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Probabilistic forecasts of international bilateral migration flows.
- Source :
-
Proceedings of the National Academy of Sciences of the United States of America . 8/30/2022, Vol. 119 Issue 35, p1-8. 286p. - Publication Year :
- 2022
-
Abstract
- We propose a method for forecasting global human migration flows. A Bayesian hierarchical model is used to make probabilistic projections of the 39,800 bilateral migration flows among the 200 most populous countries. We generate out-of-sample forecasts for all bilateral flows for the 2015 to 2020 period, using models fitted to bilateral migration flows for five 5-y periods from 1990 to 1995 through 2010 to 2015. We find that the model produces well-calibrated out-of-sample forecasts of bilateral flows, as well as total country-level inflows, outflows, and net flows. The mean absolute error decreased by 61% using our method, compared to a leading model of international migration. Out-of-sample analysis indicated that simple methods for forecasting migration flows offered accurate projections of bilateral migration flows in the near term. Our method matched or improved on the out-of-sample performance using these simple deterministic alternatives, while also accurately assessing uncertainty. We integrate the migration flow forecasting model into a fully probabilistic population projection model to generate bilateral migration flow forecasts by age and sex for all flows from 2020 to 2025 through 2040 to 2045. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00278424
- Volume :
- 119
- Issue :
- 35
- Database :
- Academic Search Index
- Journal :
- Proceedings of the National Academy of Sciences of the United States of America
- Publication Type :
- Academic Journal
- Accession number :
- 158982945
- Full Text :
- https://doi.org/10.1073/pnas.2203822119