An Inclusive Economy classification for local authorities in Great Britain

Keywords: Inclusion, inclusivity, inclusive economy, synthetic populations, synthetic datasets, physical health, mental health
Abstract Type: Virtual Paper Abstract

Abstract

In this paper we assess the spatial distribution of variables which measure how inclusive the economy of Great Britain is. In collaboration with policy experts and community panels we identify 13 indicators of inclusivity which encapsulate access to services and jobs, inclusion in decision making, access to affordable housing and differences in earnings and wealth which all vary spatially and temporally. Using clustering techniques we create two area-based classifications from these indicators, one at local authority level and one at neighbourhood level (proxied using the statistical geography of Wards). The data inputs to the higher-level local authority classification are primarily open source, so the classification is reproducible and easily updated. The more spatially detailed neighbourhood classification is built from a proprietary synthetic dataset, constructed by combining census and survey data. We compare our clusters to understand how (un)equal the distribution of inclusivity is across Great Britain. Our inclusive economy indicators are designed for inclusion in models of relationships between policies for economic inclusion and health outcomes and we assess healthy life expectancy and lifespan variation for each of our clusters. Early results reveal a correlation between inclusivity and healthy life expectancy. The results will help policy makers by demonstrating where specific need exists across the inclusive economy domains and so aid in the better targeting of resources. This work is part of the Systems Science in Public Health and Health Economics Research (SIPHER) programme, developing research to prevent physical and mental ill health, and tackle persistent health inequalities.