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The MIMOSA Model for Estimating International Migration in the European Union. James Raymer and Guy Abel February 2008. MI gration MO delling for S tatistical A nalyses (Eurostat Project 2006/S 100-106607/EN, LOT 2). MIMOSA project. Aim of project
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The MIMOSA Model for Estimating International Migration in the European Union James Raymer and Guy Abel February 2008 MIgration MOdelling for Statistical Analyses (Eurostat Project 2006/S 100-106607/EN, LOT 2)
MIMOSA project • Aim of project • Development and application of statistical modelling techniques for the estimation of missing data on migration flows and foreign population stocks • Work with National Statistical Agencies to improve their data • Funded by Eurostat, December 2006-2009 • Netherlands Interdisciplinary Demographic Institute (Coordinator) • Central European Forum for Migration and Population Research • Southampton Statistical Sciences Research Institute • GéDAP, Université Catholique de Louvain • Focus of this presentation: Migration flow estimation
Significance • The study of international migration in the European Union is currently hindered by data availability, quality and consistency • Harmonization of data collection processes and the data they generate is not even close to being realized, therefore our understanding of population change and migration policy is therefore currently limited • To overcome these obstacles, we need models to (i) harmonise and correct for inadequacies in the available data and (ii) estimate the missing patterns
Data used in this study • Provided by Eurostat (i.e., data comes from the Joint Questionnaire on International Migration) • Immigration and emigration flows by previous / next country of residence (32 by 32 matrix) • 31 European countries: EU plus Iceland, Liechtenstein, Norway and Switzerland • Rest of world • Years: 2002, 2003, 2004 and 2005
Double-entry matrix for selected countries, 2003 I = Receiving country’s reported flow; E = sending country’s reported flow; … = no reported data available
Double-entry matrix for selected countries, 2003 I = Receiving country’s reported flow; E = sending country’s reported flow; … = no reported data available
Double-entry matrix for selected countries, 2003 I = Receiving country’s reported flow; E = sending country’s reported flow; … = no reported data available
Data • Only partial data exists between 2001 and 2004; • Italics: No data exists between 2001 and 2004
Methodology • Harmonise and clean available data • Identify base data (DK, FI, SE and NO) • Calculate adjustment ratios and adjust reported data by using iterative procedure • Estimate missing data • Immigration and emigration totals for European matrix • Associations between origins and destinations
Step 1 of iterative adjustment procedure: Identify and adjust base data Note, procedure applied to 2002-2005 data pooled over time
Step 2 of iterative adjustment procedure: Calculate adjustment ratios Note, procedure applied to 2002-2005 data pooled over time
Step 3 of iterative adjustment procedure: Add adjusted flows to base data Note, procedure applied to 2002-2005 data pooled over time
Adjustment factors for receiving country (I) and sending country (E) migration data, 2002-2005
Estimated coefficients for regressions on natural logarithms of available immigration and emigration flows from / to EU matrix and rest of world (n = 59)
Multiplicative component model Origin by destination migration flow table Multiplicative components where
Estimating the ODij assocations • ODij = reported to expected flows • Expected flows obtained using iterative proportional fitting (IPF) and estimated margins from EU matrix • Two sets of ODij • Available data • Missing data:
Estimated coefficients for regression on available origin-destination associations within the EU matrix (n=2540)
Estimated migration totals, 2002-2005: within the EU matrix and from / to rest of world
Top 20 estimated immigration and emigration countries (in thousands), 2002-2005 Immigration Emigration
Summary • To produce an overall picture of EU migration, one has to address issues concerning the availability, quality and consistency of migration data • Harmonisation and cleaning of reported data • Estimation of missing data (marginal totals and origin-destination associations) based on patterns found in available data and covariates
Next steps • Much research still needed • Integration • EM and Bayesian methods • Standard errors of estimates • MIMOSA project • Flows by age, sex and citizenship • Flows to be linked to population estimates and change