EconPapers    
Economics at your fingertips  
 

Revisiting Event Study Designs: Robust and Efficient Estimation

Kirill Borusyak (), Xavier Jaravel and Jann Spiess

Papers from arXiv.org

Abstract: We develop a framework for difference-in-differences designs with staggered treatment adoption and heterogeneous causal effects. We show that conventional regression-based estimators fail to provide unbiased estimates of relevant estimands absent strong restrictions on treatment-effect homogeneity. We then derive the efficient estimator addressing this challenge, which takes an intuitive "imputation" form when treatment-effect heterogeneity is unrestricted. We characterize the asymptotic behavior of the estimator, propose tools for inference, and develop tests for identifying assumptions. Extensions include time-varying controls, triple-differences, and certain non-binary treatments. We show the practical relevance of these insights in a simulation study and an application. Studying the consumption response to tax rebates in the United States, we find that the notional marginal propensity to consume is between 8 and 11 percent in the first quarter -- about half as large as benchmark estimates used to calibrate macroeconomic models -- and predominantly occurs in the first month after the rebate.

Date: 2021-08, Revised 2022-04
New Economics Papers: this item is included in nep-ecm and nep-isf
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31) Track citations by RSS feed

Downloads: (external link)
http://arxiv.org/pdf/2108.12419 Latest version (application/pdf)

Related works:
Working Paper: Revisiting Event Study Designs: Robust and Efficient Estimation (2022) Downloads
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:arx:papers:2108.12419

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().

 
Page updated 2022-08-10
Handle: RePEc:arx:papers:2108.12419