Better Bunching, Nicer Notching
55 Pages Posted: 23 Mar 2018 Last revised: 20 Aug 2020
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Better Bunching, Nicer Notching
Better Bunching, Nicer Notching
Date Written: August 14, 2020
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, tax kink, earned income tax credit
JEL Classification: C14, H24, J20
Suggested Citation: Suggested Citation