IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v208y2011i2p170-176.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(10)00613-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kumbhakar, Subal C. & Wang, Hung-Jen, 2006. "Estimation of technical and allocative inefficiency: A primal system approach," Journal of Econometrics, Elsevier, vol. 134(2), pages 419-440, October.
    2. Brissimis, Sophocles N. & Delis, Manthos D. & Tsionas, Efthymios G., 2010. "Technical and allocative efficiency in European banking," European Journal of Operational Research, Elsevier, vol. 204(1), pages 153-163, July.
    3. Tim Coelli & Gholamreza Hajargasht & C.A. Knox Lovell, 2008. "Econometric Estimation of an Input Distance Function in a System of Equations," CEPA Working Papers Series WP012008, School of Economics, University of Queensland, Australia.
    4. Per Krusell & Lee E. Ohanian & JosÈ-Victor RÌos-Rull & Giovanni L. Violante, 2000. "Capital-Skill Complementarity and Inequality: A Macroeconomic Analysis," Econometrica, Econometric Society, vol. 68(5), pages 1029-1054, September.
    5. John C. Panzar & Robert D. Willig, 1977. "Economies of Scale in Multi-Output Production," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 91(3), pages 481-493.
    6. Yu, Ming-Miin & Fan, Chih-Ku, 2008. "The effects of privatization on return to the dollar: A case study on technical efficiency, and price distortions of Taiwan's intercity bus services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(6), pages 935-950, July.
    7. José Zofío & Angel Prieto, 2006. "Return to Dollar, Generalized Distance Function and the Fisher Productivity Index," Spanish Economic Review, Springer;Spanish Economic Association, vol. 8(2), pages 113-138, June.
    8. COELLI, Tim, 2000. "On the econometric estimation of the distance function representation of a production technology," LIDAM Discussion Papers CORE 2000042, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Fare, Rolf & Grosskopf, Shawna & Zaim, Osman, 2002. "Hyperbolic efficiency and return to the dollar," European Journal of Operational Research, Elsevier, vol. 136(3), pages 671-679, February.
    10. Reinhard, Stijn & Knox Lovell, C. A. & Thijssen, Geert J., 2000. "Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA," European Journal of Operational Research, Elsevier, vol. 121(2), pages 287-303, March.
    11. Bhattacharyya, Arunava & Lovell, C. A. K. & Sahay, Pankaj, 1997. "The impact of liberalization on the productive efficiency of Indian commercial banks," European Journal of Operational Research, Elsevier, vol. 98(2), pages 332-345, April.
    12. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    13. Subal C. Kumbhakar, 2001. "Estimation of Profit Functions When Profit Is Not Maximum," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(1), pages 1-19.
    14. Banos-Pino, Jose & Fernandez-Blanco, Victor & Rodriguez-Alvarez, Ana, 2002. "The allocative efficiency measure by means of a distance function: The case of Spanish public railways," European Journal of Operational Research, Elsevier, vol. 137(1), pages 191-205, February.
    15. ZELLNER, Arnold & KMENTA, Jan & DREZE, Jacques H., 1966. "Specification and estimation of Cobb-Douglas production function models," LIDAM Reprints CORE 12, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Subal Kumbhakar & Sjur Baardsen & Gudbrand Lien, 2012. "A New Method for Estimating Market Power with an Application to Norwegian Sawmilling," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 40(2), pages 109-129, March.
    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. Badunenko, Oleg & D’Inverno, Giovanna & De Witte, Kristof, 2023. "On distinguishing the direct causal effect of an intervention from its efficiency-enhancing effects," European Journal of Operational Research, Elsevier, vol. 310(1), pages 432-447.
    11. 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.
    12. 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.
    13. Manuel Llorca & Ana Rodriguez-Alvarez, 2023. "Economic, Environmental, and Energy Equity Convergence: Evidence of a Multi-Speed Europe?," Efficiency Series Papers 2023/05, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    14. 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.
    15. 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.
    16. 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.
    17. Kumbhakar, Subal C., 2012. "Specification and estimation of primal production models," European Journal of Operational Research, Elsevier, vol. 217(3), pages 509-518.
    18. Maximilian Koppenberg & Stefan Hirsch, 2022. "Output market power and firm characteristics in dairy processing: Evidence from three EU countries," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(2), pages 490-517, June.
    19. Lukáš Čechura & Heinrich Hockmann, 2017. "Heterogeneity in Production Structures and Efficiency: An Analysis of the Czech Food Processing Industry," Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 702-719, October.
    20. Subal Kumbhakar & Frank Asche & Ragnar Tveteras, 2013. "Estimation and decomposition of inefficiency when producers maximize return to the outlay: an application to Norwegian fishing trawlers," Journal of Productivity Analysis, Springer, vol. 40(3), pages 307-321, December.
