ADVANCED ECONOMETRICS A

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Subtitle	Mathematical Foundation of Regression Analysis
Lecturer(s)	NAKATSUMA, TERUO
Credit(s)	2
Academic Year/Semester	2024 Fall
Day/Period	Mon.3
Campus	Mita
Class Format	Face-to-face classes (conducted mainly in-person)
Registration Number	25372
Faculty/Graduate School	ECONOMICS
Department/Major	ECONOMICS PEARL COURSE
Year Level	3, 4
Field	MAJOR SUBJECTS CORE COURSES : B ECONOMETRICS AND STATISTICS
Grade Type	This item will appear when you log in (Keio ID required).
Course Description	This course aims to deepen student's theoretical understanding on the methods used in Econometrics. Specifically, the course deals with topics, such as the theory of M-estimation, the theory of maximum likelihood estimation, least squares methods, 2S least squares methods, generalized method of moments methods, and quantile regression methods, etc.
K-Number	FEC-EC-34112-212-07

Course Administrator	Faculty/Graduate School	FEC	ECONOMICS
Course Administrator	Department/Major	EC	ECONOMICS
Main Course Number	Level	3	Third-year level coursework
	Major Classification	4	Major Subjects Course- Core Course
	Minor Classification	11	Lecture - Econometrics and Statistics
	Subject Type	2	Elective required subject
Supplemental Course Information	Class Classification	2	Lecture
	Class Format	1	Face-to-face classes (conducted mainly in-person)
	Language of Instruction	2	English
Academic Discipline		07	Economics, business administration, and related fields

Course Contents/Objectives/Teaching Method/Intended Learning Outcome

This course aims at providing a mathematical foundation of regression analysis for advanced undergraduate students or graduate students who have studied intermediate-level econometrics and are familiar with probability theory and regression models. In this course, we will study about estimation methods for regression models such as ordinary least squares (OLS), generalized least squares (GLS), instrumental variables (IV) estimation, and the generalized method of moments (GMM) in a mathematically rigorous fashion.