A probabilistic population and household forecasting model for subnational regions, with application to Sydney, Australia

Over the last two decades significant progress has been made in the development of probabilistic population forecasting methods, and many applications to countries and global regions are now in evidence. Unfortunately little interest has been shown in the extension of these methods to subnational areas. Given that forecast error is inversely related to population size, coupled with the fact that much planning occurs at the local and regional scale, the need to quantify forecast uncertainty for subnational regions is arguably even greater than at the national scale. This paper presents a regional probabilistic population and household projection for Sydney, Australia’s largest metropolitan region and home to about 4.6 million people. A bi-regional framework is adopted consisting of the region of interest and the rest of the country; predictive intervals for fertility, mortality, internal migration, international migration and living arrangements are formulated on the basis of time series models, past errors and expert judgement. The results demonstrate the considerable extent of forecast uncertainty for the region, and reveal how the official high-low projection range provides a misleading indication of uncertainty. The paper concludes by discussing how probabilistic forecasts might be applied in metropolitan regional planning.