Microeconometrics (PhD)

I teach PhD Micro-Econometrics at Kansas State University. This is a second year PhD course that aims to introduce important econometric tools used in empirical micro research.

I was also the TA for the corresponding course at Boston University for 4 years. See below for links to some of my discussion slides.


Course Outline:

1. Causality and potential outcomes framework

2. Instrumental variables and LATE

3. SUTVA, incidental parameters problem, improving precision, randomization schemes, bad controls 

4. Difference-in-differences 

5. Event study, Synthetic controls

6. Clustering standard errors

7. Propensity scores and Matching

8. Weighting regressions 

9. Oster bias correction 

10. Multiple hypothesis testing 

11. Regression discontinuity

12. Selection models

13. Handling zeros and effects of measurement units 

14. Discrete choice models

15. Count data

16. Numerical optimization methods 

17. Miscellaneous topics (if time permits): Randomization inference, bootstrapping standard errors, Bartik instruments, Judge instruments, simulation methods, nonparametrics, control functions.

I was the TA for Graduate Microeconometrics (2nd year PhD course) from Fall 2019-2022 at Boston University. The slides I made for some of my weekly discussions can be found below. They all borrow from various sources, and I've tried my best to list all the references.