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Specification Tests for the Distribution of Errors in Nonoarametric Regression: A Martingale Approach

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Author Info
Alicia Pérez Alonso () (Universidad de Alicante)
Juan Mora () (Universidad de Alicante)
Abstract

We discuss how to test whether the distribution of regression errors belongs to a parametric family of continuous distribution functions, making no parametric assumption about the conditional mean or the conditional variance in the regression model. We propose using test statistics that are based on a martingale transform of the estimated empirical process. We prove that these statistics are asymptotically distribution-free, and two Monte Carlo experiments show that they work reasonably well in practice.

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File URL: http://www.ivie.es/downloads/docs/wpasad/wpasad-2008-11.pdf
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Publisher Info
Paper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie AD with number 2008-11.

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Length: 36 pages
Date of creation: Jun 2008
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Publication status: Published by Ivie
Handle: RePEc:ivi:wpasad:2008-11

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Keywords: Specification Tests Nonparametric Regression Empirical Processes.

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  1. Jushan Bai, 2003. "Testing Parametric Conditional Distributions of Dynamic Models," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 531-549, 06. [Downloadable!] (restricted)
  2. Michael G. Akritas, 2001. "Non-parametric Estimation of the Residual Distribution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association and Swedish Statistical Association, vol. 28(3), pages 549-567. [Downloadable!] (restricted)
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This page was last updated on 2008-8-10.

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