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Measuring the economic inefficiency of Nepalese rice farms using data envelopment analysis

  • Dhungana, Basanta R.
  • Nuthall, Peter L.
  • Nartea, Gilbert V.
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    A data envelopment analysis of a sample of 76 Nepalese rice farmers reveals average relative economic, allocative, technical, pure technical and scale inefficiencies as 34, 13, 24, 18 and 7 per cent, respectively. The significant variations in the level of inefficiency across sample farms are attributed to the variations in the ‘use intensities’ of resources such as seed, labour, fertilisers and mechanical power. In addition, a second stage Tobit regression shows the variation is also related to farm‐specific attributes such as the farmers’ level of risk attitude, the farm manager's gender, age, education and family labour endowment. Based on the empirical findings, policy implications and development strategies for improving efficiency of Nepalese rice farms are briefly discussed.

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    File URL: http://purl.umn.edu/117966
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    Article provided by Australian Agricultural and Resource Economics Society in its journal Australian Journal of Agricultural and Resource Economics.

    Volume (Year): 48 (2004)
    Issue (Month): 2 (June)
    Pages:

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    Handle: RePEc:ags:aareaj:117966
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    1. Jirong Wang & Eric J. Wailes & Gail L. Cramer, 1996. "A Shadow-Price Frontier Measurement of Profit Efficiency in Chinese Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(1), pages 146-156.
    2. Shafiq, Muhammad & Rehman, Tahir, 2000. "The extent of resource use inefficiencies in cotton production in Pakistan's Punjab: an application of Data Envelopment Analysis," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 22(3), April.
    3. Xu, Xiaosong & Jeffrey, Scott R., 1998. "Efficiency and technical progress in traditional and modern agriculture: evidence from rice production in China," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 18(2), March.
    4. Abdul Wadud & Ben White, 2000. "Farm household efficiency in Bangladesh: a comparison of stochastic frontier and DEA methods," Applied Economics, Taylor & Francis Journals, vol. 32(13), pages 1665-1673.
    5. Tadesse, Bedassa & Krishnamoorthy, S., 1997. "Technical efficiency in paddy farms of Tamil Nadu: An analysis based on farm size and ecological zone," Agricultural Economics, Blackwell, vol. 16(3), pages 185-192, August.
    6. Simar, L. & Wilson, P.W., 2000. "Testing Restrictions in Nonparametric Efficiency Models," Papers 0013, Catholique de Louvain - Institut de statistique.
    7. Torkamani, Javad & Hardaker, J. Brian, 1996. "A study of economic efficiency of Iranian farmers in Ramjerd district: an application of stochastic programming," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 14(2), July.
    8. 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.
    9. 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.
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