Dynamic Bunching Estimation with Panel Data

Benjamin Marx

Journal of Econometric Methods, 2024, vol. 13, issue 2, 225-249

Abstract: Bunching estimation of distortions in a distribution around a policy threshold provides a means of studying behavioral parameters. Standard cross-sectional bunching estimators rely on identification assumptions about heterogeneity that I show can be violated by serial dependence of the choice variable or attrition related to the threshold. I propose a bunching estimation design that exploits panel data to obtain identification from relative within-agent changes in income and to estimate new parameters. Simulations using household income data demonstrate the benefits of the panel design. An application to charitable organizations demonstrates opportunities for estimating elasticity correlates, causal effects, and extensive-margin responses.

Keywords: longitudinal; serial dependency; extensive margin; causal (search for similar items in EconPapers)
JEL-codes: B40 C23 D04 H00 (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/jem-2022-0031 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
Working Paper: Dynamic Bunching Estimation with Panel Data (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:jecome:v:13:y:2024:i:2:p:225-249:n:1002

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/jem/html

DOI: 10.1515/jem-2022-0031

Access Statistics for this article

Journal of Econometric Methods is currently edited by Tong Li and Zhongjun Qu

More articles in Journal of Econometric Methods from De Gruyter
Bibliographic data for series maintained by Peter Golla ().