Better Bunching, Nicer Notching

Marinho Bertanha, Andrew McCallum and Nathan Seegert

No 2021-002, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

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.

Keywords: Partial identification; Censored regression; Bunching; Notching (search for similar items in EconPapers)
JEL-codes: C14 H24 J20 (search for similar items in EconPapers)
Pages: 66
Date: 2021-01-12
New Economics Papers: this item is included in nep-ore
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Citations: View citations in EconPapers (7)

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Related works:
Journal Article: Better bunching, nicer notching (2023)
Working Paper: Better Bunching, Nicer Notching (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2021-02

DOI: 10.17016/FEDS.2021.002

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