EconPapers    
Economics at your fingertips  
 

Inference in Differences-in-Differences with Few Treated Groups and Heteroskedasticity

Bruno Ferman and Cristine Pinto ()

MPRA Paper from University Library of Munich, Germany

Abstract: Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, inference in DID models when there are few treated groups is still an open question. We show that usual inference methods used in DID models might not perform well when there are few treated groups and residuals are heteroskedastic. In particular, when there is variation in the number of observations per group, we show that inference methods designed to work when there are few treated groups would tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups would have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) dataset to show that this problem is relevant even in datasets with large number of observations per group. Then we derive alternative inference methods that provide accurate hypothesis testing in situations of few treated groups and many control groups in the presence of heteroskedasticity (including the case of only one treated group). The main assumption is that we know how the heteroskedasticity is generated, which is the case when it is generated by variation in the number of observations per group. Finally, we also show that an inference method for the Synthetic Control Estimator proposed by Abadie et al. (2010) can correct for the heteroskedasticity problem, and derive conditions under which this inference method provides accurate hypothesis testing.

Keywords: differences-in-differences; inference; heteroskedasticity; clustering; few clusters; bootstrap (search for similar items in EconPapers)
JEL-codes: C12 C21 C33 (search for similar items in EconPapers)
Date: 2015-11-06
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8) Track citations by RSS feed

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/67665/1/MPRA_paper_67665.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/68271/1/MPRA_paper_68271.pdf revised version (application/pdf)
https://mpra.ub.uni-muenchen.de/73683/7/MPRA_paper_73683.pdf revised version (application/pdf)
https://mpra.ub.uni-muenchen.de/81988/1/MPRA_paper_81988.pdf revised version (application/pdf)

Related works:
Journal Article: Inference in Differences-in-Differences with Few Treated Groups and Heteroskedasticity (2019) Downloads
Working Paper: Inference in differences-in-differences with few treated groups and heteroskedasticity (2015) 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:pra:mprapa:67665

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

 
Page updated 2021-06-10
Handle: RePEc:pra:mprapa:67665