A settlement-level perspective of the spatial relationship between economic performance and population change in South Africa between 2001 and 2011

Migration has long been an important phenomenon shaping the demographic profile of South Africa, and migration and labour are often considered to be intrinsically linked. The push–pull theory of migration, which still tends to dominate gravity-based migration modelling as well as academic thinking, is grounded on the assumption that migration is a functional and inevitable outcome of spatial inequality. Economic drivers of migration are most frequently used to explain population movements in the South African context, given, especially, that slow and uneven economic growth, economic disparities, inequality and unemployment persist as some of the country's biggest socio-economic challenges. Urban living holds the promise of employment prospects and improved conditions, and thus the basic premise of many micro-level models of migrant decision-making is that migration occurs with the expectation of being better off in doing so. The research design of this study set out to empirically investigate the theoretical perspective of the push–pull model of migration from an economic and settlement-based standpoint, and makes novel contributions to the disciplines of Geography, Geographical Information Science, and Urban and Regional Planning. The ultimate aim was to establish a settlement-level perspective of the spatial relationship between economic output (as a measure of economic performance) and working-age population change in South Africa between the Census years of 2001 and 2011. To support the settlement-level analysis scale, special attention was paid to sourcing fine-resolution economic and population datasets covering both the national spatial extent, as well as the tenyear temporal analysis window, and applying advanced GIS methods and techniques to prepare, align, analyse and visualise these datasets. In addition, traditional non-spatial statistical analyses were also employed to measure and quantify the relationship using a correlation-based research approach. Furthermore, the research also proposed a novel way of classifying settlements in South Africa, according to their economic profiles. Based on the research findings, the study identified eight broad settlement types in South Africa, according to an economically profiled settlement classification typology. Population change in the working-age population was found to have a positive statistically significant association with economic performance at settlement level in South Africa. This relationship proved to be multifaceted, given the complex nature of the South African economic landscape at settlement level, with considerable variability (based on the strength of the relationship) between different settlement types. While none of the settlement types exhibited a very strong relationship between economic performance and population change, several settlement types did indicate a moderate to strong association, while other settlement types were shown to have negligible to weak associations. Furthermore, in certain settlement types, some demographic groups, based on age, gender, employment status, and skill level, were found to have markedly higher associations with the economy than others. In its empirical contribution towards evidence-based decision-making, especially in the domain of urban and regional planning, the research findings are valuable in helping to support future policy and development interventions so that development planning can be more successfully targeted and more sensitive to the local South African context, given that South Africa has an intricate history of labour migration, and labour-force participation is a key factor for individuals to improve their socio-economic status. The study highlights important spatial linkages between economic opportunities and patterns of population change in South Africa, and defines and explores a new perspective of this relationship at settlement level. The results of this study further reinforce the literature, that nuanced and dynamic interplays are evident between the push and pull factors influencing population-change dynamics, in that, on its own, economic performance was not found to be a definitive predictor of population change or migration likelihood at settlement level