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Improved Average Estimation in Seemingly Unrelated Regressions

Author

Listed:
  • Ali Mehrabani

    (UCR)

  • Aman Ullah

    (Department of Economics, University of California Riverside)

Abstract
In this paper, we propose an efficient weighted average estimator in Seemingly Unrelated Regressions. This average estimator shrinks a generalized least squares (GLS) estimator towards a restricted GLS estimator, where the restrictions represent possible parameter homogeneity specifications. The shrinkage weight is inversely proportional to a weighted quadratic loss function. The approximate bias and second moment matrix of the average estimator using the large-sample approximations are provided. We give the conditions under which the average estimator dominates the GLS estimator on the basis of their mean squared errors. We illustrate our estimator by applying it to a cost system for U.S. Commercial banks, over the period from 2000 to 2018. Our results indicate that on average most of the banks have been operating under increasing returns to scale. We find that over the recent years, scale economies are a plausible reason for the growth in average size of banks and the tendency toward increasing scale is likely to continue.

Suggested Citation

  • Ali Mehrabani & Aman Ullah, 2020. "Improved Average Estimation in Seemingly Unrelated Regressions," Working Papers 202013, University of California at Riverside, Department of Economics, revised Jun 2020.
    • Handle: RePEc:ucr:wpaper:202013
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    References listed on IDEAS

    as
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    Cited by:

    1. Ali Mehrabani & Aman Ullah, 2022. "Weighted Average Estimation in Panel Data," Working Papers 202209, University of California at Riverside, Department of Economics, revised Apr 2022.
    2. Jesus M. Padilla-Atondo & Jorge Limon-Romero & Armando Perez-Sanchez & Diego Tlapa & Yolanda Baez-Lopez & Cesar Puente & Sinue Ontiveros, 2021. "The Impact of Hydrogen on a Stationary Gasoline-Based Engine through Multi-Response Optimization: A Desirability Function Approach," Sustainability, MDPI, vol. 13(3), pages 1-18, January.
    3. Shahnaz Parsaeian, 2024. "Stein-like Common Correlated Effects Estimation under Structural Breaks," Econometrics, MDPI, vol. 12(2), pages 1-23, April.

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    More about this item

    Keywords

    Key Words: Stein-type Shrinkage Estimator; Asymptotic Approximations; SUR; GLS;
    All these keywords.

    JEL classification:

    • B23 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Econometrics; Quantitative and Mathematical Studies
    • C - Mathematical and Quantitative Methods
    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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