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Random Sets in Econometrics by Francesca Molinari & Ilya Molchanov to be Published Online in April 2018

By: Heather LaCombe, 
Wed, 02/28/2018

Online publication for Ilya Molchanov and Francesca Molinari’s book Random Sets in Econometrics is planned for April of this year. Random set theory is a branch of mathematics that merges methods from topology, convex geometry, and probability theory. Random set theory has become an important tool in econometrics and finance. Charles Manski, the Board of Trustees Professor in Economics at Northwestern University praises the book by saying “Molchanov and Molinari, a brilliant collaboration of mathematician and econometrician, present the fundamentals meticulously and describe the fruitful applications to date. Their book provides the foundation for much more to come.”

Molchanov and Molinari’s book touts the honor of being the first book committed to the use of theory in econometrics and is written to be manageable for readers without much experience in pure mathematics. Victor Chernozhukov of the Economics Department and Center for Statistics and Data Science at MIT says that this book “should be of equal interest to students and researchers in mathematical statistics, econometrics, and machine learning, particularly in problems where set-valued predictions arise, in either observational or counterfactual settings.” To read more about Random Sets in Econometrics click here.

Francesca Molinari is the H.T. Warshow and Robert Irving Warshow Professor at Cornell University. Her research interests are in econometrics, both theoretical and applied. Most of her theoretical work is in partial identification, while her empirical work is concerned with estimation of risk preferences.

Ilya Molchanov is the Professor of Probability Theory, Director of studies in Statistics, and Director of IMSV at the Universität Bern, Switzerland. Some of his research interests include random sets, stochastic geometry, multivalued functions, and extreme values.

Random Sets in Econometrics Book Cover