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Farming Households Facing Food Insecurity in Cameroon: What Indicators for Resilience?

Author

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  • Julien Brice Minkande

    (University of Douala
    Research Group in Economics and Management)

Abstract

As in other Sub-Saharan African countries, food security in Cameroon is very negatively affected by environmental and socio-economic crises. While almost the entire country has very high prevalence rates of food insecurity, the central region seems relatively less affected. To this end, this study questions the indicators that can explain the resilience of this region. It uses the RIMA II approach to analyze data collected from 617 farming households. The results show that the region is moderately resilient, and that the asset pillar (AST) is the one that contributes most to this resilience. Within this pillar, access to land is the most significant indicator. To this end, it is recommended to develop policies aimed at increasing household assets (AST). However, in the spirit of Markowitzian diversification for optimizing resilience policies, emphasis should be placed on the other pillars.

Suggested Citation

  • Julien Brice Minkande, 2025. "Farming Households Facing Food Insecurity in Cameroon: What Indicators for Resilience?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 177(2), pages 809-832, March.
    • Handle: RePEc:spr:soinre:v:177:y:2025:i:2:d:10.1007_s11205-025-03534-9
    DOI: 10.1007/s11205-025-03534-9
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    More about this item

    Keywords

    Resilience; Farming households; Food security; RIMA II; Shiny RIMA; Cameroon;
    All these keywords.

    JEL classification:

    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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