93674 - Quantitative Economics And Public Policy

Course Unit Page

Academic Year 2022/2023

Learning outcomes

The course provides an overview of some of the most widely used quantitative methods for social sciences and economics, with an emphasis on regression analysis. The general linear regression model is considered at length, together with some of its incarnations and extensions. These include: the instrumental variables method, models for discrete random variables, models for panel data, and models for time series data. The course has an applied orientation. Examples draw heavily from the political sciences, and are analyzed using the R programming language. At the end of the course, diligent students will be able to apply the methods considered, using R, and to correctly interpret the results of their analyses.

Course contents

The course will introduce the basics of regression analysis and cover simple applications of the theoretical models by analysing real-world data using the software Stata.
In particular, the course will cover:

- Linear Regression with One Regressor.

- Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals

- Linear Regression with Multiple Regressors.

- Hypothesis Tests and Confidence Intervals in Multiple Regression

- Interactions between Independent Variables


James H. Stock, Mark W. Watson - Introduction to Econometrics, Fourth Edition (Chapters 4, 5, 6, 7, 8.3)

Teaching methods

- Taught Classes

- In-class individual exercises and group work with the Stata software.

During the lectures, the presentation of theoretical issues will be complemented by critical discussion of some micro-economic applications from recent research using different econometric models and techniques.

Students will receive data to practice at the computer and learn how to apply the various models using the software STATA, which is available to them through the CAMPUS license.

Assessment methods

There are two components of the course assessment: an optional take-home assignment and a written exam.

The optional take-home exercise is based on programming, and it is aimed at testing the ability to apply the methods learnt to simulated or real data, using Stata.

The written exam aims at testing the acquired knowledge of the theoretical concepts and the ability to interpret estimation results in the light of the underlying theory.


The maximum possible score is 30 cum laude, in case all answers are correct, complete and formally rigorous.
Passing numerical grades are intended to match the following qualitative description:

18-23: sufficient
24-27: good
28-30: very good
30 cum laude: excellent.

Teaching tools

Dedicated page on the Virtuale platform (virtuale.unibo.it) containing:

  • News and updated information
  • Lectures slides
  • Stata lab material

Software Stata 17 SE: can be installed on students' personal computers (CAMPUS license) and is available at the Computer Lab of the School of Economics and Management.

You can download Stata here.

Office hours

See the website of Antonio Schiavone