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Nonparametric Analysis of Technology and Productivity under Non-Convexity

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  • Chavas, Jean-Paul
  • Kim, Kwansoo

Abstract

This paper investigates the nonparametric analysis of technology under non-convexity. The analysis extends two approaches now commonly used in efficiency and productivity analysis: Data Envelopment Analysis (DEA) where convexity is imposed; and Free Disposal Hull (FDH) models. We argue that, while the FDH model allows for non-convexity, its representation of non-convexity is too extreme. We propose a new nonparametric model that relies on a neighborhood-based technology assessment which allows for less extreme forms of non-convexity. The distinctive feature of our approach is that it allows for non-convexity to arise in any part of the feasible set. We show how it can be implemented empirically by solving simple linear programming problems. And we illustrate the usefulness of the approach in an empirical application to the analysis of technical and scale efficiency on Korean farms.

Suggested Citation

  • Chavas, Jean-Paul & Kim, Kwansoo, 2013. "Nonparametric Analysis of Technology and Productivity under Non-Convexity," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149684, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea13:149684
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    File URL: http://purl.umn.edu/149684
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    References listed on IDEAS

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    1. Kerstens, Kristiaan & Vanden Eeckaut, Philippe, 1999. "Estimating returns to scale using non-parametric deterministic technologies: A new method based on goodness-of-fit," European Journal of Operational Research, Elsevier, vol. 113(1), pages 206-214, February.
    2. Peter Bogetoft & Joseph M. Tama & Jørgen Tind, 2000. "Convex Input and Output Projections of Nonconvex Production Possibility Sets," Management Science, INFORMS, vol. 46(6), pages 858-869, June.
    3. repec:cor:louvrp:-1828 is not listed on IDEAS
    4. Léopold Simar & Valentin Zelenyuk, 2011. "Stochastic FDH/DEA estimators for frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(1), pages 1-20, August.
    5. repec:pal:jorsoc:v:60:y:2009:i:12:d:10.1057_jors.2008.142 is not listed on IDEAS
    6. Kristof Witte & Rui Marques, 2011. "Big and beautiful? On non-parametrically measuring scale economies in non-convex technologies," Journal of Productivity Analysis, Springer, vol. 35(3), pages 213-226, June.
    7. Leleu, Herve, 2006. "A linear programming framework for free disposal hull technologies and cost functions: Primal and dual models," European Journal of Operational Research, Elsevier, vol. 168(2), pages 340-344, January.
    8. AGRELL, Per J. & BOGETOFT, Peter & BROCK, Michael & TIND, Jorgen, 2005. "Efficiency evaluation with convex pairs," CORE Discussion Papers RP 1828, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Walter Briec & Kristiaan Kerstens & Philippe Venden Eeckaut, 2004. "Non-convex Technologies and Cost Functions: Definitions, Duality and Nonparametric Tests of Convexity," Journal of Economics, Springer, vol. 81(2), pages 155-192, February.
    10. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    11. H Leleu, 2009. "Mixing DEA and FDH models together," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1730-1737, December.
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    More about this item

    Keywords

    technology; productivity; nonparametric; non-convexity; Farm Management; Production Economics; Productivity Analysis; Research Methods/ Statistical Methods;

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