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Profit efficiency analysis under limited information with an application to German farm types

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  • Cherchye, Laurens
  • Van Puyenbroeck, Tom

Abstract

Lack of information about technology and prices often hampers the empirical assessment of the profit maximization hypothesis (viz. by measuring the degree of profit efficiency). The non-parametric Data Envelopment Analysis (DEA) methodology can deal with such incomplete information. We exploit the implicit but largely neglected profit interpretation of the DEA model that builds on assumptions of monotone and convex production possibility sets. We show how its embedded assessment of necessary conditions for profit maximization can be strengthened given partial information in the form of monetary sub-cost/-revenue data (that are often easier obtained than the pure quantity data). Finally, we argue that a 'mix' efficiency analysis is naturally complementary to such a profit efficiency analysis. An application to German farm types complements our methodological discussion. By using non-parametric statistical tests, we further demonstrate the potential of the non-parametric approach in deriving strong and robust statistical evidence while imposing minimal structure on the setting under study. In particular, we look for significant efficiency variation over regions.

Suggested Citation

  • Cherchye, Laurens & Van Puyenbroeck, Tom, 2007. "Profit efficiency analysis under limited information with an application to German farm types," Omega, Elsevier, vol. 35(3), pages 335-349, June.
  • Handle: RePEc:eee:jomega:v:35:y:2007:i:3:p:335-349
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    Cited by:

    1. Avkiran, Necmi K., 2009. "Opening the black box of efficiency analysis: An illustration with UAE banks," Omega, Elsevier, vol. 37(4), pages 930-941, August.
    2. Ketikidis, P.H. & Koh, S.C.L. & Dimitriadis, N. & Gunasekaran, A. & Kehajova, M., 2008. "The use of information systems for logistics and supply chain management in South East Europe: Current status and future direction," Omega, Elsevier, vol. 36(4), pages 592-599, August.
    3. Nin-Pratt, Alejandro & McBride, Linden, 2014. "Agricultural intensification in Ghana: Evaluating the optimist’s case for a Green Revolution," Food Policy, Elsevier, vol. 48(C), pages 153-167.
    4. Vasileiou, Konstantinos Z., 2010. "Exploring the role of fertilizer application on the sustainability of Greek potato farms: A DEA application," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 0(Issue 1), pages 1-16, January.
    5. Odeck, James, 2009. "Statistical precision of DEA and Malmquist indices: A bootstrap application to Norwegian grain producers," Omega, Elsevier, vol. 37(5), pages 1007-1017, October.
    6. Leleu, Hervé, 2013. "Inner and outer approximations of technology: A shadow profit approach," Omega, Elsevier, vol. 41(5), pages 868-871.
    7. Elie Appelbaum & Aman Ullah, 1997. "Estimation Of Moments And Production Decisions Under Uncertainty," The Review of Economics and Statistics, MIT Press, vol. 79(4), pages 631-637, November.
    8. Zhao, Y. & Triantis, K. & Murray-Tuite, P. & Edara, P., 2011. "Performance measurement of a transportation network with a downtown space reservation system: A network-DEA approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1140-1159.
    9. Cherchye, Laurens & De Rock, Bram & Walheer, Barnabé, 2016. "Multi-output profit efficiency and directional distance functions," Omega, Elsevier, vol. 61(C), pages 100-109.
    10. Kuosmanen, Timo & Kazemi Matin, Reza, 2011. "Duality of weakly disposable technology," Omega, Elsevier, vol. 39(5), pages 504-512, October.
    11. Kuosmanen, Timo & Kortelainen, Mika & Sipiläinen, Timo & Cherchye, Laurens, 2010. "Firm and industry level profit efficiency analysis using absolute and uniform shadow prices," European Journal of Operational Research, Elsevier, vol. 202(2), pages 584-594, April.
    12. Atici, Kazim Baris & Podinovski, Victor V., 2015. "Using data envelopment analysis for the assessment of technical efficiency of units with different specialisations: An application to agriculture," Omega, Elsevier, vol. 54(C), pages 72-83.
    13. Cherchye, Laurens & De Rock, Bram & Hennebel, Veerle, 2014. "The economic meaning of Data Envelopment Analysis: A ‘behavioral’ perspective," Socio-Economic Planning Sciences, Elsevier, vol. 48(1), pages 29-37.

    More about this item

    Keywords

    Profit maximization hypothesis Data envelopment analysis Non-parametric techniques Agriculture;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • P32 - Economic Systems - - Socialist Institutions and Their Transitions - - - Collectives; Communes; Agricultural Institutions
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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