A Bootstrap Test for Single Index Models
AbstractSingle 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 specification test that detects nonparametric deviations of the link function, e. g., testing against a semiparametric alternative. Simulations with single index models have shown that the empirical power of this test may be affected in small samples. In this work the bootstrap is used with the aim to find a more accurate distribution under the null than the standard normal. We prove that the statistic and its bootstrapped version have the same asymptotic distribution. A simulation study is performed to investigate the empirical behaviour of this approach. The bootstrapped critical values yield better approximations to the true values.
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Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 1993025.
Date of creation: 01 Jun 1993
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Other versions of this item:
- Wolfgang Haerdle & Enno MAMMEN & Isabel Proenca, 2005. "A Bootstrap Test for Single Index Models," Econometrics 0508007, EconWPA.
- Härdle, Wolfgang & Mammen, Enno & Proença, Isabel, 2000. "A bootstrap test for single index models," SFB 373 Discussion Papers 2000,20, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
- C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
- C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
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- H rdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2004.
"Bootstrap Inference In Semiparametric Generalized Additive Models,"
Cambridge University Press, vol. 20(02), pages 265-300, April.
- Härdle, Wolfgang & Huet, Sylvie & Mammen, Enno & Sperlich, Stefan, 2001. "Bootstrap Inference in Semiparametric Generalized Additive Models," Finance Working Papers 01-3, University of Aarhus, Aarhus School of Business, Department of Business Studies.
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