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Model selection tests for moment inequality models
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DOI：10.1016/j.jeconom.2015.01.004.png)
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Abstract
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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 consistent against fixed alternatives and local alternatives converging to the null at rates arbitrarily close to n(-1/2). We demonstrate the finite-sample performance of the tests with Monte Carlo simulation of a missing data example. The tests are relatively easy to implement. (C) 2015 Elsevier B.V. All rights reserved.
Keywords:
Asymptotic size
Kullback-Leibler divergence
Model selection test
Moment inequalities
Overlapping models
Partial identification
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