70141 - HEALTH ECONOMETRICS

Conoscenze e abilità da conseguire

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.

Contenuti

The focus will be on theoretical discussion of causal inference and estimation of treatment effects. We will first discuss a general causal model using the counterfactual outcomes framework; we will then go through the main methods available to the empirical researcher to estimate causal parameters. We will stress how these methods require different assumptions about the assignment mechanism, i.e. the mechanism used to assign individuals to the treatment. We start with the assumption that assignment is (conditionally) random, and discuss suitable methods such as matching and OLS regression. We will then consider a confounded assignment mechanism, and discuss instrumental variable analysis (IV) as well as regression discontinuity design (RDD), which exploits changes in the probability of receiving treatment due to discontinuities in the assignment mechanism. Finally, we will discuss methods which rely on longitudinal information to recover causal parameters

Testi/Bibliografia

Introductory Econometrics: A Modern Approach, 2019, 7th Edition, Jeffrey M. Wooldridge.

Causal Inference: The Mixtape. Yale University Press, 2021. Cunningham, Scott. https://mixtape.scunning.com/

Blundell, R., and M. Costa Dias (2009). "Alternative Approaches to Evaluation in Empirical Microeconomics." Journal of Human Resources, 44(3), 565-640.

Imbens, G., and J.F. Wooldridge (2009). "Recent Developments in the Econometrics of Program Evaluation." Journal of Economic Literature, 47(1): 5-8

Athey, S., and Imbens, G. W. (2017). "The State of Applied Econometrics: Causality and Policy Evaluation." Journal of Economic Perspectives, 31(2), 3–32.

Metodi didattici

Face-to-face lectures based on professor's slides.

In class tutorials with hands-on practical examples.

Modalità di verifica e valutazione dell'apprendimento

The final grade will depend on:

• Quizzes in class
• Group problem sets
• Final exam

More details will be provided in the Virtuale page of the course.

The maximum possible score is 30 cum laude, in case all answers/course works are correct, complete and formally rigorous.

The grade is graduated as follows:

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

Strumenti a supporto della didattica

Dedicated page on the VIRTUALE platform containing:

• News and updated information
• Lectures slides
• STATA lab 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.

Software R: freely available online.

Orario di ricevimento

Consulta il sito web di Pietro Biroli