Evaluating multi-regional population projections with Taylor’s law of mean–variance scaling and its generalisation

Meng Xu (), Helge Brunborg () and Joel E. Cohen ()
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Meng Xu: Pace University
Helge Brunborg: Statistics Norway
Joel E. Cohen: The Rockefeller University and Columbia University

Journal of Population Research, 2017, vol. 34, issue 1, No 4, 79-99

Abstract: Abstract Organisations that develop demographic projections usually propose several variants with different demographic assumptions. Existing criteria for selecting a preferred projection are mostly based on retrospective comparisons with observations, and a prospective approach is needed. In this work, we use the mean–variance scaling (spatial variance function) of human population densities to select among alternative demographic projections. We test against observed and projected Norwegian county population density using two spatial variance functions, Taylor’s law (TL) and its quadratic generalisation, and compare each function’s parameters between the historical data and six demographic projections, at two different time scales (long term: 1978–2010 vs. 2011–2040; and short term: 2006–2010 vs. 2011–2015). We find that short-term projections selected by TL agree more accurately than the other projections with the recent county density data and reflect the current high rate of international migration to and from Norway. The variance function method implemented here provides an empirical test of an ex ante approach to evaluating short-term human population projections.

Keywords: Demographic projection; Net immigration; Population variability; Taylor’s law; Power law; Variance function; Fluctuation scaling; Multi-regional projection (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s12546-016-9181-0

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