Measuring urban inequality in income and working conditions for left-behind groups

Rising economic inequality poses a significant urban challenge. Research indicates that current deficiencies in defining urban economic inequality hinder monitoring and policy formulation. We propose that the emphasis on decent work and inclusive growth outlined in the Sustainable Development Goals (SDGs), particularly SDG 8 and 10, could aid in refining this definition. By integrating insights from urban inequality research in regional science with space-neutral inequality domains from SDG literature, we present a novel characterisation of urban inequality encompassing income and working conditions. Our approach emphasises the inclusion of populations not captured by official registries, multidimensionality, and within-city metrics, which we operationalise in a monitoring framework. We validate our framework through mixed-method analysis, employing the city of Bologna, Italy, as a case study and engaging local stakeholders to interpret the findings. Our metrics reveal spatial patterns of inequality overlooked by conventional approaches. Multidimensional measures, integrating employment with underemployment and income with demographic factors, unveil nuanced inequality dynamics both between and within urban areas. Similarly, metrics incorporating homeless individuals and irregular migrants in the target population illuminate previously obscured dimensions of inequality. Finally, we underscore the utility of data generated by municipalities and other local stakeholders, which remain underutilised in urban inequality research.