| Academic Year |
2025Year |
School/Graduate School |
School of Economics Economics Day Course |
| Lecture Code |
G5051121 |
Subject Classification |
Specialized Education |
| Subject Name |
計量経済学１ |
Subject Name
（Katakana） |
ケイリヨウケイザイガクイチ |
Subject Name in
English |
Econometrics 1 |
| Instructor |
HAYAKAWA KAZUHIKO |
Instructor
(Katakana) |
ハヤカワ カズヒコ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
2nd-Year, First Semester, 1Term |
| Days, Periods, and Classrooms |
(1T) Weds1-4：ECON B257 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
Face-to-face, Online (simultaneous interactive) |
| Basically, Face-to-Face lectures are provided. However, it may switch to online lecture depending on the circumstances. |
| Credits |
2.0 |
Class Hours/Week |
4 |
Language of Instruction |
J
:
Japanese |
| Course Level |
2
:
Undergraduate Low-Intermediate
|
| Course Area（Area） |
24
:
Social Sciences |
| Course Area（Discipline） |
03
:
Economics |
| Eligible Students |
second year |
| Keywords |
statistical analysis of economic data, regression analysis, empirical analysis |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | Economic Analysis
（Abilities and Skills）
・The ability of developing mathematical analysis applying knowledge Economic theory, Statistics and Econometrics. |
|---|
Class Objectives
/Class Outline |
Econometrics is an interdisciplinary subject composed of economics, statistics and mathematics. In this course, the statistics part is mainly considered. Specifically, this course provide a series of lectures associated with regression analysis. The goal of this course is to provide basic skills so that students can carry out simple statistical analysis. |
| Class Schedule |
lesson1: Guidance
lesson2: What is econometrics?
lesson3: Review of statistics
lesson4: Review of statistics
lesson5: Review of statistics
lesson6: Simple regression model
lesson7: Simple regression model
lesson8: Simple regression model
lesson9: Multiple regression model
lesson10: Multiple regression model
lesson11: Multiple regression model
lesson12: Functional form
lesson13: Dummy variable
lesson14: Dummy variable
lesson15: Summary of the course
class room report, final exam |
Text/Reference
Books,etc. |
distribute the materials via webpage |
PC or AV used in
Class,etc. |
Handouts, Microsoft Teams, Microsoft Stream, moodle |
| (More Details) |
slides |
| Learning techniques to be incorporated |
|
Suggestions on
Preparation and
Review |
Every classes are interdependent, so students are required to review each class. |
| Requirements |
It is desirable to have already taken Statistics 1 or to have enough knowledge to understand the meaning of expected value, variance, and correlation.
It is desirable to be able to perform basic Excel operations (four arithmetic operations, etc.).
To take “Econometrics 2,” it is necessary to have taken this lecture or to have equivalent knowledge. |
| Grading Method |
HW and final exam |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
Students who are interested in data analysis are most welcome. |
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |