As the impact of climate change increases it is more likely that we will see an increase of extreme weather events leading to significant food production losses. Therefore, understanding the complexities of how production losses impact on policy (through export or import restrictions) and prices (through markets) is important for the governance of the global food system in the future. In this paper our aim is to understand the variability of food prices utilizing a statistical methodology relating to the detection of extreme values and change points in the decomposed time series of food price indices (change-point analysis). These change points are identified using the FAO total food price index and also the indices for meat, oil, cereal, dairy and sugar. The results of the study highlight for the first time specific change points within these food categories when these changes occur and also the duration of these periods before the next change.
Bibliographical noteCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding: Science and Technology Facilities Council through the STFC Food Security Network+ (STFC grant no: ST/P003079/1).