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Estimating SUR system with random coefficients: the unbalanced panel data case

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  • Erik Biørn

Abstract

A system of regression equations for analyzing panel data with random heterogeneity in intercepts and coefficients, and unbalanced panel data is considered. A maximum likelihood (ML) procedure for joint estimation of all parameters is described. Since its implementation for numerical computation is complicated, simplified procedures are presented. The simplifications essentially concern the estimation of the covariance matrices of the random coefficients. The application and ‘anatomy’ of the proposed algorithm for modified ML estimation are illustrated by using panel data for output, inputs and costs for 111 manufacturing firms observed up to 22 years. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Erik Biørn, 2014. "Estimating SUR system with random coefficients: the unbalanced panel data case," Empirical Economics, Springer, vol. 47(2), pages 451-468, September.
    • Handle: RePEc:spr:empeco:v:47:y:2014:i:2:p:451-468
    DOI: 10.1007/s00181-013-0753-y
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    1. Wansbeek, Tom & Kapteyn, Arie, 1989. "Estimation of the error-components model with incomplete panels," Journal of Econometrics, Elsevier, vol. 41(3), pages 341-361, July.
    2. Erik Biørn & Terje Hagen & Tor Iversen & Jon Magnussen, 2010. "How different are hospitals’ responses to a financial reform? The impact on efficiency of activity-based financing," Health Care Management Science, Springer, vol. 13(1), pages 1-16, March.
    3. Badi H. Baltagi, 2021. "Seemingly Unrelated Regressions with Error Components," Springer Texts in Business and Economics, in: Econometric Analysis of Panel Data, edition 6, chapter 0, pages 149-155, Springer.
    4. Silvia Platoni & Paolo Sckokai & Daniele Moro, 2012. "A Note on Two-Way ECM Estimation of SUR Systems on Unbalanced Panel Data," Econometric Reviews, Taylor & Francis Journals, vol. 31(2), pages 119-141.
    5. Badi Baltagi & Seuck Song, 2006. "Unbalanced panel data: A survey," Statistical Papers, Springer, vol. 47(4), pages 493-523, October.
    6. Avery, Robert B, 1977. "Error Components and Seemingly Unrelated Regressions," Econometrica, Econometric Society, vol. 45(1), pages 199-209, January.
    7. Wansbeek, Tom & Kapteyn, Arie, 1982. "A Class of Decompositions of the Variance-Covariance Matrix of a Generalized Error Components Model," Econometrica, Econometric Society, vol. 50(3), pages 713-724, May.
    8. Erik Biørn & Kjersti-Gro Lindquist & Terje Skjerpen, 2002. "Heterogeneity in Returns to Scale: A Random Coefficient Analysis with Unbalanced Panel Data," Journal of Productivity Analysis, Springer, vol. 18(1), pages 39-57, July.
    9. Hsiao, Cheng, 1975. "Some Estimation Methods for a Random Coefficient Model," Econometrica, Econometric Society, vol. 43(2), pages 305-325, March.
    10. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, July-Dece.
    11. Baltagi, Badi H., 1985. "Pooling cross-sections with unequal time-series lengths," Economics Letters, Elsevier, vol. 18(2-3), pages 133-136.
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    More about this item

    Keywords

    Panel data; Unbalanced data; Random coefficients ; Heterogeneity; Regression systems; Iterated maximum likelihood; C33; C51; C63; D24;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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