In an article for the “In Focus” section of Political Insight (September 2014, Volume 5, Issue 2) we looked at the results of this year’s election to the European Parliament.
In May 2014 the citizens of the 28 member states of the European Union (EU) went to the polls to elect the 751 new Members of the European Parliament (MEPs). The distribution of seats in the European Parliament is not directly proportional to each country’s total population. A so-called ‘degressive proportionality’ principle gives small countries a few more seats than what would have been the case if strict proportionality were applied. The voter turnout across the EU was 43%. Belgium and Luxemburg have the highest rate of voter participation (90%). On the other hand, the smallest voter turnout is observed in Slovakia (13%) and the Czech Republic (19.5%), whereas the United Kingdom had the 11th lowest rate in Europe (36%). More than 90% of all elected MEPs belong to one of the seven political groups of the European Parliament. There is a minimum of 25 members needed to form a political group and at least one quarter of all member states must be represented within this group.
The map series in the article presents the geographical distribution of the votes across member states. All countries in these maps are shaded using a rainbow colour scheme, starting with shades of dark red to demarcate the countries with the most recent association with the EU and moving through to a shade of violet for the oldest member states.
In an article for the “In Focus” section of Political Insight (April 2014, Volume 5, Issue 1) Danny Dorling and I looked at the overheating of the housing market in London. The graphics that I created for this feature visualise the considerable changes that took place in recent years using data from an analysis reported in the Guardian: In 2012, the total value of residential property in London was reported to be £1.37 trillion. The value of housing in the capital dominated the UK housing market. By 2013, the value of London housing had risen to £1.47 trillion. Some £100 billion had been added in just one year, an additional £30,000 per property if the rise had been evenly spread out across the capital. However, just as within England, this increase was concentrated within certain areas, particularly those closest to the centre.
When London is redrawn with each borough sized according to the value of residential property, the largest borough becomes Kensington and Chelsea where the average home now costs £1.57 million. Westminster, with more housing but an average value of ‘only’£1.1 million is almost as large. Wandsworth, more typical at £527,000 a home, is more than three times the size of Newham despite having just 30 per cent more homes. However, even in Newham, the ‘cheapest borough’, the average property now sells for over £218,000.
In an article for the “In Focus” section of Political Insight (December 2013, Volume 4, Issue 3) Jan Fichtner of the University of Frankfurt a.M. and I analysed the size of the foreign assets in the world’s largest offshore financial centres. All ‘offshore financial centres’ (OFCs) have one characteristic feature in common; they offer very low tax rates and lax regulations to non-residents with the aim to attract foreign financial assets. OFCs essentially undercut ‘onshore’ jurisdictions at their expense. The main beneficiaries are high-net-worth individuals and large multinational corporations that have the capital and expertise required to utilise OFCs. Beyond its geographical connotation the phenomenon of ‘offshore’ represents a withdrawal of public regulation and control, primarily over finance. Some important OFCs are in fact located ‘onshore’, e.g. Delaware in the USA and the City of London in the UK. However, historically many OFCs have literally developed ‘off-shore’, mostly on small islands.
OFCs as defined by Zoromé (2007) are jurisdictions that provide financial services to non-residents on a scale that is excessive compared to the size and the financing of their domestic economies. The graphic shows combined data on securities (Coordinated Portfolio Investment Survey by the IMF) and on deposits/loans (Locational Banking Statistics by the BIS) at the end of 2011. Capturing the two by far most important components of financial centres allows a reasonable approximation of the real size of OFCs while avoiding double counting. The larger the size of the circles on the map, the more foreign financial assets have been attracted to the particular jurisdiction. The vast majority of the almost US$70 trillion foreign financial assets are concentrated in North America, Europe and Japan. Areas with assets below $US50bn are not shown for their relative insignificance in the global context.
The Eurovision song contest voting patterns is a popular theme for the analysis of European identity and culture. In an article for the “In Focus” section of Political Insight (September 2013, Volume 4, Issue 2) Dimitris Ballas, Danny Dorling and I looked at the voting patterns of this year’s contest that was held in Malmö (Sweden). It has long been argued that there are clear patterns based on geographical region as well as cultural and linguistic bonds and there has typically been labelling of groups of countries that give their votes to each other as ‘blocs’ such as the ‘Scandinavian bloc’, the ‘Mediterranean’, ‘Western’, ‘Eastern’, ‘Scandinavian’, the ‘Balkan’ bloc etc. It can also be argued that political considerations may also affect these voting patterns and this may be particularly interesting in the recent Eurovision song context with voting patterns possibly influenced by the on-going political and economic crisis in the European Union (EU). This map series puts a focus on those countries being closely associated with the EU, either by being current members or official candidate member states (or official potential candidate for EU accession) and/or signed up to any of the following agreements: European Economic Area, the Schengen Zone, the European Monetary Union. The maps are based on European states that currently meet at least one of these criteria, leaving the remaining participants of the song contest aside.
In an article for the “In Focus” section of Political Insight (April 2013, Volume 4, Issue 1) Danny Dorling and I looked at the global geography of wealth. The map that I created for this feature displays data published by Forbes Magazine in spring 2012 (updated annualy). For 2012 Forbes counted 1153 billionaires across the globe (this figure includes families, but excludes fortunes dispersed across large families where the average wealth per person is below a billion). The total wealth of the billionaires was US$3.7 trillion – as great as the annual gross domestic product of Germany. Top of this league table is the US with 424 billionaires (or billionaire families), followed by Russia (96) and China (95). The following cartogram animation shows, how the distribution of billionaires and the distribution of their total wealth compares. Although there are only small changes between the two maps, it is quite apparent that the wealthiest in the wealthier parts of the world accumulate slightly higher shares of wealth than those living in the emerging economies such as China (though this may be some of the less worrying inequalities that exist globally):
(click for larger version)
George Osborne’s autumn statement on the government’s budget rekindled the ongoing debate about the fairness of the coalition’s spending cuts. How does it look like if you take a look at the richest and the poorest parts of society? In an article for the “In Focus” section of Political Insight (December 2012, Volume 3, Issue 3) Danny Dorling and I plotted the geography of the wealthiest of the wealthy in the United Kingdom in comparison to poverty.
The map that I created for this feature displays the distribution of the top 1% of the wealthiest 1% according to information published by the agency WealthInsight, one of the companies trying to gather information on this part of the publication that is a prime target for exclusive marketing. Displayed in the map are data on people with assets in excess of US$30 million and where they have their prime address registered in the UK. The extent of the data is very limited because WealthInsight releases data for only 20 UK cities and regions based on postcode areas (Northern Ireland is a single postcode area which is why we did not correlate that data with Belfast’s overall population). Here we have superimposed that data on a population cartogram of the country, drawing circles with an area in proportion to the numbers of super-rich (in red) over people living in each city (in blue). Where they overlap, the circles turn into a purple colour. Where there are more super-rich people than population alone would predict, there is an orange ring around a purple core, as shown around London. Where there are fewer super-rich than the population of a city might predict, there is a blue outer-ring, as around Birmingham. The underlying map shows the distribution of poverty in the UK in five shades of grey.
Cities such as Leeds, Birmingham and Nottingham have fewer super-rich than might be expected – partly because they are not especially affluent urban centres but also, most probably, because their postcode does not include nearby areas such as the North Yorkshire stockbroker belt or the Cotswolds. Aberdeen, in contrast, has some multimillionaires: beneficiaries of the oil boom with an Aberdeen postcode who live some distance from that city. With Manchester it is hard not to speculate that a few extra footballers may have tipped it over the limit.