IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i19p8194-d423810.html
   My bibliography  Save this article

Effects of Agricultural Cooperative Society on Farmers’ Technical Efficiency: Evidence from Stochastic Frontier Analysis

Author

Listed:
  • Ruopin Qu

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Science, Beijing 100081, China)

  • Yongchang Wu

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Science, Beijing 100081, China)

  • Jing Chen

    (Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Science, Beijing 100081, China)

  • Glyn D. Jones

    (School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
    FERA Sciences Ltd., National Agri-Food Innovation Campus, Sand Hutton YO41 1LZ, UK)

  • Wenjing Li

    (School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
    FERA Sciences Ltd., National Agri-Food Innovation Campus, Sand Hutton YO41 1LZ, UK)

  • Shan Jin

    (School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK)

  • Qian Chang

    (National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China)

  • Yiying Cao

    (RSK ADAS Ltd., Spring Lodge, 172 Chester Road, Helsby WA6 0AR, UK)

  • Guijun Yang

    (National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China)

  • Zhenhong Li

    (School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK)

  • Lynn J. Frewer

    (School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK)

Abstract

The impact of agricultural cooperatives on apple farmers’ technical efficiency (TE) in China was examined. The cooperatives were divided into two groups: a collective marketing group for farmers and an equivalent non-marketing group that did not provide a marketing service, although other functions remained the same. Using the propensity score matching (PSM) procedure and stochastic production frontier (SPF) modelling, cooperatives’ key functions that potentially increase farmers’ TE can be identified. The results indicate that membership of either group is positively related to yield. However, cooperatives that were not engaged in marketing achieved higher TE than non-members. This suggests that policy makers should encourage cooperatives to focus on activities that do not include direct marketing to increase TE in apple production in China.

