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Forecasting International Migration in Europe: A Bayesian View

Part of the The Springer Series on Demographic Methods and Population Analysis Book Series (volume 24)

DOI: 10.1007/978-90-481-8897-0

ISBN: 978-90-481-8896-3

Publisher: Springer Netherlands - Springer Journals

Sep 20, 2010

1 - 10 of 12 Chapters

LitStream

Introduction and Background

Bijak, Jakub

Pages: 3 –13

[The current book is devoted to known (although seldom used by demographers) Bayesian statistical methods, applied in one of the most under-researched areas of population forecasting; that is, predictions of international migration. The study aims to keep up to date with the methodological...
LitStream

Preliminaries

Bijak, Jakub

Pages: 15 –34

[In the current chapter, four issues are briefly addressed, which are vital to the further discussion, yet not sufficiently within the scope of the topic of this book to be presented in full. Firstly, the problems with migration data are dealt with, focusing on the diversity of definitions,...
LitStream

Explaining Migration: Brief Overview of Selected Theories

Bijak, Jakub

Pages: 37 –51

[Attempts to synthesise knowledge on population movements in the form of a coherent theory date back to migration laws of Ravenstein (1885; 1889). Ravenstein generalised observations on internal migration in Great Britain and found that the intensity of the process was influenced by several...
LitStream

Forecasting Migration: Selected Models and Methods

Bijak, Jakub

Pages: 53 –87

[In the current chapter, a survey of various models and methods used in migration predictions to date is offered. The rationale is that socio-economic predictions can be based not only on general, well-grounded laws and theories, but also on descriptive models designed to suit specific research...
LitStream

Bayesian Model Selection and Forecast Averaging

Bijak, Jakub

Pages: 91 –116

[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...
LitStream

Bayesian VAR Modelling ‘from General to Specific’

Bijak, Jakub

Pages: 117 –136

[The current chapter outlines the second of proposed perspectives on migration forecasting, which applies the ‘from general to specific’ modelling principle in the context of nested vector autoregression (VAR) models. In this way, the impact of various theory-based interdependent variables on...
LitStream

Selected Approaches to Discontinuities in Trends

Bijak, Jakub

Pages: 137 –152

[This chapter presents some basic possibilities of acknowledging unpredictable events and structural changes, which are important factors causing discontinuities in observed migration trends. Also here, the relevant models are proposed within the Bayesian framework. In particular, two classes of...
LitStream

Evaluation of Presented Forecasts of European Migration

Bijak, Jakub

Pages: 153 –173

[The current chapter focuses on two aspects of evaluating the forecasts of migration flows, presented earlier in Chapters 5, 6 and 7. Firstly, Section 8.1 deals with the sensitivity of the results to changes in the assumed prior distributions and in the information they carry. The focus of the...
LitStream

Bayesian Computing in Practice

Bijak, Jakub

Pages: 175 –196

[This chapter starts with a short survey of available software for the Bayesian analysis (Section 9.1), with the emphasis laid on high-level programming languages and free, open-source software issued under the GNU General Public License. Further, in Section 9.2, the WinBUGS environment for...
LitStream

Extensions and Limitations of Migration Forecasts

Bijak, Jakub

Pages: 199 –216

[The current chapter focuses on migration, and to some extent population forecasts from the point of view of forecast makers: official statisticians and individual researchers. Three possible pathways of extending the modelling framework are discussed in more detail, following the recent...

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