Special Lecture on Natural Resources Economics IIIB
| Numbering Code | G-AGR06 7FC04 LJ82 | Year/Term | 2022 ・ Second semester | |
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| Number of Credits | 1 | Course Type | Lecture | |
| Target Year | Target Student | |||
| Language | Japanese and English | Day/Period | ||
| Instructor name | Not fixed (Kyoto University) | |||
| Outline and Purpose of the Course | This class will give you theoretical grounds required for understanding empirical papers in the eld of Agricultural Economics, Development, and Environmental Economics etc. Students will acquire working knowledge to carry out empirical analysis by experiencing data management and empirical exercises through Stata tutorials. This class will be taught in English unless all the students are native Japanese speakers. In class, any questions/comments are welcomed in either English or Japanese. Lecture slides are in English. | |||
| Course Goals |
To understand what conditions are needed to identity the causal impact of x on y in regression frameworks To acquire working knowledge to interpret speci cations and estimation results in empirical research papers To acquire working knowledge to choose an appropriate econometric method, depending on the natures of data and contexts To obtain practical skills to carry out empirical projects with Stata |
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| Schedule and Contents |
1． Selection on Observables and Coefficient Stability 2． Regression Discontinuity Design (RDD) 3． Panel Data 4． Difference-in-Differences (DID) 5. Introduction to Structural Estimation 6. Resampling Methods 7． Stata tutorial (全15回） |
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| Evaluation Methods and Policy |
Problem sets (10%*4), Final exam(60%) Refer to "2020 Guide to Degree Programs" for attainment levels of evaluation. |
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| Course Requirements | This course is taught at a graduate level. The only pre-requisite is any course covering basic probability and statistics. | |||
| Study outside of Class (preparation and review) |
Lecture slides and exercise materials will be distributed by email. Check emails on a regular basis. All students must write up their problem sets individually. However, you may work in groups of up to 2 people, though you are not required to work in groups at all. |
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| Textbooks | Textbooks/References |
. Stock, J. H., & Watson, M. W. (2018). Introduction to Econometrics, 4th Edition, Pearson Education Inc. (SW) . Abadie, A., & Cattaneo, M. D. (2018). Econometric methods for program evaluation. Annual Review of Economics, 10, 465-503. (AC) . Imbens, G. W., & Wooldridge, J. M. (2009). Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature, 47(1), 5-86. (IW) . Du o, E., Glennerster, R., & Kremer, M. (2007). Using Randomization in Development Economics Research: A toolkit. Handbook of Development Economics, 4, 3895-3962. (DGK) . Glennerster, R., & Takavarasha, K. (2013). Running randomized evaluations: A practical guide. Prince-ton University Press. (GT) |
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| References, etc. |
. Angrist, J. D., & Pischke, J. S. (2014). Mastering’metrics: The path from cause to e ect. Princeton University Press. (AP) . Cameron, A. C., and Trivedi, P. K. (2010). Microeconometrics Using Stata. . Mitchell, M. N. (2012). A Visual Guide to Stata Graphics. StataCorp LP. |
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