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Model Specification Testing in Nonparametric and Semiparametric Time Series Econometric Models

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  • Jiti Gao
  • Maxwell King

Abstract

We propose a simultaneous model specification procedure for the conditional mean and conditional variance in nonparametric and semiparametric time series econometric models. An adaptive and optimal model specification test procedure is then constructed and its asymptotic properties are investigated. The main results extend and generalize existing results for testing the mean of a fixed design nonparametric regression model to the testing of both the conditional mean and conditional variance nonparametric and semiparametric time series econometric models. In addition, we develop computer-intensive bootstrap simulation procedures for the selection of an interval of bandwidth parameters as well as the choice of asymptotic critical values. An example of implementation is given to show how to implement the proposed simultaneous model specification procedure in practice. Moreover, finite sample studies are presented to support the proposed test procedure

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Bibliographic Info

Paper provided by Econometric Society in its series Econometric Society 2004 North American Winter Meetings with number 225.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nawm04:225

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Related research

Keywords: model specification; nonpatametric and semiparametric time series econometrics;

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Cited by:
  1. Juan Carlos Escanciano, 2006. "Joint Diagnostic Tests for Conditional Mean and Variance Specifications," Faculty Working Papers 02/06, School of Economics and Business Administration, University of Navarra.
  2. Gao, Jiti & Lu, Zudi & Tjostheim, Dag, 2003. "Semiparametric spatial regression: theory and practice," MPRA Paper 11991, University Library of Munich, Germany, revised Oct 2006.
  3. Amaro de Matos, Joao & Fernandes, Marcelo, 2007. "Testing the Markov property with high frequency data," Journal of Econometrics, Elsevier, vol. 141(1), pages 44-64, November.

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