  The link between age and migration propensity is long established, but
existing models of country-level net 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 over quinquennial periods from 1990 through 2020 to
decompose past net migration rates into in-migration rates 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
show that this can be done very simply, using a quantity we call the migration
age structure index (MASI). We use a Bayesian hierarchical model to generate
joint probabilistic forecasts of total and age- and sex- specific net migration
rates over five-year periods for all countries from 2020 through 2100. We find
that accounting for population age structure in historic and forecast net
migration rates leads to narrower prediction intervals by the end of the
century for most countries. Also, applying a Rogers & Castro-like migration age
schedule to migration outflows reduces uncertainty in population pyramid
forecasts. Finally, 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.
