This project has one aim: to integrate multidisciplinary knowledge about economic inequality and urban segregation to better understand and counter the dynamics of economic segregation in cities, by modelling the main drivers of urban economic segregation and comparing remediatory policies at various geographical scales. I devised three research objectives to address this aim:
1. To uncover the theoretical interactions between the processes generating urban economic segregation at various scales, and particularly the impact of economic inequality on economic segregation.
So far, I reviewed a multidisciplinary and multilingual literature on the relationship between economic inequality and economic segregation. This literature is not well integrated because it spans two very large fields which follow distinct research traditions. Consequently, causal pathways which link economic inequality and economic segregation are not well understood, yet addressing this literature means considering thousands of references, which is unfeasible for most researchers with limited resources. After identifying, screening, reading and analysing the findings of hundreds of (overlooked) research articles, I wrote a new state of the art of our current knowledge base on the causal pathways and theoretical mechanisms involved in the relationship between economic inequality and economic segregation. I did so using state-of-the-art methods of systematic literature reviews and developing them in the process (Cottineau-Mugadza, 2024). In conclusion, I show that variations in economic segregation tend to follow differences in economic inequality in the short term while the reverse causality is more probable in the longer term (i.e. from segregation to inequality). The housing market is the most cited mediator between economic inequality and economic segregation, yet a diversity of theories and mechanisms are mobilized to explain their empirical connections.
2. to “describe” and "animate" this combination of explanatory processes of urban economic segregation using analytical and agent-based models.
So far, we were able to produce detailed indicators of income inequality and segregation (disaggregated by income percentile to analyse the segregation of affluence and poverty), on an annual basis, for all Dutch urban areas – i.e. beyond the situation of well-known capital cities and largely populated cities, after successfully linking datasets describing the entire population residing in the Netherlands in terms of income, wealth, residential location and household composition between 2011 and 2021 (San Millán et al., 2025). We show that inequality and segregation remained stable or decreased in most cities – although large variations exist between cities – and that unequal cities tend to also be more segregated, but patterns vary and the same segregation levels can coexist with diverse inequality metrics.
3. To use these integrated models of urban economic segregation to develop, compare and assess policy scenarios of segregation reduction ex ante.
Work is underway to review relevant policies to reduce urban economic segregation, find empirical cases in the Netherlands where their effectiveness could be measured and evaluated, and design policy scenarios to be used in the ABM, based on this empirical knowledge base. Initial requirements for geospatial population synthesis to initialise agent-based models were outlined in Roxburgh et al. (2025).
