10-12 July 2017
Summer School on 'Impact Evaluation Methodologies'
The fourth edition of the Summer School on " Methodologies for Impact Evaluation", co-sponsored by the European Social Fund Project (ESF), the Ministry of Labour, Employment and the Social and Solidarity Economy of Luxembourg, ARCO (Action Research for CO-Development) & LISER, will be held in Luxembourg on the 10th-12th July 2017 and is directed to consultants, doctoral and post-doctoral students, academics, as well as anyone interested in methods used in evidence-based policy making.
Professors Donald B. Rubin, Fabrizia Mealli and Alfonso Flores-Lagunes will be among the instructors of the summer school. Participants will have the opportunity to appraise cutting-edge methodologies directly from some of the scholars who are currently setting the methodological frontier. The school will also be a valuable opportunity for networking with other impact evaluation professionals coming from diverse fields.
Introduction to Causal Inference. Causal inference and the Rubin Causal Model. Potential outcomes. Assignment mechanism. Randomized experiments. Different modes of inference.
Observational Studies. Unconfoundedness assumption. The role of the propensity score in designing observational studies. Estimating average treatment effects. Matching. Sensitivity analysis.
Causal inference with instrumental variables (IV) bridging randomized trials with noncompliance. Other broken randomized experiments: principal stratification. Regression discontinuity (RDD) designs: sharp and fuzzy designs.
| Prof. Donald B. Rubin |
Donald B. Rubin is John L. Loeb Professor of Statistics, Harvard University, where he has been professor since 1983, and Department Chair for 13 of those years. He has been elected to be a Fellow/Member/Honorary Member of: the Woodrow Wilson Society, John Simon Guggenheim Memorial Foundation, Alexander von Humbolt Foundation, American Statistical Association, Institute of Mathematical Statistics, International Statistical Institute, American Association for the Advancement of Science, American Academy of Arts and Sciences, European Association of Methodology, British Academy, and the U.S. National Academy of Sciences. He has authored/coauthored nearly 400 publications (including ten books), has four joint patents, and has made important contributions to statistical theory and methodology, particularly in causal inference, design and analysis of experiments and sample surveys, treatment of missing data, and Bayesian data analysis. Among his other awards and honors, Professor Rubin has received the Samuel S. Wilks Medal from the American Statistical Association, the Parzen Prize for Statistical Innovation, the Fisher Lectureship, and the George W. Snedecor Award of the Committee of Presidents of Statistical Societies. He was named Statistician of the Year, American Statistical Association, Boston and Chicago Chapters. He has served on the editorial boards of many journals, including: Journal of Educational Statistics, Journal of American Statistical Association, Biometrika, Survey Methodology, and Statistica Sinica. Professor Rubin has been, for many years, one of the most highly cited authors in mathematics in the world (ISI Science Watch), as well as in economics (Highly Cited Economists), with nearly 160,000 citations by autumn 2014, with over 16,000 in 2013 (according to Google Scholar). For decades he has given keynote lectures and short courses in the Americas, Europe, and Asia. He has also received honorary doctorate degrees from Otto Friedrich University, Bamberg, Germany; the University of Ljubljana, Slovenia, and Universidad Santo TomÃ¡s, BogotÃ¡, Colombia; as well as honorary professorships from University of Utrecht, The Netherlands; Nanjing University of Science & Technology, Nanjing, China; Xian University of Technology, Xian, China; and Shanghai Finance University, Shanghai, China.
| Prof. Fabrizia Mealli |
Fabrizia Mealli is Professor of Statistics at the Department of Statistics, Computer Science, Applications "G. Parenti", University of Florence. She is also external Research Associate at the Institute for Social and Economic Research (ISER), University of Essex (UK). She received her PhD in Applied Statistics from the University of Florence in 1994. She held visiting positions at UCLA (Dept. of Economics) in 2000 and at Harvard University (Dept. Of Statistics) in 2001, 2011 and 2015. She has given short courses in Causal Inference and Missing Data in Europe and in the US. Her research interests cover the following topics: causal inference, program evaluation, estimation techniques, simulation methods, missing data, models for transition data, Bayesian inference. She has published in statistics, applied statistics, biostatistics, econometrics, economics, and demography journals. She is elected fellow of the American Statistical Association. She is currently Associate editor for the Journal of the Royal Statistical Society â Series A, the Journal of the American Statistical Association â T&M, the Annals of Applied Statistics and Biometrics. Fabrizia Mealli is from 2014 Scientific Coordinator of the Impact Evaluation Unit of ARCO lab.
| Prof. Alfonso Flores-Lagunes |
Alfonso Flores-Lagunes is professor of economics at the Maxwell School of Citizenship and Public Affairs and Senior Research Associate at the Center for Policy Research as of August 2014. He is a research fellow at the Institute for the Study of Labor (IZA), an international network of researchers around labor market research and policies, since 2008. Dr. Flores-Lagunes has held faculty appointments at the State University of New York at Binghamton, University of Florida, and University of Arizona. He has been a visiting fellow at the Industrial Relations Section and the Department of Economics of Princeton University, and visiting scholar or lecturer at Cornell, The Ohio State, LISER (Luxembourg), and the Central Bank of Mexico. He holds a B.A. in economics from Monterrey Institute of Technology (ITESM) in Mexico, and M.A. and Ph.D. degrees in economics from The Ohio State University.
The summer school will be followed by a 2-day International Workshop on "Causal Inference, Program Evaluation and External Validity" (13-14 July, 2017).