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Consistent Nonparametric Entropy-Based Testing

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  • P. M. Robinson

Abstract

The Kullback-Leibler information criterion is used as a basis for one-sided testing of nested hypotheses. No distributional form is assumed, so nonparametric density estimation is used to form the test statistic. In order to obtain a normal null limiting distribution, a form of weighting is employed. The test is also shown to be consistent against a class of alternatives. The exposition focusses on testing for serial independence in time series, with a small application to testing the random walk hypothesis for exchange rate series, and tests of some other hypotheses of econometric interest are briefly described.

Suggested Citation

  • P. M. Robinson, 1991. "Consistent Nonparametric Entropy-Based Testing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(3), pages 437-453.
    • Handle: RePEc:oup:restud:v:58:y:1991:i:3:p:437-453.
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