Ladies and gentlemen, and all the diligent students,
Today, we are so honored to have Prof. Wooldridge here for our guest lecture tonight. So there are just a lot we have to introduce about him. He is an American Econometrician. In class, we had talked about three methodologies in Economics: modeling, data analysis, and also experimental economics. And Econometrics is a very central method in economics when we do data analysis and very related to the top one major, data science at Duke Kunshan University. So I guess a lot of you would be very interested in how Econometric methods can help us answer social questions by analyzing big data. And he is most famous for his two textbooks. Later on, if you go to higher level Econ classes, like intermediate microeconomics, you are going to have his textbook as an introduction of you to a higher level data analysis. The two books are called: Introductory Econometrics: A Modern Approach, and Econometric Analysis of Cross Section and Panel Data.
Personally, I have three highlights for Jeffrey:
The first thing is that I really resonate with him in that he explores different fields. He mentioned in high school; he started with advanced math class, and later on he went to business school, but he took classes in economics and computer science, and something clicked there. Finally he found that he fits very well into Econometrics. So I think his story encourages our students to explore your interest.
The second thing that I really admire him is that he is a theoretical econometrician, but he mentioned that he really like to help the empirical people solve real-world problems. He came to look at what problems the empirical people want to solve and he develops methods on top of it. So I think that’s a very inspiring attitude of an Economist, not only enjoy our own happiness of thinking but also analyze real-world problems.
Last but not the least, I admire he for that he seems to have the dream of human civilization. He doesn’t like the machine learning methods that’s not explainable, just keep changing the parameter, but he really wants to find the causal inferences: a much higher level of human intelligence.
Watch More About Prof. Jeffrey Woodridge
Stata Happy Hour with Dr. Jeff Wooldridge
Methods Lecture Summer Institute 2007 - Wooldridge (Part I)
SciEcon AMA: The Current and Future of Econometrics
Prof. Jeffrey Wooldridge is a University Distinguished Professor of Economics at Michigan State University, where he has taught since 1991. He is the author of two very popular econometrics textbooks, Introductory Econometrics: A Modern Approach, and Econometric Analysis of Cross Section and Panel Data, one for undergraduates and one for graduates. Students at Duke including myself all study introductory econometrics using Prof. Wooldridge’s book.
Known for his theoretical contributions to analysis of cross-sectional and panel data, Prof. Wooldridge has published more than 70 articles in internationally recognized journals, as well as several chapters in well-respected books. His work has earned numerous awards, including the Alfred P. Sloan Research Fellowship, the Plura Scripsit award from Econometric Theory, the Sir Richard Stone prize from the Journal of Applied Econometrics, and three graduate teacher-of-the-year awards from MIT. A fellow of the Econometric Society, the Journal of Econometrics, and the International Association for Applied Econometrics, Dr. Wooldridge has been editor of the Journal of Business and Economic Statistics and econometrics co-editor of Economics Letters. Dr. Wooldridge received his Ph.D. in economics from the University of California, San Diego.
References:
[1] Abadie, A., Athey, S., Imbens, G.W. and Wooldridge, J.M. (2020), Sampling-Based versus Design-Based Uncertainty in Regression Analysis. Econometrica, 88: 265-296. https://doi.org/10.3982/ECTA12675
[2] Słoczyński, T., & Wooldridge, J.M. (2018). A General Double Robustness Result for Estimating Average Treatment Effects. Econometric Theory, 34(1), 112-133. https://doi.org/10.1017/S0266466617000056
[4] Wooldridge, J.M., (2021), Two-Way Fixed Effects, the Two-Way Mundlak Regression, and Difference-in-Differences Estimators. Available at SSRN: https://ssrn.com/abstract=3906345 or http://dx.doi.org/10.2139/ssrn.3906345
[5] Stata Happy Hour with Dr. Jeff Wooldridge [URL]
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