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Testing the null hypothesis of zero serial correlation in short panel time series: a comparison of tail probabilities

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  • Shelton Peiris

Abstract

It is known that the analysis of short panel time series data is very important in many practical problems. This paper calculates the exact moments up to order 4 under the null hypothesis of no serial correlation when there are many independent replications of size 3. We further calculate the tail probabilities under the null hypothesis using the Edgeworth approximation for $$n=3, 4$$ and $$5,$$ when the structure of the pdf (probability density function) of the test statistic is in essence different. Finally, we compare the three types of tail probabilities, namely, the Edgeworth approximation, the normal approximation and the exact probabilities through a large scale simulation study. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Shelton Peiris, 2014. "Testing the null hypothesis of zero serial correlation in short panel time series: a comparison of tail probabilities," Statistical Papers, Springer, vol. 55(2), pages 513-523, May.
    • Handle: RePEc:spr:stpapr:v:55:y:2014:i:2:p:513-523
    DOI: 10.1007/s00362-012-0495-5
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    1. Claudia Czado & Peter Song, 2008. "State space mixed models for longitudinal observations with binary and binomial responses," Statistical Papers, Springer, vol. 49(4), pages 691-714, October.
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    3. Perera, D.I. & Peiris, M.S. & Robinson, J. & Weber, N.C., 2008. "The empirical saddlepoint method applied to testing for serial correlation in panel time series data," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2876-2882, December.
    4. Benjamin Born & Jörg Breitung, 2016. "Testing for Serial Correlation in Fixed-Effects Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1290-1316, August.
    5. Manfred Mudelsee, 2001. "Note on the bias in the estimation of the serial correlation coefficient of AR(1) processes," Statistical Papers, Springer, vol. 42(4), pages 517-527, October.
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