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A solution for multicollinearity in stochastic frontier production function models

Author

Listed:
  • Elkin Castaño

    (Universidad de Antioquia)

  • Santiago Gallón

    (Universidad de Antioquia)

Abstract

This paper considers the problem of collinearity among inputs in a stochastic frontier production model, an issue that has received little attention in the econometric literature. To address this problem, a principal-component-based solution is proposed, which allows carrying out a joint interpretation of technical efficiency and the technology parameters of the model. Applications of the method to simulated and real data show its usability and effective performance

Suggested Citation

  • Elkin Castaño & Santiago Gallón, 2017. "A solution for multicollinearity in stochastic frontier production function models," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 86, pages 9-23, Enero - J.
    • Handle: RePEc:lde:journl:y:2017:i:86:p:9-23
    DOI: 10.17533/udea.le.n86a01
    as

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    References listed on IDEAS

    as
    1. Ian T. Jolliffe, 1982. "A Note on the Use of Principal Components in Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(3), pages 300-303, November.
    2. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    3. Mason, Robert L. & Gunst, Richard F., 1985. "Selecting principal components in regression," Statistics & Probability Letters, Elsevier, vol. 3(6), pages 299-301, October.
    4. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    stochastic frontier analysis; technical efficiency; productivity; multicollinearity; principal component estimation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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