The gap between wealthy and disadvantaged neighbourhoods seems to be increasing in many contemporary Western cities. Most studies of neighbourhood change focus on specific case-studies of neighbourhood downgrading or gentrification. Studies investigating socio-spatial polarisation in larger urban areas often compare neighbourhoods at two points in time, neglecting the underlying dynamic character of neighbourhoods. In the current literature, the question if neighbourhoods with similar characteristics experience similar changes over time remains unanswered. As a result, it is unclear why some neighbourhoods appear to be more prone to change than others. In this paper, we propose a dual approach for analysing neighbourhood change. We argue that researchers should both adopt a long-term perspective (20-40 years), because significant changes are only visible after longer periods of time, and focus on more detailed neighbourhood trajectories to understand how neighbourhood change is interrelated with context. Focussing on Dutch neighbourhoods over the period 1971-2013, we analyse the role of physical characteristics on low-income neighbourhood trajectories using an innovative visualisation technique. A tree-structured discrepancy analysis allows for the visualisation of complete neighbourhood pathways, enabling the analysis of complex, contextualised patterns of change. We find that the original quality of neighbourhoods and dwellings seems to be an important predictor for future neighbourhood trajectories, indicating a high level of path-dependency.

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Western cities are increasingly ethnically diverse, and in most cities, the share of the population belonging to an ethnic minority is growing. Studies analysing changing ethnic geographies often limit their analysis to changes in ethnic concentrations in neighbourhoods between 2 points in time. Such a temporally limited approach limits our understanding of pathways of ethnic neighbourhood change and of the underlying factors contributing to change. This paper analyses full trajectories of neighbourhood change in the 4 largest cities in the Netherlands between 1999 and 2013. Our modelling strategy categorises neighbourhoods based on their unique growth trajectories of the ethnic population composition, providing insight in processes of ethnic segregation and its drivers. Our main conclusion is that the ethnic composition in neighbourhoods remains relatively stable over time.We however find evidence for a slow trend towards deconcentration of ethnic minorities and increased population mixing in most neighbourhoods. Spatial mixing appears to be driven by the selective mobility patterns of the native Dutch population as a result of urban restructuring programmes. However, these pathways towards deconcentration are mitigated by processes of ethnic natural growth that reinforce existing patterns of segregation. Despite an increasing inflow of the native Dutch into ethnic concentration neighbourhoods, segregation at the top and bottom ends of the distribution seems to be persistent: High concentrations of ethnic minorities in disadvantaged neighbourhoods versus high concentrations of the native population in more affluent neighbourhoods continue to be a feature of Dutch cities.

Research has shown that there is a strong negative relationship between social spending and poverty levels. Among urban inequality researchers it is often assumed that, compared with the USA, the welfare state has mitigated social differences explaining lower levels of urban inequality in most European countries. However, research on the role of the welfare state is often conducted on the national level, and is thus unable to draw conclusions on the effects of social spending and redistribution on a lower level, failing to take the within-country variation into account. This study connects welfare state research to urban inequality research by investigating the effects of social spending on poverty in urban and non-urban areas. We have conducted a cross-national multilevel logistic regression analysis using Eurostat and European Social Survey data of 2008. Our findings suggest that the effects of social spending are unequally distributed within countries.