OECD
World
Forum
onon
Key
Indicators
OECD
World
Forum
Key
Indicators
Statistics,
Statistics,Knowledge
Knowledgeand
andPolicy
Policy
Palermo,
10-13
November
2004
Palermo,
10-13
November
2004
Territorial Indicators for
Regional Policies
Vincenzo Spiezia
Head, Territorial Statistics and Indicators, OECD
OECD World Forum “Statistics, Knowledge and Policy”, Palermo, 10-13 November 2004
2
Territorial Indicators
for Regional Policies
Vincenzo Spiezia
OECD – Territorial Statistics and Indicators
OECD World Forum
Palermo (Italy) 10 November 2004
OECD

Territorial Development Committee

Policy focus:
to enhance regional competitiveness

Working Party on Territorial Indicators

Statistical focus:
to benchmark the policy debate
OECD

2 “policy” questions for “statistics”
1.Why does regional matter?
National performances are driven by a
small number of regions
2.What objectives for regional policy?
Making the Best of
Local Resources
Answer 1
Regions as the Actors of
National Growth
From 1996 to 2001, employment growth
varied significantly among OECD
countries…
Australia
1.9%
Austria
1.2%
-0.9%
0.7%
Finland
France
Canada
-3%
Czech Republic
-3%
0.3%
Germany
Greece
0.3%
Greece
Hungary
1.2%
5.8%
Japan
-0.2%
0.7%
Korea
2.5%
Netherlands
2.6%
1.4%
OECD average
1.4%
Poland
Sweden
Switzerland
2%
United States
OECD
-6%
Poland
-6%
United Kingdom
1.6%
0.0%
2.0%
6.0%
8.0%
Average annual employment growth rate (1996-2001)
-10%
2%
14%
3%
-1%
3%
-3%
1%
-1%
7%
-1%
3%
-2%
8%
-3%
6%
-2%
United States
4.0%
6%
7%
-1%
Turkey
1.3%
13%
-1%
Switzerland
0.3%
United Kingdom
3%
Sweden
1.0%
4%
-2%
Spain
1.4%
9%
1%
-5%
Portugal
4.6%
-2.0%
-1%
Slovak Republic
Spain
-4.0%
-1%
Norway
3.0%
Turkey
Italy
Japan
Netherlands
-0.9%
2%
4%
New Zealand
-1.1%
Portugal
Slovak Republic
2%
1%
Mexico
1.1%
Norway
5%
2%
-3%
Korea
Mexico
New Zealand
-1%
Ireland
1.3%
2%
4%
-2%
Hungary
Ireland
Italy
7%
0%
-1%
France
Germany
3%
0%
Finland
1.8%
1%
1%
Denmark
2.1%
5%
0%
Belgium
2.4%
Denmark
-1%
Austria
Canada
Czech Republic
Australia
0.5%
Belgium
…but the differences in employment
growth were even larger among regions
within countries.
14%
-1%
-5%
6%
0%
5%
10%
15%
Variation of regional employment growth (1996-2001)
10% of regions explained for 56% of
employment creation in OECD countries.
Australia
75%
Belgium
Canada
17%
Czech Republic
76%
Canada
56%
Finland
27%
100%
94%
France
41%
France
Germany
80%
Finland
34%
Denmark
100%
Australia
55%
Austria
69 % of job losses in OECD countries
was due to only 10 % of regions.
Germany
64%
44%
Greece
92%
Greece
Hungary
32%
Korea
100%
Japan
79%
Korea
Mexico
23%
New Zealand
49%
53%
Norway
81%
100%
Mexico
43%
New Zealand
53%
Netherlands
53%
Japan
40%
Italy
100%
Italy
39%
Ireland
31%
Norway
69%
OECD average
69%
Poland
28%
56%
OECD average
Slovak Republic
50%
Portugal
Slovak Republic
91%
Sweden
Turkey
69%
Turkey
64%
0%
20%
40%
100%
51%
93%
United Kingdom
45%
United States
55%
Switzerland
34%
United Kingdom
100%
Sweden
59%
Switzerland
22%
Spain
43%
Spain
93%
Portugal
99%
Poland
60%
80%
United States
100%
120%
Proportion of national employment creation due to 10% of regions
with largest employment increase
39%
0%
50%
100%
15
Proportion of total job losses due to 10% of regions with largest
employment decrease
On average, 37 per cent of national unemployment in
2001 was concentrated in only 10 per cent of regions.
Australia
Concentration of unemployment does not
mirror concentration of the labour force.
0.9
62%
Austria
41%
Belgium
26%
Canada
0.8
55%
Czech Republic
28%
Denmark
22%
0.7
26%
France
34%
Germany
34%
Greece
Concentration index
Finland
48%
Hungary
26%
Iceland
57%
Ireland
25%
Italy
48%
Japan
36%
Korea
38%
Mexico
57%
Netherlands
25%
New Zealand
0.6
0.5
0.4
0.3
38%
Norway
0.2
23%
OECD average
37%
Poland
20%
Portugal
0.1
47%
19%
Spain
39%
Sweden
0.0
36%
Switzerland
31%
Turkey
48%
United Kingdom
33%
United States
50%
0%
10%
20%
30%
40%
50%
60%
Unemployment share of the 10% regions with the highest
concentration of unemployment
70%
.Slovak Rep
.Czech Rep
Poland
Hungary
Belgium
Turkey
Germany
Netherlands
Denmark
Italy
Ireland
Switzerland
France
Austria
Greece
New Zealand
Japan
Norway
Spain
Finland
United Kingdom
Korea
United States
Sweden
Portugal
Mexico
Iceland
Australia
Canada
Slovak Republic
Labour Force
Unemployment
Regional policy may give a significant contribution to
the reduction of total unemployment
-0.7%
-0.4%
-0.6%
-0.1%
-0.2%
-0.2%
-0.4%
-0.3%
-0.3%
-0.5%
-0.6%
-0.1%
-0.3%
-0.3%
-0.3%
-0.4%
-0.5%
-0.3%
-0.4%
-0.2%
-0.2%
-0.4%
-0.1%
-0.4%
-0.3%
-0.3%
-0.4%
-0.3%
-0.5%
Australia
Australia
Austria
Austria
Belgium
Belgium
Canada
Canada
Czech
Republic
Czech Republic
Denmark
Denmark
Finland
Finland
France
France
Germany
Germany
Greece
Greece
Hungary
Hungary
Iceland
Iceland
Ireland
Ireland
Italy
Italy
Japan
Japan
Korea
Korea
Mexico
Mexico
Netherlands
Netherlands
New Zealand
New Zealand
Norway
Norway
Poland
Poland
Portugal
Portugal
Slovak Republic Slovak Republic
Spain
Spain
Sweden
Sweden
Switzerland
Switzerland
T urkey
Turkey
United
United
United
States
United States
-1.0%
-0.5%
0.0%
Potential decrease in the national unemployment rate
due to a 1% decrease in the unemployment rate of 10%
regions with the largest unemployment
0%
7%
4%
13%
7%
5%
6%
15%
11%
10%
10%
2%
3%
14%
5%
5%
1%
2%
15%
8%
3%
21%
8%
3%
26%
13%
5%
12%
6%
5%
5%
10%
15%
20%
25%
30%
Une mployme nt rate in the 10% re gions with the large st
numbe r of une mploe d pe ople
Answer 2
Making the Best of Local
Resources
Identifying Unused Resources
Methodology

