Resilience Measurement: A Moment-Based Approach to Resilience Identification and Aggregation

The international community has recently been focused on the importance of building resilience to avoid repeated humanitarian disasters and improve the sustainability of development outcomes. Despite this consensus, there is little agreement on how best to measure resilience at the microeconomic level. The goal of this paper is to develop an empirical strategy for estimating individual or household level resilience based on theoretical work by Barrett & Constas. The moments-based approach allows us to estimate stochastic and possibly nonlinear well-being dynamics, with obvious benefits over linear models in contexts where poverty traps may be found. We then develop a decomposable resilience measure based on the Foster, Greer, & Thorbecke class of poverty measures, giving us the ability to compare the resilience of various sub-populations of interest. We finish with an empirical example of resilience measurement using household panel data from Northern Kenya where we find there are strong path dynamics in resilience, both in terms of dietary diversity and livestock holdings. Resilience is negatively impacted by drought and also strongly correlated with several household-level characteristics