Measuring Household Resilience to Food Insecurity: Application to Palestinian Households

Most of the current literature on food security focuses on assessing household vulnerability in food-insecure regions. However, although the concept of vulnerability is dynamic and forward-looking, almost all statistical methodologies applied until now have been static and unable to predict future events. The main reasons for this are conceptual – for example, arising from the complexity (multidimensionality) of the concept of food security and the unpredictability of the many shocks that cause food insecurity – and empirical, such as the absence of longitudinal data over sufficiently long periods to identify the various sources of risk and thereby allow the analysis of trends and risks. The concept of resilience has recently been introduced into food security literature. It aims to measure households’ capability to absorb the negative effects of unpredictable shocks, as a legitimate component of vulnerability analysis. The definition of resilience to food insecurity has a direct effect on the methodology used to measure it, and the model described in this document, considers resilience to be a latent variable defined according to four building blocks: income and food access; assets; access to public services; and social safety nets. Two additional dimensions – stability and adaptive capacity – cut across these building blocks and account for households’ capacity to respond and adapt to shocks; these too are latent variables. To measure the whole system, two approaches can be pursued. The first measures each dimension separately using different multivariate techniques (factor analysis, principal components analysis and optimal scaling) before estimating the resilience index; the classification and regression tree (CART) methodology has also been used for the understanding of the process. The second approach measures all the dimensions simultaneously through structural equation models, and is based on normality assumptions on observed variables. As most of the variables in resilience measurement are ordinal or categorical, the first approach was adopted in this document. The role of the estimated resilience index in measuring vulnerability to food insecurity was then assessed through a regression model with food consumption in logarithmic scale as a dependent variable and the resilience index and other household characteristics as independent variables. The document also discusses the policy implications of resilience, using the results of testing the methodology in the Palestinian context.