Econometrics
A.Y. 2025/2026
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 cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second trimester
Course syllabus
1. Economic Questions and the problem of causal inference
2. Simple regression model: properties and assumptions of the Ordinary Least Squares (OLS) estimator
3. Multiple regression model: estimation and inference
4. Limited dependent variable models: basic notions of Logit and Probit models; Linear probability model
5. Instrumental variables estimation and the Two Stage Least Squares (TSLS) estimator
6. Regression analysis with time series data
7. Introduction to panel data: fixed effects and random effects models
2. Simple regression model: properties and assumptions of the Ordinary Least Squares (OLS) estimator
3. Multiple regression model: estimation and inference
4. Limited dependent variable models: basic notions of Logit and Probit models; Linear probability model
5. Instrumental variables estimation and the Two Stage Least Squares (TSLS) estimator
6. Regression analysis with time series data
7. Introduction to panel data: fixed effects and random effects models
Prerequisites for admission
Introductory course in Statistics, including notions of inferential statistics. Notions of calculus and matrix algebra.
Teaching methods
Frontal lectures and practical examples in class using statistical software.
Teaching Resources
Wooldridge J. "Introductory Econometrics"
Angrist J., Pischke J.S. "Mostly Harmless Econometrics"
Stock J., Watson M. "Introduction to Econometrics"
Angrist J., Pischke J.S. "Mostly Harmless Econometrics"
Stock J., Watson M. "Introduction to Econometrics"
Assessment methods and Criteria
Written exam
Professor(s)