Topics in Labor Economics (2026 Spring) 

Syllabus 

Suggestive Textbooks

• Huntington-Klein, N. (2021), The Effect: An Introduction to Research Design and Causality

• Scott Cunningham (2020), Causal Inference: The Mixtape

• Alberto Abadie1 and Matias D. Cattaneo (2018), Econometric Methods for Program Evaluation

• Angrist and Pischke (2016), Mastering Metrics: The Path from Cause to Effect (MM)

• Angrist and Pischke (2009), Mostly Harmless Econometrics (MHE)

• Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (2017), An Introduction to Statistical Learning with Applications in R

• George Borjas (2016), Labor Economics, 7th Edition

• Pierre Cahuc, Stephane Carcillo and Andre Zylberberg (2018), Labor Economics, 2nd Edition

• Anton Korinek (2023), Generative AI for Economic Research: Use Cases and Implications for Economists

• Anton Korinek (2025), AI Agents for Economic Research

Learning Resources 

• Stata

• R

• Latex (overleaf)

• GitHub

Class Data 

• You can get access to the data or program used in this class through this link

Class Slides 

• 2/25

  • Course Introduction

  • Data Source

    • 中研院資料申請範例

• 3/4

  • Potential Outcome Framework

    • Preview Videos on The Effect

      • Ep 21: Treatment Effects

      • Ep 22: Conditional Average Treatment Effects

  • Selection Bias

  • Randomized Controlled Trial

  • STATA Section

    • Introduction to STATA

    • Stata Learning Resources

  • R Section

    • Introduction

    • Basic

    • R Learning Resources

• 3/11

  • Matching Methods

    • Preview Videos on The Effect

      • Ep 35: Matching

      • Ep 36: Five Questions About Matching

      • Ep 37: Distance Matching

      • Ep 38: Propensity Score Matching

• 3/18

  • Regression and Causal Inference

    • Preview Videos on The Effect

      • Ep 25: Regression and The Error Term

      • Ep 26: Regression and Sampling Variation

      • Ep 27: Reading Regression Tables

      • Ep 28: Interpreting a Regression Coefficient

      • Ep 29: Polynomials in Regression

      • Ep 30: Logarithms in Regression

      • Ep 31: Categorical Predictors

      • Ep 32: Interaction Terms

      • Ep 33: Your Standard Errors are Wrong

• 3/25

  • Causal Machine Learning

  • Homework 1 (due on 4/12)

    • Please upload your answer sheet and log file to here

    • The format of answer sheet: here 

    • Stata Learning Resources

  • Latex Template

    • Homework: here

    • Slides: here

    • Term Paper: here

    • 本機端執行的tex檔: here

  • Oral Exam 1 (held on 4/22)

    • Guideline

    • Please book a slot: here

    • Please upload your slides: here

• 4/1

  • Fixed Effects Regression

    • Preview Videos on The Effect

      • Fixed Effects

      • Estimating Fixed Effects

• 4/8

  • Difference-in-Differences Design

    • Preview Videos on The Effect

      • Difference in Differences

      • Parallel Trends

      • Estimating Difference in Differences

      • Supporting Parallel Trends

      • Dynamic Difference-in-Differences

  • Staggered DID Design

    • Preview Videos on The Effect

      • Staggered Treatment in Difference-in-Differences

• 4/15

  • Synthetic Control Method

    • Preview Videos on The Effect

      • Other Standard Research Designs

  • Reading Group Presentation (3-4 people)

    • Guideline

    • Please sign up: here

• 4/22

  • Oral Exam 1

• 4/29

  • Instrumental Variable Design

    • Preview Videos on The Effect

      • Ep 57: Instrumental Variables

      • Ep 58: Instrumental Variable Validity

      • Ep 59: Estimating Instrumental Variables

      • Ep 60: Testing Instrumental Variables Assumptions

  • Shift-Share IV Design

  • Homework 2 (due on 5/17, 11:00pm)

    • Please upload your answer sheet and R script to here

    • The format of answer sheet: here 

    • R Learning Resources

• 5/6

  • Regression Discontinuity Design

  • Preview Videos on The Effect

    • Ep 61: Regression Discontinuity

    • Ep 62: Estimating Regression Discontinuity

    • Ep 63: Adjustments to Regression Discontinuity

    • Ep 64: Checking Regression Discontinuity Assumptions

• 5/13

  • Regression Discontinuity Design

  • IV and (Quasi)-Experimental Designs

  • Guidelines for Final Presentation

  • Guideline for Your Term Paper

  • Concluding Remarks for This Course

  • Oral Exam 2 (held during 5/27 week)

    • Please book a slot: here

    • Please upload your slides: here

• 5/20

  • No Class

• 5/27 Week

  • Oral Exam 2

• 5/27

  • Reading Group Presentation 1

    • Upload your team's slides: link

    • Download slides: link

    • Presentation order: link 

    • Peer evaluation: link

• 6/3

  • Reading Group Presentation 2

    • Upload your team's slides: link

    • Download slides: link

    • Presentation order: link  

    • Peer evaluation: link

• 6/10

  • Final Presentation

    • Guidelines for Final Presentation

    • Upload your slides: link

    • Download slides:link

    • Presentation order: link

    • Peer evaluation: link

• 6/17

  • Term Paper (due on 6/17) 

    • Guideline for Your Term Paper

    • Upload your paper: link

    • Latex Template

      • 本機端執行的tex檔: here

      • Overleaf端執行的tex檔: here

    • Term Paper Example

      • Example 1: here

      • Example 2: here

    • Table Template

      • Example 1: here

    • Equation Template

      • Example 1: here