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Optimization-Conscious Econometrics Conference II

Astonishing recent progress in numerical optimization presents many opportunities and challenges for modern data analysis and scientific inference. Econometrics and statistics offer a valuable angle from which to study optimization problems and, conversely, operations research offers a productive perspective from which to consider many problems in econometrics and statistics, whence the importance of fostering interactions between academic communities.

This conference brought together scholars from economics, applied mathematics, operations research, computer science and statistics to share their experience and expertise on these important issues.

This conference was held in-person at the University of Chicago.

As part of the Optimization-Conscious Econometrics Conference, the Griffin Applied Economics Incubator will also host the Optimization-Conscious Econometrics Summer School. Learn more.


View 2019 Conference


Friday, June 9, 2023
8:00 am - 8:25 am
Registration and Breakfast
Kapani Family Lounge
8:25 am - 8:30 am
Opening Remarks
Room 601
8:30 am - 9:15 am
Distributionally Robust Gaussian Nonparametric Estimation

Jose Blanchet, Stanford University (Presenter)

Jiajin Li, Stanford University (Co-author)

Sirui Lin, Stanford University (Co-author)

Youssef Marzouk, Massachusetts Institute of Technology (Co-author)

Viet Anh Nguyen, University of Hong Kong (Co-author)

Sven Wang, Massachusetts Institute of Technology (Co-author)

Xuhui Zhang, Stanford University (Co-author)

9:15 am - 10:00 am
Quantifying Distributional Model Risk in Relaxed Marginal Problems via Optimal Transport

Yanqin Fan, University of Washington (Presenter)

Hyeonseok Park, University of Washington (Co-author)

Gaoqian Xu, University of Washington (Co-author)

10:00 am - 10:45 am
Dynamic Inverse Optimal Transport, with an Application to Employer-Employee Matching

Alfred Galichon, New York University (Presenter)

Pauline Corblet, New York University Abu Dhabi (Co-author)

Jeremy Fox, Rice University (Co-author)

10:45 am - 11:00 am
11:00 am - 11:45 am
Conformal Scorecasting: Anticipatory Uncertainty Quantification for Distribution Shift in Time Series

Ryan Tibshirani, University of California, Berkeley (Presenter)

Anastasios Angelopopulos, University of California, Berkeley (Co-author)

Emmanuel Candes, Stanford University (Co-author)

11:45 am - 12:30 pm
Semi-Discrete Optimal Transportation with Unknown Costs

Yinchu Zhu, Brandeis University (Presenter)

Ilya Ryzhov, University of Maryland (Co-author)

12:30 pm - 1:40 pm
1st Floor Dining Room
1:40 pm - 2:00 pm
Optimal Transport as a Reduced Form Regression Tool

Samuel Higbee, University of Chicago (Presenter)

Omkar Katta, University of Chicago (Co-author)

Guillaume Pouliot, University of Chicago (Co-author)

2:00 pm - 2:45 pm
Memorization and Interpolation in Optimization and Machine Learning

John Duchi, Stanford University (Presenter)

Hilal Asi, Stanford University

Chen Cheng, Stanford University

Rohith Kuditipudi, Stanford University

2:45 pm - 3:30 pm
Challenges with Covariate Shift: What is it and what to do about it?

Martin Wainwright, University of California, Berkeley (Presenter)

Cong Ma, University of Chicago (Co-author)

Reese Pathak, University of California, Berkeley (Co-author)

3:30 pm - 4:00 pm
4:00 pm - 4:45 pm
A Coupling-Based Estimator of the Asymptotic Variance in the Central Limit Theorem for Markov Chain Ergodic Averages

Pierre Jacob, École Supérieure des Sciences Economiques et Commerciales

4:45 pm - 5:30 pm
Semiparametric Bayesian Estimation of Dynamic Discrete Choice Models

Andriy Norets, Brown University (Presenter)

Kenichi Shimizu, University of Glasgow (Co-author)

5:30 pm
Conference Adjourns
Saturday, June 10, 2023
8:00 am - 8:30 am

Kapani Family Lounge

8:30 am - 9:15 am
Stochastic Approximation to Generalized Method of Moments
Xiaohong ChenYale University
9:15 am - 10:00 am
Constrained Optimization of Objective Functions Determined from Random Forests

Rim Hariss, McGill University

10:00 am - 10:45 am
A Dual Approach to Robust Counterfactuals

Jiaying Gu, University of Toronto (Presenter)

Thomas Russell, Carleton University (Co-author)

10:45 am - 11:00 am
11:00 am - 11:45 am
The Chritoffel Function: Connections and Applications in Data Analysis and Mining.

Jean-Bernard Lasserre, Laboratory for Analysis and Architecture of Systems

11:45 am - 12:30 pm
Numerical Algebraic Geometry for the Method of Moments and Beyond
Jose Israel Rodriguez, University of Wisconsin, Madison
12:30 pm - 1:20 pm
1st Floor Dining Room
1:20 pm - 1:40 pm
Demand Estimation with Finitely Many Consumers

Thomas Wiemann, University of Chicago (Presenter)

Jonas Lieber, University of Chicago (Co-author)

1:40 pm - 2:25 pm
Neighborhood Adaptive Estimators for Causal Inference Under Network Interference

Alexandre Belloni, Duke University (Presenter)

Fei Fang, Yale University

Alexander Volfovsky, Duke University

2:25 pm - 3:00 pm
Old and New Results About Statistical Inference of Empirical Estimates in Stochastic Optimization

Alexander Shapiro, Georgia Institute of Technology

3:00 pm
Closing Remarks