Econometrics
A.Y. 2023/2024
Course offered to students on the PhD programme in
Visit the PhD website for the course schedule and other information
Lead instructor: 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.
Assessment methods
Esame
Assessment result
voto verbalizzato in trentesimi
How to enrol
Deadlines
The course enrolment deadline is usually the 27th day of the month prior to the start date.
How to enrol
- Access enrolment on PhD courses online service using your University login details
- Select the desired programme and click on Registration (Iscrizione) and then on Register (Iscriviti)
Ignore the option "Exam session date” that appears during the enrolment procedure.
Contacts
For help please contact [email protected]
Professor(s)
Reception:
Tuesday 13-16
MS Teams (please send email for confirmation)