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Negative variance estimates in panel data models

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Author Info

  • Laura Magazzini

    ()
    (Department of Economics (University of Verona))

  • Giorgio Calzolari

    ()
    (University of Florence)

Abstract

Negative values for estimated variances can arise in a panel data context. Empirical and theoretical literature dismisses the problem as not serious and a practical solution is to replace negative variances by its boundary value, i.e. zero. While this is not a concern when the individual variance components is "small" with respect to idiosyncratic variance component (making it indistinguishable from zero in practice), we claim that a negative estimated variance can also arise with a "large" individual variance component, when the orthogonality condition between the individual effects and regressors fails. Estimation problems are considered in the (feasible) generalized least squares and maximum likelihood frameworks.

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Bibliographic Info

Paper provided by University of Verona, Department of Economics in its series Working Papers with number 15/2010.

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Date of creation: Oct 2010
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Handle: RePEc:ver:wpaper:15/2010

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Keywords: Panel data; random effect estimation; negative variances; maximum likelihood;

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  1. Fuller, Wayne A. & Battese, George E., 1974. "Estimation of linear models with crossed-error structure," Journal of Econometrics, Elsevier, vol. 2(1), pages 67-78, May.
  2. Amemiya, Takeshi, 1971. "The Estimation of the Variances in a Variance-Components Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 12(1), pages 1-13, February.
  3. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
  4. Hsiao,Cheng, 2003. "Analysis of Panel Data," Cambridge Books, Cambridge University Press, number 9780521522717, October.
  5. Berzeg, Korhan, 1979. "The error components model : Conditions for the existence of the maximum likelihood estimates," Journal of Econometrics, Elsevier, vol. 10(1), pages 99-102, April.
  6. Wallace, T D & Hussain, Ashiq, 1969. "The Use of Error Components Models in Combining Cross Section with Time Series Data," Econometrica, Econometric Society, vol. 37(1), pages 55-72, January.
  7. Sven Schreiber, 2008. "The Hausman Test Statistic can be Negative even Asymptotically," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 228(4), pages 394-405, August.
  8. Swamy, P A V B & Arora, S S, 1972. "The Exact Finite Sample Properties of the Estimators of Coefficients in the Error Components Regression Models," Econometrica, Econometric Society, vol. 40(2), pages 261-75, March.
  9. Maddala, G S, 1971. "The Use of Variance Components Models in Pooling Cross Section and Time Series Data," Econometrica, Econometric Society, vol. 39(2), pages 341-58, March.
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