Applied Microeconometrics

In Autumn 2020, I held weekly discussion sections in the second-year Ph.D. course Applied Microeconometrics taught by Alex Torgovitsky.

1. Tools and Frameworks for Causal Inference
   
2. Selection on Observables: Theory
   
3. Selection on Observables: Implementation
   
4. The Theory of Identification
   
5. Instrumental Variables
   
6. Marginal Treatment Effects: Theory
   
7. Marginal Treatment Effects: Implementation
   
8. Discontinuity Designs
   
9. Difference-in-Differences

Difference-in-Differences Designs

In Spring 2022, I organized a student reading group to explore recent advances in the literature on difference-in-differences designs.

1. Introduction
   
2. Goodman-Bacon (2021), by Colin Aitken
   
3. Sun and Abraham (2021), by Myungkou Shin
   
4. Callaway and Sant’Anna (2021), by Jonas Lieber
   
5. Borusyak, Jaravel, and Spiess (2022), by Sasha Petrov

I also presented and discussed two papers in our Econometrics Advising Group.

• de Chaisemartin and D’Haultfœuille (2018), Fuzzy Difference-in-Differences
• The Common Trends Restriction and Dynamic Models of Economic Choice: a Reconciliation

Structural Econometrics Methods

In Spring 2020, I organized a student reading group to explore commonly used methods for the estimation of structural parameters in economic models.

1. Method of Maximum Simulated Likelihood
   
2. Method of Simulated Moments, by Olivia Bordeu and Lillian Rusk
   
3. Tebaldi, Torgovitsky, and Yang (2022), by Nadav Kunievsky
   
4. Shift-Share Designs, by Peter Hull
   
5. Bunching Designs, by Shanon Hsuan-Ming Hsu
   
6. Heathcote, Storesletten, and Violante (2014), by Thomas Bourany