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A Bayesian analysis of multiple-output production frontier

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Abstract

In this paper we develop Bayesian tools for estimating multi-output production frontiers in applications where only input and output data are available. Firm-specific inefficiency is measured relative to this frontier. Our work has important differences from the existing literature, which either assumes a classical econometric perspective with restrictive functional form assumptions, or a non-stochastic approach which directly estimates the output distance function. Bayesian inference is implemented using a Markov Chain Monte Carlo algorithm. A banking application shows the ease and practicality of our approach.

Suggested Citation

  • Carmen Fernandez & Gary Koop & Mark F J Steel, 1999. "A Bayesian analysis of multiple-output production frontier," Edinburgh School of Economics Discussion Paper Series 21, Edinburgh School of Economics, University of Edinburgh.
    • Handle: RePEc:edn:esedps:21
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    1. Adams, Robert M & Berger, Allen N & Sickles, Robin C, 1999. "Semiparametric Approaches to Stochastic Panel Frontiers with Applications in the Banking Industry," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(3), pages 349-358, July.
    2. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 1994. "Bayesian Efficiency Analysis with a Flexible Form: The AIM Cost Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 339-346, July.
    3. Koop, Gary & Osiewalski, Jacek & Steel, Mark F J, 1999. "The Components of Output Growth: A Stochastic Frontier Analysis," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(4), pages 455-487, November.
    4. Koop, Gary & Osiewalski, Jacek & Steel, Mark F. J., 1997. "Bayesian efficiency analysis through individual effects: Hospital cost frontiers," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 77-105.
    5. Fernandez, Carmen & Osiewalski, Jacek & Steel, Mark F. J., 1997. "On the use of panel data in stochastic frontier models with improper priors," Journal of Econometrics, Elsevier, vol. 79(1), pages 169-193, July.
    6. Fernández, Carmen & Steel, Mark F.J., 2000. "Bayesian Regression Analysis With Scale Mixtures Of Normals," Econometric Theory, Cambridge University Press, vol. 16(1), pages 80-101, February.
    7. Berger, Allen N. & Humphrey, David B., 1997. "Efficiency of financial institutions: International survey and directions for future research," European Journal of Operational Research, Elsevier, vol. 98(2), pages 175-212, April.
    8. Kumbhakar, Subal C., 1987. "The specification of technical and allocative inefficiency in stochastic production and profit frontiers," Journal of Econometrics, Elsevier, vol. 34(3), pages 335-348, March.
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    11. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    12. Lau, Lawrence J, 1972. "Profit Functions of Technologies with Multiple Inputs and Outputs," The Review of Economics and Statistics, MIT Press, vol. 54(3), pages 281-289, August.
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    More about this item

    Keywords

    banking data; efficiency; productivity; Markov chain Monte Carlo;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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