French Presidential Election 2017

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The second (and decisive) round of this year’s French presidential election has led to a decisive victory of Emmanuel Macron of the social-liberal En Marche! party which was founded just a year before. Unlike other recent votes that have reached global attention, this vote was not close and was widely described as a sweeping victory. Macron secured 66.1% (20,743,128) of the second round votes against Marine Le Pen of Front National who received 33.9% (10,638,475) of the votes. Another difference was also the political message which did less resonate with nationalist or far-right rhetoric but was built on a pro-European and liberal campaign. 11.52% of the voters gave neither of the two candidates their vote by handing in blank or null ballots. Turnout was at 74.46%, only slightly lower than in the first round (77.77%) where none of the 11 candidates could secure an overall majority (Macron received 24.01%, Le Pen 21.30% which put them in the second round).
The following cartogram shows how decisive the political landscape of France in the second round of the election including the winning candidate’s vote share at municipal level (commune) in an equal-population projection, complemented by a normal map showing the overall distribution of winning votes at the same geographical level:

Gridded Population Cartogram of the French Presidential Election 2017
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The regional geography of poverty, austerity and inequality in Europe

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Europe is currently suffering a deep political and economic crisis following years of turmoil and austerity measures that have disproportionately and brutally hit the most disadvantaged regions and citizens across most of the continent. At the same time, there has been a revival of nationalisms and divisions in this part of the world that, a decade ago, seemed to be united in diversity and moving towards ever-closer union. Concentrated poverty near to riches and profound spatial inequality have long been persistent features of all European countries, with disparities often being most stark within the most affluent cities and regions, such as London. In other parts of Europe levels of inequality and poverty have been reducing and are often much lower. However, the severe economic crisis and austerity measures have led, in many cases, to an enhancement of existing disparities. The following eight maps show how the regional geography has changed in the light of these developments:

GDP
Analysing the regional geography of poverty, austerity and inequality in Europe: Mapping GDP
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EU Migration to and from the UK

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The recent UK government defeat on its Brexit bill by the House of Lords based on the demand that ministers should guarantee EU nationals’ right to stay in the UK after Brexit was just the latest tale in the debate about EU migration and the United Kingdom’s role in it. The topic of migrants in the UK was an important element of the EU referendum campaigns in 2016 which led to the decision to leave the European Union. The government’s position sees the question of the rights of EU migrants as part of the upcoming negotiations with the EU where also the rights of UK citizens living in the European Unions need to be agreed. In terms of absolute numbers, this is a much smaller share of affected people (approximately 1.2 million UK citizens are estimated to live in other EU countries) compared to other EU citizens living in the UK (estimated at around 3.2 million). The following two maps show these numbers in comparison in their geographical dimension. Using the most recent annual estimates (published in late 2016 by the ONS and further data from the UN) the cartograms show the countries of the EU (excluding the UK) distorted by the number of UK citizens who are living in another EU country (left map) and by the number of other EU citizens who are living in the UK. The countries are shaded by their ratio between the number of UK migrants in the EU and the number of other EU migrants in the UK:

Migration maps between the UK and the EU
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Home Ownership in Britain

Housing has always been a decisive and sometimes divisive political issue. Home ownership has of course long been an aspiration for many people, and in the post-war period between 1953 and 1971 the number of households renting and owning reached an equal level, as documented in official census statistics for England and Wales. Ownership then surpassed renting, reaching its peak in 2001 at 69%. In the decade that followed, this number went down to 64%. The following two maps show the ownership rate in the UK in a conventional and an equal population projection:

Cartogram and map of home ownership in the UK
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US Presidential Election 2016

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The electorate of the United States of America has come to a decision about who is to become their next president. But not quite the whole electorate went to the polls: Turnout was at a long-term low with about 55% of voting age citizen having cast their ballot in the 2016 presidential election. Long gone are the days in which up to around 80% of the electorate went to the polls: This was last seen in the 19th century.
62,979,636 votes (46.1%) were cast for Donald Trump, while Hillary Clinton received 65,844,610 votes (48.2%). Other candidates put together reached 7,804,213 votes (5.7%). The following cartogram shows the distribution of votes for the two main candidates. Shown in diverging colours is each respective candidate who received the largest share of votes in each county. The cartogram itself shows an equal-population projection (gridded population cartogram) where each grid cell in the map is resized according to the total number of people living there. The main cartogram is accompanied by a second cartogram showing the distribution of votes that went to neither of the two candidates, and a ‘conventional’ reference map that also shows the states of Alaska and Hawaii:

Gridded Population Cartogram of the US Presidential Election 2016
(click for larger and labelled version)

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EU Referendum Statistics

Sanity is not statistical.” The political rhetoric in the aftermath of the EU referendum in the United Kingdom has brought us closer to Orwell’s infamous state of Airstrip One then one could have possibly envisaged. Each side of the debate twists and turns the statistics and ‘facts’ to keep supporting their argument, while neither political party has yet managed to end the political stalemate in the country, which finds itself in a state of ‘post-truth democracy‘ that it slowly entered during the pre-referendum campaigns. All sides claim what can be best explained with the German word ‘Deutungshoheit’ (a form of prerogative of interpreting the numbers behind the result as the ultimate truth). The real truth perhaps is that there is no truth, and the deeper you delve into the results, the more complexity you find. So here are some more less-talked about findings that emerge when taking a second look at the EU referendum statistics.
As mentioned in my earlier piece on mapping the referendum outcome, of all those who were allowed to vote in this referendum, 13 million people did decide not to cast their vote, which – despite the higher than currently usual turnout – is a significant number that could have made a difference in the close outcome either way. Amongst those that voted the immediate picture that emerged from the polls published after the referendum was confusing. Several polls, such as those paid for by Lord Ashcroft and used for this analysis, agreed that the older people were those who were more likely to vote for Leave, while the youngest had the largest share voting for Remain. However, when taking the total electorate into account, and considering those who – according to SkyData – chose not to vote (or spoilt their ballot), this picture became far less clear than it first seemed:

EU Referendum 2016 Statistics: Age groups

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