Integrated Modeling of European Migration
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.
This project has two main objectives. First, we will develop a Bayesian statistical model for migration count data that allows for flows to be measured to different accuracies and that is able to incorporate auxiliary information on the associations between origins and destinations of migration (e.g., language, borders and distance) to estimate missing patterns. Second, the model will accommodate the various complexities in the reported international migration data in the modelling framework. This involves the reconciliation of reported flows based on various definitions used by countries to measure international migration and the use of multiple sources of data on particular flows, including the use of qualitative judgements. The modelling approach will include multiple time periods and disaggregation by age and sex.
This project is led by experienced researchers 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 team includes both senior-level researchers and junior-level research assistants. The Principal Investigator, James Raymer (University of Southampton) is an expert in migration estimation. His group also includes Jonathan J. Forster, Peter W.F. Smith, Guy Abel, Jakub Bijak and Arkadiusz Wisniowski, experts in Bayesian modelling, categorical data analysis and migration forecasting. Nico Keilman (University of Oslo) is an expert in population forecasting and demographic uncertainty. Rob van der Erf (Netherlands Interdisciplinary Demographic Institute) is an expert in migration statistics and data-base development.
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.
Dr. James Raymer, University of Southampton