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Hausman tests for the error distribution in conditionally heteroskedastic models

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  • Zhu, Ke

Abstract

This paper proposes some novel Hausman tests to examine the error distribution in conditionally heteroskedastic models. Unlike the existing tests, all Hausman tests are easy-to-implement with the limiting null distribution of $\chi^{2}$, and moreover, they are consistent and able to detect the local alternative of order n−1=2. The scope of the Hausman test covers all Generalized error distributions and Student’s t distributions. The performance of each Hausman test is assessed by simulated and real data sets.

Suggested Citation

  • Zhu, Ke, 2015. "Hausman tests for the error distribution in conditionally heteroskedastic models," MPRA Paper 66991, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:66991
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    References listed on IDEAS

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    More about this item

    Keywords

    Conditionally heteroskedastic model; Consistent test; GARCH model; Goodness-of-fit test; Hausman test; Nonlinear time series.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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