IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i4p487-d780950.html
   My bibliography  Save this article

The Analysis of Family Farm Efficiency and Its Influencing Factors: Evidence from Rural China

Author

Listed:
  • Zhigang Chen

    (Institute of Regional and Urban-Rural Development, Wuhan University, Wuhan 430072, China)

  • Qianyue Meng

    (Institute of Regional and Urban-Rural Development, Wuhan University, Wuhan 430072, China)

  • Kaixin Yan

    (Institute of Regional and Urban-Rural Development, Wuhan University, Wuhan 430072, China)

  • Rongwei Xu

    (School of Economics, Shandong Normal University, Jinan 250358, China)

Abstract

Improving the efficiency of family farms is of great significance to rural revitalization and agricultural modernization in China. In order to find out the development status and shortcomings of family farms in China, and put forward targeted policy recommendations to improve the efficiency of various family farms, this paper applies the DEA model to measure the efficiency of family farms from a micro perspective by using the field survey data of the national family farm demonstration bases of Wuhan and Langxi, China. In addition, the Tobit model is further applied to explore the factors that affect the efficiency of full sample family farms, as well as to compare and analyze the differences in the efficiency in different regions and of different operation types. The results show that the efficiency of family farms is low, the efficiency of family farms in Wuhan is higher than that in Langxi, and the efficiency of breeding family farms is higher than that of planting family farms and mixed family farms. Capital input, farmers’ education level, market channels, brand registration, fertilizer usage and financial credit have positively affected the efficiency of family farms, while government subsidies and natural disasters have had negative effects on it. Specially, the land operating area shows a U-shaped relationship with farm efficiency. The efficiency of planting family farms is positively affected by labor input, while that of breeding and mixed family farms rely more on capital input and financial credit instead.

Suggested Citation

  • Zhigang Chen & Qianyue Meng & Kaixin Yan & Rongwei Xu, 2022. "The Analysis of Family Farm Efficiency and Its Influencing Factors: Evidence from Rural China," Land, MDPI, vol. 11(4), pages 1-19, March.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:4:p:487-:d:780950
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/4/487/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/4/487/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ayal Kimhi, 2006. "Plot size and maize productivity in Zambia: is there an inverse relationship?," Agricultural Economics, International Association of Agricultural Economists, vol. 35(1), pages 1-9, July.
    2. Milu Muyanga & T S Jayne, 2019. "Revisiting the Farm Size-Productivity Relationship Based on a Relatively Wide Range of Farm Sizes: Evidence from Kenya," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(4), pages 1140-1163.
    3. Dietrich Vollrath, 2007. "Land Distribution and International Agricultural Productivity," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(1), pages 202-216.
    4. Basanta R. Dhungana & Peter L. Nuthall & Gilbert V. Nartea, 2004. "Measuring the economic inefficiency of Nepalese rice farms using data envelopment analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 48(2), pages 347-369, June.
    5. Andrew D. Foster & Mark R. Rosenzweig, 2022. "Are There Too Many Farms in the World? Labor Market Transaction Costs, Machine Capacities, and Optimal Farm Size," Journal of Political Economy, University of Chicago Press, vol. 130(3), pages 636-680.
    6. Catherine Paul & Richard Nehring & David Banker & Agapi Somwaru, 2004. "Scale Economies and Efficiency in U.S. Agriculture: Are Traditional Farms History?," Journal of Productivity Analysis, Springer, vol. 22(3), pages 185-205, November.
    7. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    8. Xueqin Zhu & Alfons Oude Lansink, 2010. "Impact of CAP Subsidies on Technical Efficiency of Crop Farms in Germany, the Netherlands and Sweden," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(3), pages 545-564, September.
    9. Charnes, A. & Cooper, W. W. & Rhodes, E., 1979. "Measuring the efficiency of decision-making units," European Journal of Operational Research, Elsevier, vol. 3(4), pages 339-338, July.
    10. Richard Hornbeck & Suresh Naidu, 2014. "When the Levee Breaks: Black Migration and Economic Development in the American South," American Economic Review, American Economic Association, vol. 104(3), pages 963-990, March.
    11. Jamison, Dean T. & Moock, Peter R., 1984. "Farmer education and farm efficiency in Nepal: The role of schooling, extension services, and cognitive skills," World Development, Elsevier, vol. 12(1), pages 67-86, January.
    12. Cornia, Giovanni Andrea, 1985. "Farm size, land yields and the agricultural production function: An analysis for fifteen developing countries," World Development, Elsevier, vol. 13(4), pages 513-534, April.
    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. Donghui Song & Fengbo Chen & Xi Ouyang, 2024. "The Impact of Changes in Rural Family Structure on Agricultural Productivity and Efficiency: Evidence from Rice Farmers in China," Sustainability, MDPI, vol. 16(10), pages 1-20, May.
    2. Wencheng Li & Lei Wang & Qi Wan & Weijia You & Shaowen Zhang, 2022. "A Configurational Analysis of Family Farm Management Efficiency: Evidence from China," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    3. Wei Wei & Guanyi Yin & Shuai Xie & Qingzhi Sun & Zhan Zhang & Guanghao Li, 2023. "The Spatio-Temporal Patterns and Influencing Factors of Different New Agricultural Business Entities in China—Based on POI Data from 2012 to 2021," Agriculture, MDPI, vol. 13(8), pages 1-26, July.
    4. Zhiping Huang & Tianran Wang & Na Li, 2022. "Reciprocal and Symbiotic: Family Farms’ Operational Performance and Long-Term Cooperation of Entities in the Agricultural Industrial Chain—From the Evidence of Xinjiang in China," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
    5. Yumei Lin & Chenghan Li, 2023. "Does rural e-commerce agglomeration help expand family farms’ size? Evidence from Taobao villages in China's Yangtze River Delta," Electronic Commerce Research, Springer, vol. 23(3), pages 1731-1752, September.

