Course Information
Course title
Topics in Labor Economics: Empirical Methods and Applications 
Semester
110-2 
Designated for
COLLEGE OF SOCIAL SCIENCES  GRADUATE INSTITUTE OF ECONOMICS  
Instructor
TZU-TING YANG 
Curriculum Number
ECON5163 
Curriculum Identity Number
323EU4100 
Class
 
Credits
2.0 
Full/Half
Yr.
Half 
Required/
Elective
Elective 
Time
Monday 6,7(13:20~15:10) 
Remarks
Restriction: juniors and beyond OR Restriction: MA students and beyond OR Restriction: Ph. D students
The upper limit of the number of students: 30. 
Course
Website
https://causaldatalab.wordpress.com/2021/02/21/topics-in-labor-economics-empirical-methods-and-applications-spring-2021/ 
Course introduction video
 
Table of Core Capabilities and Curriculum Planning
Table of Core Capabilities and Curriculum Planning
Course Syllabus
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Course Description

This course will survey recent advances in labor economics. The topics will cover labor supply, labor demand, labor market discrimination, tax incidence, social insurance, and behavioral labor economics. In particular, we emphasize the link between theory and empirical evidence. Thus, for each theoretical topic, we will also survey a specific empirical strategy commonly used in labor economics, such as differencing methods, event study method, synthetic control method, bunching method, regression discontinuity (kink) design, geographic data analysis, and text data analysis. 

Course Objective
1. Be able to understand and use recent advances in labor economics and empirical methods

2. Be able to implement a good empirical research and evaluate an empirical studies

3. Have a good start of your research 
Course Requirement
Term paper (70%): milestones throughout the term
Referee Report (10%): comment on your classmate's term paper
Homework(20%) 
Student Workload (expected study time outside of class per week)
 
Office Hours
 
Designated reading
 
References
(LE) Pierre Cahuc, Stephane Carcillo and Andre Zylberberg, Labor Economics, Second Edition
(MHE) Angrist and Pischke, Mostly Harmless Econometrics
(MM) Angrist and Pischke, Mastering Metrics: The Path from Cause to Effect 
Grading
   
Progress
Week
Date
Topic