70141 - Health Econometrics

Learning outcomes

At the end of the course the students have knowledge of a number of econometric models designed to study the behavior of economic agents using cross sectional and longitudinal data. They are able to critically evaluate the applications of the methods in the health economics field and to perform their own analysis in the context of new case studies.

Course contents

• Binary models
• Cross-sections and panel data models
• Event studies
• Survival models
• Synthetic controls

Readings/Bibliography

• Introductory Econometrics: A Modern Approach, 2019, 7th Edition, Jeffrey M. Wooldridge.
• Causal Inference: The Mixtape. Yale University Press, 2021. Cunningham, Scott.
• Survival analysis. 2005 Unpublished manuscript, Institute for Social and Economic Research, University of Essex, Colchester, UK. Jenkins, Stephen P.

Teaching methods

During each lecture we will discuss a different method and its applications to real-life problems. We will discuss and interpret empirical findings coming from published research articles. Data analysis with Stata will allow deeper understanding of the methods presented in class.

Assessment methods

The assessments include problem sets, in class participation and written exam.

The maximum possible score is 30 cum laude, in case all anwers and exercises are correct, complete and formally rigorous.

The grade is expressed as follows:

<18 failed
18-23 sufficient
24-27 good
28-30 very good
30 e lode excellen

Teaching tools

• Lectures slides
• References to published research articles
• STATA material

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

Office hours

See the website of Elisabetta De Cao