GDP per capita is a commonly used measure of the affluence of a country. However, it is a coarse-grained aggregate measure (it is simply the value of goods and services produced within a country divided by the population of that country) which does not provide information on how income is distributed across the different regions of a country. By considering, instead, regional GDP per capita we can obtain a more fine-grained picture of the geographic distribution of income within countries. For example, we can gain insights into:
Much popular discussion of inequality focuses upon differences in income across a country as a whole. Such discussions run the risk of conflating differences between high-income and low income groups within a region with differences in the incomes of regions as whole (whereby both richer and poorer citizens within one region might have materially lower incomes than those in other regions).
At the other end of the spectrum, when regional analysis is conducted, it is often done at a fairly crude level of considering only the incomes of richer and poorer regions but without considering what proportion of the total population lives in those regions.
Specifically, here we consider regional data for Germany, France, Italy and the UK.
The analysis we provide here is based on regional (NATS-3 level) GDP per capita and population data for Germany, France, Italy, and the UK. The data is sourced from Eurostat and refer to 2014. In order to ensure comparability across countries we use GDP figures expressed in Purchasing Power Standards (PPS).[1] Using regional GDP per capita and population figures, it is possible to construct, for each country, a chart that describes which percentage of the country’s population t lives in an areas with a GDP per capital of less than a given value. An example of how such a chart (which we refer to as “GDP cumulative distribution chart”) is constructed and should be are interpreted is provided below.
Table 1.1: Illustration of the data underpinning a “GDP Cumulative distribution chart”
Country A | GDP per capita | Population (thousands) | % of country’s population |
Region A1 | 15,000 | 500 | 5% |
Region A2 | 20,000 | 1,000 | 10% |
Region A3 | 25,000 | 1,500 | 15% |
Region A4 | 30,000 | 1,500 | 15% |
Region A5 | 35,000 | 2,500 | 25% |
Region A6 | 40,000 | 1,500 | 15% |
Region A7 | 45,000 | 1,000 | 10% |
Region A8 | 50,000 | 500 | 5% |
The raw data consists of regional GDP per capita and population data (column two and column three in Table 1.1 ). If we rank the regions by GDP per capita (from lower to higher) we can then use information on the percentage of the country’s population living in each region to plot the following chart.
Figure 1.1: Interpretation of the “GDP cumulative distribution chart”
The chart above indicates that:
Notice that, since Table 1.1 the region with the highest GDP per capita is region A8 — with a GDP of €50,000 — in Figure 1.1 in correspondence of a value of 50,000 on the “X” axis, we have a “Y” value of 100 per cent — i.e. the entire population of country A has a GDP per capita of at most €50,000.
We start by providing national GDP per capita figures for each country and for the EU28 as a whole. As we can see in Figure 1.2 Germany is the country with the highest GDP per capita, followed by the UK and France. Among the countries considered, Italy is the only one with a GDP per capita level below the EU28 average.
Figure 1.2: GDP per capita (PPS) at the national level (2014)
Having presented national GDP figures we illustrate in Figure 1.3 the distribution of GDP per capita for each country. For presentational purposes, GDP levels are truncated at €65,000. Therefore Figure 1.3 does not reflect NATS-3 regions with extremely high levels of GDP per capita (we consider such regions in Section 1.5). In Figure 1.3 the vertical line indicates the GDP per capita level of the EU28.
Figure 1.3. GDP per capita cumulative distributions
From Figure 1.3 a number of interesting observations can be made:
We re-present similar information in the chart below, which indicates the distribution of national population across different GDP per capita ranges.
Figure 1.4: Distribution of national populations across different GDP per capita ranges
Cumulative distribution charts can also be used to gain insights on the degree of regional inequality within a country. We report below a variation of Figure 1.3 where the absolute level of GDP per capita on the “X” axis is replaced by a ratio the regional GDP over the national average. So, for a value of 0.5 on the “X” axis, the “Y” axis represents the share of the population living in regions with a GDP level which is less than half of the national average; for a value of 1.0 on the “X” axis, the “Y” axis represents the share of the population living in regions with a GDP level below the national average, etc. Again, for presentational purposes the “X” axis value has been truncated at 2.0 (i.e. we do not report distribution lines that reflect regions with a GDP per capita which is more than twice the national average).
