People

Directors

Joel HorowitzJoel Horowitz
Charles E. and Emma H. Morrison Professor

Joel Horowitz’s research is concerned with estimation and inference under weak assumptions about the process that generates the available data. It is also concerned with improving the accuracy of inference with samples of practical size and with using shape restrictions provided by economic theory to improve estimation and inference. He is a former co-editor of Econometrica and Econometric Theory, a Fellow of the Econometric Society and of the American Statistical Association, and an elected member of the International Statistical Institute.

Charles ManskiCharles Manski
Board of Trustees Professor

Charles Manski’s research spans econometrics, judgement and decision, and the analysis of social policy. He is author of Public Policy in an Uncertain World, Identification for Prediction and Decision, and Identification Problems in the Social Sciences. He has served as Director of the Institute for Research on Poverty and editor of the Journal of Human Resources. He is an elected member of the National Academy of Sciences, and a Fellow of the Econometric Society and of the American Academy of Arts and Sciences.

Members

Ivan Canay
HSBC Research Professor

Ivan Canay is a theoretical econometrician with specific interests in developing tests for assessing models that are partially identified or semi-parametric. His most recent work includes methods for inference on individual components of parameters defined by moment inequalities, inference in models with few clusters via randomization tests, and inference under covariate adaptive randomization. He is currently the co-editor of the the Journal of Business and Economic Statistics.

Eric Auerbach
Assistant Professor

Eric Auerbach works on identification and estimation with network data. His most recent work studies a linear models in which the regressors and error covary with drivers of link formation in a large sparse network and shows how the model is identified by variation in the regressor unexplained by the distribution of network links.

Federico BugniFederico Bugni
Professor

Federico Bugni has worked on a wide variety of topics
in econometrics, with an emphasis on statistical inference and identification in micro-econometrics. He is known for having tackled challenging open problems in a set of distinct areas, including inference in randomized controlled experiments, randomization tests, estimation and testing in dynamic discrete choice games, high dimensional models, and functional data, among others. He is best known for his contributions to the literature on inference in partially identified models. Bugni is currently an Associate Editor of Quantitative Economics, Journal of Econometrics, Journal of Business and Economic Statistics, and The Econometrics Journal.

Current Graduate Students

  • Deborah Kim
  • Ahnaf Rafi
  • Filip Obradovic
  • Amilcar Velez-Salamanca
  • Federico crippa
  • Bruno Fava
  • Danil Fedchenko
  • Kenneth Fu
  • Shuyan Huang