Program Evaluation Methods in Econometrics


Bertinoro, 18 - 23 July 2022



Francesco Ravazzolo

Free University of Bozen-Bolzano
4 Universitätsplatz 1 - piazza Università, 1
39100 Bozen-Bolzano



  • Matias D. Cattaneo, (Department of Operations Research and Financial Engineering Princeton University, USA)
  • Michael Jansson, (Department of Economics UC-Berkeley, USA & CREATES, DK )


The course is conditional to the recruitment of a minimum of 15 participants in presence. The maximum number of allowed participants in presence is 30.

If the conditions of the ongoing COVID 19 pandemic do not allow an in presence event, the course will be cancelled.

Basic knowledge of econometrics and statistics. 


Reference textbooks for the course:

  • Abadie, A. and Cattaneo, M. D. (2018). “Econometric methods for program evaluation,” Annual Review of Economics, 10, 465–503.
  • Angrist, J. D. and Pischke, J.-S. (2008). Mostly harmless econometrics: Princeton university press.
  • Cattaneo, M. D., Crump, R. K., Farrell, M. H., and Feng, Y. (2022a). “On binscatter,” arXiv preprint arXiv:1902.09608.
  • Cattaneo, M. D., Gong, A., Jansson, M., and Newey, W. K. (2022b). “Cluster Robust Inference in Linear Regression Models with Many Covariates.”
  • Cattaneo, M. D., Idrobo, N., and Titiunik, R. (2019). A practical introduction to regression discontinuity designs: Foundations: Cambridge University Press.
  • Cattaneo, M. D., Jansson, M., and Ma, X. (2020). “Simple local polynomial density estimators,” Journal of the American Statistical Association, 115(531), 1449–1455.
  • Cattaneo, M. D., Jansson, M., and Newey, W. K. (2018). “Inference in linear regression models with many covariates and heteroscedasticity,” Journal of the American Statistical Association, 113(523), 1350–1361.
  • Cattaneo, M. D. and Titiunik, R. (2022). “Regression Discontinuity Designs,” Annual Review of Economics.
  • Imbens, G. W. and Rubin, D. B. (2015). Causal inference in statistics, social, and biomedical sciences: Cambridge University Press.
  • Li, Q. and Racine, J. S. (2007). Nonparametric econometrics: theory and practice: Princeton University Press.

Handouts, readings and further material will be provided before the beginning of the course and during the lectures. 


Course description
The summer school offers a selective introduction to program evaluation methods in econometrics. The focus will be mostly on methodological developments, but applications will also be discussed as necessary. It would be ideal if participants had elementary working knowledge of statistics and econometrics at the master level, but the lectures will be self-contained. Topics covered include causal inference, linear regression methods, semi-/non-parametric regression methods, and regression discontinuity designs

Schedule of the course:

• Mon 18-Jul – Introduction and Causal inference.
• Tue 19-Jul – Linear and Non-linear models.
• Wed 20-Jul – Standard Errors and Inference (morning), and Student Presentations (afternoon).
• Thu 21-Jul – Semi-/Non-parametrics (morning), and Homework Computer Session (afternoon).
• Fri 22-Jul – Regression Discontinuity Designs.
• Sat 23-Jul – Student presentations (morning).


Venue and timetables

The Module will last one week and will be held in the University Residential Centre, Via Frangipane 6, 47032 Bertinoro (FC). Participants will be hosted in the Centre guest quarters (in case of reduced availability of rooms in the Centre, they will be accommodated in local hotels).
Lectures and tutorials will be in English, with the following schedule:

  • Monday to Friday: lectures 9:00-13:00, 15:00-17:00
  • Saturday: lectures 9:00-13:00.