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Data Envelopment Analysis as a Complement to Marginal Analysis

Author

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  • Theodoridis, A.M.
  • Psychoudakis, A.
  • Christofi, A.

Abstract

The consideration in the present study is mainly conceptual. The objective is to show how Data Envelopment Analysis (DEA) can be used to reveal the true input-output relations in an industry. In the estimation of a production function it is assumed that all firms use the existing technology efficiently. However, in the real world the observed firms produce homogeneous outputs with differences in factor intensities and in managerial capacity. Hence, inefficiencies are hidden in the estimated production functions. In order to overcome this drawback of the parametric approach and to reveal the true nature of the input-output relations in production, given the available technology, the DEA approach is applied. In this study DEA is applied in order to select the farms that utilize efficiently the existing technology, allowing the estimation of a production function that reveals the true input-output relations in sheep-goat farming, using farm accounting data from a sample of 108 sheep-goat farms.

Suggested Citation

  • Theodoridis, A.M. & Psychoudakis, A. & Christofi, A., 2006. "Data Envelopment Analysis as a Complement to Marginal Analysis," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 7(2), pages 1-11, July.
  • Handle: RePEc:ags:aergaa:44113
    DOI: 10.22004/ag.econ.44113
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    1. Faqir S. Bagi, 1981. "Relationship Between Farm Size and Economic Efficiency: An Analysis of Farm-Level Data from Haryana (India)," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 29(3), pages 317-326, November.
    2. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    3. Rajiv D. Banker & Robert F. Conrad & Robert P. Strauss, 1986. "A Comparative Application of Data Envelopment Analysis and Translog Methods: An Illustrative Study of Hospital Production," Management Science, INFORMS, vol. 32(1), pages 30-44, January.
    4. William H. Greene, 1993. "Frontier Production Functions," Working Papers 93-20, New York University, Leonard N. Stern School of Business, Department of Economics.
    5. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    6. Howard E. Doran, 1985. ""Small" or "Large" Farm: Some Methodological Considerations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 67(1), pages 130-132.
    7. Lau, Lawrence J & Yotopoulos, Pan A, 1971. "A Test for Relative Efficiency and Application to Indian Agriculture," American Economic Review, American Economic Association, vol. 61(1), pages 94-109, March.
    8. Mickael Lothgren & Magnus Tambour, 1999. "Bootstrapping the data envelopment analysis Malmquist productivity index," Applied Economics, Taylor & Francis Journals, vol. 31(4), pages 417-425.
    9. Zvi Griliches, 1957. "Specification Bias in Estimates of Production Functions," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 39(1), pages 8-20.
    10. Yotopoulos, Pan A., 1968. "On the Efficiency of Resource Utilization in Subsistence Agriculture," Food Research Institute Studies, Stanford University, Food Research Institute, vol. 8(2), pages 1-12.
    11. Corbo, Vittorio & Meller, Patricio, 1979. "The translog production function : Some evidence from establishment data," Journal of Econometrics, Elsevier, vol. 10(2), pages 193-199, June.
    12. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    13. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    14. Tsybakov, A.B. & Korostelev, A.P. & Simar, L., 1992. "Efficient Estimation of Monotone Boundaries," Papers 9209, Catholique de Louvain - Institut de statistique.
    15. Berndt, Ernst R. & Christensen, Laurits R., 1973. "The translog function and the substitution of equipment, structures, and labor in U.S. manufacturing 1929-68," Journal of Econometrics, Elsevier, vol. 1(1), pages 81-113, March.
    16. Schmidt, Peter & Sickles, Robin, 1977. "Some Further Evidence on the Use of the Chow Test under Heteroskedasticity," Econometrica, Econometric Society, vol. 45(5), pages 1293-1298, July.
    17. Korostelev, A. P. & Simar, L. & Tsybakov, A. B., 1995. "Estimation of monotone boundaries," LIDAM Reprints CORE 1178, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Kneip, A & Park, B-U & Simar, L, 1996. "A Note on the Convergence of Nonparametric DEA Efficiency Measures," Papers 9603, Catholique de Louvain - Institut de statistique.
    19. W. David Hopper, 1965. "Allocation Efficiency in a Traditional Indian Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 47(3), pages 611-624.
    20. Charnes, A. & Cooper, W. W. & Rhodes, E., 1979. "Measuring the efficiency of decision-making units," European Journal of Operational Research, Elsevier, vol. 3(4), pages 339-338, July.
    21. 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.
    22. Singh, Rajvir & Patel, R. K., 1973. "Returns to Scale, Farm Size and Productivity in Meerut District," Indian Journal of Agricultural Economics, Indian Society of Agricultural Economics, vol. 28(2), April.
    23. Seiford, Lawrence M. & Thrall, Robert M., 1990. "Recent developments in DEA : The mathematical programming approach to frontier analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 7-38.
    24. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
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    4. Alexandra Sintori & Penelope Gouta & Vasilia Konstantidelli & Irene Tzouramani, 2024. "Eco-Efficiency of Olive Farms across Diversified Ecological Farming Approaches," Land, MDPI, vol. 13(1), pages 1-19, January.

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