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Imposing Weak Monotonicity on Parametric Distance Function Estimations

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  • Perelman, Sergio
  • Santín, David

Abstract

The technology set involved in the estimation of a production frontier theoretically implies monotonicity in outputs. This is because an efficient firm cannot reduce the vector of outputs holding fixed the vector of inputs while it still belongs to the frontier. Very often, however, this hypothesis is violated in empirical studies dealing with the estimation of parametric distance functions. We propose an approach allowing the easy imposition of weak monotonicity on outputs in this context together with an illustrative example in the educational sector.

Suggested Citation

  • Perelman, Sergio & Santín, David, 2008. "Imposing Weak Monotonicity on Parametric Distance Function Estimations," Efficiency Series Papers 2008/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    • Handle: RePEc:oeg:wpaper:2008/02
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    File URL: https://www.unioviedo.es/oeg/ESP/esp_2008_02.pdf
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    References listed on IDEAS

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    1. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
    2. Gary Ferrier & Michael Rosko & Vivian Valdmanis, 2006. "Analysis of uncompensated hospital care using a DEA model of output congestion," Health Care Management Science, Springer, vol. 9(2), pages 181-188, May.
    3. A. T. Flegg & D. O. Allen & K. Field & T. W. Thurlow, 2004. "Measuring the efficiency of British universities: a multi-period data envelopment analysis," Education Economics, Taylor & Francis Journals, vol. 12(3), pages 231-249.
    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.
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