Bayesian forecasting of immigration to selected European countries by using expert knowledge
Source: Journal of the Royal Statistical Society: Series A (Statistics in Society), Volume 173, Number 4, October 2010 , pp. 775-796(22)
The aim of the paper is to present Bayesian forecasts of immigration for seven European countries to 2025, based on quantitative data and qualitative knowledge elicited from country-specific migration experts in a two-round Delphi survey. In line with earlier results, most of the immigration processes under study were found to be barely predictable in the long run, exhibiting non-stationary features. This outcome was obtained largely irrespectively of the expert knowledge input, which nevertheless was found useful in describing the predictive uncertainty, especially in the short term. It is argued that, under the non-stationarity of migration processes, too long forecasts horizons are inadequate, which is a serious challenge for population forecasts in general.
Document Type: Research Article
Affiliations: 1: University of Southampton, UK, and Central European Forum for Migration and Population Research, Warsaw, Poland 2: Central European Forum for Migration and Population Research, Warsaw, and Warsaw School of Economics, Poland
Publication date: October 1, 2010