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A solution for multicollinearity in stochastic frontier production function models

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  • Castano, Elkin
  • Gallon, Santiago

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. Resumen: Este artículo considera el problema de colinealidad entre insumos en un modelo de producción de frontera estocástica, un tema que ha recibido poca atención en la literatura econométrica. Para abordar el problema, se propone una solución basada en componentes principales que permite interpretar conjuntamente la eficiencia técnica y los parámetros de tecnología del modelo. Los resultados de la aplicación del método con datos simulados y reales muestran que éste es fácil de usar y presenta un buen desempeno

Suggested Citation

  • Castano, Elkin & Gallon, Santiago, 2016. "A solution for multicollinearity in stochastic frontier production function models," Revista Lecturas de Economía, Universidad de Antioquia, CIE, issue 86, pages 9-23, December.
    • Handle: RePEc:col:000174:015393
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    References listed on IDEAS

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    1. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    2. Mason, Robert L. & Gunst, Richard F., 1985. "Selecting principal components in regression," Statistics & Probability Letters, Elsevier, vol. 3(6), pages 299-301, October.
    3. 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.
    4. Jaume Puig‐Junoy, 2001. "Technical Inefficiency and Public Capital in U.S. States: A Stochastic Frontier Approach," Journal of Regional Science, Wiley Blackwell, vol. 41(1), pages 75-96, February.
    5. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    6. 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.análisis de frontera estocástica; eficiencia técnica; productividad; multicolinealidad; estimación de componentes principales;
    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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