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

• 成果类型: Article
• 署名作者: Ferman, Bruno; Pinto, Cristine
• 署名单位: Getulio Vargas Foundation
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/rest_a_00759
• 发表日期: 2019-07
• 页码: 452-467
• 关键词: generalized least-squares; errors; tests; panel

摘要

We derive an inference method that works in differences-in-differences settings with few treated and many control groups in the presence of heteroskedasticity. As a leading example, we provide theoretical justification and empirical evidence that heteroskedasticity generated by variation in group sizes can invalidate existing inference methods, even in data sets with a large number of observations per group. In contrast, our inference method remains valid in this case. Our test can also be combined with feasible generalized least squares, providing a safeguard against misspecification of the serial correlation.