Sex Differences in the Performance of Models for Bilateral Migration Predictions

Athina Anastasiadou , Max Planck Institute for Demographic Research
Emilio Zagheni, Max Planck Institute for demographic Research

Migration is a complex process and difficult to predict. Nevertheless, predictions of migration are vital for demographic projections and policy making. At the same time, migration is known to be a highly gendered process reflecting different motivations, propensities, and outcomes of migration by gender. Such differences are mirrored in the fact that on average 44.7% of the bilateral migration corridors worldwide are male-dominated while only 28.2% are female-dominated. As theories and models have been shaped over decades around the narrative of the male migrant, this can potentially translate into discrepancies in migration predictions by sex. Using one of the most comprehensive macro-level data sets on bilateral migration flows disaggregated by sex, we aim to explore and understand such differences in migration predictions. We compare the predictive performance of a basic gravity model with demographic and geographic covariates to an extended version of that model including gender-sensitive predictors. Our preliminary findings show that indeed worse performance measures are achieved for female migration flows compared to male when applying the baseline model. Expanding the model by adding gender-sensitive indicators improves the model performance for the predictions. The next steps involve comparing other common demographic and econometric models of migration prediction. Further enhancing our understanding of the underlying mechanisms resulting in different prediction accuracy has the potential to inform the work of international organizations, researchers, and policy-makers.

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 Presented in Session 54. Flash session International Migration