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Updated A.Y. 2021-2022


The aim of this course is to provide a survey of state-of-the-art microeconometric techniques. We will cover linear models for longitudinal data and a variety of causal inference designs and methods. We will discuss the strengths and weaknesses of these tools using economic applications.

A willingness to work hard on possibly unfamiliar material is key and, in addition to the material covered in the Mathematics (8011190), Statistics (8010848) and Econometrics (8011571) courses, I also expect that you are reasonably proficient with the Stata statistical software.



- Causal inference: main assumptions and estimands
- Regression (reloaded)
- Propensity score estimators
- Matching

  • Matching on the PS

- Regression discontinuity

  • Sharp design
  • Fuzzy design

- Panel data

  • Pooling
  • Random-effects
  • Fixed-effects (within group and first-differences estimators)
  • Interactive fixed-effects
  • Correlated random-effects
  • Hausman type tests

- Difference-in-differences
- (Generalized) Synthetic controls



The main references are Wooldridge (2010) and Cunningham (2021). For further study in microeconometrics I suggest: Hansen (2021), Hsiao (2014), Cameron and Trivedi (2005) and Peracchi (2001). Angrist and Pischke (2009) for applied issues. Lecture notes, slides and Stata codes will be posted in the material section. Suggestions for further reading will be provided in class. 

Wooldridge J.M., (2010), Econometric Analysis of Cross-Section and Panel Data, 2nd ed., MIT Press, Cambridge (MA).

Hansen B.E., (2020), Econometrics, download the book here.

Peracchi F. (2001), Econometrics, Wiley, Chichester (UK).

Cameron C., Trivedi P.K., (2005), Microeconometrics: methods and applications, Cambridge University Press.

Hsiao C.,(2014), Analysis of Panel Data. Cambridge University Press, New York, NY, 3rd edition.

For a focus on applied issues see

Cunningham S., (2021) Causal Inference: The Mixtape. Yale University Press.

Angrist J.D., and Pischke J.-S., (2009), Mostly Harmless Econometrics: An Empiricists’s Companion, Princeton University Press, Princeton.