Quantifying the impact of weather extremes on global food security: A spatial bio-economic approach

Abstract

This study uses a spatial bio-economic modelling framework to estimate the impact of the 2012 weather extreme in the USA on food security in the developing world. The study also quantifies the potential effects of a similar weather extreme occurring in 2050 under climate change. The study results indicate that weather extremes that affect maize productivity in key grain baskets can negatively affect food security in vulnerable countries. The 2012 weather extreme which occurred in the USA reduced US and global maize production by 29% compared to trend; maize consumption in the country decreased by 5% only and this resulted in less surplus maize for exports from the largest maize exporter in the world. Global maize production decreased by 6% compared to trend. The decrease in global maize production coupled with a reduction in the volume of global maize exports worsened food insecurity in eastern Africa, the Caribbean and Central America and India. The effects of the weather extreme on global food security would be worse, if the latter were to occur under climate change in 2050, assuming no climate change adaptation worldwide over the years. In addition, the hardest-hit regions would remain the same, whether the weather extreme occurs in 2012 instead of 2050: Sub-Saharan Africa (SSA), South Asia and the Latin America and Caribbean (LAC) region. However, sustained growth in per capita income across world economies between 2000 and 2050 would allow few countries in SSA and the LAC region to virtually eliminate hunger within their borders. In these countries, per capita income would be high enough by 2050 to completely offset the negative effect of the weather extreme. The study results are also consistent with USDA׳s estimates on US and global maize production and consumption in 2012 after the weather extreme. Some discrepancy is found on the volume of global maize trade; this implies that the bio-economic model likely overestimates the effect of the weather extreme on food insecurity. However, the trends from the analysis are likely to be valid. Further research would involve using a CGE model that can capture the net effects of weather extremes.