IDEAS home Printed from https://ideas.repec.org/a/ags/afjrde/280068.html
   My bibliography  Save this article

Effects of social capital on technical efficiency of cassava production in Oyo State, Nigeria

Author

Listed:
  • OLUROTIMI, P. O.
  • BAMIRE, A. S.
  • OGUNLEYE, A. S.

Abstract

This paper evaluates the effects of social capital available in Innovation Platforms on the technical efficiency of cassava production in Humidtropics field sites in Oyo State, Nigeria. Multistage sampling procedure was used to select 100 respondents, comprising of 41 platform members and 59 non-members in the sites. Data were collected with the aid of pre-tested structured questionnaire on socio-economic characteristics, farm size, forms of social capital network as well as quantities of inputs and outputs. Data were analysed using descriptive statistics, stochastic frontier function and Tobit regression model. The results of the study revealed that the technical efficiency of the farmers are high and membership in the Innovation platform increased the technical efficiency of cassava production. It was recommended that policies should be directed towards the creation of social capital networks through the establishment of Innovation platforms in order to increase the technical efficiency to boost cassava production for food security and better livelihood.

Suggested Citation

  • Olurotimi, P. O. & Bamire, A. S. & Ogunleye, A. S., 2018. "Effects of social capital on technical efficiency of cassava production in Oyo State, Nigeria," African Journal of Rural Development (AFJRD), AFrican Journal of Rural Development (AFJRD), vol. 3(1), March.
    • Handle: RePEc:ags:afjrde:280068
    DOI: 10.22004/ag.econ.280068
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/280068/files/8.%20Peter%20O.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.280068?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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. Tamon Baba & Hisako Nomura & Pao Srean & Tha Than & Kasumi Ito, 2022. "Effects of Mechanization and Investments on the Technical Efficiency of Cassava Farms in Cambodia," Agriculture, MDPI, vol. 12(4), pages 1-13, March.
    2. Nguyen-Anh, Tuan & Hoang-Duc, Chinh & Tiet, Tuyen & Nguyen-Van, Phu & To-The, Nguyen, 2022. "Composite effects of human, natural and social capitals on sustainable food-crop farming in Sub-Saharan Africa," Food Policy, Elsevier, vol. 113(C).

    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. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    2. Hasan, Iftekhar & Lozano-Vivas, Ana, 2002. "Organizational Form and Expense Preference: Spanish Experience," Bulletin of Economic Research, Wiley Blackwell, vol. 54(2), pages 135-150, April.
    3. 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.
    4. Richard A. Hofler & John A. List, 2004. "Valuation on the Frontier: Calibrating Actual and Hypothetical Statements of Value," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(1), pages 213-221.
    5. 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.
    6. Daniel Solís & Boris E. Bravo‐Ureta & Ricardo E. Quiroga, 2009. "Technical Efficiency among Peasant Farmers Participating in Natural Resource Management Programmes in Central America," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(1), pages 202-219, February.
    7. Subhash C. Ray, 2004. "A Simple Statistical Test of Violation of the Weak Axiom of Cost Minimization," Indian Economic Review, Department of Economics, Delhi School of Economics, vol. 39(1), pages 111-121, January.
    8. 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.
    9. Jan Kluge & Sarah Lappöhn & Kerstin Plank, 2023. "Predictors of TFP growth in European countries," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 50(1), pages 109-140, February.
    10. 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.
    11. 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.
    12. Kwan, Simon H., 2006. "The X-efficiency of commercial banks in Hong Kong," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1127-1147, April.
    13. repec:lan:wpaper:4471 is not listed on IDEAS
    14. Barros, Carlos Pestana & Williams, Jonathan, 2013. "The random parameters stochastic frontier cost function and the effectiveness of public policy: Evidence from bank restructuring in Mexico," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 98-108.
    15. 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.
    16. Wu, Yanrui, 1995. "The productive efficiency of Chinese iron and steel firms A stochastic frontier analysis," Resources Policy, Elsevier, vol. 21(3), pages 215-222, September.
    17. Valeriy Makarov & Albert Bakhtizin, 2014. "The Estimation Of The Regions’ Efficiency Of The Russian Federation Including The Intellectual Capital, The Characteristics Of Readiness For Innovation, Level Of Well-Being, And Quality Of Life," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(4), pages 9-30.
    18. Kui-Wai Li & Tung Liu & Lihong Yun, 2007. "Technology Progress, Efficiency, and Scale of Economy in Post-reform China," Working Papers 200701, Ball State University, Department of Economics, revised Apr 2007.
    19. 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.
    20. Rossi, Martín, 2000. "Análisis de eficiencia aplicado a la regulación ¿Es importante la Distribución Elegida para el Término de Ineficiencia?," UADE Textos de Discusión 22_2000, Instituto de Economía, Universidad Argentina de la Empresa.
    21. Markose Chekol Zewdie & Michele Moretti & Daregot Berihun Tenessa & Zemen Ayalew Ayele & Jan Nyssen & Enyew Adgo Tsegaye & Amare Sewnet Minale & Steven Van Passel, 2021. "Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach," Land, MDPI, vol. 10(3), pages 1-17, March.

    More about this item

    Keywords

    Marketing;

    Statistics

    Access and download statistics

    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:ags:afjrde:280068. 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: AgEcon Search (email available below). General contact details of provider: http://afjrd.org/jos/index.php/afjrd/index .

    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.