Modelling the effects of rainstorm adaptation strategies on maize yield among rural farmers in Ekiti State, Nigeria

Abstract

The increased recurrence of rainstorms remains a concern for productivity and economic development, especially in developing countries. Therefore, focusing on rainstorm adaptation and its impact on agricultural productivity will play a vital role in shaping policy decisions. Based on this fact, the study models the effects of rainstorm adaptation strategies on maize yield among rural farmers in Ekiti State, Nigeria, using an endogenous switching regression model. By the cross-sectional data of 293 farmers, the model accounts for selectivity bias. The result recognised that the rainstorm event had caused economic and environmental damage. However, the farmers do make proactive efforts to adapt to rainstorms in the area. The results further revealed that age, education, income, fertilizer applications, hill region, participation in training, and climate information determine the adoption of rainstorm adaptation decision-making. Our findings show that the adoption of rainstorm adaptation increased maize yield, as an average farmer who adopted it produced nearly 57% more than farmers who did not adopt it. Again, adopters would have lost about 44% value of yield if they had decided not to adopt, whereas approximately 28% value of yield would have accrued by the non-adopters if they had adopted. Again, the number of assets owned, fertilizer application, climate belief, and participation in climate-related training are the significant factors explaining higher adopters’ yield. Therefore, the study suggests policy interventions that will promote the wide adoption of rainstorm adaptations. Also, improved weather forecasting services and better access to relevant climate information can help farmers make better decisions and plan their agricultural activities.