- Docente: Denni Tommasi
- Crediti formativi: 6
- SSD: SECS-P/05
- Lingua di insegnamento: Inglese
- Modalità didattica: Convenzionale - Lezioni in presenza
- Campus: Bologna
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Corso:
Laurea in
Scienze statistiche (cod. 8873)
Valido anche per Laurea Magistrale in Statistical Sciences (cod. 9222)
Conoscenze e abilità da conseguire
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.
Contenuti
- Potential outcomes framework
- Matching
- Instrumental variables
- Regression discontinuity design (RDD)
- Difference-in-Differences (DID)
Testi/Bibliografia
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.
Metodi didattici
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.
Modalità di verifica e valutazione dell'apprendimento
Written exam, problem sets and in-class participation.
Strumenti a supporto della didattica
We will discuss several empirical analysis using the econometric software STATA.
Orario di ricevimento
Consulta il sito web di Denni Tommasi