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ABSTRACT
The mismatch between local voting and the local economic consequences of Brexit. Regional Studies. This paper reveals that in the 2016 UK referendum regarding whether to remain in or leave the European Union, the regions that voted strongly for leave tended also to be those same regions with greatest levels of dependency on European Union markets for their local economic development. This observation flies in the face of pro-leave narratives that posited that the major beneficiaries of European Union membership were the ‘metropolitan elites’ of London. Economic geography dominated the observed voting patterns, and geography will also certainly dominate the post-Brexit economic impacts, but not necessarily in a way that voters anticipated or wished for.
摘要
英国脱欧的地方投票与地方经济结果之间的不同调。Regional Studies. 本文揭露 2016 年英国有关是否续留或脱离欧盟的公投中，强力投票支持脱欧的区域，同时也很可能是该地的在地经济发展对欧盟市场依赖程度最高的区域。此一观察当面拒斥了主张欧盟会员资格的主要受益者是伦敦 ‘大都会精英’ 此般支持脱欧的叙事。经济地理支配了观察到的投票模式，而地理必将同时支配脱欧后的经济冲击，但不必然是透过选民所期待或希冀的方式。
RÉSUMÉ
Disparité entre le vote local et les conséquences économiques du Brexit. Regional Studies. La présente communication révèle que lors du référendum de 2016, au Royaume-Uni, qui devait décider si le Royaume-Uni souhaitait rester dans l’Union européenne ou la quitter, les régions qui votèrent le plus fort pour quitter l’UE sont également celles qui présentent une dépendance plus prononcée des marché de l’Union européenne pour leur développement économique local. Cette observation va à l’encontre des discours favorables au départ de l’UE, qui soutenaient que les principaux bénéficiaires de l’adhésion à l’Union européenne sont les «élites métropolitaines» de Londres. La géographie économique domina les tendances du vote, et la géographie dominera sans aucun doute, une fois de plus, les conséquences économiques du Brexit, mais pas nécessairement de la façon prévue ou souhaitée par les électeurs.
ZUSAMMENFASSUNG
Die Diskrepanz zwischen dem lokalen Abstimmungsverhalten und den lokalen wirtschaftlichen Auswirkungen des Brexit. Regional Studies. In diesem Beitrag zeigen wir, dass es sich bei den Regionen, die im britischen Referendum von 2016 über den Verbleib in oder den Austritt aus der EU mit starker Mehrheit für einen Austritt votierten, tendenziell um dieselben Regionen handelt, die für ihre lokale Wirtschaftsentwicklung am stärksten auf die Märkte der Europäischen Union angewiesen sind. Diese Beobachtung steht im krassen Widerspruch zur Argumentation der Austrittsbefürworter, nach der die ‘metropolitanen Eliten’ von London am stärksten von der Mitgliedschaft in der Europäischen Union profitieren. Die beobachteten Abstimmungsmuster wurden von der Wirtschaftsgeografie dominiert, und die Geografie wird zweifellos auch die wirtschaftlichen Auswirkungen nach dem Brexit dominieren – allerdings nicht unbedingt so wie von den Wählern erwartet oder gewünscht.
RESUMEN
La discrepancia entre los votos locales y las consecuencias para la economía local del Brexit. Regional Studies. En este artículo mostramos que en el referéndum de 2016 en el Reino Unido sobre la permanencia o salida de la Unión Europea, las regiones que votaron con gran mayoría a favor del Brexit fueron en general las regiones con niveles más altos de dependencia de los mercados de la Unión Europea para su desarrollo económico local. Esta observación contradice los argumentos de los partidarios del Brexit que criticaban que los principales beneficiarios de la Unión Europea eran las ‘elites metropolitanas’ de Londres. La geografía económica dominó los patrones de conducta observados en la votación, y también la geografía sin duda dominará las repercusiones económicas después del Brexit, pero no necesariamente tal como los votantes lo habían previsto o deseado.
