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Are Efficient Farms and Inefficient Farms Heterogeneous?

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Listed:
  • Kim, Youngjune
  • Chen, Bowen
  • Featherstone, Allen M.
  • Pendell, Dustin L.

Abstract

Data Envelopment Analysis (DEA) is one technique that is commonly used for measuring efficiency. Previous studies focus on identifying the sources of inefficiency with implicit assumption of homogeneity between efficient and inefficient farms. Since technical efficiency cannot be greater than one in the standard DEA, those studies are not capturing the marginal effects of input variables on the efficiency improvement for efficient farms, which leaves the heterogeneity in the marginal effects hard to be examined. We exploit a methodology called super DEA, which facilitates the study on the heterogeneity by producing the ranking information in the efficient Decision Making Units(DMUs). A quantile regression is employed to identify the sources of efficiency for efficient farms and inefficient farms, respectively. Using the Kansas Farm Management Association (KFMA), we find that an increase in feed affects efficiency in opposite ways for efficient farms and inefficient farms. This result suggests that efficient and inefficient farms are heterogeneous.

Suggested Citation

  • Kim, Youngjune & Chen, Bowen & Featherstone, Allen M. & Pendell, Dustin L., 2017. "Are Efficient Farms and Inefficient Farms Heterogeneous?," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252830, Southern Agricultural Economics Association.
  • Handle: RePEc:ags:saea17:252830
    DOI: 10.22004/ag.econ.252830
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    References listed on IDEAS

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    1. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Helfand, Steven M. & Levine, Edward S., 2004. "Farm size and the determinants of productive efficiency in the Brazilian Center-West," Agricultural Economics, Blackwell, vol. 31(2-3), pages 241-249, December.
    4. Chen, Yao, 2005. "Measuring super-efficiency in DEA in the presence of infeasibility," European Journal of Operational Research, Elsevier, vol. 161(2), pages 545-551, March.
    5. McDonald, John, 2009. "Using least squares and tobit in second stage DEA efficiency analyses," European Journal of Operational Research, Elsevier, vol. 197(2), pages 792-798, September.
    6. Tim Coelli & Sanzidur Rahman & Colin Thirtle, 2002. "Technical, Allocative, Cost and Scale Efficiencies in Bangladesh Rice Cultivation: A Non‐parametric Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 53(3), pages 607-626, November.
    7. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    8. Hoff, Ayoe, 2007. "Second stage DEA: Comparison of approaches for modelling the DEA score," European Journal of Operational Research, Elsevier, vol. 181(1), pages 425-435, August.
    9. Chesher, Andrew D, 1984. "Testing for Neglected Heterogeneity," Econometrica, Econometric Society, vol. 52(4), pages 865-872, July.
    10. Reynolds, Anderson & Shonkwiler, J S, 1991. "Testing and Correcting for Distributional Misspecifications in the Tobit Model: An Application of the Information Matrix Test," Empirical Economics, Springer, vol. 16(3), pages 313-323.
    11. Blundell, Richard & Meghir, Costas, 1987. "Bivariate alternatives to the Tobit model," Journal of Econometrics, Elsevier, vol. 34(1-2), pages 179-200.
    12. Mei Xue & Patrick T. Harker, 2002. "Note: Ranking DMUs with Infeasible Super-Efficiency DEA Models," Management Science, INFORMS, vol. 48(5), pages 705-710, May.
    13. Featherstone, Allen M. & Langemeier, Michael R. & Ismet, Mohammad, 1997. "A Nonparametric Analysis of Efficiency for a Sample of Kansas Beef Cow Farms," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 29(1), pages 175-184, July.
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    Keywords

    Farm Management; Production Economics; Productivity Analysis;
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