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Normality Tests for Dependent Data

Author

Listed:
  • Zacharias Psaradakis

    (University of London)

  • Marian Vavra

    (National Bank of Slovakia)

Abstract

The paper considers the problem of testing for normality of the one-dimensional marginal distribution of a strictly stationary and weakly dependent stochastic process. The possibility of using an autoregressive sieve bootstrap procedure to obtain critical values and P-values for normality tests is explored. The small-sample properties of a variety of tests are investigated in an extensive set of Monte Carlo experiments. The bootstrap version of the classical skewness–kurtosis test is shown to have the best overall performance in small samples.

Suggested Citation

  • Zacharias Psaradakis & Marian Vavra, 2017. "Normality Tests for Dependent Data," Working and Discussion Papers WP 12/2017, Research Department, National Bank of Slovakia.
    • Handle: RePEc:svk:wpaper:1053
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    References listed on IDEAS

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    1. Bontemps, Christian & Meddahi, Nour, 2005. "Testing normality: a GMM approach," Journal of Econometrics, Elsevier, vol. 124(1), pages 149-186, January.
    2. Kilian, Lutz & Demiroglu, Ufuk, 2000. "Residual-Based Tests for Normality in Autoregressions: Asymptotic Theory and Simulation Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(1), pages 40-50, January.
    3. Zacharias Psaradakis, 2016. "Using the Bootstrap to Test for Symmetry Under Unknown Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 406-415, July.
    4. Psaradakis, Zacharias & Vávra, Marián, 2017. "A distance test of normality for a wide class of stationary processes," Econometrics and Statistics, Elsevier, vol. 2(C), pages 50-60.
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    Cited by:

    1. Marián Vávra, 2020. "Assessing distributional properties of forecast errors for fan-chart modelling," Empirical Economics, Springer, vol. 59(6), pages 2841-2858, December.
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    3. Elena Jianu & Ramona Pîrvu & Gheorghe Axinte & Ovidiu Toma & Andrei Valentin Cojocaru & Flavia Murtaza, 2021. "EU Labor Market Inequalities and Sustainable Development Goals," Sustainability, MDPI, vol. 13(5), pages 1-17, March.

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    More about this item

    Keywords

    Autoregressive sieve bootstrap; Normality test; Weak dependence;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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