5 Discussió
6.1 Limitacions i propostes de millora
than in rural regions
6.1 Capital metropolitan regions
performed well until the crisis led to
above average employment losses
In 2011, metropolitan regions (Map 1.7) accounted for 59% of EU population, 62% of EU employment and 67% of EU GDP. Accordingly, they are major cen- tres of employment and of business activity which have a higher level of productivity than elsewhere. In all Member States, GDP per head is higher in met- ropolitan regions than in other regions, though this does not always translate into higher growth rates. For example, between 2000 and 2011, GDP per head grew faster in non-metropolitan regions in Germany, Austria, Sweden, Finland, Portugal and Spain.
Nevertheless, in both the EU-15 and EU-13, real GDP per head in metropolitan regions grew faster than in
other regions between 2000 and 2008 (Table 1.4). Growth rates in capital city regions were especial- ly high, partly because of their higher productivity growth in the EU-15 and higher employment growth in the EU-13.
Growth in second-tier metropolitan regions was the same as at the national level, but below the rate in the capital metropolitan regions. Smaller metropoli- tan regions grew more slowly than the other met- ropolitan regions. In the EU-15, they had the same rate of growth as in non-metropolitan regions. In the EU-13, the smaller metropolitan regions had a sig- nificantly lower rate of growth than the non-metro- politan ones.
The crisis had a different effect on the metropolitan regions in the EU-15 and the EU-13 between 2008 and 2011. In the EU-15, GDP in the capital metro- politan regions declined at the same rate as in other regions. In the EU-13, GDP in the capital metropolitan regions declined, while it grew in the other regions. In
Table 1.4 Change in GDP per head, productivity and employment per head by type of metropolitan region, 2000–2008 and 2008–2011
2000–2008 2008–2011
Average annual change (%) GDP per head Producti- vity Employment per head GDP per head Producti- vity Employment per head EU-15
Capital metropolitan region 1.4 0.9 0.6 -0.8 0.3 -1.1
Second tier metropolitan region 1.3 0.7 0.6 -0.8 0.1 -0.9
Smaller metro region 1.2 0.7 0.5 -0.6 0.2 -0.8
Non-metropolitan region 1.2 0.8 0.4 -0.8 0.2 -1.0
Total 1.3 0.8 0.5 -0.7 0.2 -0.9
EU-13
Capital metropolitan region 5.5 3.6 1.9 -0.3 1.0 -1.3
Second tier metropolitan region 4.9 4.1 0.8 1.4 1.3 0.1
Smaller metro region 3.7 3.6 0.1 1.4 1.2 0.2
Non-metropolitan region 4.5 4.4 0.0 0.6 1.7 -1.1
Total 4.9 4.3 0.6 0.7 1.4 -0.8
EU-28
Capital metropolitan region 1.9 1.0 0.9 -0.7 0.5 -1.2
Second tier metropolitan region 1.6 1.0 0.6 -0.6 0.1 -0.7
Smaller metro region 1.3 0.8 0.5 -0.5 0.2 -0.8
Non-metropolitan region 1.6 1.3 0.3 -0.5 0.5 -1.0
Total 1.6 1.1 0.5 -0.5 0.4 -0.9
both cases, this was accompanied by a larger reduc- tion in employment than elsewhere.
In the EU-15, in second-tier and smaller metropolitan regions, productivity growth was low and employ- ment declined, the fall in GDP per head being similar to that in the EU-15 as a whole.
In the EU-13, in second-tier and smaller metropolitan regions growth of GDP per head was twice the EU-13 average as a result of high productivity growth and no reduction in employment. It will be interesting to see whether this launches a period of higher growth rates outside the capital metropolitan regions lead- ing to a narrowing of the gap in GDP per head with the latter.
A new ESPON study3 specifically examining the performance of second-tier cities concluded that although some of these make a substantial contri- bution to the national economy, in most countries, they do not contribute as much as capital cities. It is
argued that they could contribute more, however, if they were given greater EU and national support. The tendency to over-invest in the capitals and un- der-invest in second-tier cities is shown to be strong in many countries and it is arguable that higher level governments should resist this tendency and create territorial policies specifically for second-tier cities. This highlights the importance of a tailored, place- based development policy and of taking explicit ac- count of the different territorial impact of national policies on R&D, innovation, education and skills and transport and connectivity.
