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Consistent model specification tests based on k-nearest-neighbor estimation method
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DOI：10.1016/j.jeconom.2016.03.004.png)
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Abstract
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We propose a simple consistent test for a, parametric regression functional form based on k-nearest-neighbor (k-nn) method. We derive the null distribution of the test statistic and show that the test achieves the minimax rate optimality against smooth alternatives. A wild bootstrap method is used to better approximate the null distribution of the test statistic. We also propose a k-nn statistic which tests for omitted variables nonparametrically. Simulations and an empirical application using US economics new Ph.D. job market matching data show that the k-nn method is more appropriate than the kernel method to analyze unevenly distributed data. (C) 2016 Elsevier B.V. All rights reserved.
Keywords:
k-nearest-neighbor method
Consistent test
Bootstrap
Empirical application
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