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Cost Changes and Technical Efficiency of Grain Production in China against a Background of Rising Factor Prices

Author

Listed:
  • Xiaoli Zhu

    (College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China)

  • Chenglong Li

    (College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China)

  • Hong Zhou

    (College of Economics and Management, Nanjing Agricultural University, Nanjing 210095, China)

Abstract

Based on panel data for the inputs and outputs of the three major staple grains (rice, wheat and corn) in China from 2000 to 2020, we calculated the cost efficiency using the stochastic frontier cost function model and examined the effects of cost changes for the three major grains to explore the sources of cost increases for grain production. On this basis, the impact of the input factor structures on the technical efficiency of the three food grains was further analyzed under the conditions of price increases. We found that the labor prices and production costs showed the same trends of changes. Compared to 2000, the labor prices in 2020 increased 7.33-fold and the technical efficiency values for the three grains were all close to 0.9 (0.8689, 0.8912 and 0.8451). An efficiency decomposition showed that the adjustment effect of labor prices was the main factor in cost increases, but the effects of technological progress and efficiency improvement could effectively reduce the costs of grain production (the largest average value for technological progress was for rice at 0.4569). In comparison, the effects of technological progress on cost reduction were more obvious. By analyzing the influence of input factor structures on technical efficiency, it was found that the influence of different input factor structures on technical efficiency was heterogeneous among the different grains. This paper puts forward the following policy recommendations: first, improve the level of mechanization by developing social services to reduce the dependence on labor; secondly, promote the construction of agricultural informatization, such as accelerating the research and development of intelligent agricultural machinery and promoting the transformation of traditional agriculture to intelligent agriculture; finally, promote the marketization of land element price through land trusteeship to reduce the land transfer price.

Suggested Citation

  • Xiaoli Zhu & Chenglong Li & Hong Zhou, 2022. "Cost Changes and Technical Efficiency of Grain Production in China against a Background of Rising Factor Prices," Sustainability, MDPI, vol. 14(19), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12852-:d:936896
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    References listed on IDEAS

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    1. Xu Tian & Fujin Yi & Xiaohua Yu, 2019. "Rising cost of labor and transformations in grain production in China," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 12(1), pages 158-172, December.
    2. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    3. Fujia Sui & Yinsheng Yang & Shizhen Zhao, 2022. "Labor Structure, Land Fragmentation, and Land-Use Efficiency from the Perspective of Mediation Effect: Based on a Survey of Garlic Growers in Lanling, China," Land, MDPI, vol. 11(6), pages 1-17, June.
    4. Hongyun Han & Hanning Li & Liange Zhao, 2018. "Determinants of Factor Misallocation in Agricultural Production and Implications for Agricultural Supply†side Reform in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 26(3), pages 22-42, May.
    5. Lu, Hua & Xie, Hualin & He, Yafen & Wu, Zhilong & Zhang, Xinmin, 2018. "Assessing the impacts of land fragmentation and plot size on yields and costs: A translog production model and cost function approach," Agricultural Systems, Elsevier, vol. 161(C), pages 81-88.
    6. Liqun Tang & Qiang Liu & Wanjiang Yang & Jianying Wang, 2018. "Do agricultural services contribute to cost saving? Evidence from Chinese rice farmers," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 10(2), pages 323-337, May.
    7. Minten, Bart & Dorosh, Paul A., 2019. "Rising cereal prices in Ethiopia: An assessment and possible contributing factors," ESSP research notes 73, International Food Policy Research Institute (IFPRI).
    8. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
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    Cited by:

    1. Yaoyao Wang & Yuanpei Kuang, 2023. "Evaluation, Regional Disparities and Driving Mechanisms of High-Quality Agricultural Development in China," Sustainability, MDPI, vol. 15(7), pages 1-20, April.

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