cwreed/africa-flooding-food-security

Time series analysis of the impacts of flooding on food security over sub-Saharan Africa. # Flooding and food security in Sub-Saharan Africa This repository contains the source code for our analysis of where and to what extent flooding impacts food security in Sub-Saharan Africa. We make use of econometric time series analysis techniques—including panel Granger causality and static panel regression—to quantify the effects of floods on the integrated food security phase classification (IPC) metric at the place of their occurrence up to roughly one year after their onset. ## Data and feature engineering The data used in this analysis include: - IPC over sub-Saharan Africa at a seasonal timestep from 2009–2020 produced by FEWS NET available here - Flood data from shapefiles produced by the Dartmouth Flood Observatory as part of the *Global Active Archive of Large Flood Events, 1985–Present* available here - Population data as of 2020 produced by WorldPop available here All of the data was harmonized to a spatial scale at the intersection of administrative level 2 units and FEWS NET Livelihood Zones (a 'panel') and a time scale corresponding to the reporting period of the IPC data. Furthermore, all time series were first-differenced to enforce stationarity. Code is available in `scripts/`. Reed, C. et al. The impact of flooding on food security across Sub-Saharan Africa. (In review). --> ## Summary of results ### Where does flooding affect food security? We used panel Granger causality analysis as a way to identify where there exists a significant Granger-causal relationship between any of the derived flood variables (occurrences, area as proportion of panel area, and duration) and the IPC using a lag of up to four seasons. The code for this analysis is available in `analysis/modeling/granger-causality.R`. A global test for homogeneous non-causality (i.e., a global null hypothesis of field significance) which accounts for the cross-sectional dependence of the data was conducted in Stata. The figure below highlights the panels for which the indicated …