Bayesian Model Selection and Forecast Averaging

Chapter
Part of the The Springer Series on Demographic Methods and Population Analysis book series (PSDE, volume 24)

Abstract

This chapter presents the first out of four perspectives proposed for designing a modelling framework for Bayesian forecasting of international migration. In particular, it explores the Bayesian model selection and forecast averaging techniques, based on the posterior odds criterion. Theoretical foundations are laid in Section 5.1, together with a framework proposed for migration predictions on the basis of simple, non-nested stochastic processes. The computational details of the Carlin–Chib procedure used for model selection are also provided. Section 5.2 presents empirical results of forecasts of international migration among selected European countries for 2005–2015, yielded by various models, with focuses on individual and averaged forecasts from simple stochastic processes.

Keywords

Posterior Probability Analytic Hierarchy Process Predictive Distribution Emigration Rate High Posterior Density 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.School of Social Sciences, Centre for Population Change and S3RI, University of SouthamptonSouthamptonUK

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