後期 火曜日 ２講時 第３小講義室. 単位数/Credit(s): 2. 担当教員/Instructor: KO IAT MENG. 対象学年/Eligible Participants: 全／ALL. 履修年度: 2024. 科目ナンバリング/Course Numbering: EEM-ECO506E. 使用言語/Language Used in Course: English.
Intermediate Econometrics II
ＫＯ ＩＡＴ ＭＥＮＧ
This course is a one-semester introduction to econometrics. The course will cover fundamental knowledge of linear regression in economic data analysis. Necessary probability and statistic concepts will be taught and reviewed. Empirical applications, rather than theoretical proofs, will be emphasized. Empirical examples will be demonstrated in class. The R program will be taught and used throughout the course.
Textbook
Wooldridge, J. M. (2020). Introductory econometrics: A modern approach, 7th ed., Cengage.
(E-Book available from the university library website)
The students are expected to have a deep understanding of modern econometric methods in economic data analysis. Also, the course is designed as a prerequisite for advanced econometrics courses. The students will be able to apply basic econometric tools in empirical research (cross-sectional data) after the course.
1. Economic data structure (Wooldridge Chapter 1 and Appendix B & C)
Basic probability & statistics for econometrics
Conditional expectation (conditional mean)
Causality & Ceteris Paribus
2. Linear regression model estimation (Wooldridge Chapter 2 & 3)
Simple & multiple regression
Gauss-Markov Assumptions
Unbiasedness, Efficiency, BLUE
3. Multiple regression inference (Wooldridge Chapter 4)
Classical linear model (CLM) Assumptions
t and F tests
4. Large sample regression model (Wooldridge Chapter 5) and Consistency (Wooldridge Appendix C-3)
Asymptotic normality
Large sample inference
5. Multicollinearity (Wooldridge Chapter 3, 3-4a) and Heteroskedasticity (Wooldridge Chapter 8)
Robust standard error & inference
Diagnostic tests for Heteroskedasticity
Weighted Least Square (WLS) estimator
6. Endogeneity (Wooldridge Chapter 15)
Instrumental variable & 2SLS
Testing for endogeneity & overidentification
7. Miscellaneous topics (Wooldridge Chapter 6)
Beta Coefficients
Functional forms
Goodness-of-fit & selection of regressors
8 Regression with qualitative information (Wooldridge Chapter 7)
Dummy regressors
Linear probability model
9 Model specification, measurement error, and sample issues (Wooldridge Chapter 9)
Not all topics in each chapter will be covered. Please refer to the lecture notes distributed during
the class.
Assignments (30%)
Mid-term exam (30%)
Final exam (40%)
Google Classroom: yl6gxoi