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Testing for Non-Nested Conditional Moment Restrictions Using Unconditional Empirical Likelihood

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Abstract

We propose non-nested hypotheses tests for conditional moment restriction models based on the method of generalized empirical likelihood (GEL). By utilizing the implied GEL probabilities from a sequence of unconditional moment restrictions that contains equivalent information of the conditional moment restrictions, we construct Kolmogorov-Smirnov and Cramer-von Mises type moment encompassing tests. Advantages of our tests over Otsu and Whang's (2007) tests are: (i) they are free from smoothing parameters, (ii) they can be applied to weakly dependent data, and (iii) they allow non-smooth moment functions. We derive the null distributions, validity of a bootstrap procedure, and local and global power properties of our tests. The simulation results show that our tests have reasonable size and power performance in finite samples.

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Bibliographic Info

Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1660.

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Length: 29 pages
Date of creation: May 2008
Date of revision:
Handle: RePEc:cwl:cwldpp:1660

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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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Keywords: Empirical likelihood; Non-nested tests; Conditional moment restrictions;

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Cited by:
  1. Komunjer, Ivana & Ragusa, Giuseppe, 2009. "Existence and Uniqueness of Semiparametric Projections," University of California at San Diego, Economics Working Paper Series qt0wg3j51c, Department of Economics, UC San Diego.

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