From July 31 to August 21, 2021, Associate Professor Teppei Yamamoto (Department of Political Science, Massachusetts Institute of Technology) gave an intensive summer course at Waseda University entitled “Advanced Topics in Political Economy: Causal Inference”. Prof. Yamamoto was invited to the Faculty of Political Science and Economics through the Center for Positive/Empirical Analysis of Political Economy. The class sessions were organized in a hybrid format, with the first half of the class delivered online and the second half using both in-person and online teaching. Prof. Yamamoto is a leading scholar in the field of political methodology. From his lectures, the students had the opportunity to systematically learn the basics of statistical causal inference, which is becoming increasingly important in social science research. About 20 students participated in the course and were able to study various methods of statistical causal inference through five problem sets, a mid-term exam, and a final extensive problem set in a short period of time.
On August 17, a workshop was organized for students to present their ongoing research. The presenters received comments from Prof. Yamamoto and their classmates, which gave them an opportunity to learn how to effectively apply causal inference to their own research beyond the class-room materials.
In this workshop, three students presented their ongoing research: “Short-Term Productivity Impact of Smoking Cessation Programs” by Kohei Takahashi (doctoral student, Graduate School of Economics), The Effect of Health Insurance Provision on Crime -The Case of Mexico-” by Takamasa Yamaguchi (master’s student, Graduate School of Economics), and “Telling China’s stories well: How Public Diplomacy has Changed under Difficulties” by Kentaro Nakamura (Department of Political Science, Faculty of Political Science and Economics). All the presentations employed state-of-the-art methodologies such as statistical causal inference, and Prof. Yamamoto gave them numerous pieces of constructive advice on how to develop their research and how to get published in peer-reviewed journals.
Kentaro Nakamura (Department of Political Science, Faculty of Political Science and Economics):
“At the seminar, Prof. Yamamoto gave me very detailed comments on how to improve the design of my research, how to frame the arguments more effectively, and how to better structure them. His advice was very helpful.”
Kohei Takahashi (doctoral student, Graduate School of Economics):
“Dr. Yamamoto kindly provided me with a variety of critical points about our research on the smoking cessation experiment in the workshop. I can expect to add refined discussion in my paper. I really appreciate the causal inference seminar which gave me such an opportunity.”
Takamasa Yamaguchi (master’s student, Graduate School of Economics):
“In class and office hours, Prof. Yamamoto and Mr. Kitagawa (who served as TA) gave detailed explanations to my questions, which helped me to enhance my understanding. The class covered a range of topics that are not treated in econometrics classes. If we prepared well and participated actively, we were able to acquire a lot even in such a short period of time. As for the workshop, Prof. Yamamoto pointed out the shortcomings of my research and how to improve them in a precise manner. Through this practical experience, I was able to deepen my understanding of causal inference. I think this class is very useful for students who have serious interests in properly understanding empirical research and conducting empirical analysis.”
In short, the summer intensive course offered by Prof. Yamamoto was challenging and not an easy course to complete because it consisted of lectures, TA sessions, multiple assignments, exams, and a workshop in a short period of time. Through this intensive work, the students were able to acquire important methodological foundations for social science research, apply the knowledge gained in this lecture to their own research, and obtain useful suggestions for presenting their research outcomes.