Econometrics
A.A. 2023/2024
Insegnamento per
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Docente responsabile: Andrea Bastianin
This course covers the statistical tools needed to understand empirical economic research and to plan and execute independent research projects.
Estimation and testing of economic models will be an important part of the course. This course begins with the linear model but considers extensions in several directions: (1) predetermined but not exogenous regressors; (2) heteroskedasticity and serial correlation; (3) classical GLS; (4) instrumental variables and generalized method of moments estimators. Maximum likelihood estimation and inference are discussed.
This course covers the statistical tools needed to understand empirical economic research and to plan and execute independent research projects.
Estimation and testing of economic models will be an important part of the course. This course begins with the linear model but considers extensions in several directions: (1) predetermined but not exogenous regressors; (2) heteroskedasticity and serial correlation; (3) classical GLS; (4) instrumental variables and generalized method of moments estimators. Maximum likelihood estimation and inference are discussed.
This course covers the statistical tools needed to understand empirical economic research and to plan and execute independent research projects. Estimation and testing of economic models will be an important part of the course. This course begins with the linear model but considers extensions in several directions: (1) predetermined but not exogenous regressors; (2) heteroskedasticity and serial correlation; (3) classical GLS; (4) instrumental variables and generalized method of moments estimators. Maximum likelihood estimation and inference are discussed.
Estimation and testing of economic models will be an important part of the course. This course begins with the linear model but considers extensions in several directions: (1) predetermined but not exogenous regressors; (2) heteroskedasticity and serial correlation; (3) classical GLS; (4) instrumental variables and generalized method of moments estimators. Maximum likelihood estimation and inference are discussed.
This course covers the statistical tools needed to understand empirical economic research and to plan and execute independent research projects.
Estimation and testing of economic models will be an important part of the course. This course begins with the linear model but considers extensions in several directions: (1) predetermined but not exogenous regressors; (2) heteroskedasticity and serial correlation; (3) classical GLS; (4) instrumental variables and generalized method of moments estimators. Maximum likelihood estimation and inference are discussed.
This course covers the statistical tools needed to understand empirical economic research and to plan and execute independent research projects. Estimation and testing of economic models will be an important part of the course. This course begins with the linear model but considers extensions in several directions: (1) predetermined but not exogenous regressors; (2) heteroskedasticity and serial correlation; (3) classical GLS; (4) instrumental variables and generalized method of moments estimators. Maximum likelihood estimation and inference are discussed.
Knowledge of Statistics and Mathematical analysis (linear algebra).
For first year students - Mandatory for Economics PhD students.
For first year students - Mandatory for Economics PhD students.
Modalità di valutazione
Esame
Giudizio di valutazione
voto verbalizzato in trentesimi
Iscrizioni
Scadenze
Il termine di iscrizione ai corsi è previsto generalmente entro il 27° giorno del mese precedente al mese di avvio.
Come iscriversi
- Autenticarsi al servizio di iscrizione con le credenziali di Ateneo
- Selezionare l’insegnamento scelto e cliccare su Iscrizione e infine su Iscriviti
Trascurare del tutto la voce "Data di appello" che appare durante la procedura di iscrizione.
Assistenza
Per informazioni e richieste di chiarimento scrivere a: [email protected]
Docente/i
Ricevimento:
Martedì 13-16
MS TEAMS (previo appuntamento via email)