Shocks and rural food insecurity: Insights from high frequency data during the COVID-19 pandemic in Malawi

Abstract

It is widely recognized that national or global shocks can affect household food security in rural areas of low-income countries. However, there is still limited rigorous micro-level evidence regarding how such impacts manifest and are distributed. A primary reason for this gap is data limitations; many studies are unable to adequately control for the seasonal and inter-annual variations in production and consumption that can bias identification of the effects of large, covariate shocks. We use three years of monthly household panel data to characterize the food security effects of COVID-19 in Southern Malawi. These high frequency data begin two years before the pandemic, allowing us to control for seasonality and inter-annual variation in growing conditions and to demonstrate how these confounding factors can lead to spurious estimates. We find that a strong 2020 harvest coincided with the COVID-19 shock and buffered households on average from food insecurity. We show, however, that the strong harvest on average was insufficient to protect the poorest households: the majority (74 %) of the most food insecure households pre-pandemic were worse-off in 2020 than they would have been otherwise. We use qualitative methods to explore underlying mechanisms: the pandemic led better-off households to reduce their demand for local labor, resulting in declining earning opportunities for the poorest households. Our findings demonstrate the importance of controlling for concurrent dynamics to generate more accurate estimates about how large covariate shocks are associated with household food security, particularly among the most vulnerable rural households.