This research aims at analysing the extent to which climate change affects cotton and cashew nuts production and exports in West African countries in the presence of intermediary market power. To that end, the paper uses a combination of approaches to calibrate a price endogenous regional bio-economic optimisation model and handles uncertainties inherent to future socioeconomic scenarios through Monte Carlo simulations. The results show that the effects of climate change on cotton and cashew nuts land use are mixed under the two simulated climate change scenarios. In fact, the effects vary across countries, ranging from experiencing only a decline, or only an increase to both a decline and an increase in land use. Similarly, the effects of climate change on the quantities of cotton and cashew nuts exported are also mixed, with the positive effects being more pronounced for cotton. Simulations of reductions in the market power exerted by intermediaries on cotton producers also show that such a scenario could to some extent mitigate the negative effects of climate change on cotton exports for some countries. Therefore, actions that include corrections to cotton market imperfection could be undertaken to mitigate the negative effects of climate change on cotton and cashew...

Changes in climate conditions are expected to significantly alter food production patterns and increase food price volatility, leading to challenges for food and nutrition security. Thus, this paper aims to investigate the extent to which climate factors contribute to the volatility of maize price in Benin, using monthly data from 7 markets. To this end, an autoregressive conditional heteroskedasticity in mean (ARCH-M) model is estimated. Mean and variance equations of monthly maize price are specified as functions of temperature, rainfall of the growing season and a set of control variables including a policy variable and the international price of maize with an ARCH(1) term in the variance equation. The findings from the mean equation suggest that rainfall has a negative effect on maize prices. Moreover, the estimation results from the variance equation indicate that rainfall and temperature are negatively associated with price volatility. Therefore, the findings indicate that climate change will affect maize price volatility.