2021 Faculty Courses School of Engineering Undergraduate major in Industrial Engineering and Economics
Econometrics II
- Academic unit or major
- Undergraduate major in Industrial Engineering and Economics
- Instructor(s)
- Kota Ogasawara / Tatsuki Inoue
- Class Format
- Lecture
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 1-2 Tue (W931) / 1-2 Fri (W932)
- Class
- -
- Course Code
- IEE.B301
- Number of credits
- 200
- Course offered
- 2021
- Offered quarter
- 1Q
- Syllabus updated
- Jul 10, 2025
- Language
- Japanese
Syllabus
Course overview and goals
This course provides the theory and techniques of modern econometric analysis and reviews empirical studies. The aim of this course is to illustrate the theory and techniques of modern econometric analysis.
Course description and aims
By the end of this course, students will be able to: 1) Explain causal inference and endogeneity. 2) Use instrumental variable. 3) Use panel data methods. 4) Understand the validity of econometric analyses.
Keywords
Endogeneity, Ordinary Least Squares, Instrumental Variable, Panel Data
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
First, causal inference and endogeneity are explained, and then each topic is discussed in two lectures.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Orientation and introduction | Orientation and introduction |
| Class 2 | Causality and endogeneity | |
| Class 3 | Instrumental variables (1) | |
| Class 4 | Instrumental variables (2) | |
| Class 5 | Panel data: Fixed effects model (1) | |
| Class 6 | Panel data: Fixed effects model (2) | |
| Class 7 | Panel data: Other models (1) | |
| Class 8 | Panel data: Other models (2) | |
| Class 9 | Difference-in-Differences (1) | |
| Class 10 | Difference-in-Differences (2) | |
| Class 11 | Regression discontinuity design (1) | |
| Class 12 | Regression discontinuity design (2) | |
| Class 13 | Review | |
| Class 14 | Exercise | |
| Class 15 | Final |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
None
Reference books, course materials, etc.
Bruce E. Hansen. Econometrics. University of Wisconsin, 2020. Nishiyama, Shintani, Kawaguchi, and Okui. Econometrics: Statistical Data Analysis for Empirical Economics. Yuhikaku, 2019. (in Japanese)
Evaluation methods and criteria
Problem solving or midterm 30%, final exams 70% (In-person final exams). Exams may occur online due to the spread of COVID-19.
Related courses
- IEE.B207 ： Econometrics I
- IEE.B405 ： Advanced Econometrics
- IEE.A204 ： Probability for Industrial Engineering and Economics
- IEE.A205 ： Statistics for Industrial Engineering and Economics
Prerequisites
The prerequisites for this course are Statistics for Industrial Engineering and Economics (IEE.A205), Probability for Industrial Engineering and Economics (IEE.A204), and Econometrics I (IEE.B207).