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Targeting rural development interventions: Empirical agent-based modeling in Nigerien villages

Author

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  • Saqalli, M.
  • Gérard, B.
  • Bielders, C.L.
  • Defourny, P.

Abstract

The aim of this article is to analyze the impact of development interventions on the population of three Nigerien villages that differ in terms of their agro-ecological, social and economic characteristics. This is performed by simulating the behavior of individuals in an agent-based modeling framework which integrates the village characteristics as well as the family internal rules that condition access to economic and production activities. Villagers are differentiated according to the social and agro-ecological constraints they are subjected to. Two development project interventions are simulated, assuming no land scarcity: increasing the availability of inorganic fertilizers for farmers and an inventory credit technique based on millet grain. Two distinct approaches were used to model the rationale of farmers' decision making: gains or losses in economic value or gains or losses in within-village "reputation". Our results show that village populations do not respond en masse to development interventions. Reputation has little effect on the population behavior and should be considered more as a local proxy for wealth amongst villagers, suggesting the monetization of these societies. Populations involve themselves in the two simulated development interventions only at sites where savings are possible. Some level of household food security and investment capacity is actually required to take part in the development interventions, which are largely conditioned by family manpower and size. As long as uncultivated land remains available in the village territory, support for inorganic fertilizers has little impact in the absence of any intensification process. Inventory credit engages a maximum of 25% of the population at the site with medium agro-ecological conditions. Therefore, both interventions should be viewed as a potential support tool for a limited part of the population capable of going beyond the survival level, but not as a generic poverty-alleviation panacea.

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  • Saqalli, M. & Gérard, B. & Bielders, C.L. & Defourny, P., 2011. "Targeting rural development interventions: Empirical agent-based modeling in Nigerien villages," Agricultural Systems, Elsevier, vol. 104(4), pages 354-364, April.
    • Handle: RePEc:eee:agisys:v:104:y:2011:i:4:p:354-364
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    4. Berre, D. & Diarisso, T. & Andrieu, N. & Le Page, C. & Corbeels, M., 2021. "Biomass flows in an agro-pastoral village in West-Africa: Who benefits from crop residue mulching?," Agricultural Systems, Elsevier, vol. 187(C).
    5. Tian, Qing & Holland, John H. & Brown, Daniel G., 2016. "Social and economic impacts of subsidy policies on rural development in the Poyang Lake Region, China: Insights from an agent-based model," Agricultural Systems, Elsevier, vol. 148(C), pages 12-27.
    6. Oleg V. Zakharchenko, 2020. "Improving the socio-economic well-being of the population in rural areas in the context of improving the economic security of the state," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(2), pages 512-532, December.
    7. Zheng, Chaohui & Liu, Yi & Bluemling, Bettina & Chen, Jining & Mol, Arthur P.J., 2013. "Modeling the environmental behavior and performance of livestock farmers in China: An ABM approach," Agricultural Systems, Elsevier, vol. 122(C), pages 60-72.
    8. Roberto Calisti & Primo Proietti & Andrea Marchini, 2019. "Promoting Sustainable Food Consumption: An Agent-Based Model About Outcomes of Small Shop Openings," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 22(1), pages 1-2.

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