January 2021

Better Bunching, Nicer Notching

Marinho Bertanha, Andrew H. McCallum, and Nathan Seegert


We seek the bunching identification map 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 now not, when the distribution of agents is fully versatile. We negate novel non-parametric and semi-parametric identification assumptions on the distribution of agents that are weaker than assumptions currently made sms lån på minuttetin the literature. We revisit the novel empirical utility of the bunching estimator and gather that our weaker identification assumptions lead to meaningfully diverse estimates. We present the Stata package deal bunching to put into effect our procedures.

Keywords: partial identification, censored regression, bunching, notching

DOI: https://doi.org/10.17016/FEDS.2021.002

Beefy Paper

Support to High

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January 12, 2021

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