Digitale und Computergestützte Demografie
Auf einen Blick
Die Modellierung internationaler Migrationsbewegungen durch die Integration verschiedener Datenquellen
Maciej Danko, Emanuele Del Fava, Dmitri A. Jdanov, Domantas Jasilionis, Emilio Zagheni, Aliakbar Akbaritabar; in Zusammenarbeit mit Arkadiusz Wisniowski (The University of Manchester, Großbritannien)
In order to improve our understanding of the causes and consequences of migratory movements, scholars, official statisticians, and policy makers must overcome the limitations inherent in the various data sources that each country uses to produce statistics on migration, especially on flows between countries. The sources used to produce statistics on migration are highly heterogeneous (e.g., population censuses, administrative registers, household surveys, residence and work permits, and registers of foreigners). Even the Internet and social media might be relied on as a source of information on migration flows. Although all of these sources contain information on migration, they are usually not explicitly designed to measure it. Their use for the assessment of migration patterns may therefore be hindered by inconsistencies in availability, definitions, and quality. We might thus expect high variability in the reported numbers, due for instance to differences in the nature and the quality of the collected data, the timing criterion underlying the definition of a migration event in a given country, and the coverage of the national collection systems. Discrepancies are expected to emerge between data sources within a country, but even more so between countries in the context of estimating bilateral migration flows.
The data limitations mentioned above restrict our ability to rely on a single source to investigate migration flows between pairs of countries. Our proposed solution is to integrate the available data within the same statistical modeling framework through building a ''synthetic database''. In this project, we thus extend previous work on estimating international migration by developing a Bayesian model that integrates and harmonizes different migration data sources , as well as socioeconomic and demographic information. More specifically, the statistical model includes information on both the single countries and the relationships between pairs of countries, information that may be predictive of migration patterns. The purpose is to obtain new estimates of migration flows between pairs of countries and across time to improve our understanding of the causes and consequences of migration. Considering that data for some flows in some years may be missing in a data source, either because they are not collected or they are not available for various other reasons, the data integration approach enables us to account for information available for other countries. When data for a specific flow are missing across available data sources, the Bayesian framework borrows information from available data for other countries and periods, as well as from the prior distributions, to obtain an estimate for those missing flows.
This project is a first step in the methodological development of an approach for the construction of a Human Migration Database, i.e., a synthetic database of migration data for developed countries at the highest possible level of quality, providing detailed, uniformly estimated, and continually updated migration data.
SocArXiv papers. unpublished. (2019)