| Abstract: | ![]()
Socio‐demographic data are typically collected at various levels of aggregation, leading to the modifiable areal unit problem. Spatial non‐stationarity of statistical associations between variables further influences the demographic analyses. This study investigates the implications of these two phenomena within the context of migration‐environment associations. Global and local statistical models are fit across increasing levels of aggregation using household level survey data from rural South Africa. We raise the issue of operational scale sensitivity, which describes how the explanatory power of certain variables depends on the aggregation level. We find that as units of analysis (households) are aggregated, some variables become non‐significant in the global models, while others are less sensitive to aggregation. Local model results show that aggregation reduces spatial variation in migration‐related local associations but also affects variables differently. Spatial non‐stationarity appears to be the driving force behind this phenomenon as the results from the global model mask this relationship. Operational scale sensitivity appears related to the underlying spatial autocorrelation of the non‐aggregated variables but also to the way a variable is constructed. Understanding operational scale sensitivity can help to refine the process of selecting variables related to the scale of analysis and better understand the effects of spatial non‐stationarity on statistical relationships. |
