- Docente: Denni Tommasi
- Credits: 6
- SSD: SECS-P/05
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
-
Corso:
First cycle degree programme (L) in
Statistical Sciences (cod. 8873)
Also valid for Second cycle degree programme (LM) in Statistical Sciences (cod. 9222)
Learning outcomes
By the end of the course the student should be familiar with the theory and practice of single-equation linear econometric modelling. In particular, the student should be able to: - specify and estimate linear, single-equation econometric models with stochastic and possibly endogenous regressors; - derive and employ the asymptotic properties of linear method-of moments parameter estimators (OLS and IV) in these models; - perform a specification analysis of these models, - perform asymptotically valid inference based on these models.
Course contents
- Potential outcomes framework
- Matching
- Instrumental variables
- Regression discontinuity design (RDD)
- Difference-in-Differences (DID)
Readings/Bibliography
Scott Cunningham. Causal Inference: The Mixtape. New Haven: Yale University Press, 2021.
Joshua D. Angrist & Jörn‑Steffen Pischke: Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton: Princeton University Press, 2009.
Teaching methods
For each topic we will first introduce the relevant theory, and then move to its empirical application. Special emphasis will be placed on the economic interpretation of the results.
Assessment methods
Written exam, problem sets and in-class participation.
Teaching tools
We will discuss several empirical analysis using the econometric software STATA.
Office hours
See the website of Denni Tommasi