The making of a non-parametric multi-shock index (MSI)

Households in low- and middle-income countries increasingly face overlapping economic, climatic, health, and conflict-related shocks that jointly erode welfare and food security. Yet many empirical and operational tools still measure shocks one at a time or aggregate them using ad hoc rules that assume equal severity and linear effects. This paper proposes a non-parametric multi-shock index (MSI) that summarizes household exposure to multiple shocks using an assumption-light, data-driven approach. The MSI construction proceeds in two steps: (i) shocks are empirically filtered based on their observed negative association with food security outcomes (anchored to the Food Consumption Score), and (ii) retained shocks are aggregated using alternative weighting schemes, including unweighted, population-weighted, and prevalence-weighted variants. We validate the MSI using multiple food security measures—Food Consumption Score (FCS), Reduced Coping Strategy Index (rCSI), Food Insecurity Experience Scale (FIES), and Household Dietary Diversity Score (HDDS). An application using FAO’s Data in Emergencies (DIEM) household survey for Nigeria illustrates the approach and shows that cumulative exposure—especially systemic and compound exposure—is strongly associated with deteriorating food security outcomes. Among tested variants, the prevalence-weighted MSI provides the clearest discriminatory power and distributional sensitivity, supporting its use for targeting, monitoring, and shock-responsive programming (FAO, 2016; Maxwell et al., 2014; World Bank, 2018).