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Testing for spurious regression in a panel data model with the individual number and time length growing

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  • Wen-Den Chen

Abstract

This article shows a test for the spurious regression problem in a panel data model with a growing individual number and time series length. In the estimation, tapers are used and the integrated order for the remainder disturbance is extended to a real number; at the same time, the spurious regression problem can be detected without prior knowledge. Through Monte Carlo experiments, we examine the consistent estimators by various sizes of time length and individual number, in which the remainder disturbance is assumed to be either stationary or non-stationary. In addition, the asymptotic normality properties are discussed with a quasi log-likelihood function. From the power tests we can see that the estimators are quite successful and powerful.

Suggested Citation

  • Wen-Den Chen, 2006. "Testing for spurious regression in a panel data model with the individual number and time length growing," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(8), pages 759-772.
    • Handle: RePEc:taf:japsta:v:33:y:2006:i:8:p:759-772
    DOI: 10.1080/02664760600741989
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    References listed on IDEAS

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    8. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    9. Harris, Richard D. F. & Tzavalis, Elias, 1999. "Inference for unit roots in dynamic panels where the time dimension is fixed," Journal of Econometrics, Elsevier, vol. 91(2), pages 201-226, August.
    10. G. S. Maddala & Shaowen Wu, 1999. "A Comparative Study of Unit Root Tests with Panel Data and a New Simple Test," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(S1), pages 631-652, November.
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    Cited by:

    1. Louis Anthony (Tony) Cox, Jr., 2009. "Why Reduced‐Form Regression Models of Health Effects Versus Exposures Should Not Replace QRA: Livestock Production and Infant Mortality as an Example," Risk Analysis, John Wiley & Sons, vol. 29(12), pages 1664-1671, December.

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