99 citations · 108 across the 9 of their papers we have counts for
10 papers
Local Asymptotics for Treatment Choice with Partial Identification
José Luis Montiel Olea, Chen Qiu, Jörg Stoye
We provide a new asymptotic framework to derive approximately optimal treatment assignments when sampling noise from data is compounded by fundamental uncertainty due to partial id…
Statistical Decisions and Partial Identification: With Application to Boundary Discontinuity Design
Chen Qiu, Jörg Stoye
We are delighted to respond to the excellent surveys by Cattaneo et al. (2026) and Hirano (2026). Our discussion will attempt two things: first, we show how statistical decision th…
Approximate Least-Favorable Distributions and Nearly Optimal Tests via Stochastic Mirror Descent
Andrés Aradillas Fernández, José Blanchet, José Luis Montiel Olea +3
We consider a class of hypothesis testing problems where the null hypothesis postulates distributions for the observed data, and there is only one possible distribution under t…
Epsilon-Minimax Solutions of Statistical Decision Problems
Andrés Aradillas Fernández, José Blanchet, José Luis Montiel Olea +3
A decision rule is epsilon-minimax if it is minimax up to an additive factor epsilon. We present an algorithm for provably obtaining epsilon-minimax solutions for a class of statis…
Robust Bayes Treatment Choice with Partial Identification
Andrés Aradillas Fernández, José Luis Montiel Olea, Chen Qiu +2
We study a class of binary treatment choice problems with partial identification through the lens of robust (multiple prior) Bayesian analysis. We use a convenient set of prior dis…
Externally Valid Selection of Experimental Sites via the k-Median Problem
José Luis Montiel Olea, Brenda Prallon, Chen Qiu +2
We present a decision-theoretic justification for viewing the question of how to best choose where to experiment in order to optimize external validity as a -median problem, a p…
Decision Theory for Treatment Choice Problems with Partial Identification
José Luis Montiel Olea, Chen Qiu, Jörg Stoye
We apply classical statistical decision theory to a large class of treatment choice problems with partial identification. We show that, in a general class of problems with Gaussian…
Bounding Infection Prevalence by Bounding Selectivity and Accuracy of Tests: With Application to Early COVID-19
Jörg Stoye
I propose novel partial identification bounds on infection prevalence from information on test rate and test yield. The approach utilizes user-specified bounds on (i) test accuracy…
Revealed Stochastic Preference: A One-Paragraph Proof and Generalization
Jörg Stoye
McFadden and Richter (1991) and later McFadden (2005) show that the Axiom of Revealed Stochastic Preference characterizes rationalizability of choice probabilities through random u…
Nonparametric Analysis of Random Utility Models
Yuichi Kitamura, Jörg Stoye
This paper develops and implements a nonparametric test of Random Utility Models. The motivating application is to test the null hypothesis that a sample of cross-sectional demand…