BFI Working Papers

Sharing research in progress—and refining it through rigorous discussion and debate—is a hallmark of scholarship at the Becker Friedman Institute for Economics.
Filter by
BFI Working Paper Oct 16, 2020

How Well Generative Adversarial Networks Learn Distributions

Tengyuan Liang
Topics:  Technology & Innovation
BFI Working Paper Oct 16, 2020

Estimating Certain Integral Probability Metrics (IPMs) Is as Hard as Estimating under the IPMs

Tengyuan Liang
Topics:  Technology & Innovation
BFI Working Paper Oct 16, 2020

A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-L1-Norm Interpolated Classifiers

Tengyuan Liang, Pragya Sur
Topics:  Technology & Innovation
BFI Working Paper Oct 16, 2020

Mehler’s Formula, Branching Process, and Compositional Kernels of Deep Neural Networks

Tengyuan Liang, Hai Tran-Bach
Topics:  Technology & Innovation
BFI Working Paper Oct 5, 2020

An Adversarial Approach to Structural Estimation

Tetsuya Kaji, Elena Manresa, Guillaume Pouliot
Topics:  Economic Mobility & Poverty
BFI Working Paper Jul 16, 2020

Inference with Imperfect Randomization: The Case of the Perry Preschool Program

James Heckman, Rodrigo Pinto, Azeem Shaikh
Topics:  Early Childhood Education
BFI Working Paper Apr 23, 2019

Inference in Experiments with Matched Pairs

Yuehao Bai, Joseph P. Romano, Azeem Shaikh
Topics:  Technology & Innovation
BFI Working Paper Sep 1, 2017

A Distributional Framework for Matched Employer Employee Data

Stéphane Bonhomme, Thibaut Lamadon, Elena Manresa
Topics:  Employment & Wages