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ISBN Number: 9789264009875
OECD Regions at a Glance: 2007 Edition
National economic performance is often compared across countries, and such comparisons are frequently used to highlight countries whose national policies appear to promote growth and development more successfully. However, national averages can hide wide regional differences in economic conditions and performances. OECD Regions at a Glance therefore presents a set of regional indicators – mainly in the form of graphs and maps – in order to identify those regions that outperform their country as a whole or the OECD area and those that lag behind. The patterns of development may differ widely in urban and rural areas, for example, and some areas may lag behind even when the national economy is performing well.
Part I presents a number of broad macroeconomic indicators of regional development, including the concentration of population, output, industrial concentration, and innovation, as well as the regional contribution to national growth in output and employment. In OECD member countries, population is generally fairly unevenly distributed among regions: in 2003, approximately 40% of the OECD population was located in just 10% of regions. The concentration was greatest in Australia and Canada, where 10% of regions accounted for 64% and 61%, respectively, of the national population (Figure 1.1).
Output and innovation are also fairly unevenly distributed among regions. In 2003, 38% of total OECD GDP was generated by only 10% of regions and 57% of all patents were recorded by just 10% of regions.
The contribution of few regions to national growth is also very significant. For instance during 1998-2003 more than half of OECD area employment growth occurred in just 10% of regions and over 40% of the total increase in GDP in OECD countries was spurred by 10% of regions.
In most countries, the concentration of the population has been increasing in recent years, partly owing to increasing urbanisation, a pattern that is reinforced by the greater availability of economic opportunities and services in urban areas. In 2003, almost half of the total OECD population (46%) was living in urban regions, and the concentration was particularly high in the Netherlands, Belgium and the United Kingdom.
By the same token, the proportion of the population living in rural areas has declined. The fact that younger people tend to migrate from rural to urban areas to a greater extent than older ones has also contributed to an increasing concentration of the elderly population in rural and intermediate regions. In most countries, dependency rates (the ratio of the elderly population to the working age population) are already high in rural areas, with implications for the capacity of such regions to provide adequate heath care and other services as populations continue to age.
Part II. Making the Best of Local Assets
Part II looks at some of the factors that may explain regional variations in economic performance and GDP per capita. These include differences in labour productivity, degrees of industry specialisation, education levels among the labour force, and rates of employment and labour force participation. Although substantial, international disparities in GDP per capita are often smaller than differences among regions of the same country. In the United Kingdom, for instance, GDP per capita ranged from five times the national average in the richest region to just above half the national average in the poorest. This is by no means an isolated example; there are also significant territorial disparities in Turkey, the United States, France, Poland and Mexico. In these countries, income per head in the richest region was at least four times higher than in the poorest.
These differences are also linked to urbanisation. In 2003, GDP per head in OECD urban regions was 51% higher than the country’s average; in intermediate and rural regions it was 77% and 64% of the national average, respectively. Higher GDP per capita in urban regions is a result of agglomeration economies. The clustering of businesses and people in urban regions and large towns improves the efficiency of the local economy and leads to higher productivity.
In today’s knowledge-based economies, a region’s growth prospects depend in part on its ability to generate and use innovation. This capability, in turn, depends on skills level of the regional labour force. The proportion of the adult population with tertiary education – university-level education, from courses of short and medium duration to advanced research qualifications – is a common proxy for a region’s skills level. Regional variations in educational levels are considerable. In France, Australia, the United Kingdom and Canada differences in tertiary educational attainments between the best and worst performing regions exceeded 30 percentage points. Differences were also considerable (between 20 and 30 percentage points) in New Zealand, Japan, the United States, Mexico, Hungary, Norway, Korea, Poland, Spain and Denmark.
Here again, urban regions tend to fare better than intermediate or rural ones: on average, 57% of the OECD adult population with a tertiary education lives in urban regions, 19% in intermediate regions and 24% in rural ones. The concentration in urban regions is often the result of migration away from rural areas. The existence of significant differentials in the return to education between rural and urban areas is a major incentive for individuals with advanced education to migrate to urban regions.
