Inference in Incomplete Models
AbstractWe provide a test for the specification of a structural model without identifying assumptions. We show the equivalence of several natural formulations of correct specification, which we take as our null hypothesis. From a natural empirical version of the latter, we derive a Kolmogorov-Smirnov statistic for Choquet capacity functionals, which we use to construct our test. We derive the limiting distribution of our test statistic under the null, and show that our test is consistent against certain classes of alternatives. When the model is given in parametric form, the test can be inverted to yield confidence regions for the identified parameter set. The approach can be applied to the estimation of models with sample selection, censored observables and to games with multiple equilibria.
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Bibliographic InfoPaper provided by Columbia University, Department of Economics in its series Discussion Papers with number 0506-28.
Length: 51 pages
Date of creation: 2006
Date of revision:
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