2025 (Current Year) Faculty Courses School of Engineering Undergraduate major in Industrial Engineering and Economics
Econometrics
- Academic unit or major
- Undergraduate major in Industrial Engineering and Economics
- Instructor(s)
- Kota Ogasawara
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 5-6 Tue / 5-6 Fri
- Class
- -
- Course Code
- IEE.B301
- Number of credits
- 200
- Course offered
- 2025
- Offered quarter
- 1Q
- Syllabus updated
- Mar 19, 2025
- Language
- Japanese
Syllabus
Course overview and goals
This course is designed for 3rd year undergraduate students and is taught in Japanese. English language is used for the blackboarding in the preparation for Advanced Econometrics (IEE.B 405).
Course description and aims
The course aims to present and illustrate the theory and techniques of modern econometric analysis. Students will be able to explain causal inference and endogeneity.
Keywords
Ordinary Least Squares, Endogeneity, Instrumental Variable, Panel Data
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
The first part begins with concepts of the regression. The second part examines concepts of the endogeneity, instrumental variable technique, and panel data analysis.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Orientation and introduction | Orientation and introduction |
| Class 2 | Basic concepts: Regression and CEF | Basic concepts: Regression and CEF |
| Class 3 | Linear projection model | Linear projection model |
| Class 4 | Least square estimator | Least square estimator |
| Class 5 | Finite sample properties | Finite sample properties |
| Class 6 | Normal regression model | Normal regression model |
| Class 7 | Endogeneity | Endogeneity |
| Class 8 | Instrumental variable technique I | Instrumental variable technique I |
| Class 9 | Instrumental variable technique II | Instrumental variable technique II |
| Class 10 | Panel data analysis I | Panel data analysis I |
| Class 11 | Panel data analysis II | Panel data analysis II |
| Class 12 | Panel data analysis III | Panel data analysis III |
| Class 13 | Additional issues and Additional issues and applications: Quantitative studies in Economics | Additional issues and applications: Quantitative studies in Economics |
| Class 14 | Review | Review |
| Class 15 | Final | 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)
Nishiyama, Shintani, Kawaguchi, and Okui. Econometrics: Statistical Data Analysis for Empirical Economics. Yuhikaku, 2019. (in Japanese)
Reference books, course materials, etc.
Bruce E. Hansen. Econometrics. University of Wisconsin, 2022.
西山・新谷・川口・奥井（2019）『計量経済学』，有斐閣
Evaluation methods and criteria
Final 100%
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) and Probability for Industrial Engineering and Economics (IEE.A204).