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Estimation of input‐oriented technical efficiency using a nonhomogeneous stochastic production frontier model

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  • Subal C. Kumbhakar
  • Efthymios G. Tsionas

Abstract

Technical inefficiency can be modeled as either input‐oriented (IO) or output‐oriented (OO). However, in the estimation of parametric stochastic production frontier models which use maximum likelihood method only the OO measure is used. In this article we consider a simple nonhomogeneous production function and estimate it with both IO and OO specifications. A sample of 80 Spanish dairy data (1993–1998) is used to estimate both models. We consider one output (liters of milk) and four variable inputs (viz., number of cows, kilograms of concentrates, hectares of land, and labor [measured in man‐equivalent units]). We find that returns to scale (RTS) and technical efficiency results derived from these models are different because either estimated technologies are different, or they are evaluated at different points. Using a Monte Carlo analysis we show that if RTS is close to unity differences in the estimates of RTS and technical efficiency are smaller. This holds true for estimates of both RTS and technical efficiency.

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  • Subal C. Kumbhakar & Efthymios G. Tsionas, 2008. "Estimation of input‐oriented technical efficiency using a nonhomogeneous stochastic production frontier model," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 99-108, January.
    • Handle: RePEc:bla:agecon:v:38:y:2008:i:1:p:99-108
    DOI: 10.1111/j.1574-0862.2007.00285.x
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    Cited by:

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    3. Bao Hoang Nguyen & Robin C. Sickles & Valentin Zelenyuk, 2022. "Efficiency Analysis with Stochastic Frontier Models Using Popular Statistical Softwares," Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 129-171, Springer.
    4. Tsakiridis, Andreas & Mateo-Mantecón, Ingrid & O'Connor, Eamonn & Hynes, Stephen & O'Donoghue, Cathal, 2021. "Efficiency benchmarking of Irish and North Atlantic Spanish ports: Implications for blue growth," Utilities Policy, Elsevier, vol. 72(C).
    5. Kok Fong See & Shawna Grosskopf & Vivian Valdmanis & Valentin Zelenyuk, 2021. "What do we know from the vast literature on efficiency and productivity in healthcare? A Systematic Review and Bibliometric Analysis," CEPA Working Papers Series WP072021, School of Economics, University of Queensland, Australia.
    6. Alghalith, Moawia, 2010. "Preferences estimation without approximation," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1144-1146, December.
    7. Moawia Alghalith, 2006. "Joint production and price uncertainty: hypothesis tests," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 49(3), pages 265-274.
    8. Bokusheva, Raushan & Kumbhakar, Subal C., 2014. "A Distance Function Model with Good and Bad Outputs," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182765, European Association of Agricultural Economists.

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