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Estimation of production technology when the objective is to maximize return to the outlay

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  • Kumbhakar, Subal C.

Abstract

This paper deals with estimation of production technology where endogeneous choice of input and output variables is explicitly recognized. To address this endogeneity issue, we assume that producers maximize return to the outlay. We start from a flexible (translog) transformation function with a single output and multiple inputs and show how the first-order conditions of maximizing return to the outlay can be used to come up with an 'estimating equation' that does not suffer from the econometric endogeneity problem although the output and input variables are chosen endogenously. This is because the regressors in this estimating equation are in ratio forms which are uncorrelated with the error term under the assumption that producers maximize return to the outlay. The analysis is then extended to the multiple outputs and multiple inputs case with technical inefficiency. Although the estimating equations in both single and multiple output cases are neither production nor distance functions, they can be estimated in a straightforward manner using the standard stochastic frontier technique without worrying about endogeneity of the regressors. Thus, we provide a rationale for estimating the technology parameters consistently using an econometric model which requires data on only input and output quantities.

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  • Kumbhakar, Subal C., 2011. "Estimation of production technology when the objective is to maximize return to the outlay," European Journal of Operational Research, Elsevier, vol. 208(2), pages 170-176, January.
  • Handle: RePEc:eee:ejores:v:208:y:2011:i:2:p:170-176
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    Cited by:

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    2. Víctor Fernández-Blanco & Ana Rodríguez-Álvarez & Aleksandra Wiśniewska, 2019. "Measuring technical efficiency and marginal costs in the performing arts: the case of the municipal theatres of Warsaw," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(1), pages 97-119, March.
    3. Victor Fernandez-Blanco & Ana Rodriguez-Alvarez, 2015. "Measuring allocative efficiency in cultural economics: The case of Fundacion Princesa de Asturias," ACEI Working Paper Series AWP-09-2015, Association for Cultural Economics International, revised Oct 2015.
    4. Lien, Gudbrand & Kumbhakar, Subal C. & Alem, Habtamu, 2018. "Endogeneity, heterogeneity, and determinants of inefficiency in Norwegian crop-producing farms," International Journal of Production Economics, Elsevier, vol. 201(C), pages 53-61.
    5. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    6. Kamil Makieła & Błażej Mazur, 2022. "Model uncertainty and efficiency measurement in stochastic frontier analysis with generalized errors," Journal of Productivity Analysis, Springer, vol. 58(1), pages 35-54, August.
    7. Koppenberg, Maximilian & Hirsch, Stefan, 2020. "Comparing methods for markup estimation with an application to EU food retailing," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304272, Agricultural and Applied Economics Association.
    8. Llorca, Manuel & Jamasb, Tooraj, 2017. "Energy efficiency and rebound effect in European road freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 98-110.
    9. Rodríguez-Álvarez, A. & Orea, L. & Jamasb, T., 2016. "Fuel poverty and well-being: a consmer theory and stochastic fronteir approach," Cambridge Working Papers in Economics 1668, Faculty of Economics, University of Cambridge.
    10. Rodriguez-Alvarez, Ana & Orea, Luis & Jamasb, Tooraj, 2019. "Fuel poverty and Well-Being:A consumer theory and stochastic frontier approach," Energy Policy, Elsevier, vol. 131(C), pages 22-32.
    11. Marchioni, Andrea & Magni, Carlo Alberto, 2018. "Investment decisions and sensitivity analysis: NPV-consistency of rates of return," European Journal of Operational Research, Elsevier, vol. 268(1), pages 361-372.
    12. Víctor Fernández-Blanco & Ana Rodríguez-Álvarez, 2018. "Measuring allocative efficiency in Cultural Economics: the case of “Fundación Princesa de Asturias” (The Princess of Asturias Foundation)," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 42(1), pages 91-110, February.
    13. Maximilian Koppenberg & Stefan Hirsch, 2022. "Markup estimation: A comparison of contemporary methods at the example of European food retailers," Agribusiness, John Wiley & Sons, Ltd., vol. 38(1), pages 108-133, January.
    14. Tsionas, Mike G. & Andrikopoulos, Athanasios, 2020. "On a High-Dimensional Model Representation method based on Copulas," European Journal of Operational Research, Elsevier, vol. 284(3), pages 967-979.
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