Student authentication

Is it the first time you are entering this system?
Use the following link to activate your id and create your password.
»  Create / Recover Password



Learning Objectives

Learning outcomes: The aim of this course is to provide students with the core methods in Econometrics.

Knowledge and understanding: On successful completion of the course, students will be able to understand standard econometric tools. Specifically, we will study cross-sectional regression analysis in presence of continuous or limited dependent variables. Emphasis will be placed on robust inference and how to address endogeneity issues using instrumental variables estimation.

Applying knowledge and understanding: On successful completion of the course, students will be able to master the common formats of economic data and implement a regression analysis using the Stata statistical software.

Making judgements: On successful completion of the course, students will be able to orient themselves between different techniques and choose the best for the case at hand.

Communication skills: Students will be able to effectively communicate the results of their own elaborations and analyses.


Students should have completed Mathematics (8011190) and Statistics (8010848). A basic knowledge of the Stata statistical software is required.


- Intro:
Econometric modeling and the structure of economic data
Ordinary Least-squares and the simple linear regression model

- Multiple Regression Analysis:
Algebraic aspects of least squares
Least squares statistical (finite samples) properties
Qualitative information
The Gaussian linear model and exact statistical inference
Least-squares asymptotic and approximate inference
Robust inference
Testing for heteroskedasticity and Generalized Least Squares

- Endogeneity and the Instrumental Variables (IV) approach:
Main assumptions
Simple IV and the Wald estimator
Two Stage Least Squares
Testing for endogeneity, instruments' relevance, and overidentifying restrictions

- Models for limited dependent variables:
Binary outcomes
Multinomial outcomes
Count outcomes
Truncation and sample selection


The main reference is Wooldridge J.M., (2016), Introductory Econometrics: A Modern Approach, 6th ed., Cengage Learning.

For some topics, Wooldridge (2016) will be complemented by selected articles which will be made available on the material section of the course website and by some chapters from:

Greene W.H., Econometric Analysis, 8th ed., Pearson.


For further study in econometrics, I suggest Peracchi (2001), Wooldridge (2010) and references therein:

Peracchi F. (2001), Econometrics, Wiley, Chichester (UK).
Wooldridge J.M., (2010), Econometric Analysis of Cross-Section and Panel Data, 2nd ed., MIT Press, Cambridge (MA).

Teaching methods

Lectures will be held in class.

Exam Rules

The final exam is a one and a half hours written test consisting of three exercises. Some exercises will report Stata’s output and will require their interpretation. To pass the exam, the student must get a mark of 18 in at least two exercises. The final mark will be computed as the average of the three exercises. For each exercise, the mark can range from 0 to 33, so students can obtain a final mark of 30 even without getting a mark of 30 to all exercises. The exam is aimed at assessing whether the student has acquired a solid knowledge of the topics covered during the course, both from a theoretical and a practical point of view. Students must book for the final exam on https://delphi.uniroma2.it. Students who fail or withdraw from the exam may take it again in the same session.