    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. Andrew D. Foster & Mark R. Rosenzweig, 2022. "Are There Too Many Farms in the World? Labor Market Transaction Costs, Machine Capacities, and Optimal Farm Size," Journal of Political Economy, University of Chicago Press, vol. 130(3), pages 636-680.
    2. William J. Burke & Stephen N. Morgan & Thelma Namonje & Milu Muyanga & Nicole M. Mason, 2023. "Beyond the “inverse relationship”: Area mismeasurement may affect actual productivity, not just how we understand it," Agricultural Economics, International Association of Agricultural Economists, vol. 54(4), pages 557-569, July.
    3. Mensah, Edouard R. & Kostandini, Genti, 2020. "The inverse farm size-productivity relationship under land size mis-measurement and in the presence of weather and price risks: Panel data evidence from Uganda," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304477, Agricultural and Applied Economics Association.
    4. Wencheng Li & Lei Wang & Qi Wan & Weijia You & Shaowen Zhang, 2022. "A Configurational Analysis of Family Farm Management Efficiency: Evidence from China," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    5. Omotilewa, Oluwatoba J. & Jayne, T.S. & Muyanga, Milu & Aromolaran, Adebayo B. & Liverpool-Tasie, Lenis Saweda O. & Awokuse, Titus, 2021. "A revisit of farm size and productivity: Empirical evidence from a wide range of farm sizes in Nigeria," World Development, Elsevier, vol. 146(C).
    6. Qiu, Tongwei & Shi, Xinjie & He, Qinying & Luo, Biliang, 2021. "The paradox of developing agricultural mechanization services in China: Supporting or kicking out smallholder farmers?," China Economic Review, Elsevier, vol. 69(C).
    7. Rangalal Mohapatra & Bondona Lama, 2024. "An analysis of the determinants of productivity of Assam tea growers," SN Business & Economics, Springer, vol. 4(12), pages 1-33, December.
    8. Rada, Nicholas E. & Fuglie, Keith O., 2019. "New perspectives on farm size and productivity," Food Policy, Elsevier, vol. 84(C), pages 147-152.
    9. Raushan Bokusheva & Lukáš Čechura & Subal C. Kumbhakar, 2023. "Estimating persistent and transient technical efficiency and their determinants in the presence of heterogeneity and endogeneity," Journal of Agricultural Economics, Wiley Blackwell, vol. 74(2), pages 450-472, June.
    10. Watkins, K. Bradley & Hristovska, Tatjana & Mazzanti, Ralph & Wilson, Charles E. Jr & Schmidt, Lance, 2014. "Measurement of Technical, Allocative, Economic, and Scale Efficiency of Rice Production in Arkansas Using Data Envelopment Analysis," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 46(1), pages 1-18, February.
    11. Klaus Deininger & Denys Nizalov & Sudhir K Singh, 2013. "Are mega-farms the future of global agriculture? Exploring the farm size-productivity relationship for large commercial farms in Ukraine," Discussion Papers 49, Kyiv School of Economics.
    12. Anup Kumar Bhandari & Vipin V, 2018. "Does Export Intensity Affect Firm Performance? Evidence from Basic Metal Industry in India," Working Papers id:12767, eSocialSciences.
    13. Bao Jiang & Enxin Chi & Jian Li, 2022. "Uncertain Data Envelopment Analysis for Cross Efficiency Evaluation with Imprecise Data," Mathematics, MDPI, vol. 10(13), pages 1-9, June.
    14. Chen, Shuo & Lan, Xiaohuan, 2020. "Tractor vs. animal: Rural reforms and technology adoption in China," Journal of Development Economics, Elsevier, vol. 147(C).
    15. Valentina Bosetti & Mariaester Cassinelli & Alessandro Lanza, 2007. "Benchmarking in Tourism Destinations; Keeping in Mind the Sustainable Paradigm," Springer Books, in: Álvaro Matias & Peter Nijkamp & Paulo Neto (ed.), Advances in Modern Tourism Research, chapter 0, pages 165-180, Springer.
    16. Amar Oukil & Slim Zekri, 2021. "Investigating farming efficiency through a two stage analytical approach: Application to the agricultural sector in Northern Oman," Papers 2104.10943, arXiv.org.
    17. Ali Kabasakal & Aziz Kutlar & Murat Sarikaya, 2015. "Efficiency determinations of the worldwide railway companies via DEA and contributions of the outputs to the efficiency and TFP by panel regression," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(1), pages 69-88, March.
    18. Korhonen, Pekka J. & Dehnokhalaji, Akram & Nasrabadi, Nasim, 2018. "A lexicographic radial projection onto the efficient frontier in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1005-1012.
    19. Ferreira, D.C. & Marques, R.C., 2019. "Do quality and access to hospital services impact on their technical efficiency?," Omega, Elsevier, vol. 86(C), pages 218-236.
    20. repec:ags:phajad:199094 is not listed on IDEAS
    21. M. Lábaj & M. Luptáčik & E. Nežinský, 2014. "Data envelopment analysis for measuring economic growth in terms of welfare beyond GDP," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(3), pages 407-424, August.

    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:jlands:v:11:y:2022:i:4:p:487-:d:780950. 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.