This chapter explores multi-scale estimation methods as an important future direction for segregation research in China. We explain how these recently developed methods help address many longstanding problems in traditional index-based segregation research and open up new avenues of research on Chinese cities. We explain the conceptual framework underpinning multilevel analysis in the form of a series of propositions that capture the theoretical basis and outline why a multilevel approach to segregation is advantageous. We then illustrate how this approach can be applied to China using census data on Shijiazhuang, the capital city of Hebei Province. We use the model to consider segregation of different ethnic groups and of migrants versus non-migrants. We conclude with a discussion of our findings and our thoughts on future directions for research and the implications for policy.@en

There has been a growing appreciation that the processes generating urban residential segregation operate at multiple scales, stimulating innovations into the measurement of their outcomes. This paper applies a multi‐level modelling approach to that issue to the situation in Auckland, where multiple migration streams from both Pacific Island and Asian origins have created a complex multi‐ethnic city. We identify two distinct trends. For the larger ethnic groups segregation remained static despite rapid growth over a recent twelve‐year period. For the smaller groups growth has been combined with considerable change; they initially clustered in a few localities and areas within them but then experienced considerable reduction in the intensity of that segregation. By spatially decomposing the segregation levels, this paper extends our appreciation of its underpinning processes when they apply to migration streams that differ in their nature from those on which traditional residential location‐decision theory has been based.@en

Traditional studies of residential segregation use a descriptive index approach with predefined spatial units to report the degree of neighbourhood differentiation. We develop a model-based approach which explicitly includes spatial effects at multiple scales, recognising the complexity of the urban environment while simultaneously distinguishing segregation at each scale net of all other scales. Moreover, this model distinguishes segregation as unevenness and as spatial clustering in the presence of stochastic variation. The modelling approach, unlike traditional index approaches, allows hypothesis evaluation concerning alternative scales and zonation through an accompanying badness-of-fit measure. Ultimately, this permits the identification of the scale and zonation regime where the spatial patterns come into focus thereby directly tackling the modifiable areal unit problem. The model is applied to Indian ethnicity in Leicester, UK, finding segregation as unevenness and as spatial clustering at multiple scales.@en