Projections of future populations are integral to many planning applications, yet are often poorly understood. This analysis focuses on the implications of the choices planners make when they construct projections. Specifically, it examines the impact of length of base period, analyzes the error structure of projection techniques for counties in the aggregate and by size and growth rates, investigates the role of averaging, and compares the performance of trend extrapolation and cohort–component methods.
Many studies have evaluated the impact of differences in population size and growth rate on population forecast accuracy. Virtually all these studies have been based on aggregate data; that is, they focused on average errors for places with particular size or growth rate characteristics. In this study, we take a different approach by investigating forecast accuracy using regression models based on data for individual places.