2019 Econometrics II

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Academic unit or major
Undergraduate major in Industrial Engineering and Economics
Ogasawara Kota 
Course component(s)
Day/Period(Room No.)
Mon7-8(W932)  Thr7-8(W932)  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
Language used
Access Index

Course description and aims

This course is designed for 3rd or 4th year undergraduate students and is taught in Japanese. English language is used for the blackboarding in the preparation for Advanced Econometrics (IEE.B 405). Note that some students audit both Econometrics II and Advanced Econometrics in this quarter.

Student learning outcomes

The course aims to present and illustrate the theory and techniques of modern econometric analysis.


Least square estimation, normal regression model, maximum likelihood estimation, nonlinear models, endogeneity, panel data

Competencies that will be developed

Intercultural skills Communication skills Specialist skills Critical thinking skills Practical and/or problem-solving skills
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Class flow

The first part begins with concepts of the conditional expectation. The second part introduces concepts of the least square regression. The third part examines concepts of the normal regression model, maximum likelihood estimator, and a few nonlinear models. The final part introduces concepts of endogeneity.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Orientation and introduction Orientation and introduction
Class 2 Basic concepts I: Conditional expectation function
Class 3 Basic concepts II: Properties of the conditional expectation
Class 4 The linear projection model
Class 5 The algebra of least squares I: Least squares estimator
Class 6 The algebra of least squares II: FWL theorem
Class 7 Finite-sample properties of the OLSE
Class 8 Normal regression model and MLE I
Class 9 Normal regression model and MLE II
Class 10 Nonlinear models
Class 11 Endogeneity I: Concept of causal effect
Class 12 Endogeneity II: Two-stage least squares
Class 13 Panel data
Class 14 Review
Class 15 Final


Asano, S., and Nakamura, J. (2009). Econometrics. (in Japanese)

Reference books, course materials, etc.

I recommended Econometrics by Bruce E. Hansen as a supplement of the lecture notes (Chapter 1--5). A recommended supplementary monograph is Mastering Metrics by Joshua D. Angrist & Jorn-Steffen Pischle.

Assessment criteria and methods

Problem solving or midterm 30%, final exams 70%.

Related courses

  • IEE.B207 : Econometrics I
  • IEE.B405 : Advanced Econometrics
  • IEE.B334 : Cliometrics
  • IEE.A204 : Probability for Industrial Engineering and Economics
  • IEE.A205 : Statistics for Industrial Engineering and Economics
  • IEE.B434 : Advanced Topics in Econometrics

Prerequisites (i.e., required knowledge, skills, courses, etc.)

The course prerequisite is Econometrics I (level: IEE 200) by Professor Yoichiro Higuchi. I recommended Introductory Courses in Statistics and Probability (level: IEE 200) by Professor Masami Miyakawa as the prerequisites. Students should be familiar with basic concepts in probability and statistical inference. Familiarity with matrix algebra is preferred.

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