We propose a computationally feasible inference method in finite games of complete information. Galichon and Henry, 2011 and Beresteanu, Molchanov, and Molinari, 2011 show that the empirical content in such models is characterized by a collection of moment inequalities whose number increases...

We consider a matching model in which individuals belonging to two populations (\textquotedblleft males\textquotedblright\ and \textquotedblleft females\textquotedblright ) can match to share their exogenous income risk. Within each population, individuals can be ranked by risk aversion in the...

In this note, we address nonparametric identification of a collective model of household behavior in the presence of additive unobserved heterogeneity in the sharing rule. We show that the (nonstochastic part of the) sharing rule is nonparametrically identified. Moreover, under independence...

While many theoretical works, particularly in Family Economics, rely on the Transferable Utility (TU) assumption, its exact implications in terms of individual preferences have never been fully worked out. In this paper, we provide a set of necessary and sufficient conditions for a group to...

Under the assumption that individuals know the conditional distributions of signals given the payoff-relevant parameters, existing results conclude that as individuals observe infinitely many signals, their beliefs about the parameters will eventually merge. We first show that these results are...

We consider the problem of inference on a class of sets describing a collection of admissible models as solutions to a single smooth inequality. Classical and recent examples include the Hansen–Jagannathan sets of admissible stochastic discount factors, Markowitz–Fama mean–variance sets...

Triangular systems with nonadditively separable unobserved heterogeneity provide a theoretically appealing framework for the modeling of complex structural relationships. However, they are not commonly used in practice due to the need for exogenous variables with large support for...