In our paper, we present a methodology to infer the age and sex profiles of net migration. This research supports the United Nations Population Division’s estimation and population projection procedures for producing the World Population Prospects (WPP). Age and sex profiles of net migration are required as inputs into demographic accounting models for population estimation and projection. However, most countries in the world do not directly measure migration and residual methods for inferring the patterns have proven inadequate, due to errors in the measures of populations, births and deaths.

As net migration does not exhibit regularities across age and sex, we developed a strategy to first estimate flows of immigration and emigration by age and sex, which do exhibit regularities. Differences from these estimates are then calculated to obtain net international migration by age and sex. Based on empirical tests, using data from Sweden, South Korea, Australia, Canada and New Zealand, the methodology shows great promise for overcoming a major data limitation countries around the world. Further, we apply the model to countries where the age and sex patterns of net migration are unknown and show the results. The paper ends with a discussion of next steps and further extensions.

This event is presented in person and online. Zoom details below.

Speaker
James Raymer is a Professor of Demography at the Australian National University. His research focuses on developing innovative methodologies and analytical frameworks to study migration processes. His current research focuses on estimating international migration flows in the Asia Pacific region and small area population projections in Australia. For the past four years, he has been an active participant in the United Nations’ Expert Group on Migration Statistics.

This series is spearheaded by the ANU Migration Hub hosted at RegNet, in collaboration with the School of Archaeology and Anthropology.

For online attendance, see Zoom details below https://anu.zoom.us/j/86557701787?pwd=cnIreVB5eG8vNmlibWtHMjRKaEtIZz09
(Meeting ID: 865 5770 1787. Password: 836061)