Evaluation of the Effects of Introducing Risk Management Tools in Agricultural Development: The Case of PADAER Senegal

This study aims to assess the effects of risk management tools on the agricultural performance of rural producers benefiting from the joint support of the Senegalese state and the International Fund for Agricultural Development (IFAD) through the co-financed project PADAER. Data collection covers two regions in Senegal: Kolda and Tambacounda. The sample comprises 1167 farmers, including 379 beneficiaries of the index-based insurance facilitated by PADAER (Programme d'Appui au Developpement Agricole et a l'Entreprenariat Rural). The quasi-experimental method known as the propensity score matching method was used to determine the impact of subscribing to index-based insurance on the farmer's production, agricultural investments, and annual income. Although the results of the estimates show that the project has not yet had any effect on production, without the intervention of this project, farmers would have recorded a loss of about USD 115 (FCFA 57,600). Not only did the index-based insurance for the harvest facilitated by the PADAER allow the beneficiary to cover this loss and realize a gain estimated at USD 25 (FCFA 12,749), but the added value of this paper is that it measures the effects of agricultural index-based insurance in Africa using real-world statistical data.

Automated summary

This study evaluates the impact of risk management tools on the agricultural performance of rural producers in Senegal, who benefit from the joint support of the Senegalese state and the International Fund for Agricultural Development (IFAD) through the co-financed project PADAER. Using data from two regions in Senegal, the study found that subscribing to index-based insurance facilitated by PADAER had a positive effect on the farmers' income by covering potential losses and generating additional gains. This study contributes to the understanding of the effects of agricultural index-based insurance in Africa using real-world statistical data.