Integrating uncertainty in time series population forecasts: An illustration using a simple projection model

Journal article

Background: Population forecasts are widely used for public policy purposes. Methods to quantify the uncertainty in forecasts tend to ignore model uncertainty and to be based on a single model. Objective: In this paper, we use Bayesian time series model

Authors: Abel, G; Bijak, J; Forster, JJ; Raymer, J; Smith, PWF

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Max Planck Institute for Demographic Research
• Journal: Demographic Research
• Volume: 29
• Pages: 1187-1226
• Article number: 43
• Publication date: 2013-12-10
• DOI: 10.4054/demres.2013.29.43
• EISSN: 1435-9871
• ISSN: 1435-9871
• Language: English
• Keywords: Statistics; Projections of population growth; Population projection; Population; Algorithm; Series (stratigraphy); Economics; Mathematics; Simple (philosophy); Computer science; Population growth; Demography; Consensus forecast; Econometrics; Projection (relational algebra); Population model