A paper that I am a co-author on, looking at uncertainty in population forecasting generated by different measures of migration, came out this week in Environment and Planning A. Basically, try and avoid using net migration measures. Not only do they tend to give some dodgy projections, we also found out that they give you more uncertainty. Using in and out measures of migration in a projection model give a big reduction in uncertainty over a net measure. They also are a fairly good approximation to the uncertainty from a full multiregional projection model. Plots in the paper were done by my good-self using the fanplot package.
Raymer J., Abel, G.J. and Rogers, A. (2012). Does Specication Matter? Experiments with Simple Multiregional Probabilistic Population Projections. Environment and Planning A 44 (11), 2664–2686.
Population projection models that introduce uncertainty are a growing subset of projection models in general. In this paper we focus on the importance of decisions made with regard to the model specifications adopted. We compare the forecasts and prediction intervals associated with four simple regional population projection models: an overall growth rate model, a component model with net migration, a component model with in-migration and out-migration rates, and a multiregional model with destination-specific out-migration rates. Vector autoregressive models are used to forecast future rates of growth, birth, death, net migration, in-migration and out-migration, and destination-specific out-migration for the North, Midlands, and South regions in England. They are also used to forecast different international migration measures. The base data represent a time series of annual data provided by the Office for National Statistics from 1976 to 2008. The results illustrate how both the forecasted subpopulation totals and the corresponding prediction intervals differ for the multiregional model in comparison to other simpler models, as well as for different assumptions about international migration. The paper ends with a discussion of our results and possible directions for future research.