Figure 1.5: Regional inequalities
The most striking initial observation is that at the average income, regional inequality is almost identical in Germany, France but materially lower in Italy. Whereas 70 per cent of Germans, French people and Britons live in regions with GDP per capita below the average, only a little less than 50 per cent of Italians do so. But the picture changes dramatically when we go to two thirds of the average (at or about the levels, relative to the average, often focused upon in definitions of poverty lines). There are materially more Italians living in regions with GDP per capita below around two thirds of the average (around 30 per cent) than of Britons and Germans (at around 10 to 15 per cent) and they in turn are much higher than the equivalent figure for France (only some 5 to 10 per cent).
To a large extent the results for Italy reflect the economic divide between southern Italian regions and the rest of the country and the fact that the south is significantly less populated than the north. In fact we can see from the bar chart in Figure 1.4 that, for Italy the two largest bars for Italy are in correspondence of low GDP per capita levels (i.e. 21 per cent of the Italian population resides in a region with a GDP lower than €17,600) and a level just above the national average (i.e. 31 per cent resides in a region with a GDP level between € 27,600 and € 32,600.).
Another aspect worth noticing from Figure 1.5 is that at higher income levels, in Germany there appear to be more regional inequality than in France or the UK. This is illustrated by fact that for “X” axis values larger than 1.0, the cumulative distribution line for Germany increases at a slower rate than those of France and the UK.
We conclude by providing figures for NATS-3 regions with extraordinary economic performance, i.e. regions with a GDP per capita higher than € 65,000. First, we note there are no such regions in Italy. Germany is the country with the highest share (around 6.1 per cent) of the national population living in outperforming regions followed by France (5.8 per cent of the population lives in an outperforming regions) and the UK (1.7 per cent). We also note that the GDP per capita level of two top performing regions of the UK is extraordinary high. This is the case because such regions include business districts (e.g. the City of London) with a low population relative to the economic wealth therein generated.
Figure 1.6: Outperforming regions in Germany
NATS-3 region | Percentage of national population | GDP per capita |
Aschaffenburg, Kreisfreie Stadt | 0.08% | € 65,200 |
Ulm, Stadtkreis | 0.15% | € 66,400 |
München, Kreisfreie Stadt | 1.74% | € 67,500 |
Bonn, Kreisfreie Stadt | 0.39% | € 71,300 |
Ludwigshafen am Rhein, Kreisfreie Stadt | 0.20% | € 71,800 |
Düsseldorf, Kreisfreie Stadt | 0.74% | € 74,400 |
Coburg, Kreisfreie Stadt | 0.05% | € 74,800 |
Stuttgart, Stadtkreis | 0.75% | € 76,100 |
Regensburg, Kreisfreie Stadt | 0.17% | € 79,600 |
Erlangen, Kreisfreie Stadt | 0.13% | € 80,700 |
Frankfurt am Main, Kreisfreie Stadt | 0.87% | € 88,600 |
Schweinfurt, Kreisfreie Stadt | 0.06% | € 89,900 |
München, Landkreis | 0.41% | € 95,300 |
Ingolstadt, Kreisfreie Stadt | 0.16% | € 118,000 |
Wolfsburg, Kreisfreie Stadt | 0.15% | € 131,000 |
Total of the national population | 6.06% |
Figure 1.7: Outperforming regions in France
NATS-3 region | Percentage of national population | GDP per capita |
Paris | 3.37% | € 85,000 |
Hauts-de-Seine | 2.42% | € 87,800 |
Total of the national population | 5.79% |
Figure 1.8: Outperforming regions in the UK
NATS-3 region | Percentage of national population | GDP per capita |
Kensington and Chelsea & Hammersmith and Fulham | 0.52% | € 73,500 |
Tower Hamlets | 0.43% | € 113,000 |
Westminster | 0.35% | € 268,800 |
Camden & City of London | 0.37% | € 350,900 |
Total of the national population | 1.67% |
[1] See http://ec.europa.eu/eurostat/w...
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