Leveraging optimal portfolio of Drought-Tolerant Maize Varieties for weather index insurance and food security

We investigate the impact of optimizing a portfolio of Drought-Tolerant Maize Varieties (DTMVs) to manage weather risk and its implications on the development of sustainable micro-insurance markets. We use high-resolution climate data and on-farm trial data, involving 20 DTMVs, over 49 locations spanning eight countries in Africa and 5 mega-environments. Markov chain and multivariate spatial Bayes models are employed to generate multivariate space-time rainfall and maize yield distributions, and derive optimal semi-variance portfolio of DTMVs. We find that optimal portfolios significantly outperformed naive portfolios, overall, reducing insurance premium rates by 31–55%.