Putting the Pieces of the Puzzle Together: Age and Sex-Specific Estimates of Migration amongst Countries in the EU/EFTA, 2002–2007

Assembler les pièces du puzzle: estimations de la migration entre les pays de l’UE et de l’AELE par âge et par sexe, 2002–2007
  • James RaymerEmail author
  • Joop de Beer
  • Rob van der Erf


Because of inconsistencies in the reported migration flows and large amounts of missing data, our knowledge of international migration patterns in the Europe is limited. Methods for overcoming data obstacles and harmonising international migration data, however, are improving. In this article, we provide a methodology for integrating various pieces of incomplete information together, including a partial set of harmonised migration flows, to estimate a complete set of migration flows by origin, destination, age and sex for the 31 countries in the European Union and European Free Trade Association from 2002 to 2007. The results represent a synthetic data base that can be used to inform population projections, policy decisions and migration theory.


International migration Europe Log-linear models Combining data 


Du fait d’incohérences dans l’enregistrement des flux migratoires et du grand nombre de données manquantes, notre connaissance des schémas de migrations internationales en Europe reste limitée. Cependant, les méthodes disponibles pour surmonter les obstacles liés aux données et pour harmoniser les données sur la migration internationale s’améliorent. Dans cet article, nous proposons une méthode pour combiner les différents éléments de ces informations incomplètes, incluant un ensemble partiel de données harmonisées sur les flux migratoires, afin d’estimer une série complète de flux migratoires par pays d’origine, pays de destination, âge et sexe pour les 31 pays de l’Union Européenne et de l’Association Européenne de Libre Echange de 2002 à 2007. Les résultats constituent une base de données synthétique pouvant servir de base pour les projections de population, les décisions politiques et les théories relatives à la migration.


Migration internationale Europe Modèles log-linéaire Données combinées 



This study was supported by a European Commission/Eurostat tender no 2006/S100 106607 (OJ 27/05/2006) for the supply of statistical services. The authors would like to thank the other team members of the MIMOSA (MIgration MOdelling for Statistical Analyses) project, and two reviewers of European Journal of Population for their comments and suggestions on our earlier efforts. The estimates described in this article are freely available on the Netherlands Interdisciplinary Demographic Institute’s website at


