On the testability of identification in some nonparametric models with endogeneity
Andres Santos and
Azeem Shaikh ()
No CWP18/12, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies
This paper examines three distinct hypothesis testing problems that arise in the context of identification of some nonparametric models with endogeneity. The first hypothesis testing problem we study concerns testing necessary conditions for identification in some nonparametric models with endogeneity involving mean independence restrictions. These conditions are typically referred to as completeness conditions. The second and third hypothesis testing problems we examine concern testing for identification directly in some nonparametric models with endogeneity involving quantile independence restrictions. For each of these hypothesis testing problems, we provide conditions under which any test will have power no greater than size against any alternative. In this sense, we conclude that no nontrivial tests for these hypothesis testing problems exist.
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Journal Article: On the Testability of Identification in Some Nonparametric Models With Endogeneity (2013)
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