The Southampton Statistical Sciences Research Institute has recently been awarded a NORFACE (New Opportunities for Research Funding Agency Co-operation in Europe) grant to develop an integrated model for estimating migration flows between countries in Europe.
This project is led by James Raymer (P.I.), Jonathan J. Forster, Peter W.F. Smith, Jakub Bijak, Nico Keilman (University of Oslo) and Rob van der Erf (Netherlands Interdisciplinary Demographic Institute, NIDI), who have a good track record in handling and collecting migration data, quantifying demographic uncertainty, estimating migration patterns and statistical modelling, including methods to deal with inadequate or missing data. The S3RI team is responsible for the development of a Bayesian modelling approach to estimate international migration flows, the NIDI team is responsible for the collection and assessment of international migration data and the Oslo team is responsible for the quantification of uncertainty in the available data and expert judgements.
The overall aim of this research is to provide a general framework for modelling migration flows between countries in the world in the context of inconsistent, inadequate and missing data. The focus is on estimating recent international migration flows between countries in the European Union, using data primarily collected by Eurostat and other publicly available sources, as well as qualitative information from experts. This project has the following main objectives.
In order to fully understand the causes and consequences of international movements in Europe, researchers and policy makers need to overcome the limitations of the various data sources, including inconsistencies in availability, definitions and quality. At present, there has been little research on combining international migration data to provide overall pictures of population movements. So, how does one overcome these obstacles to obtain an overall and consistent picture of the migration patterns occurring within Europe? The proposed research seeks to answer this question by applying Bayesian methods to harmonise and correct for inadequacies in the available data and to estimate completely missing flows. The methodology will be integrated and capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters. Having such a data base will allow us to better understand the underlying mechanisms and reasons for recent migration trends.
The advantages in having a consistent and reliable set of migration flows are numerous. Estimates of migration flows are needed so that governments have the means to improve their planning policies directed at supplying particular social services or at influencing levels of migration. This is important because migration is currently (and increasingly) the major factor contributing to population change. Furthermore, our understanding of how or why populations change requires reliable information about migrants. Without this, the ability to predict, control or understand that change is limited. Finally, countries will soon be required to provide harmonised migration flow statistics to Eurostat as part of a new regulation passed by the European Parliament. Recognising the many obstacles with existing data, Article 9 of the Regulation states that 'As part of the statistics process, scientifically based and well documented statistical estimation methods may be used.' Our proposed framework helps countries achieve this aim and provides measures of accuracy required for understanding the estimated parameters and flows.