Beyond the social and economic: Spatial regression analysis of built environment effects on multidimensional poverty in Kenya

The Sustainable Development Goal (SDG) to end poverty is a global challenge, especially in urban areas. There is a gap in understanding how the built environment affects urban poverty. Although studies view poverty through economic and social lenses, few examine the role of the built environment in multidimensional poverty analysis. Understanding spatial associations and spillover effects between the built environment and poverty is incomplete, with many studies not considering spatial dependence, leading to biased results. We used spatial econometric analysis and Bayesian Model Comparison to explore local and global spillover effects. We quantified poverty using a multidimensional poverty index (MPI) and evaluated the built environment using spatial opportunity and accessibility indicators. We used data from a geocoded household survey of Kenyan urban areas. The results suggest that incorporating built environment indicators in the MPI increases the magnitude and incidence of poverty. We find significant spatial dependence and identify local rather than global spillover effects, leading to the specification of a Spatial Durbin Error Model (SDEM). Deprivation of road infrastructure and transport services had significant direct and spillover effects associated with higher household multidimensional poverty. These findings highlight an urban planning perspective in poverty analysis which uncovers hidden deprivation. The results suggest the need for urban policy interventions that adopt a multidimensional approach to poverty alleviation incorporating the built environment. An integrated approach blending public transport and road improvements, park provision, street lighting, with traditional social protection and employment creation plans at the local neighbourhood level is suggested. • Inclusion of built environment dimensions and indicators increases the magnitude and incidence of multidimensional poverty • Spatial dependence was observed in the association between multidimensional poverty and the built environment • Accessibility - road surface and transport- has significant direct and spillover effects on multidimensional poverty • Poverty measurement and analysis can be improved by including built environment dimensions • Poverty interventions can be strengthened by addressing built environment deprivation in roads and transport services