Bringing Age Back in: Accounting for Population Age Distribution in Forecasting Migration

Nathan Welch, University Of Washington
Hana Sevcikova, University of Washington
Adrian Raftery, University of Washington, Seattle

Existing models of country-level migration ignore the effect of population age distribution on past and projected migration rates. We propose a method to estimate and forecast international net migration rates for the 200 most populous countries, taking account of changes in population age structure. We use age-standardized estimates of country-level net migration rates and in-migration rates from 1990 through 2020 to decompose past net migration rates into in- and out- migration rates. We then recalculate historic migration rates on a scale that removes the influence of the population age distribution. This is done by scaling past and projected migration rates in terms of a reference population and period. We use a Bayesian hierarchical model to generate probabilistic forecasts of total and age- and sex- specific net migration rates over five-year periods for all countries through 2100. Accounting for population age structure leads to narrower prediction intervals by the end of the century for most countries. Furthermore, accounting for population age structure leads to less out-migration among countries with rapidly aging populations that are forecast to contract most rapidly by the end of the century. This leads to less drastic population declines than are forecast without accounting for population age structure.

Keywords: International Migration, Population projections, forecasts, and estimations, Data and Methods

See paper.