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Tests for normality based on the quantile-mean covariance

Author

Listed:
  • Javier Alejo

    (Universidad de La Plata)

  • Anil Bera

    (University of Illinois at Urbana–Champaign)

  • Antonio Galvao

    (University of Iowa)

  • Gabriel Montes-Rojas

    (Universitat Autònoma de Barcelona)

  • Zhijie Xiao

    (Boston College)

Abstract

We present a new command, qctest, to implement tests for normality of a random variable based on the quantile-mean covariance. The test procedures are based on recent results by Bera et al. (2016, Econometric Theory 32: 1216– 1252) and are an efficient alternative to existing normality tests in the literature. Copyright 2016 by StataCorp LP.

Suggested Citation

  • Javier Alejo & Anil Bera & Antonio Galvao & Gabriel Montes-Rojas & Zhijie Xiao, 2016. "Tests for normality based on the quantile-mean covariance," Stata Journal, StataCorp LP, vol. 16(4), pages 1039-1057, December.
    • Handle: RePEc:tsj:stataj:v:16:y:2016:i:4:p:1039-1057
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    Citations

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    Cited by:

    1. Gabriel Montes Rojas & Andrés Sebastián Mena, 2020. "Density estimation using bootstrap quantile variance and quantile-mean covariance," Documentos de trabajo del Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET) 2020-50, Universidad de Buenos Aires, Facultad de Ciencias Económicas, Instituto Interdisciplinario de Economía Política IIEP (UBA-CONICET).
    2. Tauchmann, Harald, 2019. "Fixed-effects estimation of the linear discrete-time hazard model: An adjusted first-differences estimator," FAU Discussion Papers in Economics 09/2019, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.

    More about this item

    Keywords

    qctest; skewness; kurtosis; normality;
    All these keywords.

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