This PhD thesis aims to move beyond the standard treatments of neighbourhoods in research on spatially transmitted inequality. The research questions explored in the four empirical chapters of the thesis delve into under-researched elements of sociospatial inequality transmission in neighbourhoods. The thesis uses statistical models to analyse register and survey data, and relies on different operationalisations of neighbourhoods: administrative and bespoke. Chapter 2 finds that controlling for selection reduces neighbourhood effects compared to when only individual characteristics are controlled for, and provides insight into the differing patterns of neighbourhood selection and effects in Dutch regional housing markets. Chapter 3 shows that the strength of the observed relationship between neighbourhood poverty and educational attainment is dependent on how exposure is measured and conceptualized, and highlights the importance of choosing the temporal aspects of individual neighbourhood histories based on the theoretical scope of a study. Chapter 4 finds that in the Netherlands, the positive effect of neighbourhood affluence on educational attainment is stronger than the negative effect of neighbourhood
poverty. Chapter 5 addresses the discrepancy between the registered data-based measurements of neighbourhood characteristics, specifically the share of neighbours with foreign background and low income, and the individual perceptions of those characteristics by the inhabitants of the neighbourhood. The findings of the thesis confirm the validity of treating the neighbourhood as a social setting that interacts with the micro and macro contexts, rather than simply as an aggregated characteristic which can be controlled for.

This thesis has developed alternative methods of operationalising neighbourhoods at multiple spatial scales and used them to advance our understanding of spatial inequalities and neighbourhood effects. The underlying problem that motivated this thesis is that many empirical studies use predefined administrative units, and often this does not align with the underlying theory or geography. Despite the extensive literature on neighbourhood effects and, more generally, on sociospatial inequalities, spatial scale remains an under-analysed concept. As a response to this research gap, this thesis takes a multiscale approach to both theory and the empirical analysis of neighbourhood effects, highlighting the multitude of spatial processes that may affect individual outcomes of people. To operationalise this, we created bespoke areas (centred around each residential location) at a range of one hundred scales representing people’s residential contexts, primarily in the Netherlands but also in multiple European capitals. Using microgeographic data and a large number of scales combined with small distance increments revealed subtle changes in sociodemographic characteristics across space. In doing so, we provided new insights into ethnic segregation, potential exposures to poverty, and neighbourhood effects on income, all in light of the fundamental issue of spatial scale: The analyses of sociospatial inequalities are substantially affected by the scale used to operationalise spatial context, and this varies within and between cities and urban regions. The aim of this thesis was therefore not to find a single, ‘true’ scale of neighbourhood, but to acknowledge, operationalise, and better understand the multiplicity of spatial scales.

Neighborhoods represent a scale at which inequalities are reflected in the unequal spatial distribution of ethnic and income groups across urban space. However, neighborhoods are not static entities and spatial patterns of socioeconomic and ethnic inequality shift over time as a result of processes of neighborhood change. This dissertation has adopted a longitudinal approach to analyze patterns of neighborhood change on a relatively low spatial scale. This dissertation illustrates that neighborhoods remain relatively stable over time in their socioeconomic and ethnic status and that change takes several decades to take effect. This dissertation finds that neighborhoods exhibit a strong degree of path-dependency and demonstrates how the housing stock influences neighborhood trajectories. In addition, it shows how large-scale changes to the housing stock in the context of urban restructuring affect residential mobility and neighborhood upgrading. This dissertation also reveals the ways in which different population dynamics interact to inhibit or generate neighborhood change to reproduce socio-spatial inequalities. Moreover, the innovative methods that are explored in this dissertation contribute to broadening the scope of statistical methods for the longitudinal analysis of neighborhood change.