Econometrics
A.Y. 2024/2025
Learning objectives
The objective of Econometrics is to provide students with the basic principles of the econometric analysis. All the theoretical aspects of the econometric modelling will be treated jointly with interesting and modern empirical applications in order to motivate students and try to respond to real-world questions with specific numerical answers.
Expected learning outcomes
By the end of the module you will be able to:
Estimate a model using Least Squares.
Interpret the regression estimate and the computer output.
Apply diagnostics to check if the model is correctly specified and propose procedures to correct the miss-specification.
Run an independent analysis in an applied project.
Estimate a model using Least Squares.
Interpret the regression estimate and the computer output.
Apply diagnostics to check if the model is correctly specified and propose procedures to correct the miss-specification.
Run an independent analysis in an applied project.
Lesson period: Second trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
Second trimester
Course syllabus
ECONOMETRICS
· The nature of econometrics and economic data
· Regression analysis with cross sectional data
· Linear Regression with One Regressor
· Linear Regression with Multiple Regressors
· Hypothesis Testing
· Large samples
· Further issues in the linear regression model
· Instrumental Variable Regression (IV-TSLS)
· Regression with a Binary Dependent Variable
· Regression with pooled cross sections
· Regression with panel data
· Regression with time series data
· The nature of econometrics and economic data
· Regression analysis with cross sectional data
· Linear Regression with One Regressor
· Linear Regression with Multiple Regressors
· Hypothesis Testing
· Large samples
· Further issues in the linear regression model
· Instrumental Variable Regression (IV-TSLS)
· Regression with a Binary Dependent Variable
· Regression with pooled cross sections
· Regression with panel data
· Regression with time series data
Prerequisites for admission
This module is taught in English.
The module requires knowledge of differential calculus and of Statistical Theory at introductive level.
The module requires knowledge of differential calculus and of Statistical Theory at introductive level.
Teaching methods
20 two-hours lectures
Teaching Resources
ECONOMETRICS
The reference book is:
∙ Wooldridge, J., 2003. Introductory econometrics, 2nd ed., South Western College Publishing, or more recent editions.
The reference book is:
∙ Wooldridge, J., 2003. Introductory econometrics, 2nd ed., South Western College Publishing, or more recent editions.
Assessment methods and Criteria
Assessment
Econometrics is assessed by means of a 90 minutes written exam only.
Only for the first assessment, (at the end of the lectures) it is possible to complement the Econometrics exam with a Mini-Project.
Econometrics is assessed by means of a 90 minutes written exam only.
Only for the first assessment, (at the end of the lectures) it is possible to complement the Econometrics exam with a Mini-Project.
Professor(s)
Reception:
Thursday, 11AM to 1PM. Please email me to arrange an appointment
Stanza 4 (Second floor)