[Forum SIS] Short Course: Statistical methods for policy evaluation and causal inference in observational studies

[Domenico Vistocco]

Segnalo la seguente iniziativa organizzata presso il Dipartimento di Economica e Giurisprudenza dell'Università degli Studi di Cassino e del Lazio Meridionale, nell'ambito della scuola estiva su R.

Sono a disposizione per ulteriori dettagli relativi all'iscrizione.

Un cordiale saluto
domenico vistocco


+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
UNIVERSITA' DEGLI STUDI DI CASSINO E DEL LAZIO MERIDIONALE
DIPARTIMENTO DI ECONOMIA E GIURISPRUDENZA
Via S.Angelo - Località Folcara, 03043 Cassino
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

SHORT COURSE
Statistical methods for policy evaluation and causal inference in observational studies
------------------------------------------------------------------------------------------------------------------------
BRUNO ARPINO
Department of Political and Social Sciences
Universitat Pompeu Fabra
Barcelona, Spain
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

GIOVEDI 19 - VENERDI 20 SETTEMBRE 2013 
	- ore 9:00   - 13:00 Aula 1.01 
	- ore 14:30 - 17:30 Aula 1.05 (laboratorio Informatico)

------------------------------------------------------------------------------------------------------------------------

SHORT DESCRIPTION:
What is the effect of smoking on health? Does having an additional child increase the risk of poverty? Are the development policies targeted on small firms effective in increasing investments?
Most studies in the social sciences are motivated by questions that are causal in nature. However, in these areas experiments are very rare because of ethical or practical reasons and the estimation of causal effects has to rely on observational studies. The validity of inference will then strictly depend on the plausibility of the assumptions underlying the employed statistical techniques. Special emphasis will be placed during the course on the language used in formulating those assumptions and on some of the statistical methods that have been developed for the assessment of causal claims.
This short course will offer participants theoretical and applied perspectives on the covered topics. Examples will be drawn from economics, political science, sociology, public health and policy evaluation. A lab session will be organized to demonstrate the implementation of some of the covered techniques using the software R.

------------------------------------------------------------------------------------------------------------------------

PROGRAM
DAY 1:
Why do we need causal inference? (Introduction to causal inference)
What assumptions do we need to identify causal effects? (Assignment mechanisms; randomized experiments versus observational studies)
How can we estimate causal effects? (Part 1: Propensity score techniques; Alternative matching strategies)
DAY 2:
How can we estimate causal effects? (Part 2: Instrumental variables regression; Regression Discontinuity Design)
Are our conclusions robust to violation of assumptions? (Sensitivity analysis)

LAB SESSIONS in R

------------------------------------------------------------------------------------------------------------------------

ABOUT THE INSTRUCTOR

Bruno Arpino is an assistant professor at the Department of Political and Social Sciences, Universitat Pomepu Fabra. Previously, he has been working as post-doc research fellow at Bocconi University in Milan (Italy). He obtained a PhD in Applied Statistics from the University of Florence (Italy) in 2008 with a thesis titled "Causal inference for observational studies extended to a multilevel setting. The impact of fertility on poverty in Vietnam"ˇ. The thesis was awarded by the Italian Statistical Society the price as the best thesis in Applied Statistics 2007/2008. His main research interests are in the areas of causal inference and multilevel models and their application in the socio-demographic field. He has published articles in international peer-reviewed journals such as Journal of the Royal Statistical Society A, Computational Statistics and Data Analysis, Empirical Economics, Regional Studies, Environment and Planning A, Quality & Quantity.

Web-page: https://sites.google.com/site/brunoarpino/

+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://www.stat.unipg.it/pipermail/sis/attachments/20130913/4c0b4b92/attachment.html>