Uncovering Migrant Fertility Patterns through Consumer Data

Francesco Rampazzo , University of Manchester
Micol Morellini, University of Oxford
Ridhi Kashyap, Oxford University
Douglas Leasure, University of Oxford
Melinda Mills, University of Oxford
Jason Bell, Penn State
Andrew Stephen, University of Oxford

Traditional demographic data often fail to capture the complex interplay between migration and fertility, particularly for populations that are highly mobile or underrepresented in official statistics. This study employs large-scale consumer transaction data from MammaPack, an e-commerce platform serving over 22,000 Italian migrants across 21 European countries, to examine how migration reshapes fertility behaviours abroad. By integrating individual purchase histories with an online survey of 700 participants, we assess whether consumer behaviour can serve as a reliable proxy for fertility outcomes and family formation. Using dimensionality reduction and generalized linear mixed models, we predict the presence of children in households with 76% accuracy, showing that spending patterns, especially on childcare products, are strong indicators of fertility. The analysis reveals that Italian migrants are more likely to have children in destination countries with higher fertility norms and stronger family policies, such as Germany and Ireland, than in Italy itself. These findings suggest that migration not only reflects economic or social mobility but also represents a reproductive strategy influenced by destination contexts. They provide empirical support for the selection and adaptation hypotheses of immigrant fertility, highlighting how migrants’ fertility behaviours evolve in response to new normative and institutional environments. Beyond its methodological innovation, this research underscores the importance of integrating migration dynamics into fertility analysis, offering new insights into how cross-border movement shapes demographic change and family life in contemporary Europe.

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 Presented in Session P8. Demographic Trends, History, Data and Methods