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Productivity Growth, Technology Progress, And Efficiency Change In Chinese Agricultural Production From 1984 To 1993

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  • Mao, Weining
  • Koo, Won W.
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    Abstract

    This study applies a Data Envelopment Analysis (DEA) approach to analyze total factor productivity, technology, and efficiency changes in Chinese agricultural production from 1984 to 1993. Twenty- nine provinces in China were classified into advanced-technology and low-technology categories. The Malmquist productivity measures were decomposed into two components: technical change index and efficiency change index. The results showed that total factor productivity has risen in most provinces for both technology categories. Technical progress has been the most important factor to Chinese agricultural productivity growth since 1984 and will remain crucial to productivity growth in low-technology provinces. Low efficiency in many important agricultural provinces indicates a great potential for China to increase productivity through improving technical efficiency. Continuously expanding market economy and enhancing rural education may also help farmers to improve technical efficiency and productivity in agricultural production.

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    File URL: http://purl.umn.edu/23442
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    Bibliographic Info

    Paper provided by North Dakota State University, Department of Agribusiness and Applied Economics in its series Agricultural Economics Reports with number 23442.

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    Date of creation: 1996
    Date of revision:
    Handle: RePEc:ags:nddaer:23442

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    Web page: http://www.ext.nodak.edu/homepages/aedept/
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    Related research

    Keywords: Chinese agriculture; Total Factor Productivity (TFP); technology; technical efficiency; Data Envelopment Analysis (DEA).; Productivity Analysis; Research and Development/Tech Change/Emerging Technologies;

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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. Travers, Lee & Ma, Jun, 1994. "Agricultural productivity and rural poverty in China," China Economic Review, Elsevier, vol. 5(1), pages 141-159.
    3. Lin, Justin Yifu, 1992. "Rural Reforms and Agricultural Growth in China," American Economic Review, American Economic Association, vol. 82(1), pages 34-51, March.
    4. McMillan, John & Whalley, John & Zhu, Lijing, 1989. "The Impact of China's Economic Reforms on Agricultural Productivity Growth," Journal of Political Economy, University of Chicago Press, vol. 97(4), pages 781-807, August.
    5. Arnade, Carlos A., 1994. "Using Data Envelopment Analysis to Measure International Agricultural Efficiency and Productivity," Technical Bulletins 156761, United States Department of Agriculture, Economic Research Service.
    6. Carlos Arnade, 1998. "Using a Programming Approach to Measure International Agricultural Efficiency and Productivity," Journal of Agricultural Economics, Wiley Blackwell, vol. 49(1), pages 67-84.
    7. Putterman, Louis & Chiacu, Ana F., 1994. "Elasticities and factor weights for agricultural growth accounting: A look at the data for China," China Economic Review, Elsevier, vol. 5(2), pages 191-204.
    8. Gaynor, Martin & Putterman, Louis, 1993. "Productivity consequences of alternative land division methods in China's decollectivization An econometric analysis," Journal of Development Economics, Elsevier, vol. 42(2), pages 357-386, December.
    9. 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.
    10. 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.
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