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Farmers’ adoption of multiple climate-smart agricultural technologies in Ghana: determinants and impacts on maize yields and net farm income

Author

Listed:
  • Bright O. Asante

    (Kwame Nkrumah University of Science and Technology)

  • Wanglin Ma

    (Lincoln University)

  • Stephen Prah

    (Kwame Nkrumah University of Science and Technology)

  • Omphile Temoso

    (University of New England)

Abstract

This study investigates the factors affecting maize farmers’ decisions to adopt climate-smart agricultural (CSA) technologies and estimates the impacts of CSA technology adoption on maize yields and net farm income. Unlike most previous studies that analyze a single technology, we consider different combinations of three CSA technologies (zero tillage, row planting, and drought-resistant seed). A multinomial endogenous switching regression model addresses selection bias issues arising from observed and unobserved factors and analyses data collected from 3197 smallholder farmers in three Ghana regions (Brong-Ahafo, Northern, and Ashanti). The findings show that smallholder farmers’ decisions to adopt multiple CSA technologies are influenced by farmer-based organization membership, education, resource constraints such as lack of land, access to markets, and production shocks such as perceived pest and disease stress and drought. We also find that adopting all three CSA technologies together has the largest impact on maize yields, while adopting row planting and zero tillage as a combination has the largest impact on net farm income. Governments should collaborate with farmer-based groups and extension officers to improve farmers’ awareness and understanding of the benefits associated with CSA technologies and help them adopt multiple technologies that generate higher benefits.

Suggested Citation

  • Bright O. Asante & Wanglin Ma & Stephen Prah & Omphile Temoso, 2024. "Farmers’ adoption of multiple climate-smart agricultural technologies in Ghana: determinants and impacts on maize yields and net farm income," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 29(2), pages 1-23, February.
  • Handle: RePEc:spr:masfgc:v:29:y:2024:i:2:d:10.1007_s11027-024-10114-8
    DOI: 10.1007/s11027-024-10114-8
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    Keywords

    Climate-smart agriculture; Maize yields; Net farm income; MESR model; Ghana;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • P36 - Political Economy and Comparative Economic Systems - - Socialist Institutions and Their Transitions - - - Consumer Economics; Health; Education and Training; Welfare, Income, Wealth, and Poverty
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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