HLM BACKGROUND REPORT – TERRITORIAL …



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HLM Background report ON INNOVATION AND EFFECTIVENESS IN TERRITORIAL DEVELOPMENT POLICY

Territorial Benchmarking for Competitiveness Policy

Territorial Policy includes all development policies undertaken by public authorities – the central state as well as regional and local governments – with the aim of promoting a more efficient use of resources within specific geographical areas.

As different regions have different resources, Territorial Policy needs therefore to identify the comparative advantages of each region and assess whether its resources are fully exploited

The tool for acquiring this information is territorial benchmarking. Territorial benchmarking consists in comparing economic performances between regions and assessing the scope for a better use of their resources

Figure 1 provides a benchmark of territorial competitiveness by comparing the level of real GDP per capita in each region with the OECD average[1]. More competitive regions have a level of GDP per capita higher than the average while the opposite is true for less competitive regions.

Territorial competitiveness differs significantly between regions. About 60 per cent of the regions have a level of GDP per capita that is at least 5,000 US $ above or below the OECD average. In more than 10 per cent of the regions GDP per capita exceeds the OECD average by 10,000 US $ and more; about the same proportion of regions have a level of GDP per capita that is at least 15,000 US $ lower than the average

Territorial competitiveness is the result of five major factors: sectoral specialisation, average productivity, employment rate, age of the population and participation rate

Each of these factors contributes to explain the difference between the level of GDP per capita in a region and the OECD average. For instance, a high rate of employment would result into a level of GDP per capita higher than the average (gain); a low level of productivity would determine a level of GDP per capita lower than the average (loss).

Therefore, the observed differences in GDP per capita are the sum of the gains and losses due to each of these five components[2].

Figure 2 reports the gains and losses in GDP per capita due to sectoral specialisation. This component accounts for the fact that productivity (i.e.: GDP per person employed) is not the same across sectors. In particular, productivity is lower in agriculture than in manufacturing and services so that the higher the share of employment in agriculture, the lower the level of GDP per capita

Sectoral specialisation appears to be a main factor of low competitiveness in quite a number of regions. In a majority of regions of Greece, Mexico, Poland, and Turkey the loss in GDP per capita due to sectoral specialisation is above 3,000 US $. These losses are mostly explained by the high employment share of agriculture in those regions.

Figure 3 shows the gains and losses in GDP per capita due to average productivity, i.e.: differences in productivity that are not explained by sectoral specialisation. This component captures the effects of physical capital, infrastructures, skills and technology

Average productivity turns out to be a major factor of competitiveness. In half of the OECD regions, the gains or losses in GDP per capita due to average productivity are higher than 5,000 US $. In about 20 per cent of the regions, low average productivity accounts for a loss in GDP per capita above 10,000 US $. High average productivity generates a gain in GDP per capita higher than 5,000 US $ in more than 15 per cent of the regions.

Figure 4 reports the gains and losses in GDP per capita due to employment rates. On average, the effect of this component on competitiveness appears smaller than the impact of productivity. The gains or losses in GDP per capita due to employment rates exceed 1,000 US $ in only 25 per cent of the regions. Nonetheless, low employment rates have major effects on regional competitiveness in a small group of countries, notably Germany, Italy, the Slovak Republic and Spain

The gains and losses in GDP per capita due to the age profile of the population are shown in Figure 5. This component captures the effect of age on the size of the labour force. As participation rates are lower for young people, because of full time education, and elderly people, because of retirement, the size of the labour force will be lower the higher the percentage of young and/or elderly people.

In most regions, the age profile of population seems to have a positive effect on competitiveness. In about a half of the OECD regions, age determines a gain in GDP per capita higher than 1,000 US $. On the contrary, Mexico appears to be the only country where the loss in regional GDP due to age is above 1,000 US.

These results are largely explained by the share of young population. In Mexico, the share of young population is as high as to determine a rate of participation below the OECD average. The opposite is true in most regions where age has a positive effect on competitiveness.

However, what represents a comparative advantage today is likely to turn into an obstacle to competitiveness over the next decade. This is shown in Figure 6, which reports the index of labour market pressure, i.e.: the ratio between the number of people who will leave the labour force and the number of people who will enter it. A value of the index above one indicates that labour market pressure in a region is stronger than the OECD average while the opposite is true for a value of the index below one.