    21. Tsionas, Mike G., 2017. "Microfoundations for stochastic frontiers," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1165-1170.
    22. Fang, Guozhu & Zhang, Xiaoheng & Qi, Chunjie, 2021. "Are Integrated Crop-Livestock Systems More Technical Efficiency? Evidence from Small Farmers in China," 2021 Conference, August 17-31, 2021, Virtual 315129, International Association of Agricultural Economists.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Subal Kumbhakar & Frank Asche & Ragnar Tveteras, 2013. "Estimation and decomposition of inefficiency when producers maximize return to the outlay: an application to Norwegian fishing trawlers," Journal of Productivity Analysis, Springer, vol. 40(3), pages 307-321, December.
    2. Kumbhakar, Subal C., 2013. "Specification and estimation of multiple output technologies: A primal approach," European Journal of Operational Research, Elsevier, vol. 231(2), pages 465-473.
    3. Efthymios G. Tsionas & Subal C. Kumbhakar & Emir Malikov, 2015. "Estimation of Input Distance Functions: A System Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 97(5), pages 1478-1493.
    4. Imane Bounadi & Khalil Allali & Aziz Fadlaoui & Mohammed Dehhaoui, 2023. "Water Pollution Abatement in Olive Oil Industry in Morocco: Cost Estimates and Policy Implications," Sustainability, MDPI, vol. 15(5), pages 1-19, February.
    5. Jens Kjærsgaard & Niels Vestergaard & Kristiaan Kerstens, 2009. "Ecological Benchmarking to Explore Alternative Fishing Schemes to Protect Endangered Species by Substitution: The Danish Demersal Fishery in the North Sea," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 43(4), pages 573-590, August.
    6. Manuel Llorca & Ana Rodriguez-Alvarez, 2023. "Economic, Environmental, and Energy Equity Convergence: Evidence of a Multi-Speed Europe?," Efficiency Series Papers 2023/05, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    7. César Salazar & Roberto Cárdenas-Retamal & Marcela Jaime, 2023. "Environmental efficiency in the salmon industry—an exploratory analysis around the 2007 ISA virus outbreak and subsequent regulations in Chile," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8107-8135, August.
    8. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.
    9. Yu, Xiaohong & Xu, Haiyan & Lou, Wengao & Xu, Xun & Shi, Victor, 2023. "Examining energy eco-efficiency in China's logistics industry," International Journal of Production Economics, Elsevier, vol. 258(C).
    10. Lee, Chi-Chuan & Lee, Chien-Chiang, 2022. "How does green finance affect green total factor productivity? Evidence from China," Energy Economics, Elsevier, vol. 107(C).
    11. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    12. Kellermann, Magnus A., 2015. "Total Factor Productivity Decomposition and Unobserved Heterogeneity in Stochastic Frontier Models," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 44(1), pages 1-25, April.
    13. Benjamin Hampf, 2018. "Measuring inefficiency in the presence of bad outputs: Does the disposability assumption matter?," Empirical Economics, Springer, vol. 54(1), pages 101-127, February.
    14. Chia-Yen Lee, 2017. "Directional marginal productivity: a foundation of meta-data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(5), pages 544-555, May.
    15. Juan Aparicio & Magdalena Kapelko & Lidia Ortiz, 2021. "Modelling environmental inefficiency under a quota system," Operational Research, Springer, vol. 21(2), pages 1097-1124, June.
    16. Lai, Hung-pin & Kumbhakar, Subal C., 2019. "Technical and allocative efficiency in a panel stochastic production frontier system model," European Journal of Operational Research, Elsevier, vol. 278(1), pages 255-265.
    17. García-Alonso, Carlos R. & Salvador-Carulla, Luis & Fernández-Rodríguez, Vicente, 2015. "Evaluation of system efficiency using the Monte Carlo DEA: The case of small health areasAuthor-Name: Torres-Jiménez, Mercedes," European Journal of Operational Research, Elsevier, vol. 242(2), pages 525-535.
    18. Hugo Fuentes & Emili Grifell-Tatjé & Sergio Perelman, 2001. "A Parametric Distance Function Approach for Malmquist Productivity Index Estimation," Journal of Productivity Analysis, Springer, vol. 15(2), pages 79-94, March.
    19. George Halkos & George Papageorgiou, 2016. "Spatial environmental efficiency indicators in regional waste generation: a nonparametric approach," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 59(1), pages 62-78, January.
    20. Halkos, George & Tzeremes, Nickolaos, 2013. "An additive two-stage DEA approach creating sustainability efficiency indexes," MPRA Paper 44231, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:208:y:2011:i:2:p:170-176. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.