Impact of Agricultural Credit on the Employability of Rice Farmers in a Context of Ecological Change: A Causal Analysis in the Logone Valley, Chad
Asian Journal of Agricultural Extension, Economics & Sociology · pp. 1–15 · Published 10 Apr 2026
10.9734/ajaees/2026/v44i52926Abstract
Aims: In a context of demographic pressure and ecological change in sub-Saharan Africa, agricultural credit is promoted as a key lever for rural employment. This study assesses its causal impact on the employability of rice farmers in the Logone Valley in Chad. Study Design: A mixed methodology combining a survey of 96 rice farmers with qualitative interviews. Place and Duration of Study: Logone Valley, Chad; data collected in November 2025. Methodology: Econometric models (Negative Binomial regression, OLS with interaction terms, Instrumental Variable (2SLS), and Propensity Score Matching) were employed to control for endogeneity bias linked to selective access to credit. Results: The results reveal that credit preferentially targets farmers already endowed with land, social capital (cooperative) and human capital (training). Nevertheless, its causal effect is positive: it multiplies the creation of seasonal employment by 2.32 (IRR = 2.321, p = 0.003) and increases incomes (elasticity of 0.176, p < 0.001). However, this impact is doubly conditioned. It is amplified by access to training (interaction effect: +0.341, p = 0.047) and membership in a cooperative (interaction effect: +0.412, p = 0.008), but is severely attenuated by climatic shocks, which reduce incomes by 41.2% (β = -0.412, p = 0.003). Economic diversification is favored (OR = 3.459, p = 0.009), but the jobs created remain precarious. Conclusion: Agricultural credit is an effective but imperfect and vulnerable lever. Its potential is conditioned by complementary services and cancelled out by uncovered climatic risks. A transformation of financial policies is required, integrating climate insurance, technical support and a systemic "service package" approach for inclusive and resilient rural transformation.
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