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Asymptotics for random effects models with serial correlation

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  • Jimmy Skoglund

    ()
    (Department of Economic Statistics, Stockholm School of Economics)

  • Sune Karlsson

    ()
    (Department of Economic Statistics, Stockholm School of Economics)

Abstract

This paper considers the large sample behavior of the maximum likelihood estimator of random effects models. Consistent estimation and asymptotic normality as N and/or T grows large is established for a comprehensive specification which allows for serial correlation in the form of AR(1) for the idiosyncratic or time-specific error component. The consistency and asymptotic normality properties of all commonly used random effects models are obtained as special cases of the comprehensive model. When N or T \rightarrow \infty only a subset of the parameters are consistent and asymptotic normality is established for the consistent subsets.

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Bibliographic Info

Paper provided by International Conferences on Panel Data in its series 10th International Conference on Panel Data, Berlin, July 5-6, 2002 with number A6-1.

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Date of creation: Mar 2002
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Handle: RePEc:cpd:pd2002:a6-1

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Keywords: Panel data; error components; consistency; asymptotic normality; maximum likelihood.;

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  1. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521471626, October.
  2. Lee A. Lillard & Robert J. Willis, 1976. "Dynamic Aspects of Earnings Mobility," NBER Working Papers 0150, National Bureau of Economic Research, Inc.
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  4. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521477451, October.
  5. Magnus, J.R. & Woodland, A.D., 1988. "On the maximum likelihood estimation of multivariate regression models containing serially correlated error components," Open Access publications from Tilburg University urn:nbn:nl:ui:12-153224, Tilburg University.
  6. Karlsson, Sune & Skoglund, Jimmy, 2000. "Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects," Working Paper Series in Economics and Finance 383, Stockholm School of Economics.
  7. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521477444, October.
  8. 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.
  9. Baltagi, Badi H. & Li, Qi, 1991. "A transformation that will circumvent the problem of autocorrelation in an error-component model," Journal of Econometrics, Elsevier, vol. 48(3), pages 385-393, June.
  10. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521405515, October.
  11. Baltagi, Badi H. & Li, Qi, 1994. "Estimating Error Component Models With General MA(q) Disturbances," Econometric Theory, Cambridge University Press, vol. 10(02), pages 396-408, June.
  12. Peter C.B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Cowles Foundation Discussion Papers 1222, Cowles Foundation for Research in Economics, Yale University.
  13. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January.
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