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Explaining Production Inefficiency in China’s Agriculture using Data Envelope Analysis and Semi-Parametric Bootstrapping

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  • Monchuk, Daniel C.
  • Zhuo, Chen

Abstract

In this paper we examine more closely the factors associated with production inefficiency in China’s agriculture. The approach we take involves a two-stage process where output efficiency scores are first estimated using data envelope analysis (DEA), and then in the second stage, variation in the resulting efficiency scores are explained using a truncated regression model with inference based on a semi-parametric bootstrap routine. Among the results we find a heavy industrial presence is associated with reduced agricultural production efficiency and may be an indication that externalities from the industrial process, like air and ground water pollution, affect agricultural production. We also find evidence that counties with a large percentage of the rural labor force engaged in agriculture tend to be less efficient, which suggests that policies to facilitate the removal of labor from agriculture, but not necessarily from the rural areas, would bring about enhanced agricultural efficiency and calls into question policies that promote wholesale migration from rural areas. Sensitivity analysis indicates results are robust to influential observations and outliers.

Suggested Citation

  • Monchuk, Daniel C. & Zhuo, Chen, 2008. "Explaining Production Inefficiency in China’s Agriculture using Data Envelope Analysis and Semi-Parametric Bootstrapping," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6456, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea08:6456
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    File URL: http://purl.umn.edu/6456
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    References listed on IDEAS

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    1. Jean-Paul Chavas & Ragan Petrie & Michael Roth, 2005. "Farm Household Production Efficiency: Evidence from The Gambia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(1), pages 160-179.
    2. Chen, Zhuo & Huffman, Wallace E. & Rozelle, Scott, 2009. "Farm technology and technical efficiency: Evidence from four regions in China," China Economic Review, Elsevier, vol. 20(2), pages 153-161, June.
    3. Carter, Colin A. & Chen, Jing & Chu, Baojin, 2003. "Agricultural productivity growth in China: farm level versus aggregate measurement," China Economic Review, Elsevier, vol. 14(1), pages 53-71.
    4. Konstantinos Giannakas & Kien C. Tran & Vangelis Tzouvelekas, 2003. "On the choice of functional form in stochastic frontier modeling," Empirical Economics, Springer, vol. 28(1), pages 75-100, January.
    5. Abdulai, Awudu & Huffman, Wallace, 2000. "Structural Adjustment and Economic Efficiency of Rice Farmers in Northern Ghana," Economic Development and Cultural Change, University of Chicago Press, vol. 48(3), pages 503-520, April.
    6. Maria Alberta Oliveira & Carlos Santos, 2005. "Assessing school efficiency in Portugal using FDH and bootstrapping," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 957-968.
    7. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    8. Timo Kuosmanen & Diemuth Pemsl & Justus Wesseler, 2006. "Specification and Estimation of Production Functions Involving Damage Control Inputs: A Two-Stage, Semiparametric Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(2), pages 499-511.
    9. Tulkens, Henry & Vanden Eeckaut, Philippe, 1995. "Non-parametric efficiency, progress and regress measures for panel data: Methodological aspects," European Journal of Operational Research, Elsevier, vol. 80(3), pages 474-499, February.
    10. Fan, Shenggen & Zhang, Xiaobo, 2002. "Production and Productivity Growth in Chinese Agriculture: New National and Regional Measures," Economic Development and Cultural Change, University of Chicago Press, vol. 50(4), pages 819-838, July.
    11. 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.
    12. repec:cor:louvrp:-1178 is not listed on IDEAS
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    More about this item

    Keywords

    China's agriculture; DEA; bootstrapping; technical efficiency; Production Economics; C14; Q1; R5;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • Q1 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture
    • R5 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis

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