Programma

Basic knowledge of inference and linear algebra. Classical linear regression model: basic model assumptions, least squares estimation, maximum likelihood estimation, testing of model parameters, linearity, heteroschedasticity, autocorrelation, multicollinearity, endogenous regressors and estimators to instrumental variables, linear prediction, misspecification, stability of regression function.
Fixed-effects and random-effects panel data models. Time series analysis: descriptive aspects, AR, MA, ARMA models, distributed lag models.

Testi Adottati

Introduzione all’econometria
James H. Stock - Mark W. Watson
Ed. Pearson

Econometria
Marno Verbeek
Ed. Zanichelli

Lecturer's Notes

Modalità Erogazione

Classroom lectures

Modalità Valutazione

Oral interview on course topics

Programma

Basic knowledge of inference and linear algebra. Classical linear regression model: basic model assumptions, least squares estimation, maximum likelihood estimation, testing of model parameters, linearity, heteroschedasticity, autocorrelation, multicollinearity, endogenous regressors and estimators to instrumental variables, linear prediction, misspecification, stability of regression function.
Fixed-effects and random-effects panel data models. Time series analysis: descriptive aspects, AR, MA, ARMA models, distributed lag models.

Testi Adottati

Introduzione all’econometria
James H. Stock - Mark W. Watson
Ed. Pearson

Econometria
Marno Verbeek
Ed. Zanichelli

Lecturer's Notes

Modalità Erogazione

Classroom lectures

Modalità Valutazione

Oral interview on course topics