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Developing a two way error component estimation model with disturbances following a special autoregressive (4) for quarterly data

Author

Listed:
  • Marcel die Dama

    (ESSEC-University of Douala, Cameroon)

  • Boniface ngah Epo

    (FSEG-University of Yaounde 2, Cameroon)

  • Galex syrie Soh

    (FSEG-University of Yaounde 2, Cameroon)

Abstract

This paper provides an estimation method for a two way error component regression model where the time-varying disturbances are serially correlated, following a special AR (4) process for quarterly data. The variance-covariance matrix of the compound error terms and its spectral decomposition are also derived, allowing the computation of the Generalized Least Square (GLS) estimates and residuals. The Best Quadratic Unbiased (BQU) Estimates of the variance components are proposed, as well as estimates of all parameters involved in the resulting feasible GLS method.

Suggested Citation

  • Marcel die Dama & Boniface ngah Epo & Galex syrie Soh, 2013. "Developing a two way error component estimation model with disturbances following a special autoregressive (4) for quarterly data," Economics Bulletin, AccessEcon, vol. 33(1), pages 625-634.
    • Handle: RePEc:ebl:ecbull:eb-13-00007
    as

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    References listed on IDEAS

    as
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    5. Sune Karlsson & Jimmy Skoglund, 2004. "Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects," Empirical Economics, Springer, vol. 29(1), pages 79-88, January.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Serial Correlation; Two Way Random Effect Model; Autoregressive; Best Quadratic Unbiased Estimation;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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