Apart few exceptions, Mexican regions are the only regions where the dynamics of population is likely to have a strong and positive effect on competitiveness. In above 80 per cent of the other OECD regions ageing will determine a reduction of the labour force and a decrease in GDP per capita. This process will be particularly intense in some regions localised in Finland, France, Germany, Greece, Italy, Japan, Portugal and Spain.

Finally, Figure 7 shows the gains and losses in GDP per capita due to differences in average participation rates: i.e.: differences in participation rates that are not explained by the age profile of the population. Low participation rates appear to be a major explanation of low competitiveness in quite a number of regions. In above 10 per cent of the regions, the loss in GDP per capita due to this component is above 5,000 US $. These regions are concentrated in a few countries, namely France, Greece and Italy. High participation rates have a large effect of competitiveness in about 15 per cent of regions. Most of these regions are located in Canada and the US.

To sum up, average productivity appears to be the main factor of territorial competitiveness. In half of the OECD region, the gains or losses in GDP per capita due to average productivity are higher than 5,000 US $. As differences in productivity are the result of a complex set of factors (physical capita, infrastructures, skills and technology), further analysis is needed to disentangle the effects of these factors.

Sectoral specialisation explains a large proportion of low competitiveness in most regions of Greece, Mexico, Poland, and Turkey.

Low employment rates are a major cause of low regional competitiveness in Germany, Italy, the Slovak Republic and Spain.

Over the next decade, ageing is likely to determine a decrease in competitiveness in all OECD regions except Mexico. This process will be particularly intense in some regions localised in Finland, France, Germany, Greece, Italy, Japan, Portugal and Spain

Finally, low participation rates are responsible for low competitiveness in most regions of France, Greece and Italy. High participation rates are a main source of competitiveness in a large number of regions in Canada and the US.

1. Regional differences in real GDP per capita, 20001. Regional differences in real GDP per capita, 2000"

1.a. Australia and Japan

OECD average = 23,833 US $

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Source: OECD Territorial Database.

1.b. Europe

OECD average = 23,833 US $

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Source: OECD Territorial Database.

1.c. North America

OECD average = 23,833 US $

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Source: OECD Territorial Database.

2. Gains and losses in GDP per capita due to sectoral specialisation, 20002. Gains and losses in GDP per capita due to sectoral specialisation, 2000"

2.a. Australia and Japan

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Source: OECD Territorial Database.

2.b. Europe

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Source: OECD Territorial Database.

2.c. North America

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Source: OECD Territorial Database.

3. Gains and losses in GDP per capita due to average productivity, 20003. Gains and losses in GDP per capita due to average productivity, 2000"

3.a. Australia and Japan

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Source: OECD Territorial Database.

3.b. Europe

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Source: OECD Territorial Database.

3c. North America

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Source: OECD Territorial Database.

4. Gains and losses in GDP per capita due to employment rates, 2000

4.a. Australia and Japan

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Source: OECD Territorial Database.

4.b. Europe

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Source: OECD Territorial Database.

4.c. North America

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Source: OECD Territorial Database.

5. Gains and losses in GDP per capia due to age of population, 20005. Gains and losses in GDP per capia due to age of population, 2000"

5.a. Australia and Japan

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Source: OECD Territorial Database.

5.b. Europe

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Source: OECD Territorial Database.

5.c. North America

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Source: OECD Territorial Database.

6. Labour market pressure due to ageing, 20006. Labour market pressure due to ageing, 2000"

6.a. Australia and Japan

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Source: OECD Territorial Database.

6.b. Europe

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Source: OECD Territorial Database.

6.c. North America

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Source: OECD Territorial Database.

7. Gains and losses in GDP per capita due to participation rates, 2000

7.a. Australia and Japan

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Source: OECD Territorial Database.

7.b. Europe

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Source: OECD Territorial Database.

7.c. North America

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Source: OECD Territorial Database.

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[1] Real GDP per capita accounts for differences in the cost of living between countries (Purchasing Power Parity).

[2] For instance, in the region of Queensland (Australia) GDP per capita is 2,209 US $ below the OECD average. This difference is the sum of: a gain of 337 $ due to specialisation in high productivity industries, a loss of 2,101 $ due to low average productivity, a loss of 417 $ due to low employment rate, a gain of 748 $ due to the age of the population, and a loss of 776 $ due to low participation rate.

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