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.
ORGANIZERS
Agenda
Friday, June 9, 2023
Registration and Breakfast
Opening Remarks
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)
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)
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)
Break
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)
Semi-Discrete Optimal Transportation with Unknown Costs
Yinchu Zhu, Brandeis University (Presenter)
Ilya Ryzhov, University of Maryland (Co-author)
Lunch
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)
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
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)
Break
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
Semiparametric Bayesian Estimation of Dynamic Discrete Choice Models
Andriy Norets, Brown University (Presenter)
Kenichi Shimizu, University of Glasgow (Co-author)
Conference Adjourns
Saturday, June 10, 2023
Breakfast
Kapani Family Lounge
Stochastic Approximation to Generalized Method of Moments
Constrained Optimization of Objective Functions Determined from Random Forests
Rim Hariss, McGill University
A Dual Approach to Robust Counterfactuals
Jiaying Gu, University of Toronto (Presenter)
Thomas Russell, Carleton University (Co-author)
Break
The Chritoffel Function: Connections and Applications in Data Analysis and Mining.
Jean-Bernard Lasserre, Laboratory for Analysis and Architecture of Systems
Numerical Algebraic Geometry for the Method of Moments and Beyond
Lunch
Demand Estimation with Finitely Many Consumers
Thomas Wiemann, University of Chicago (Presenter)
Jonas Lieber, University of Chicago (Co-author)
Neighborhood Adaptive Estimators for Causal Inference Under Network Interference
Alexandre Belloni, Duke University (Presenter)
Fei Fang, Yale University
Alexander Volfovsky, Duke University
Old and New Results About Statistical Inference of Empirical Estimates in Stochastic Optimization
Alexander Shapiro, Georgia Institute of Technology