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Specification test for Markov models with measurement errors

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  • Kim, Seonjin
  • Zhao, Zhibiao

Abstract

Most existing works on specification testing assume that we have direct observations from the model of interest. We study specification testing for Markov models based on contaminated observations. The evolving model dynamics of the unobservable Markov chain is implicitly coded into the conditional distribution of the observed process. To test whether the underlying Markov chain follows a parametric model, we propose measuring the deviation between nonparametric and parametric estimates of conditional regression functions of the observed process. Specifically, we construct a nonparametric simultaneous confidence band for conditional regression functions and check whether the parametric estimate is contained within the band.

Suggested Citation

  • Kim, Seonjin & Zhao, Zhibiao, 2014. "Specification test for Markov models with measurement errors," Journal of Multivariate Analysis, Elsevier, vol. 130(C), pages 118-133.
    • Handle: RePEc:eee:jmvana:v:130:y:2014:i:c:p:118-133
    DOI: 10.1016/j.jmva.2014.05.008
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    References listed on IDEAS

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    1. Zhibiao Zhao, 2008. "Parametric and nonparametric models and methods in financial econometrics," Papers 0801.1599, arXiv.org, revised Mar 2008.
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