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Monte Carlo Results on Pure and Pretest Estimators of an Error Component Model with Autocorrelated Disturbances

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  • Badi H. Baltagi
  • Qi Li

Abstract

A Monte Carlo study is used to compare the finite sample relative efficiency of a number of pure and pre-test estimators for an error component model with first-order autocorrelated remainder disturbances.

Suggested Citation

  • Badi H. Baltagi & Qi Li, 1997. "Monte Carlo Results on Pure and Pretest Estimators of an Error Component Model with Autocorrelated Disturbances," Annals of Economics and Statistics, GENES, issue 48, pages 69-82.
    • Handle: RePEc:adr:anecst:y:1997:i:48:p:69-82
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    File URL: http://www.jstor.org/stable/20076097
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    Cited by:

    1. Phillips, Robert F., 2004. "Estimation of a generalized random-effects model: some ECME algorithms and Monte Carlo evidence," Journal of Economic Dynamics and Control, Elsevier, vol. 28(9), pages 1801-1824, July.
    2. Hardy Hulley & Rebecca Mckibbin & Andreas Pedersen & Susan Thorp, 2013. "Means-Tested Public Pensions, Portfolio Choice and Decumulation in Retirement," The Economic Record, The Economic Society of Australia, vol. 89(284), pages 31-51, March.
    3. Wen‐Den Chen, 2006. "An approximate likelihood function for panel data with a mixed ARMA(p, q) remainder disturbance model," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(6), pages 911-921, November.
    4. Badi H. Baltagi & Chihwa Kao & Long Liu, 2007. "Asymptotic Properties of Estimators for the Linear Panel Regression Model with Individual Effects and Serially Correlated Errors: The Case of Stationary and Non-Stationary Regressors and Residuals," Center for Policy Research Working Papers 93, Center for Policy Research, Maxwell School, Syracuse University.

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