Difference-in-Differences in Applied Econometrics and Statistical Inferences
（Texas A&M University）
2021年6月15日10:00 腾讯会议：239 756 725
Dr. Suojin Wang is Associate Dean for Assessment in the College of Science and a Professor of Statistics at Texas A&M University. He received his Ph.D. from the University of Texas at Austin. His research interests include semi- and non-parametric statistical methodology, missing and mis-measured data analyses, asymptotic theory, sample surveys, and applied statistics. He has over 170 peer-reviewed research publications, many of which are in applied fields. He was the Editor-in-Chief of Journal of Nonparametric Statistics during 2007-2012. He is an elected Fellow of the American Statistical Association, an elected Fellow of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. He received four major teaching awards from Texas A&M University, including the most prestigious University-level Distinguished Achievement Award in Teaching.
In this presentation, we will discuss the concept of difference-in-differences (DID) and its wide applications in many fields, such as applied econometrics, accounting, social sciences and government. We will use two simple examples to illustrate the usefulness of DID and some underlying assumptions needed for its valid applications. How to make sound statistical inferences using DID will also be demonstrated in different settings. This includes proper applications of bootstrap resampling methodology to obtain statistical properties of DID. In addition, some extensions of DID will be presented.