  1. Abel, G. J. (2010). Estimation of international migration flow tables in Europe. Journal of the Royal Statistical Society Series A, 173(4), 797–825.Google Scholar
  2. Bilsborrow, R. E., Hugo, G., Oberai, A. S., & Zlotnik, H. (1998). International migration statistics: Guidelines for improving data collection systems. Geneva: International Labour Office.Google Scholar
  3. Champion, A. G. (1994). International migration and demographic change in the developed world. Urban Studies, 31(4/5), 653–677.CrossRefGoogle Scholar
  4. de Beer, J., Raymer, J., van der Erf, R., & van Wissen, L. (2010). Overcoming the problems of inconsistent international migration data: A new method applied to flows in Europe. European Journal of Population, 26, 459–481.CrossRefGoogle Scholar
  5. Deming, W. E., & Stephan, F. F. (1940). On a least squares adjustment of a sampled frequency table when the expected marginal totals are known. The Annals of Mathematical Statistics, 11(4), 424–444.Google Scholar
  6. Fienberg, S. E. (1970). An iterative procedure for estimation in contingency tables. The Annals of Mathematical Statistics, 41(3), 907–917.CrossRefGoogle Scholar
  7. Haining, R., Griffith, D. A., & Bennett, R. (1984). A statistical approach to the problem of missing spatial data using a first-order Markov model. The Professional Geographer, 36(3), 338–345.CrossRefGoogle Scholar
  8. Jennissen, R. (2004). Macro-economic determinants of international migration in Europe. Amsterdam: Dutch University Press.Google Scholar
  9. Johnston, R. J., & Pattie, C. J. (1993). Entropy-maximizing and the iterative proportional fitting procedure. The Professional Geographer, 45(3), 317–322.CrossRefGoogle Scholar
  10. Kelly, J. J. (1987). Improving the comparability of international migration statistics: Contributions by the conference of European statisticians from 1971 to date. International Migration Review (Special Issue: Measuring International Migration: Theory and Practice), 21(4), 1017–1037.Google Scholar
  11. Kraly, E. P., & Gnanasekaran, K. S. (1987). Efforts to improve international migration statistics: A historical perspective. International Migration Review (Special Issue: Measuring International Migration: Theory and Practice), 21(4), 967–995.Google Scholar
  12. Kupiszewska, D., & Nowok, B. (2008). Comparability of statistics on international migration flows in the European Union. In J. Raymer & F. Willekens (Eds.), International migration in Europe: Data, models and estimates (pp. 41–71). Chichester, England: Wiley.Google Scholar
  13. Nair, P. S. (1985). Estimation of period-specific gross migration flows from limited data: Bi-proportional adjustment approach. Demography, 22(1), 133–142.CrossRefGoogle Scholar
  14. Nowok, B., Kupiszewska, D., & Poulain, M. (2006). Statistics on international migration flows. In M. Poulain, N. Perrin, & A. Singleton (Eds.), THESIM: Towards harmonised European statistics on international migration (pp. 203–231). Louvain-la-Neuve: Presses universitaires de Louvain.Google Scholar
  15. Poulain, M., Perrin, N., & Singleton, A. (Eds.). (2006). THESIM: Towards harmonised European statistics on international migration. Louvain-la-Neuve: Presses universitaires de Louvain.Google Scholar
  16. Raymer, J. (2007). The estimation of international migration flows: A general technique focused on the origin-destination association structure. Environment and Planning A, 12, 371–388.Google Scholar
  17. Raymer, J. (2008). Obtaining an overall picture of population movement in the European Union. In J. Raymer & F. Willekens (Eds.), International migration in Europe: Data, models and estimates (pp. 209–234). Chichester, England: Wiley.Google Scholar
  18. Raymer, J., Bonaguidi, A., & Valentini, A. (2006). Describing and projecting the age and spatial structures of interregional migration in Italy. Population, Space and Place, 12, 371–388.CrossRefGoogle Scholar
  19. Raymer, J., & Rogers, A. (2007). Using age and spatial flow structures in the indirect estimation of migration streams. Demography, 44(2), 199–223.CrossRefGoogle Scholar
  20. Rees, P. H., & Duke-Williams, O. (1997). Methods for estimating missing data on migrants in the 1991 British census. International Journal of Population Geography, 3, 323–368.CrossRefGoogle Scholar
  21. Rogers, A., Little, J., & Raymer, J. (2010). The indirect estimation of migration: Methods for dealing with irregular, inadequate, and missing data. Dordrecht: Springer.Google Scholar
  22. Rogers, A., Willekens, F. J., Little, J. S., & Raymer, J. (2002). Describing migration spatial structure. Papers in Regional Science, 81, 29–48.CrossRefGoogle Scholar
  23. Rogers, A., Willekens, F. J., & Raymer, J. (2003). Imposing age and spatial structures on inadequate migration-flow datasets. The Professional Geographer, 55(1), 56–69.Google Scholar
  24. Smith, P. W. F., Raymer, J., & Giulietti, (2010). Combining available migration data in England to study economic activity flows over time. Journal of the Royal Statistical Society Series A, 173(4), 733–753.Google Scholar
  25. Sweeney, S. H., & Konty, K. J. (2002). Population forecasting with nonstationary multiregional growth matrices. Geographical Analysis, 34(4), 289–309.Google Scholar
  26. Thierry, X. (2008). Towards a harmonization of European statistics on international migration. Population and Sociétiés, 442(February), 1–4.Google Scholar
  27. United Nations. (1998). Recommendations on statistics of international migration. Statistical papers series M, No. 58, Rev. 1. Statistics Division, Department of Economic and Social Affairs, United Nations, New York.
  28. United Nations. (2002). Measuring international migration: Many questions, few answers. Population Division, Department of Economic and Social Affairs, United Nations, New York.
  29. van Wissen, L., van der Gaag, N., Rees, P., & Stillwell, J. (2008). In search of a modelling strategy for projecting internal migration in European countries. In J. Poot, B. Waldorf, & L. van Wissen (Eds.), Migration and human capital (pp. 49–74). Cheltenham, England: Edward Elgar.Google Scholar
  30. Willekens, F. (1982). Multidimensional population analysis with incomplete data. In K. Land & A. Rogers (Eds.), Multidimensional mathematical demography (pp. 43–111). New York: Academic Press.Google Scholar
  31. Willekens, F. (1983). Log-linear modelling of spatial interaction. Papers of the Regional Science Association, 52, 187–205.CrossRefGoogle Scholar
  32. Willekens, F. (1994). Monitoring international migration flows in Europe: Towards a statistical data base combining data from different sources. European Journal of Population, 10, 1–42.CrossRefGoogle Scholar
  33. Willekens, F. (2008). Models of migration: Observations and judgement. In J. Raymer & F. Willekens (Eds.), International migration in Europe: Data, models and estimates (pp. 117–147). Chichester, England: Wiley.Google Scholar
  34. Wong, D. W. S. (1992). The reliability of using the iterative proportional fitting procedure. The Professional Geographer, 44(3), 340–348.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Southampton Statistical Sciences Research InstituteUniversity of SouthamptonHampshireUK
  2. 2.Netherlands Interdisciplinary Demographic InstituteThe HagueThe Netherlands

Personalised recommendations