Combinatorial Bootstrap Inference in Partially Identified Incomplete Structural Models
35 Pages Posted: 11 Feb 2011 Last revised: 7 Dec 2011
Date Written: December 7, 2011
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 such models are equivalent to a collection of moment inequalities that increases exponentially with the number of discrete outcomes. We propose an equivalent characterization based on classical combinatorial optimization methods that alleviates this computational burden and allows the construction of confidence regions with an efficient combinatorial bootstrap procedure that runs in linear computing time. The method can also be applied to the empirical analysis of cooperative and noncooperative games, instrumental variable models of discrete choice and revealed preference analysis. We propose an application to the determinants of long term elderly care choices.
Keywords: Partial identification, confidence regions, combinatorial optimization
JEL Classification: C13, C72
Suggested Citation: Suggested Citation