CDRC-GISRUK Data Challenge: Papers online now
The Consumer Data Research Centre (CDRC) collaborated with GISRUK to host a data challenge.
Delegates were asked to develop a novel analysis or visualisation of CDRC and associated data in order to investigate the hypothesis set out in the Economist article “The immigration paradox Explaining the Brexit vote”, which argued the rate of change in number of migrants in an area rather than the total headcount influenced the Brexit vote.
We honed in on four finalists who presented their papers at GISRUK 2018 on 17 April and the winning paper announced on 19 April. A summary of the event – including reasons for selecting the winning paper – can be found here.
You can access each individual paper below:
Paper 1: Winning paper:
Title: SpaCular – Disclosure of spatial peculiarities of the Brexit
Authors: Joao Porto De Albuquerque (University of Warwick) , Konstantin Klemmer (University of Warwick) , Rene Weserholt (University of Heidelberg), Andra Sonea (University of Warwick)
Abstract: Immigration has consistently rated as the most important issue the UK faces, to a much higher degree than the average in the EU, despite UK not being among the EU countries with the highest share of foreign born or with the highest increase in foreign born population. Whilst the UK experienced, between 2002-2015, a 76% increase in immigration, at closer inspection data contradicts the stereotypical image of the immigrant so much misused during the Brexit vote: 47% of UK immigrants in the 15-64 age range have tertiary education, the highest proportion highly qualified immigrants by far among all EU countries. Additionally, non-European immigration consistently formed the majority of the immigration even after the A2 EU accession in 2007.
Title: Tension Points: A Theory & Evidence on Migration in Brexit
Author: Levi John Wolf, University of Bristol
Abstract: The GISRUK Data Challenge asked: was Brexit primarily driven by the rate of change in migration, rather than the total headcount? To interrogate this, I used local regression methods, hierarchical models, migration data provided by the Office of National Statistics, and a novel method to extract population volatility from fine-grained Consumer Data Research Centre Data. Depending on the implicit hypothesis used to operationalize the contest question, I find Brexit voting at local authority level was driven in part by the rate of change in their population structure, but some types of change drove Leave voting and some drove Remain.
Title: Rapid change in ethnic composition – part of a wider Brexit picture?
Authors: Edward Abel et al, University of Manchester
Abstract: Correlations have been reported by The Economist between a 13 year rate of change in the proportion of foreign born individuals in UK local areas and voting in the 2016 European referendum. Using regression and principal components analysis, we confirm the significance of rate of change in ethnic diversity, driven by a change in White British, White Other and Black populations. This varied by region, and the time window used for comparison also significantly impacts model results. Superficial correlations between change in Asian and Black populations and ‘leave’ voting were eliminated by including model variables linked to urban living. Age composition, turnout and population density all had smaller effect sizes than changes in ethnic composition.
Title: Investigation of the impact of changes in ethnic mix on the EU referendum result
The authors have requested for the CDRC to not publish this paper in order for it to be progressed into a journal paper.
Author: Aihua Zhang and Paul King, University of Leicester
Abstract: The Economist article “The immigration paradox Explaining the Brexit vote” (14 July 2016) argues that the rate of change in the number of migrants in an area, rather than the total headcount influenced the Brexit vote. This argument, however, was simply made by looking at the individual factor of ‘foreign-born’ (or ‘UK-born’) population in isolation, with no formal analysis. By contrast, in her recent research paper published in World Development (Volume 102, February 2018), Zhang applied two statistical analyses (Multivariate Regression and Logit Regression) to the actual referendum voting data obtained from the Electoral Commission and the UK’s latest census data. She found that the impact of the factor of ‘UK-born’ (and thus ‘foreign-born’) population proportions on the EU referendum results was insignificant, while other factors, such as, Higher Education, Turnout, Gender dominated the impacts on the outcome of the EU referendum. To address the question of ‘whether the rate of change in number of migrants in an area influenced the Brexit vote’, we apply the two aforementioned statistical approaches to the CDRC geographical dataset of 11 ethnicity categories that are mapped to the referendum results by Local Authority district or Council Area. Total headcount /level of immigration had no significant impact on the Brexit vote; the rate of change in ethnic mix had some minor impact on the referendum result;Areas in England and Wales with higher increase rates of British Chinese populations tended to vote Remain.