IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p12852-d936896.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/12852/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/19/12852/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Anbang & He, Ke & Zhang, Junbiao & Zeng, Yangmei, 2021. "Green Production Technologies and Technical Efficiency of Rice Farmers in China: A Case Study of Straw-Derived Biochar," 2021 Conference, August 17-31, 2021, Virtual 315026, International Association of Agricultural Economists.
    2. Tom Kompas & Tuong Nhu Che & R. Quentin Grafton, 2004. "Technical efficiency effects of input controls: evidence from Australia's banana prawn fishery," Applied Economics, Taylor & Francis Journals, vol. 36(15), pages 1631-1641.
    3. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    4. Andriakopoulos, Konstantinos & Ladas, Augoustinos & Andriakopoulos, Panagiotis, 2020. "Bank efficiency and leasing in U.S.A. banking system," MPRA Paper 112645, University Library of Munich, Germany.
    5. Giovanni Calice & Levent Kutlu & Ming Zeng, 2021. "Understanding US firm efficiency and its asset pricing implications," Empirical Economics, Springer, vol. 60(2), pages 803-827, February.
    6. Khanal, Aditya & Koirala, Krishna & Regmi, Madhav, 2016. "Do Financial Constraints Affect Production Efficiency in Drought Prone Areas? A Case from Indonesian Rice Growers," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 230087, Southern Agricultural Economics Association.
    7. Firna Varina & Sri Hartoyo & Nunung Kusnadi & Amzul Rifin, 2020. "The Determinants of Technical Efficiency of Oil Palm Smallholders in Indonesia," International Journal of Economics and Financial Issues, Econjournals, vol. 10(6), pages 89-93.
    8. Dhehibi, Boubaker & Lachaal, Lassaad & Elloumi, Mohamed & Messaoud, Emna B., 2007. "Measurement and Sources of Technical Inefficiency in the Tunisian Citrus Growing Sector," 103rd Seminar, April 23-25, 2007, Barcelona, Spain 9391, European Association of Agricultural Economists.
    9. Noel Uri, 2003. "The Effect of Incentive Regulation in Telecommunications in the United States," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(2), pages 169-191, May.
    10. Tauer, Loren W. & Mishra, Ashok K., 2005. "U.S. Dairy Farm Cost Efficiency," Working Papers 127079, Cornell University, Department of Applied Economics and Management.
    11. Gangopadhyay, Partha & Jain, Siddharth & Bakry, Walid, 2022. "In search of a rational foundation for the massive IT boom in the Australian banking industry: Can the IT boom really drive relationship banking?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    12. Williams, Jonathan, 2004. "Determining management behaviour in European banking," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2427-2460, October.
    13. Roy, Manish & Mazumder, Ritwik, 2016. "Technical Efficiency of Fish Catch in Traditional Fishing: A Study in Southern Assam," Journal of Regional Development and Planning, Rajarshi Majumder, vol. 5(1), pages 55-68.
    14. Veronika Fenyves & Tibor Tarnóczi & Zoltán Bács & Dóra Kerezsi & Péter Bajnai & Mihály Szoboszlai, 2022. "Financial efficiency analysis of Hungarian agriculture, fisheries and forestry sector," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(11), pages 413-426.
    15. 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.
    16. Tovar, Beatriz & Wall, Alan, 2015. "Can ports increase traffic while reducing inputs? Technical efficiency of Spanish Port Authorities using a directional distance function approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 71(C), pages 128-140.
    17. Alfonso Flores-Lagunes & William C. Horrace & Kurt E. Schnier, 2007. "Identifying technically efficient fishing vessels: a non-empty, minimal subset approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(4), pages 729-745.
    18. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    19. Sandrine Kablan & Ouidad Yousfi, 2015. "Performance of Islamic Banks across the World: An Empirical Analysis over the Period 2001-2008," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(1), pages 27-46.
    20. repec:use:tkiwps:3232 is not listed on IDEAS
    21. William Griffiths & Xiaohui Zhang & Xueyan Zhao, 2010. "A Stochastic Frontier Model for Discrete Ordinal Outcomes: A Health Production Function," Department of Economics - Working Papers Series 1092, The University of Melbourne.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12852-:d:936896. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.