Abstract

‘Destitution’ has re-entered the lexicon of UK social policy in the 2010s, highlighted by the rapid growth of food banks and rough sleeping in a context of controversial welfare reforms and austerity policies, yet theoretical literature on this remains limited. Specialist surveys have been developed to measure and profile these phenomena, but these remain separate from the mainstream statistical approach to poverty, which relies heavily on large-scale household surveys. Evidence from recent work in this area, including qualitative evidence, is very suggestive of risk and driving factors, but it is difficult to weigh the relative importance of different factors or to predict the effects of policy measures. A composite survey approach is developed, linking a specialised survey targeting households at risk of destitution with a major national household panel dataset, to enable predictive models to be fitted to data including significant representation of hard-to-reach and non-household populations. Models predicting destitution and food bank usage are developed and compared, highlighting the roles of key factors. Vignettes are used to show how the risks vary dramatically between households in different situations. The potential role of such models in micro-simulation or prediction of impacts of different scenarios is discussed.

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