Statistical modelling of international migration flows


Bijak, Jakub, Wisniowski, Arkadiusz and the IMEM Team (2011) Statistical modelling of international migration flows. 58th World Statistics Congress of the International Statistical Institute (ISI2011), 21-26 August 2011 , Dublin, IE, 21 - 26 Aug 2011. 8pp.

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Description/Abstract

The paper deals with uncertainty in estimating international migration flows for an interlinked system of countries. The related problems are discussed on the example of a dedicated model 'IMEM' (Integrated Model of European Migration). The IMEM is a hierarchical Bayesian model, which allows for combining data from different countries with meta-data on definitions and collection methods, as well as with relevant expert information. The model is applied to 31 EU and EFTA countries for the period 2002–2008. The expert opinion comes from a two-round Delphi survey carried out amongst 11 European experts on issues related to migration statistics. The adopted Bayesian approach allows for a coherent quantification of uncertainty stemming from different sources (data discrepancies, model parameters, and expert judgement). The outcomes produced by the model – whole posterior distributions of estimated flows – can be then used for assessing the true magnitude of flows at the European level, taking into account relative costs of overestimating or underestimating of migration flows. In this context, problems related to application of the decision statistical analysis to multidimensional problems are briefly discussed

Item Type: Conference or Workshop Item (Invited Paper)
Subjects: H Social Sciences > HA Statistics
Divisions: Faculty of Social and Human Sciences > Social Sciences > Social Statistics & Demography
ePrint ID: 208435
Date Deposited: 20 Jan 2012 14:49
Last Modified: 28 Mar 2014 15:13
Research Funder: ESRC
Projects:
Centre for Population Change: Understanding Population Change in the 21st Century
Funded by: ESRC (RES-625-28-0001)
Led by: Jane Cecelia Falkingham
1 January 2009 to 31 December 2013
URI: http://eprints.soton.ac.uk/id/eprint/208435

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