Abstract Details
Activity Number:
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151
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Type:
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Invited
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Date/Time:
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Monday, August 10, 2015 : 10:30 AM to 12:20 PM
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Sponsor:
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Social Statistics Section
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Abstract #314656
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Title:
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Probabilistic Population Projections with Migration Uncertainty
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Author(s):
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Adrian Raftery* and Jonathan Azose
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Companies:
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University of Washington and University of Washington
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Keywords:
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United Nations ;
Bayesian hierarchical model ;
Fertility ;
Mortality ;
Gravity model ;
Autoregressive model
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Abstract:
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The UN recently issued official probabilistic population projections for all countries for the first time. These take account of uncertainty about future fertility and mortality, but not international migration. We propose a Bayesian hierarchical autoregressive model for obtaining joint probabilistic projections of migration rates for all countries, broken down by age and sex. Joint trajectories for all countries are constrained to satisfy the requirement of zero global net migration. We evaluate our model using out-of-sample validation and compare point projections to the projected migration rates from a persistence model similar to the UN's current method for projecting migration, and also to a state of the art gravity model. We also resolve an apparently paradoxical discrepancy between growth trends in the proportion of the world population migrating and the average absolute migration rate across countries.
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Authors who are presenting talks have a * after their name.
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