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Consistent Nonparametric Entropy-Based Testing

P. M. Robinson
The Review of Economic Studies
Vol. 58, No. 3, Special Issue: The Econometrics of Financial Markets (May, 1991), pp. 437-453
Published by: Oxford University Press
Stable URL: http://www.jstor.org/stable/2298005
Page Count: 17
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Consistent Nonparametric Entropy-Based Testing
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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.

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