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Improved Post-Harvest Technology: What Impact on Nigeria s Smallholder Cassava Starch Processors Welfare?


  • Adejumo, O.
  • Okoruwa, V.
  • Abass, A.


This study examined the adoption of improved post-harvest technology for cassava processing and its impacts on welfare of Smallholder cassava starch processors. The study relied mainly on cross-sectional data collected through a survey conducted in the forest and guinea savanna zones of Nigeria. A multi-stage sampling procedure was used in selecting a sample frame of five hundred and seventy (570) cassava starch processors. Data were analysed using descriptive statistics, logit model and the propensity score matching method. Smallholder cassava starch processing in Nigeria is mostly a female enterprise. The average age of the processors was 48 years, with an average household size of six. The decision to use improved technology is explained by number of income earners in the household, years of processing experience, cost of acquiring technology and the capacity of technology. This study found a positive and significant impact of improved post-harvest technology on output and income of smallholder cassava starch processors. Therefore, designing mechanisms to help promote use of improved technology among small-scale processors by developing affordable technologies appears to be a rational policy instrument to improve cassava starch processors welfare. Key words: cassava processing, improved technologies, output, income, Nigeria JEL: C21, D13, O33, Q12 Acknowledgement : Acknowledgments The study is an output of the Cassava Web Project funded by the German Federal Ministry for Education and Research (BMBF) and the Deutsche Gesellschaft f r Internationale Zusammenarbeit (GIZ) GmbH. The Research Fellowship offered by the International Institute of Tropical Agriculture, Ibadan, Nigeria to the first author is gratefully acknowledged. The research is supported by CGIAR Program on Humidtropics and the Roots, Tubers and Bananas (RTB).

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  • Adejumo, O. & Okoruwa, V. & Abass, A., 2018. "Improved Post-Harvest Technology: What Impact on Nigeria s Smallholder Cassava Starch Processors Welfare?," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277054, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae18:277054
    DOI: 10.22004/ag.econ.277054

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    References listed on IDEAS

    1. Karanja, D. D. & Renkow, M. & Crawford, E. W., 2003. "Welfare effects of maize technologies in marginal and high potential regions of Kenya," Agricultural Economics, Blackwell, vol. 29(3), pages 331-341, December.
    2. Akhter Ali & Awudu Abdulai, 2010. "The Adoption of Genetically Modified Cotton and Poverty Reduction in Pakistan," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(1), pages 175-192, February.
    3. Owusu, Victor & Abdulai, Awudu & Abdul-Rahman, Seini, 2011. "Non-farm work and food security among farm households in Northern Ghana," Food Policy, Elsevier, vol. 36(2), pages 108-118, April.
    4. Loi, Massimo & Rodrigues, Margarida, 2012. "A note on the impact evaluation of public policies: the counterfactual analysis," MPRA Paper 42444, University Library of Munich, Germany.
    5. Verkaart, Simone & Munyua, Bernard G. & Mausch, Kai & Michler, Jeffrey D., 2017. "Welfare impacts of improved chickpea adoption: A pathway for rural development in Ethiopia?," Food Policy, Elsevier, vol. 66(C), pages 50-61.
    6. Carolyn Afolami & Abiodun Obayelu & Ignatius Vaughan, 2015. "Welfare impact of adoption of improved cassava varieties by rural households in South Western Nigeria," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 3(1), pages 1-17, December.
    7. Abdul Nafeo Abdulai, 2016. "Impact of conservation agriculture technology on household welfare in Zambia," Agricultural Economics, International Association of Agricultural Economists, vol. 47(6), pages 729-741, November.
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    Productivity Analysis;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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