79195 - Statistics for Economics

Learning outcomes

By the end of the course, the students will have a good knowledge of the issues related to the measurement and modelling of economic behaviours, and more specifically: - the ability to provide a critical assessment on the quality and reliability of data from the main types of economic survey; - a good understanding of the specification and estimation techniques for a selection of statistical models grounded in economic theory; - a basic knowledge on the statistical models employed in the evaluation of economic policies with non-experimental data.

Course contents

The course will cover the following topics:

• Statistics for economics: questions, models, data types, measurement
• Issues in estimating economic models: causality, endogeneity, corner solutions and censoring, selection biases, theoretical restrictions
• Policy evaluation with quasi-experimental data: Difference-in-Difference, Regression Discontinuity Designs, Instrumental Variables, Propensity Score Matching, Interrupted Time Series
• Applications in economics & business: modelling consumer demand; evaluating the impact of public policies; evaluating the effects of supermarket promotions; market forecasts

Readings/Bibliography

The course will be mainly based on lecture notes and chapters/papers provided through the e-learning platform

Useful reference books are:

Wooldridge, J.M. (2015). Introductory econometrics: A modern approach. South-Western Pub.

Angrist, J.D & Pischke, J-S. (2015). Mastering 'Metrics: The Path from Cause to Effect. Princeton University Press.

Teaching methods

Each topic will be covered from both a theoretical and empirical perspective. Applications will be based on real data using the software STATA ®.

Assessment methods

Written exam.

The exam will be based on theoretical and empirical questions on topics and applications discussed during the course. The written exam is structured in two parts:

- A theoretical section, with multiple choice and/or open ended questions on topics covered during the course;

- An empirical question, where the student is presented with Stata codes and outputs produced during the course lab sessions, and is asked to interpret them and answer a set of questions

The two parts will equally weigh on the final mark.

Teaching tools

The e-learning platform will provide students with:

- Lecture slides and notes

- Useful readings (articles, book chapters, etc.)

- Data and codes for Stata tutorials

- Exam-type questions

These materials will be provided and integrated throughout the course.

Office hours

See the website of Mario Mazzocchi

See the website of Beatrice Biondi