6.2 GDP growth in rural regions was
lower prior to the crisis, but proved
more resilient during the crisis years
Between 2000 and 2008, real GDP per head in rural regions (Map 1.8 and Box) in the EU-28 grew by 1.7% a year (Table 1.5), similar to the rate in other types of region. The only difference was that productivity inTable 1.5 Change in real GDP per head, productivity and employment per head growth by urban-rural typology, 2000–20011
2000–2008 2008–2011 2011
Average annual change (%)
GDP per
head Producti- vity Employment per head GDP per head Producti- vity Employment per head GDP per head (PPS) index EU-28=100 EU-15 Urban 1.3 0.8 0.5 -0.9 0.2 -1.0 124 Intermediate 1.2 0.7 0.5 -0.6 0.3 -0.8 100 Rural 1.2 0.7 0.5 -0.5 0.4 -0.9 90 Total 1.3 0.8 0.5 -0.7 0.2 -0.9 110 EU-13 Urban 5.5 3.6 1.9 0.7 0.9 -0.2 108 Intermediate 4.6 4.2 0.4 0.5 1.5 -1.0 57 Rural 4.3 4.5 -0.2 0.6 1.6 -1.1 46 Total 4.9 4.3 0.6 0.7 1.4 -0.8 64 EU-28 Urban 1.5 0.9 0.7 -0.8 0.2 -0.9 122 Intermediate 1.5 1.0 0.5 -0.4 0.4 -0.9 90 Rural 1.7 1.5 0.2 -0.3 0.7 -1.0 74 Total 1.6 1.1 0.5 -0.5 0.4 -0.9 100 Source: Eurostat and DG REGIO calculations
Chapter 1: Smart growth
19
City size, agglomeration benefits and metropolitan governanceIn all OECD countries, productivity and wages increase with city size (Figure 1.9). As a result of their high levels of productivity and their sheer size, large urban agglo- merations contribute substantially to national growth.
Why are larger cities more productive?
The productivity of cities depends on a great many factors, such as having companies which are innova- tive and skilled workers. Productivity, however, at least up to a certain point, increases with the size of cities, which raises the question of why. The reasons are, first, that larger cities tend to have higher levels of human capital, even though the relationship with city size is often non-linear, in the sense that the shares of both very high skilled workers and low skilled increase at the same time. Secondly, larger cities typically have a larger share of high productivity sectors such as consulting and legal and financial services. Thirdly, lar- ger cities are more likely to be hubs or service centres through which trade, finance and other flows are chan- nelled. These flows typically require the provision of high value-added services. Fourthly, cities profit from ’agglomeration benefits‘, which means that, on ave- rage, the productivity of a person increases with the size of the city in which they live and work. Figure 1.10 shows productivity levels for cities in Germany and the US adjusted for difference in levels of human capital. Recent OECD estimates suggest that productivity in- creases by 2–5% for every doubling of the population (Ahrend et al. (2014a)), which is in line with similar studies for individual countries (Combes et al. (2011)). Agglomeration benefits are usually thought to arise from ‘sharing’, ‘matching’ and ‘learning’ (see, e.g.,
Duranton and Puga, 2004). In larger agglomerations, firms profit from a greater supply of local public goods, as well as ’shared’, or common, facilities such as public laboratories and universities. It is also easier for them to find suppliers that more closely match their needs. Similarly, a larger labour market allows a higher level of flexibility and workers to be better matched to jobs. Equally, the easier generation, diffusion and accumula- tion of knowledge in larger agglomerations facilitates access to technologies and skills. In addition, agglo- meration benefits are often thought to be related to people being better ‘connected’ in larger cities and to arise perhaps from higher levels of “knowledge based capital” (intangible assets) in the firms located there. Agglomeration benefits not only arise from the size of population in a city itself but they can also be ’bor- rowed; from neighbouring agglomerations. For every doubling of the population living in agglomerations within a 300 km radius, the productivity of the city in the centre is estimated to increase by 1–1.5% (Ahrend
et al. (2014a)). This might explain why in the US pro-
ductivity in urban agglomerations generally increases more strongly with population size than in European countries. Essentially, because distances between ag- glomerations tend to be less in Europe, smaller cities are not so disadvantaged since they ‘borrow’ agglo- meration benefits from neighbouring towns and cities.
