We experimentally study unanimity and majority voting rules in multilateral bargaining environments with stochastic future surplus. In these settings, reaching agreement when expected future surplus is sufficiently higher than the current surplus is inefficient. Theoretically, such...

This paper develops and estimates a spatial general equilibrium job search model to study the effects of local and universal (federal) minimum wage policies on employment, wages, job postings, vacancies, migration/commuting, and welfare. In the model, workers, who differ in terms of location and...

This paper characterizes the allocations that emerge in general equilibrium economies populated by households with preferences of the additive random utility type that make discrete consumption, employment or spatial decisions. We start with a complete markets economy where households can trade...

Economics has long studied how consumers respond to the disclosure of information about firms. We study a case in which the disclosed information is unrelated to the product or firm leadership, but which could still potentially affect consumer patronage through the mechanism of repugnance, as...

While hypothesis testing is a highly formalized activity, hypothesis generation remains largely informal. We propose a systematic procedure to generate novel hypotheses about human behavior, which uses the capacity of machine learning algorithms to notice patterns people might not. We illustrate...

This article describes methods used in the field of spatial economics that combine insights from economic theory and evidence from data in order to answer counter- factual questions. I outline a general framework that emphasizes three elements: a specific question to be answered, a set of...

In this paper, we provide a suite of tools for empirical market design, including optimal nonlinear pricing in intensive-margin consumer demand, as well as a broad class of related adverse-selection models. Despite significant data limitations, we are able to derive informative bounds on demand...

Whether police misconduct can be prevented depends partly on whether it can be predicted. We show police misconduct is partially predictable and that estimated misconduct risk is not simply an artifact of measurement error or a proxy for officer activity. We also show many officers at risk of...

What do machines learn, and why? To answer these questions we import models of human cognition into machine learning. We propose two ways of modeling machine learners based on this join: feasibility-based and cost-based machine learning. We evaluate and estimate our models using a deep learning...

Income is simultaneously one of the most important variables used by economists and the variable most likely to be missing due to item non-response. While observations that are missing income responses are often dropped from analyses, such treatment is usually inappropriate. More appropriate...