科学研究

Ruixuan LIU is an Associate Professor at the Chinese University of Hong Kong (CUHK) Business School. He received his PhD in Economics from University of Washington. His research is in the area of econometrics and data science. His recent works focus on nonparametric Bayesian inference and its applications to econometric models. His research work has been published on Econometrica, Journal of Econometrics, Econometric Theory and Quantitative Economics, etc. He won the 2018 Arnold Zellner Price (jointly with Yanqin Fan) for the best theoretical econometrics paper published by Journal of Econometrics between 2016 and 2017. He is currently an associate editor of Journal of Econometrics and Econometric Reviews.

This paper studies semiparametric Bayesian inference for the average treatment effect on the treated (ATT) within the difference-in-differences research design. We propose two new Bayesian methods with frequentist validity. The first one places a standard Gaussian process prior on the conditional mean function of the control group. The second method is a double robust Bayesian procedure that adjusts the prior distribution of the conditional mean function and subsequently corrects the posterior distribution of the resulting ATT. The double robustness implies that the lack of smoothness of conditional mean functions can be compensated by high regularity of the propensity score, and vice versa. We prove semiparametric Bernstein-von Mises (BvM) theorems for both proposals. Monte Carlo simulations and an empirical application demonstrate that the proposed Bayesian DiD methods exhibit strong finite-sample performance compared to existing frequentist methods.