Quantitative Research Method
| Numbering Code | G-ECON31 5A422 LE43 | Year/Term | 2022 ・ Second semester | |
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| Number of Credits | 2 | Course Type | Lecture | |
| Target Year | Target Student | |||
| Language | English | Day/Period | Fri.2 | |
| Instructor name |
SUR, Pramod Kumar (Part-time Lecturer) YANO GO (Graduate School of Economics Professor) |
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| Outline and Purpose of the Course |
Why do some countries are poor, and some are rich? Why labor force participation rate of women is different across countries? Does education increase earnings? These are some of the fundamental empirical questions in social science. The primary goal of this course is to learn together how we can quantitatively examine such questions and conduct causal analysis using modern econometric techniques. We study some of the well-known empirical papers that apply these techniques to quantitively evaluate these questions rigorously and scientifically. Additionally, we learn how we can evaluate and replicate such empirical studies using statistical software such as STATA. |
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| Course Goals |
"The objective of this course is to learn together how to conduct rigorous empirical analysis using modern econometric techniques. In particular, students are expected to learn about how to: - Gain an understanding of the basics of causal analysis. - Critically select and apply the best suitable econometric techniques to conduct rigorous analysis. - Read empirical papers in economics and replicate the results using statistical software." |
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| Schedule and Contents |
"The main topics to be covered here include: - Causation vs. Correlation - Endogeneity Issues - Randomized Control Trials - Instrumental Variable - Regression Discontinuity Design - Difference-in-Differences - Counterfactuals" |
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| Evaluation Methods and Policy |
Classes will include lecture, presentation and, and discussion components. Student participation is required in discussions and very strongly encouraged in lectures. This class requires extensive student participation, but you should view participation as an opportunity, not a requirement. I strongly encourage all students to ask questions, make suggestions, and answer questions that I ask or fellow students ask. I will facilitate discussion but encourage students to drive the conversation. Classroom Participation and Discussion: 30% Presentation: 30% Homework: 40% |
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| Course Requirements | Basic knowledge of probability, statistics, and econometrics is required. | |||
| Textbooks | Textbooks/References |
There are no particular textbooks for this course. However, the materials for this lecture will be heavily based on the following two books. (1) Angrist, Joshua D., and Jörn-Steffen Pischke. Mastering 'metrics: The path from cause to effect. Princeton university press, 2014. (2) Cunningham, Scott. Causal Inference: The Mixtape. Yale University Press, 2021. |
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