10532 - Applied Econometrics

Course Unit Page

Academic Year 2018/2019

Learning outcomes

At the end of this course students will be able to apply basic econometric techniques to empirical settings, particularly regarding labour economics and consumer demand.

In particular, students will be able to:

- interpret and perform linear and non-linear regression analysis

- understand regression analysis with panel data, with binary dependent variables and with instrumental variables

- apply the techniques learnt to the economic context

- use Stata software to perform econometric analysis

Course contents

Students will learn new concepts but emphasis remains mainly on applications of econometrics models to economic analysis.

Linear and non-linear regression models, and models with endogenous regressors: examples and applications in the lab.

Regression models with binary dependent variables: introductory notions, estimation, hypothesis testing and applications in the lab.

Regression models with panel data: introductory notions, estimation, hypothesis testing and applications in the lab.


The following are reference books. More detailed information and material for empirical analyses will be provided during the lectures. The course web site will provide detailed references for each lecture.

Stock, J.H., Watson, M.W. "Introduzione all'econometria", 4a edizione (2016), Pearson Education Italia.

M. Verbeek, “A Guide to Modern Econometrics”, 5th edition, Wiley.

Teaching methods

Traditional lectures to introduce econometric techniques and to analyse empirical applications.

Lab sessions with real data analysed using Stata software.

Questionnaires handed out to assess learning and stimulate discussion.

Assessment methods

For students who attend lectures, written examination (80% of the final mark) and empirical econometrics project to hand in by the first full exam of the relevant academic year (20% of the final mark). For students who do not attend lectures, written examination.

The written examination aims to assess knowledge of the theoretical tools adopted in the course, the ability to apply such tools to empirical contexts, and the ability to interpret the outcome of empirical analyses. The exam will have open questions and multiple choice questions, also regarding the interpretation of Stata output, in a similar fashion to the examples seen in the course and available on the course web site. Supporting material (textbooks, notes, electronic and web enabled devices etc.) is not allowed.

The empirical project requires solving exercises using Stata, in a similar fashion to the material covered in the lab sessions.

Teaching tools

  • Slides, available on the course web site
  • Stata software
  • Data and corresponding Stata code

Office hours

See the website of Renata Bottazzi