A framework for estimating migrant stocks using digital traces and survey data: an application in the United Kingdom
2021
An accurate estimation of international migration is hampered by
a lack of timely and comprehensive data, with different definitions
and measures of migration adopted by different countries. Thus, we
complement traditional data sources for the United Kingdom with
social media data. Our aim is to understand whether information
from digital traces can help measure international migration. The
Bayesian framework proposed in the Integrated Model of European
Migration is used to combine data from the Labour Force Survey (LFS)
and the Facebook Advertising Platform in order to study the number
of European migrants in the UK, aiming to produce more accurate
estimates of European migrants. The overarching model is divided into
a Theory-Based Model of migration, and a Measurement Error Model.
We review the quality of the LFS and Facebook data, paying particular
attention to the biases of these sources. The results indicate visible
yet uncertain differences between model estimates using the Bayesian
framework and individual sources. Sensitivity analysis techniques are
used to evaluate the quality of the model. The advantages and limitations
of this approach, which can be applied in other contexts, are
also discussed. We cannot necessarily trust any individual source, but
combining them through modelling offers valuable insights.
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