Outline of lecture

Econometric Analysis introduces the first-year master students to multiple regression methods for analyzing cross-section and panel data (microeconometrics). The objective of the course is for the students to learn how to conduct and how to critique empirical studies in economics and related fields. Accordingly, the emphasis of the course is on empirical applications. In order to learn how to analyze data, the students will be assigned homework every week in which they are required to analyze data from the real world using econometrics software (Stata).

Purpose of lecture

Econometric Analysis introduces the first-year master students to multiple regression methods for analyzing cross-section and panel data (microeconometrics). The objective of the course is for the students to learn how to conduct and how to critique empirical studies in economics and related fields. Accordingly, the emphasis of the course is on empirical applications. In order to learn how to analyze data, the students will be assigned homework every week in which they are required to analyze data from the real world using econometrics software (Stata).

Plan of lecture

1. Introduction
2. Conditional Expectations
3. Basic Asymptotic Theory
4. The Single-Equation Linear Model and OLS Estimation
5. Instrumental Variables Estimation of Single-Equation Linear Models
6. Additional Single-Equation Topics
Midterm Exam
7. Estimating Systems of Equations by OLS and GLS
10. Basic Linear Unobserved Effects Panel Data Models
11. More Topics in Linear Unobserved Effects Models
8. System Equations by Instrumental Variables
9. Simultaneous Equations Models
Final Exam

Textbook and reference

Wooldridge, Jeffrey M., (2002) Econometric analysis of cross section and panel data, MIT press.
Web site: http://www.msu.edu/~ec/faculty/wooldridge/book2.htm

Related and/or prerequisite courses

The knowledge of undergraduate-level mathematical statistics and linear algebra is required. The knowledge of undergraduate-level econometrics is desired.

Evaluation

Problem Sets: 20%; Midterm Exam: 35%; Final Exam: 45%.

Comments from lecturer

The students are required to read textbook before class and solve problem sets by themselves.