CEBA talks 2020-2021
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Quantile Regression Model with Interactive Fixed Effects for Group-Level Policy Evaluation

Authors: Ruofan Xu, Jiti Gao, Dukpa Kim, Tatsushi Oka, and Yoon-Jae Whang 

Abstract: In this paper, we introduce a quantile regression model with interactive fixed effects for group-level policy evaluation. Under a variant of differences in differences framework, our model can identify heterogeneous treatment effects depending on individual observed and unobserved characteristics, while controlling for interactive fixed effects across groups. Our model also provides a parsimonious way of evaluating policy effects on inequality measures. We provide asymptotic properties of our estimators and examine their finite-sample properties through Monte Carlo experiments. As an empirical illustration, we evaluate the impact of a minimum wage policy on income distribution.