**Optimization-Conscious Econometrics Summer School**

## About

The aim of the Summer school is to equip graduate students with tools to carry forefront research at the intersection of optimization and econometrics.

The OCE Summer school will be held on the University of Chicago campus June 4-7, 2023, and students are expected to likewise attend the OCE Conference on June 9 and 10, 2023.

Students may apply for funding to support accommodations and travels. Please contact event organizer Guillaume Pouliot with any questions at guillaumepouliot@uchicago.edu.

## Application Requirements

The Summer School is designed for graduate students focused in econometrics who want to strengthen their background in optimization. **Qualified applicants should have completed their second year field courses in econometrics**.

Students would likewise attend the **BFI OCE II Conference**, on June 9-10.

## Registration

**Fill out this form to apply** for funding to attend the OCE Summer School June 4-8. *Students are expected to cover the costs for the additional accommodation associated with staying for the BFI OCE Conference II.*

As part of the application form, student applicants will be required to send their transcript and a short statement of purpose explaining how they expect the school to help in their future research.

Application Form## Speakers

#### Guillaume A. Pouliot

Assistant Professor at Chicago Harris

Guillaume Pouliot is an Assistant Professor at Chicago Harris. His research focuses on developing statistical methods for nonstandard problems in public policy and economics, the extension of machine learning methods for applications in public policy, and problems at the interface of econometrics and optimization.

Pouliot received his PhD from Harvard University. Previously, he received his B.A. (Honors) in economics as well as his M.S. (concurrent) in statistics from the University of Chicago.

#### Pierre E. Jacob

Professor of Statistics, ESSEC Business School

Pierre E. Jacob is a professor of statistics at ESSEC Business School, in Paris, France.

His research pertains to statistical inference and time series analysis. Jacobs develops Monte Carlo methods to compare models or to estimate latent variables. At ESSEC he teaches courses on forecasting and statistics in general.

Jacob received his PhD from Université Paris Dauphine. Previous to joining ESSEC, Jacob was Associate Professor at the statistics department at Harvard University.

#### Alfred Galichon

Director, NYU Paris; Professor of Economics, NYU Arts & Science; Professor of Mathematics, NYU Courant Institute; Affiliated Professor of Data Science, NYU Center for Data Science

Alfred Galichon is a professor of economics and of mathematics at New York University, an affiliated faculty of NYU’s Center for Data Science, and the director of NYU Paris. He also serves as the principal investigator of the ERC-funded EQUIPRICE project at Sciences Po, Paris.

His research interests span widely across theoretical, computational and empirical economic questions and include econometrics, microeconomic theory, and data science. He is one of the pioneers of the use of optimal transport theory in econometrics, and the author of a monograph on the topic, *Optimal Transport Methods in Economics* (Princeton, 2016).

Galichon holds a Ph.D. in economics from Harvard University (2007), and an engineering degree from Ecole Polytechnique (X97) and one from Ecole des Mines de Paris (Corps des Mines, 2002). Among his numerous awards, he is an elected Fellow of the Society for the Advancement of Economic Theory, a Fellow of the Econometric Society, a “Young leader” of the French-American foundation, and a recipient of the Edmond Malinvaud prize.

#### Jean-Bernard Lasserre

Senior Scientist at the Centre National de la Recherche Scientifique (CNRS) at LAAS in Toulouse, France; Member of the Institute of Mathematics at the University of Toulouse

Jean B. Lasserre is a Senior Scientist at the Centre National de la Recherche Scientifique (CNRS), at LAAS in Toulouse, France, and is also member of the Institute of Mathematics at the University of Toulouse. He graduated from ENSIMAG (Grenoble) and earned his PhD and Doctorat d’Etat from the University of Toulouse. He spent two one-year visits in the EECS department at UC Berkeley. A SIAM Fellow, he is the recipient of the 2015 John von Neumann Theory Prize, the 2015 Khachiyan Prize, and the 2009 Lagrange Prize in Continuous Optimization, and was the 2014 Laureate of an ERC Advanced Grant from the European Research Council (ERC), and an Invited Speaker at the ICM 2018 in Rio de Janeiro. His research interests are in Applied Mathematics, Probability and Optimization.

### Curriculum

**Guillaume Pouliot**

##### Quantile Regression

##### Modern Introduction to Quantile Regression

*à la Chamberlain*, but for quantile regression. We consider interpretation, standard inference, and their pitfalls.

##### Quantile Regression Through the Lens of Linear Programming

##### Regression Rankscore Inference

##### Instrumental Variable Quantile Regression

#### Pierre Jacob

##### Markov Chain Monte Carlo and Couplings

##### Introduction to Markov Chain Monte Carlo (MCMC)

##### MCMC Theory

##### Implementable Couplings

##### Designing Couplings

#### Alfred Galichon

##### Optimal Transport

##### Network Flow Problems

##### The Optimal Assignment Model

##### More on the Optimal Assignment Model

and ranks.