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Testing for Persistence in the Error Component Model:A One-Sided Approach

Author

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  • Walter Sosa Escudero

    () (Department of Economics, Universidad de San Andres)

Abstract

This paper proposes new simple testing procedures for the joint null hypothesis of absence of persistent e®ects in the form of random e®ects and ¯rst order serial correlation in the error component model. The fact that the presence of random effects is clearly of a one-sided nature, together with the fact that in many empirical applications researchers worry about positive serial correlation leaves room for a power gain that arises from restricting the parameter space under the alternative hypothesis, compared to existing procedures that allow for two-sided alternatives. A Monte Carlo experiment shows that the proposed statistics have good size and power performance in very small samples like those typically used in applied work in panel data. An empirical example illustrates the usefulness of the proposed statistics.

Suggested Citation

  • Walter Sosa Escudero, 2007. "Testing for Persistence in the Error Component Model:A One-Sided Approach," Working Papers 94, Universidad de San Andres, Departamento de Economia, revised Feb 2007.
  • Handle: RePEc:sad:wpaper:94
    as

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    File URL: ftp://webacademicos.udesa.edu.ar/pub/econ/doc94.pdf
    File Function: First version, 2007
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    References listed on IDEAS

    as
    1. Maxwell King & Ping Wu, 1997. "Locally optimal one-sided tests for multiparameter hypotheses," Econometric Reviews, Taylor & Francis Journals, vol. 16(2), pages 131-156.
    2. Bera, Anil K. & Sosa-Escudero, Walter & Yoon, Mann, 2001. "Tests for the error component model in the presence of local misspecification," Journal of Econometrics, Elsevier, vol. 101(1), pages 1-23, March.
    3. Inoue, Atsushi & Solon, Gary, 2006. "A Portmanteau Test For Serially Correlated Errors In Fixed Effects Models," Econometric Theory, Cambridge University Press, vol. 22(05), pages 835-851, October.
    4. Hendry, David F & Mizon, Grayham E, 1978. "Serial Correlation as a Convenient Simplification, not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England," Economic Journal, Royal Economic Society, vol. 88(351), pages 549-563, September.
    5. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521471626, March.
    6. Yuzo Honda, 1985. "Testing the Error Components Model with Non-Normal Disturbances," Review of Economic Studies, Oxford University Press, vol. 52(4), pages 681-690.
    7. Baltagi, Badi H. & Li, Qi, 1991. "A joint test for serial correlation and random individual effects," Statistics & Probability Letters, Elsevier, vol. 11(3), pages 277-280, March.
    8. Olivier Jean Blanchard & Lawrence F. Katz, 1992. "Regional Evolutions," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 23(1), pages 1-76.
    9. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," Review of Economic Studies, Oxford University Press, vol. 47(1), pages 239-253.
    10. Walter Sosa-Escudero & Mariana Marchionni & Omar Arias, 2011. "Sources of Income Persistence: Evidence from Rural El Salvador," Journal of Income Distribution, Journal of Income Distribution, vol. 20(1), pages 3-28, March.
    11. Baltagi, Badi H. & Chang, Young-Jae & Li, Qi, 1992. "Monte Carlo results on several new and existing tests for the error component model," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 95-120.
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    Citations

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    Cited by:

    1. Roberto Cortes Conde, 2008. "Spanish America Colonial Patterns: The Rio de La Plata," Working Papers 96, Universidad de San Andres, Departamento de Economia, revised Mar 2008.

    More about this item

    Keywords

    error component model; testing; random effects; serial correlation; one-sided alternatives;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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