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Halvard Buhaug
Abstract
The rise in global displacement has inspired a wave of quantitative comparative research in recent years. While deeper systematic knowledge on contextual determinants of disaster-related mobility and associated risks is in high demand, quantitative modelling of human displacement should be exercised with care. In this commentary, I reflect on three central challenges related to the quality of available displacement statistics. Future scientific progress in this field would benefit tremendously from harmonization and validation of displacement data that separate between distinct mobility responses.
INTRODUCTION
Global displacement is at an all-time high (UNHCR, 2022a). More than two-thirds of all internal displacements are driven by extreme weather events, notably floods and storms (IDMC, 2022). Since 2012, geophysical and weather-related disasters have been responsible for 230 million internal displacements, indicating the scale of the phenomenon at hand.
The rise in human displacement has motivated new quantitative analyses of, inter alia, flood-induced displacement (e.g. Vestby et al., 2023), conflict-driven mobility (e.g. Schutte et al., 2021) and scenario-based projections of future displacement (e.g. Rigaud et al., 2018). Despite significant methodological progress and immediate policy relevance, this research is not without limitations. In this commentary, I briefly reflect on three reasons why macro-level quantitative modelling of displacement remains challenging and why results from such studies should be interpreted with care. I discuss these concerns within the scope of disaster displacement, although several points raised below will be relevant for quantitative research on human mobility more generally.