An Adaptive, Rate-Optimal Test of a Parametric Model Against a Nonparametric Alternative

Joel L. Horowitz () and Vladimir G. Spokoiny
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Joel L. Horowitz: University of Iowa
Vladimir G. Spokoiny: Weierstrass Institute for Applied Stochastics

Working Papers from University of Iowa, Department of Economics

Abstract: We develop a new test of a parametric model of a conditional mean function against a nonparametric alternative. The test adapts to the unknown smoothness of the alternative model and is uniformly consistent against alternatives whose distance from the parametric model converges to zero at the fastest possible rate. This rate is slower than n-1/2. Some existing tests have non-trivial power against restricted classes of alternatives whose distance from the parametric model decreases at the rate n-1/2. There are, however, sequences of alternatives against which these tests are inconsistent and ours is consistent. As a consequence, there are alternative models for which the finite-sample power of our test greatly exceeds that of existing tests. This conclusion is illustrated by the results of some Monte Carlo experiments.

Keywords: Hypothesis testing; local alternative; uniform consistency; asymptotic power (search for similar items in EconPapers)
JEL-codes: C12 C14 C21 (search for similar items in EconPapers)
Pages: 38 pages
Date: 1999-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:uia:iowaec:99-02

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