IDEAS home Printed from https://ideas.repec.org/a/ibn/jasjnl/v12y2024i2p106.html
   My bibliography  Save this article

Technical Efficiency of Farms, and Fight Against Poverty: Case of the Cashew Sector in Côte d’Ivoire

Author

Listed:
  • Noufou Coulibaly
  • Kone Siaka
  • Yapi Yapo Magloire
  • Toure Sally

Abstract

Cashew was introduced in the north of Côte d’Ivoire to support the economy in the region. This study was conducted to evaluate the technical efficiency of cashew farms in Côte d’Ivoire. The technical efficiency of producers was measured using the Data Envelopment Analysis approach, and the determinants of this efficiency were identified using a TOBIT model. Data were collected in 4 regions- GBEKE, HAMBOL, PORO and WORODOUGOU. In the four regions studied, the average technical efficiency is 49.2% in Variable Scale Efficiency (VRS) and 38.3% in Constant Return to Scale (CRS). Based on our results, the producers in the study area were not efficient. The producers who follow the good practices, have a technical coefficient estimated at 74.2%, and superior to those who follow the good practices, of which, the coefficient is estimated at 70.2%, in Variable Scale Efficiency (VRS). The technical efficiency of farms was positively influenced by the age of farms and agricultural advisory services, and negatively influenced by the pruning practice. Income from cashew farming in the study area (21,816 to 37,987 CFAF/person/year according to region) is below extreme poverty line (CFA F 122,385/year/person), leading to deteriorating cashew/food terms of trade. Cashew farming is often used as a means of land appropriation and of getting credit. Its rapid expansion has dramatically reduced land for subsistence agriculture, raising an accute food security issue. Cashew farming has helped improve poverty indicators through macroeconomic policy. However, this impetus from the agricultural sector economy remains insufficient to boost the modernization of the agricultural sector. The country still has all assets (research institutes, schools of agronomy, skills etc.) to reverse this situation. Hence the he study recommends that producers capitalize on exogenous variables which can improve agricultural efficiency. It also recommends coaching organizations to use technical efficiency measurement and identification of effectiveness determinants to better guide their coaching. As for the Government, it should redouble efforts to implement the recommended solutions in order to avoid producer impoverishment, a barrier to harmonious development in this region of Côte d’Ivoire.

Suggested Citation

  • Noufou Coulibaly & Kone Siaka & Yapi Yapo Magloire & Toure Sally, 2024. "Technical Efficiency of Farms, and Fight Against Poverty: Case of the Cashew Sector in Côte d’Ivoire," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 12(2), pages 106-106, April.
    • Handle: RePEc:ibn:jasjnl:v:12:y:2024:i:2:p:106
    as

    Download full text from publisher

    File URL: https://ccsenet.org/journal/index.php/jas/article/download/0/0/41788/43399
    Download Restriction: no
    File URL: https://ccsenet.org/journal/index.php/jas/article/view/0/41788
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Leibenstein, Harvey, 1978. "General X-Efficiency Theory and Economic Development," OUP Catalogue, Oxford University Press, number 9780195023800.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    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. Resti, Andrea, 1997. "Evaluating the cost-efficiency of the Italian Banking System: What can be learned from the joint application of parametric and non-parametric techniques," Journal of Banking & Finance, Elsevier, vol. 21(2), pages 221-250, February.
    2. Park, Soo-Uk & Lesourd, Jean-Baptiste, 2000. "The efficiency of conventional fuel power plants in South Korea: A comparison of parametric and non-parametric approaches," International Journal of Production Economics, Elsevier, vol. 63(1), pages 59-67, January.
    3. Simpson, N.C. & Tacheva, Zhasmina & Kao, Ta-Wei, 2023. "Semi-directedness: New network concepts for supply chain research," International Journal of Production Economics, Elsevier, vol. 256(C).
    4. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    5. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499.
    6. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    7. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    8. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    9. Ruiqing Yuan & Xiangyang Xu & Yanli Wang & Jiayi Lu & Ying Long, 2024. "Evaluating Carbon-Emission Efficiency in China’s Construction Industry: An SBM-Model Analysis of Interprovincial Building Heating," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
    10. Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & de Pinho Matos, Giordano Bruno Braz, 2015. "Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 47-60.
    11. Gilligan, Daniel O., 1998. "Farm Size, Productivity, And Economic Efficiency: Accounting For Differences In Efficiency Of Farms By Size In Honduras," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20918, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    12. Ahmad, Usman, 2011. "Financial Reforms and Banking Efficiency: Case of Pakistan," MPRA Paper 34220, University Library of Munich, Germany.
    13. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    14. Juan Aparicio & Jesus T. Pastor & Jose L. Sainz-Pardo & Fernando Vidal, 2020. "Estimating and decomposing overall inefficiency by determining the least distance to the strongly efficient frontier in data envelopment analysis," Operational Research, Springer, vol. 20(2), pages 747-770, June.
    15. Büschken, Joachim, 2009. "When does data envelopment analysis outperform a naïve efficiency measurement model?," European Journal of Operational Research, Elsevier, vol. 192(2), pages 647-657, January.
    16. António Afonso & Ana Patricia Montes & José M. Domínguez, 2024. "Measuring Tax Burden Efficiency in OECD Countries: An International Comparison," CESifo Working Paper Series 11333, CESifo.
    17. 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.
    18. Andreas Dellnitz & Andreas Kleine & Madjid Tavana, 2024. "An integrated data envelopment analysis and regression tree method for new product price estimation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(4), pages 1189-1211, December.
    19. 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.
    20. Jahangoshai Rezaee, Mustafa & Jozmaleki, Mehrdad & Valipour, Mahsa, 2018. "Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 78-93.

    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:ibn:jasjnl:v:12:y:2024:i:2:p:106. 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: Canadian Center of Science and Education (email available below). General contact details of provider: https://edirc.repec.org/data/cepflch.html .

    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.