A bootstrap test for single index models

Wolfgang Härdle, Enno Mammen and Isabel Proença ()

No 2000,20, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Abstract: Single index models are frequently used in econometrics and biometrics. Logit and Probit models are special cases with fixed link functions. In this paper we consider a bootstrap specification test that detects nonparametric deviations of the link function. The bootstrap is used with the aim to find a more accurate distribution under the null than the normal approximation. We prove that the statistic and its bootstrapped version have the same asymptotic distribution. In a simulation study we show that the bootstrap is able to capture the negative bias and the skewness of the test statistic. It yields better approximations to the true critical values and consequently it has a more accurate level than the normal approximation.

Keywords: bootstrap; kernel estimate; single index model; specification test (search for similar items in EconPapers)
Date: 2000
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Citations: View citations in EconPapers (3)

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Related works:
Working Paper: A Bootstrap Test for Single Index Models (2005)
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