Suggested Citation

  • Ruopin Qu & Yongchang Wu & Jing Chen & Glyn D. Jones & Wenjing Li & Shan Jin & Qian Chang & Yiying Cao & Guijun Yang & Zhenhong Li & Lynn J. Frewer, 2020. "Effects of Agricultural Cooperative Society on Farmers’ Technical Efficiency: Evidence from Stochastic Frontier Analysis," Sustainability, MDPI, vol. 12(19), pages 1-13, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:19:p:8194-:d:423810
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/19/8194/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/19/8194/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Abdul-Rahaman, Awal & Abdulai, Awudu, 2018. "Do farmer groups impact on farm yield and efficiency of smallholder farmers? Evidence from rice farmers in northern Ghana," Food Policy, Elsevier, vol. 81(C), pages 95-105.
    2. González-Flores, Mario & Bravo-Ureta, Boris E. & Solís, Daniel & Winters, Paul, 2014. "The impact of high value markets on smallholder productivity in the Ecuadorean Sierra: A Stochastic Production Frontier approach correcting for selectivity bias," Food Policy, Elsevier, vol. 44(C), pages 237-247.
    3. Abdulai, Abdul-Nafeo & Abdulai, Awudu, 2017. "Examining the impact of conservation agriculture on environmental efficiency among maize farmers in Zambia," Environment and Development Economics, Cambridge University Press, vol. 22(2), pages 177-201, April.
    4. Ito, Junichi & Bao, Zongshun & Su, Qun, 2012. "Distributional effects of agricultural cooperatives in China: Exclusion of smallholders and potential gains on participation," Food Policy, Elsevier, vol. 37(6), pages 700-709.
    5. Ma, Wanglin & Renwick, Alan & Yuan, Peng & Ratna, Nazmun, 2018. "Agricultural cooperative membership and technical efficiency of apple farmers in China: An analysis accounting for selectivity bias," Food Policy, Elsevier, vol. 81(C), pages 122-132.
    6. Qiao Liang & George Hendrikse, 2013. "Cooperative CEO Identity and Efficient Governance: Member or Outside CEO?," Agribusiness, John Wiley & Sons, Ltd., vol. 29(1), pages 23-38, January.
    7. Valentinov, Vladislav & Iliopoulos, Constantine, 2013. "Economic theories of nonprofits and agricultural cooperatives compared: New perspectives for nonprofit scholars," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 42(1), pages 109-126.
    8. Fischer, Elisabeth & Qaim, Matin, 2012. "Linking Smallholders to Markets: Determinants and Impacts of Farmer Collective Action in Kenya," World Development, Elsevier, vol. 40(6), pages 1255-1268.
    9. Lijia Wang & Xuexi Huo & Shajahan Kabir, 2013. "Technical and cost efficiency of rural household apple production," China Agricultural Economic Review, Emerald Group Publishing Limited, vol. 5(3), pages 391-411, August.
    10. Andrei CECHIN & Jos BIJMAN & Stefano PASCUCCI & Decio ZYLBERSZTAJN & Onno OMTA, 2013. "Drivers Of Pro-Active Member Participation In Agricultural Cooperatives: Evidence From Brazil," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 84(4), pages 443-468, December.
    11. Shahidur R. Khandker & Gayatri B. Koolwal & Hussain A. Samad, . "Handbook on Impact Evaluation : Quantitative Methods and Practices," World Bank Publications, The World Bank, number 2693, September.
    12. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    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. Guoqiang Liu & Dakuan Qiao & Yuying Liu & Xinhong Fu, 2022. "Does Service Utilization Improve Members’ Welfare? Evidence from Citrus Cooperatives in China," Sustainability, MDPI, vol. 14(11), pages 1-20, May.
    2. Wijdane Rhioui & Jamila Al Figuigui & Rachid Lahlali & Salah-Eddine Laasli & Abdellatif Boutagayout & Moussa El Jarroudi & Saâdia Belmalha, 2023. "Towards Sustainable Vegetable Farming: Exploring Agroecological Alternatives to Chemical Products in the Fez-Meknes Region of Morocco," Sustainability, MDPI, vol. 15(9), pages 1-23, April.
    3. Wanglin Ma & Sanghyun Hong & W. Robert Reed & Jianhua Duan & Phong Luu, 2023. "Yield effects of agricultural cooperative membership in developing countries: A meta‐analysis," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 94(3), pages 761-780, 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. Awal Abdul‐Rahaman & Gazali Issahaku & Wanglin Ma, 2023. "Agrifood system participation and production efficiency among smallholder vegetable farmers in Northern Ghana," Agribusiness, John Wiley & Sons, Ltd., vol. 39(3), pages 812-835, July.
    2. Kuhle Prudence Mnisi & Abdul Latif Alhassan, 2021. "Financial structure and cooperative efficiency: A pecking‐order evidence from sugarcane farmers in Eswatini," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 92(2), pages 261-281, June.
    3. Ma, Wanglin & Renwick, Alan & Yuan, Peng & Ratna, Nazmun, 2018. "Agricultural cooperative membership and technical efficiency of apple farmers in China: An analysis accounting for selectivity bias," Food Policy, Elsevier, vol. 81(C), pages 122-132.
    4. Abdul-Rahaman, Awal & Issahaku, Gazali & Zereyesus, Yacob A., 2021. "Improved rice variety adoption and farm production efficiency: Accounting for unobservable selection bias and technology gaps among smallholder farmers in Ghana," Technology in Society, Elsevier, vol. 64(C).
    5. Boris E. Bravo‐Ureta & Mario González‐Flores & William Greene & Daniel Solís, 2021. "Technology and Technical Efficiency Change: Evidence from a Difference in Differences Selectivity Corrected Stochastic Production Frontier Model," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(1), pages 362-385, January.
    6. Zheng, Hongyun & Ma, Wanglin & Wang, Fang & Li, Gucheng, 2021. "Does internet use improve technical efficiency of banana production in China? Evidence from a selectivity-corrected analysis," Food Policy, Elsevier, vol. 102(C).
    7. Bravo-Ureta, Boris E. & Higgins, Daniel & Arslan, Aslihan, 2020. "Irrigation infrastructure and farm productivity in the Philippines: A stochastic Meta-Frontier analysis," World Development, Elsevier, vol. 135(C).
    8. Junying Lin & Songqing Jin & Hongdong Guo, 2023. "Do outsourcing services provided by agricultural cooperatives affect technical efficiency? Insights from tobacco farmers in China," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 94(3), pages 781-804, September.
    9. Carrer, Marcelo José & Filho, Hildo Meirelles de Souza & Vinholis, Marcela de Mello Brandão & Mozambani, Carlos Ivan, 2022. "Precision agriculture adoption and technical efficiency: An analysis of sugarcane farms in Brazil," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    10. Yun Shen & Jinmin Wang & Luyao Wang & Bin Wu & Xuelan Ye & Yang Han & Rui Wang & Abbas Ali Chandio, 2022. "How Do Cooperatives Alleviate Poverty of Farmers? Evidence from Rural China," Land, MDPI, vol. 11(10), pages 1-23, October.
    11. Lin, Bin & Wang, Xiaoxi & Jin, Songqing & Yang, Wanjiang & Li, Houjian, 2022. "Impacts of cooperative membership on rice productivity: Evidence from China," World Development, Elsevier, vol. 150(C).
    12. Ayobami Adetoyinbo & Verena Otter, 2022. "Can producer groups improve technical efficiency among artisanal shrimpers in Nigeria? A study accounting for observed and unobserved selectivity," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-33, December.
    13. Lei Wu & Chuanjian Li & Yang Gao, 2022. "Regional agricultural cooperatives and subjective wellbeing of rural households in China," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S2), pages 138-158, November.
    14. Wanglin Ma & Sanghyun Hong & W. Robert Reed & Jianhua Duan & Phong Luu, 2023. "Yield effects of agricultural cooperative membership in developing countries: A meta‐analysis," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 94(3), pages 761-780, September.
    15. Kamiche Zegarra, J. & Bravo-Ureta, B., 2018. "Are users of market information efficient? A stochastic production frontier model corrected by sample selection," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275870, International Association of Agricultural Economists.
    16. 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.
    17. Mamiit, Rusyan Jill & Yanagida, John & Villanueva, Donald, 2020. "Farm locations and dwelling clusters: Do they make production and technical efficiency spatially contagious?," Food Policy, Elsevier, vol. 92(C).
    18. Meiyuan Wang & Bin He & Jinsong Zhang & Yanan Jin, 2021. "Analysis of the Effect of Cooperatives on Increasing Farmers’ Income from the Perspective of Industry Prosperity Based on the PSM Empirical Study in Shennongjia Region," Sustainability, MDPI, vol. 13(23), pages 1-18, November.
    19. Bravo-Ureta, Boris E. & Njuki, Eric & Palacios, Ana Claudia & Salazar, Lina, 2022. "Agricultural Productivity in El Salvador: A Preliminary Analysis," IDB Publications (Working Papers) 11984, Inter-American Development Bank.
    20. Huma Neupane & Krishna P. Paudel & Mandeep Adhikari & Qinying He, 2022. "Impact of cooperative membership on production efficiency of smallholder goat farmers in Nepal," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 93(2), pages 337-356, June.

    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:12:y:2020:i:19:p:8194-:d:423810. 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.