax Records | 0.794 | 8 | 5 | 50% |
| 5 | Chernozhukov, V. and H. Hong (2002) Three-step Censored Quantile Regression and Extramarital Affairs | 0.794 | 6 | 3 | 50% |
| 6 | Kleven, H. J. and M. Waseem (2013) Using Notches to Uncover Optimization Frictions and Structural Elasticities: Theory and Evidence from Pakistan | 0.737 | 3 | 2 | 100% |
| 7 | Saez, E (2001) Using Elasticities to Derive Optimal Income Tax Rates | 0.737 | 3 | 2 | 100% |
| 8 | Bertanha, M., A. H. McCallum, and N. Seegert (2018, March) (2018) Better Bunching, Nicer Notching self | 0.644 | 2 | 2 | 100% |
| 9 | Bertanha, M., A. H. McCallum, A. Payne, and N. Seegert (2022) Bunching estimation of elasticities using stata self | 0.644 | 2 | 2 | 100% |
| 10 | Blomquist, S., A. Kumar, C.-Y. Liang, and W. Newey (2015, May) (2015) Individual Heterogeneity, Nonlinear Budget Sets, and Taxable Income | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 65 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Identification and Inference in General Bunching Designs | 0.763 | 18 | 5 |
| 2 | Identification of Causal Effects with a Bunching Design | 0.644 | 2 | 2 |
| 3 | 2428Treatment Effects in Bunching Designs: The Impact of Mandatory Overtime Pay on Hours | 0.511 | 2 | 1 |