The role of metropolitan governance structures in economic efficiency and well-being
Metropolitan areas typically span a number of admi- nistrative boundaries. They, therefore, often suffer from fragmented policymaking, and it is not uncom-
0 20,000 40,000 60,000 80,000 100,000 120,000 0 20,000 40,000 60,000 80,000 100,000 120,000
USA/Canada Europe (OECD) Japan/Korea Mexico/Chile
0.5 - 1 million inhabitants 1 - 2 millions inhabitants 2 - 5 millions inhabitants 5+ millions inhabitants GVA per person employed - USD (PPS)
Larger metropolitan areas are more productive Larger metropolitan areas are more productive Larger metropolitan areas are more productive Larger metropolitan areas are more productive Figure 1.9
Figure 1.9Figure 1.9 Figure 1.9
mon for there to be several hundred local authorities. If these are left to pursue policies independently of each other, they are unlikely to tackle the challenge of developing the economic potential of the metropolitan area as a whole and the well-being of the people living there in an adequate way. Research undertaken by the OECD shows that municipal fragmentation does indeed reduce economic growth (Figure 1.11) as well as the productivity of Metropolitan areas, estimates indica-
ting that a doubling of the number of municipalities per 100,000 people is associated with a reduction of 5–6% in productivity. It is likely that this in part is a result of sub-optimal provision of transport infrastruc- ture, exemplified by routes in many Metropolitan areas ending at administrative boundaries for no apparent reason. This can also increase the possibility of those living in badly connected areas being socially excluded. The potentially adverse effects of the fragmentation of municipalities, however, can at least be mitigated to a large extent by governance arrangements. More speci- fically, the existence of a central metropolitan gover- nance body is estimated to reduce the adverse effect of fragmentation on productivity by around a half. Metropolitan areas with a central governance body, on average, experience less urban sprawl, possibly as a result of more efficient use of land and the planning of transport (Figure 1.12). Similarly, in metropolitan areas with a transport authority, or some other body to coor- dinate transport, people tend to much more satisfied with the public transport system; the areas concerned also tend to have significantly lower levels of air pollu- tion (Ahrend et al. (2014b)).
0.5 1 1.5 0.5 1 1.5
Low Medium-low Medium-high High
Annual average growth of GDP per head, 2000-2010 (%)
Less fragmented metropolitan Less fragmented metropolitan Less fragmented metropolitan Less fragmented metropolitan areas have experienced higher areas have experienced higher areas have experienced higher areas have experienced higher growth growth growth growth Figure 1.11 Figure 1.11 Figure 1.11 Figure 1.11
Source: Ahrend et al. (2014b)
Relative degree of fragmentation
-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2
With Governance Body Without Governance Body
Central governance bodies and change in urban sprawl*
Governance institutions and Governance institutions and Governance institutions and Governance institutions and selected outcomes selected outcomes selected outcomes selected outcomes Figure 1.12 Figure 1.12 Figure 1.12 Figure 1.12
* Controlling for country fixed effects Source: Ahrend et al. (2014c)
58 63 68 73 78 58 63 68 73 78
With Transport Authority Without Transport Authority
Transport authorities -0.25 0.00 0.25 -0.25 0.00 0.25 50,000 500,000 5,000,000
City productivity (normalised)
Population size and productivity Population size and productivity Population size and productivity Population size and productivity by city by city by city by city Figure 1.10 Figure 1.10Figure 1.10 Figure 1.10 Population (log10-scale) Germany
Source: Ahrend et al.
West Germany East Germany -0.3 0 0.3 -0.3 0 0.3 300,000 3,000,000 30,000,000 Population (log10-scale) City productivity (normalized)USA
Chapter 1: Smart growth
21
rural region grew faster, while employment relativeto population (i.e. the employment rate) rose more slowly.
In the EU-15, GDP per head in rural regions grew slightly more slowly as productivity growth was lower than in other regions, but the employment rate in- creased at the same rate as in other regions.
In the EU-13, GDP per head in rural regions also grew more slowly between 2000 and 2008 than in other regions, though here productivity growth was higher and employment contracted relative to population whereas in other regions, it increased. The two ten- dencies may be linked, insofar as the higher produc- tivity growth was due to catching up in the use of technology and more efficient methods of working, including in agriculture, which in turn led to a reduc- tion in employment.
The crisis had a differentiated effect on rural regions. The reduction in GDP per head between 2008 and 2011 was less pronounced in rural regions than in urban ones in the EU-15. In the EU-13, growth rates of GDP per head between 2008 and 2011 were much lower than in the preceding period but still positive. Growth in urban regions was slightly higher than in others.
Employment declined in all types of region, by more in urban regions in the EU-15 and in rural regions in the EU-13. Productivity continued to grow in the EU- 15 and, more especially, in the EU-13. In both, growth was higher in rural regions than elsewhere.
In 2011, the differences in GDP per head between the three types of region in the EU-15 were much smaller than in the EU-13. In rural regions, average GDP per head was 90% of the EU average, in urban regions, 124% of the average, a difference of 34 per- centage points. In the EU-13, on the other hand, GDP per head in the rural regions was only 46% of the EU average, while in urban regions, it was 108% of the average, a difference of 62 percentage points.