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ACKNOWLEDGEMENTS
The data reported in this paper were undertaken as part of a much broader data-building programme contained in the multi-institution and multi-country research project ‘Smartspec – Smart Specialisation for Regional Innovation’ coordinated by Cardiff University, July 2013–June 2016. The authors are grateful to Wen Chen at the University of Groningen for data assistance.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the authors.
Notes
2. Similar anti-globalization voting patterns according to a region’s responses to globalisation are also evident in Germany (Dippel, Gold, & Heblich, Citation2016).
3. NUTS = Nomenclature des Unités Territoriales Statistiques. See http://webarchive.nationalarchives.gov.uk/20160105160709; and http://www.ons.gov.uk/ons/guide-method/geography/beginner-s-guide/eurostat/index.html/.
4. The referendum voting data were kindly supplied by John Burn-Murdoch who originally updated our Springford et al. (Citation2016a) voting preference data for the Financial Times with the actual votes (see also http://blogs.ft.com/ftdata/2016/06/24/brexit-demographic-divide-eu-referendum-results/).
5. Other analysis also finds that the likely adverse effects of leaving the Single Market are similar across many sectors with wholesale and retail, manufacturing and services all being affected due to their high levels of dependency on EU markets (Centre for Economics and Business Research (CEBR), Citation2016).
6. As Winters (Citation2016a) also explains, analysing a much longer period.
7. See http://www.bbc.com/news/uk-politics-36616028; and https://ig.ft.com/sites/elections/2016/uk/eu-referendum/.
8. The results are available from the authors upon request.
9. As against empire-era globalization processes.
10. The WIOD 2013 release demonstrates that the 2011 share of UK demand accounted for by the rest of the EU is 9.75% while the share of GDP in the rest of the EU accounted for by UK demand is only 1.6%. In other words, the UK is six times more dependent on the EU than the EU is on the UK (Springford et al., Citation2016b). The level of the UK’s GDP dependence on the EU calculated from the WIOD is slightly lower than the 10.3% share calculated by CEBR (2016). However, if we calculate these relationships in terms of gross national product (GNP) rather than GDP, then at 10.5% the EU-related shares are even larger due to the fact that almost exactly half of the UK’s inward and outward foreign direct investment (FDI) stocks are accounted for by the EU, and the UK displays a net outward FDI surplus with the EU (McCann, Citation2016).
11. Various types of possible trade model options could be adopted, as outlined in this paper, although Theresa May’s speech on 17 January 2017 suggests that the UK is seeking a uniquely customized arrangement rather than an off-the-shelf type of arrangement (BBC News, Citation2016).
12. A recent working paper casts doubt on HM Treasury’s model (Gudgin, Coutts, & Gibson, Citation2016).
13. Scotland, at 9.0%, has a slightly below-average level of dependency on EU markets, while at 17.4% its level of dependence on markets in the rest of the UK means that it is twice as dependent on the rest of the UK than on the rest of the EU. Although Scotland's economic dependence on the rest of the UK had fallen by almost one-quarter since the Millennium, from 23% in 2000 to 17.4% in 2010, this is still likely to pose some challenges for Scottish independence narratives, but again it partly depends on the outcomes of the post-Brexit trade agreements (Fraser of Allander Institute, Citation2016). The quotation from Theresa May, ‘The single market of the United Kingdom is worth four times as much to Scotland as the single market of the European Union,’ would therefore appear to be incorrect by a factor of two (iNews, Citation2016).
1. Information on WIOD is available at www.wiod.org/new_site/home.htm. The ways these WIOD figures play out for the EU-UK relationships is examined in detail in Springford et al. (Citation2016b) and McCann (Citation2016).
2. See Thissen et al. (Citation2013) for a discussion on the methodology to use both the relative and absolute errors in the minimization.
3. Since we have a non-square commodity-industry system (see Miller & Blair, Citation2009, pp. 211–213, for a discussion of these non-square systems) we determined the industry by industry matrix A of technical coefficients by multiplying the market shares matrix D (value of outputs per total output of an industry) and B (value of inputs per total output of an industry).