SemesterFall Semester, 2025
DepartmentThe International Master Program of Applied Economics and Social Development (IMES) , First Year The International Master Program of Applied Economics and Social Development (IMES) , Second Year
Course NameApplied Econometrics
InstructorFU CHIEN-HAO
Credit3.0
Course TypeSelectively
Prerequisite
Course Objective
Course Description
Course Schedule

























































































Week

Topic

Readings

1

Introduction

Anderson et al. (2020) Ch. 1-3

2

Probability

Anderson et al. (2020) Ch. 4

3

Probability Distribution I

Anderson et al. (2020) Ch. 5

4

Probability Distribution II

Anderson et al. (2020) Ch. 6

5

Hypothesis Tests

Anderson et al. (2020) Ch. 7

6

Inference about Means and Proportions

Anderson et al. (2020) Ch. 8

7

Population comparison

Anderson et al. (2020) Ch. 9

8

Midterm

 

9

ANOVA

Anderson et al. (2020) Ch. 12-13

10

Simple Linear Regression

Anderson et al. (2020) Ch. 14

11

Simple Linear Regression

Anderson et al. (2020) Ch. 14

12

Multiple Regression 1

Anderson et al. (2020) Ch. 15

13

Multiple Regression 2

Anderson et al. (2020) Ch. 16

14

Model Building

Anderson et al. (2020) Ch. 16

15

Time Series Analysis

Anderson et al. (2020) Ch. 17

16

Final Exam

 


 



The teaching schedule is subject to change. The dates for midterm and final exams are not fixed and could be moved earlier or later depending on the teaching progress. If there are any changes to the dates of the midterm or final exams, they will be announced in class and on the class website.


Teaching Methods
Teaching Assistant
Requirement/Grading

  • Assignments and Class Participation: 30%

  • Midterm and Final Exam: 70%



 


Textbook & Reference

Main Text




  • David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann. (2020) Statistics for Business & Economics, 14th Edition. ISBN: 9780357114483

  • David Dalpiaz (2022) Applied Statistics with R.



Additional Resources




  • Cunningham, S. (2021). Causal Inference: The Mixtape. Yale University Press. ISBN: 9780300251685.

  • Angrist, J. D., and J. S. Pischke. (2009) Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton University Press. ISBN: 9780691120355.

  • R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (2017) Garrett Grolemund & Hadley Wickham. Hardcover: O’Reilly, ISBN 1491910399. 


Urls about Course
Attachment