Differences in regional performance also reflect the extent to which the regional economy is able to utilise available labour. Unemployment rates and labour force participation rates provide useful indicators of this ability. Unemployment rates vary significantly among regions, and, in many countries, regional disparities have persisted for long periods of time. Such persistent disparities should encourage individuals to move from regions with high unemployment to regions with low unemployment. Mobility is not without cost, however, and even if in the long run the return to a move to another region would exceed the costs, mobility may be restrained by imperfect capital markets, risk aversion or social ties. Wage inflexibility is another potential cause of regional disparities in unemployment rates. If wages are set at the national level, regional differences in productivity should in theory result in higher unemployment rates in regions with low productivity. In fact, the evidence is mixed, although in 17 of the 25 OECD countries for which data were available, there was a negative correlation between unemployment rates and productivity levels, suggesting that wage inflexibility may indeed be a cause of high unemployment in areas with low productivity.
Part II is followed by an analysis of the key drivers of economic growth within regions, which highlights the different roles played by national and regional factors, economic policies and the existence of natural resources. Growth in regional GDP can be regarded as the joint result of several factors. First, regional performance is significantly affected by country-specific factors, such as national policies and the business cycle. Second, it depends on region-specific factors, such as demographic trends and natural resources. Finally, regional performance depends on regional policies, i.e. on the region’s ability to increase productivity, change industry specialisation to seize new market opportunities, increase the efficiency of the local labour market and invest in skills and innovation. The performance of OECD regions in 1998-2003 suggests that region-specific factors play a significant role in producing above-average rates of economic growth, and that the reverse is also true, i.e. that regional factors can significantly undermine growth.
Of course, the relative merits of different regions depend not only on macroeconomic indicators such as growth, income and employment opportunities, but also on a range of other factors that contribute to the quality of life. Part III examines regional patterns in a range of such quality of life indicators, including travel times, education, crime rates, home ownership and the environment. This list excludes health, which is such an important and complex issue that it deserves separate treatment in Part IV.
Travel times vary widely among regions. Sparsely populated countries, such as Australia, the United States and Canada, have the largest variations in travel times (about 34, 30 and 25 hours, respectively). In most European countries differences in travelling time are narrower, but Turkey and the United Kingdom are exceptions. Not surprisingly, accessibility tends to be lower in rural regions. On average, travel times are more than 3.5 hours from rural regions, about 2 hours from intermediate areas, and just 37 minutes from urban regions.
A highly educated labour force is a major factor in regional competitiveness, and enrolment rates in tertiary level education are a commonly used yardstick of skill levels. These rates vary widely from region to region, but Korea stands out as having not only the highest national average enrolment rate, but also the region with the highest enrolment rate of all OECD regions. Moreover, Korea’s lowest regional enrolment rate is above the highest regional rate in several OECD countries, suggesting that high levels of education have been a major factor in Korea’s economic development. Safety is also an important factor in the relative attractiveness of regions, and regional statistics suggest that crime rates vary widely across the regions of a given country. However, crime statistics are difficult to compare internationally, as they are affected by how crimes are defined in national legislation and by the statistical criteria used in recording offences. In addition, the propensity to report offences varies greatly, not only among countries, but also among regions in the same country. That said, the regional data suggest that, perhaps unsurprisingly, crimes against property are most prevalent in urban areas.
Part IV. Regional Focus on Health
Part IV examines a range of health indicators from a regional perspective, including mortality rates, premature mortality, the incidence of cancer, smoking and obesity, and health resources (numbers of doctors, nurses and hospital beds; access to medical technologies). One striking finding is that, in the majority of OECD countries, the male population in rural regions has the highest age-adjusted mortality rates. For females, with lower overall mortality rates than males, the pattern of adjusted mortality rates across types of region is not a clear one. Internationally, overall mortality rates were highest in Eastern Europe, where smoking, obesity and alcohol consumption are quite prevalent.
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For further information, please contact Vincenzo Spiezia by phone at + 33 1 45 24 97 45 or e-mail Vincenzo.Spiezia@oecd.org.