SPECIFICATION TESTING FORREGRESSION MODELS WITHDEPENDENT DATA

Javier Hidalgo

STICERD - Econometrics Paper Series from Suntory and Toyota International Centres for Economics and Related Disciplines, LSE

Abstract: We describe and examine a consistent test for the correct specification of aregression function with dependent data. The test is based on the supremum of thedifference between the parametric and nonparametric estimates of the regressionmodel. Rather surprisingly, the behaviour of the test depends on whether theregressors are deterministic or stochastic. In the former situation, the normalizationconstants necessary to obtain the limiting Gumbel distribution are data dependentand difficult to estimate, so to obtain valid critical values may be difficult, whereasin the latter, the asymptotic distribution may not be even known. Because of that,under very mild regularity conditions we describe a bootstrap analogue for the test,showing its asymptotic validity and finite sample behaviour in a small Monte Carloexperiment.

Keywords: Functional; specification.; Variable; selection.; Nonparametric; kernelregression.; Frequency; domain; bootstrap. (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
Date: 2007-05
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Persistent link: https://EconPapers.repec.org/RePEc:cep:stiecm:518

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