Lecture 1: Introduction

•     Meanings of Identification


•     Reduced Form vs. Structural Model Identification

Lecture 2: Counterfactual Framework and Randomized Controlled Trials 

•     Potential Outcomes


•     Selection Bias


•     RAND HIE and OHP

Lecture 3: Estimating Causal Effects Using Regression Adjustment 

•     Omitted Variable Bias


•     Practical Regression Hints  


•     Technological Change: Krueger (1993) + DiNardo and Pischke (1997) 

Lecture 4: Machine Learning for Applied Econometrics 

•     Prediction v.s. Causation


•     LASSO and Ridge Estimators


•     Double LASSO

Lecture 5: Topics on Labor Supply

•     Substitution and Income Effects of Labor Supply


•     Labor Supply Effect of Unemployment Insurance (UI)


•     Elderly Labor Supply and Retirement Benefits

Mid-Term Presentations 

Lecture 6: Panel Data and Difference-in-Differences 

•     Fixed Effect Estimation


•     Difference-in-Differences


•     DD with Variations in Treatment Timing: Andrew Goodman-Bacon (2021)

Lecture 7: Synthetic Control Method

•     Abadie (2021)


•     Peri and Yasenov (2019) and Bohn et. al (2014)

Lecture 8: Topics on Labor Demand: Minimum Wage

•     Substitution and Scale Effects of Labor Demand 


•     Recent Advances in Minimum Wage Research


•     Aaronson, French, Sorkin, and To (2018); Meer and West (2015)

Lecture 9: Instrumental Variables 

•     IV and Simultaneous Equations           


•     IV and LATE


•     Angrist and Evans (1998): Labor Supply and Fertility

Group Prsentations: present a paper from the Reading List (announced in class)

Lecture 10: Topics on Labor Demand: Bartik Instruments

•     The China Syndrome: Autor et. al (2013)


•     Bartik Instrument 


•     Sorkin (2019)

Lecture 11: Regression Discontinuity (Kink) Designs 

•     Identifying Assumptions and Estimation


•     IV and RD


•     Regression Kink Design


•     Unemployment Insurance

Lecture 12: Sufficient Statistic Approach for Welfare Analysis 

•     Basic Search Model


•     Optimal Unemployment Insurance: Baily-Chetty Formula


•     Consumption Based Approach: Gruber (1997)

Lecture 13: Decomposition Methods in Economics (Optional)

•     Oaxaca-Blinder Decomposition


•     DFL Reweighting Method


•     Chidren and Gender Inequality: Klevens et. al (2020) and Cortes et. al (2020)

Final Presentations

1. 50% Problem Sets 

We will do four problem sets during the course of semester. The problem set questions will include both theoretical questions and statistical analysis of data, which will involve the software package STATA.

2. 50% Presentations and Paper Proposal:

Each student is required to write a paper proposal. You are encouraged to meet with me to talk about a topic for your paper before midterm presentations. Final proposals are due on January 20.

Recommended Text for Labor Economics

George Borjas, Labor Economics (6^th edition)

Recommended Text for Econometrics:

Joshua D. Angrist and JÖrn-Steffen Pischke (2009), Mostly Harmless Econometrics, Princeton University Press 

Joshua D. Angrist and JÖrn-Steffen Pischke (2016), Mastering 'Metrics, Princeton University Press 

Jeffrey Wooldridge (2015), Introductory Econometrics: A Modern Approach (6th edition), Cengage 

Scott Cunningham (2021), Causal Inferences: The Mixtape, Yale University Press