Matching, Regression Discontinuity, Difference in Differences, and Beyond

ISBN-13: 9780190258733 / Angielski / Twarda / 2016 / 278 str.

Myoung-Jae Lee

Opis

Myoung-jae Lee reviews the three most popular methods (and their extensions) in applied economics and other social sciences: matching, regression discontinuity, and difference in differences. This book introduces the underlying econometric and statistical ideas, shows what is identified and how the identified parameters are estimated, and illustrates how they are applied with real empirical examples. Lee emphasizes how to implement the three methods with data: data and programs are provided in a useful online appendix. All readers-theoretical econometricians/statisticians, applied economists/social-scientists and researchers/students-will find something useful in the book from different perspectives.

Recenzje

The book under review gives an up-to-date and concise treatment of the three most recent and widely applied empirical methods to deal with confoundedness in microeconometrics, i.e., matching, regression discontinuity and difference in differences. This book gives a timely update on the author's previous book Microeconometrics for Policy, Program, and Treatment Effects with a particular concentration on these three most in fluential methodologies. This book serves as an excellent reference for both graduate students and researchers working in the field of microeconometrics.

O autorze

Professor Myoung-jae Lee is an econometrician/statistician in Korea University. He received his Ph.D. in economics from University of Wisconsin-Madison in 1989. Since then, he published about 60 papers in economic and statistic journals as well as top-rated journals in other fields, including Econometrica, Journal of the Royal Statistical Society (Series B), Journal of Econometrics, Transportation Research (Part B), and Sociological Methods & Research. He also published four single-authored micro-econometric books from Springer, Academic Press and Oxford University Press on limited dependent variables, panel data and treatment effect analysis.