Dynamic regression discontinuity under treatment effect heterogeneity
Yu‐Chin Hsu and
Shu Shen
Quantitative Economics, 2024, vol. 15, issue 4, 1035-1064
Abstract:
Regression discontinuity is a popular tool for analyzing economic policies or treatment interventions. This research extends the classic static RD model to a dynamic framework, where observations are eligible for repeated RD events and, therefore, treatments. Such dynamics often complicate the identification and estimation of long‐term average treatment effects. Empirical papers with such designs have so far ignored the dynamics or adopted restrictive identifying assumptions. This paper presents identification strategies under various sets of weaker identifying assumptions and proposes associated estimation and inference methods. The proposed methods are applied to revisit the seminal study of Cellini, Ferreira, and Rothstein (2010) on long‐term effects of California local school bonds.
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.3982/QE2150
Related works:
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:wly:quante:v:15:y:2024:i:4:p:1035-1064
Ordering information: This journal article can be ordered from
https://www.econometricsociety.org/membership
Access Statistics for this article
More articles in Quantitative Economics from Econometric Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().