An Economic Topology of the Brexit vote
Simon Rudkin and
Papers from arXiv.org
A quest to understand the decision of the UK to leave the European Union, Brexit, in the referendum of June 2016 has occupied academics, the media and politicians alike. As the debate about what the future relationship will look like rages, the referendum is given renewed importance as an indicator of the likely success, or otherwise, of any forward plans. Topological data analysis offers an ability to faithfully extract maximal information from complex multi-dimensional datasets of the type that have been gathered on Brexit voting. Within the complexity it is shown that support for Leave drew from a far more similar demographic than Remain. Obtaining votes from this concise set was more straightforward for Leave campaigners than was Remain's task of mobilising a diverse group to oppose Brexit. Broad patterns are consistent with extant empirical work, but the strength of TDA Ball Mapper means that evidence is offered to enrich the narrative on immobility, and being ``left-behind'' by EU membership, that could not be found before. A detailed understanding emerges which comments robustly on why Britain voted as it did. A start point for the policy development that must follow is given.
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