Bayesian analysis in moment inequality models

Bayesian Analysis in Moment Inequality Models

This paper presents a study of the large-sample behavior of the posterior distribution of a structural parameter which is partially identified by moment inequalities. The posterior density is derived based on the limited information likelihood. The posterior distribution converges to zero exponentially fast on any δ-contraction outside the identified region. Inside, it is bounded below by a pos...

Model selection tests for moment inequality models

We propose Vuong-type tests to select between two moment inequality models based on their Kullback–Leibler distances to the true data distribution. The candidate models can be either non-overlapping or overlapping. For each case, we develop a testing procedure that has correct asymptotic size in a uniform sense despite the potential lack of point identification. We show both procedures are cons...

Supplement to “Asymptotically Exact Inference in Conditional Moment Inequality Models”

This supplementary appendix contains auxiliary results and proofs for the main paper. Section A contains a proof of Theorem 3.1 in the case where l = dY = 1, which contains the main technical ideas of the general result, but requires less notation. Section B proposes an alternative way of obtaining critical values using the asymptotic distribution results in this paper. Section C contains proof...

Supplemental to Asymptotically Exact Inference in Conditional Moment Inequality Models

Inference in Moment Inequality Models with Combined Data Sources

In this paper, we study the estimation and inference problems for parameters when the data set is obtained by combining data from different sources. In the case where we want to estimate the means of random variables in our data set, we consider the set of estimators that are linear combinations of certain sample averages, and find that one estimator, defined to be the Adjusted estimator, that ...