Better Bunching, Nicer Notching
Andrew McCallum () and
No 2021-002, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)
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)
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Working Paper: Better Bunching, Nicer Notching (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2021-02
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