To compare regions against a common
benchmark

3 Benchmarks:
1. National Averages
2. OECD Average
3. Regional Type (Urban / Rural)
What explains regional differences
in GDP per capita?
Average Labour
Productivity
GDP
.
Employment at the workplace
Employment rate
Employment at the workplace
Labour force at the workplace
Commuting rate
Labour force at the workplace.
Resident labour force
Activity rate
Resident labour force
Resident population
What explains differences in
Average Labour Productivity?
Productivity is higher in Manufacturing than in
Agriculture or Services
Sectoral
Specialisation
Technology &
Infrastructures
What explains differences in
Employment Rates?
High-skills individuals have higher employment
rates than low-skills ones
Labour Force
Skills
Labour Market
Efficiency
What explains differences in
Activity Rates?
Activity rates are decreasing with age
Age-profile of the
population
Labour market
participation
Identifying Unused Resources
Natural
Endowments
Specialisation
Technology &
Infrastructure
Skills
Labour market
Ageing
Participation
Commuting
Unused
Resources
-Natural resources
-Infrastructures
-Geographic location
-Transportation
-Rural or urban type
-Tourism facilities
-Demographics
-Labour market
-Human capital
-Social capital
Identifying Unused Resources
Specialisation
Technology &
Infrastructure
Skills
Labour market
Ageing
Participation
Commuting
Natural
Endowments
Unused
Resources
Specialisation
Technology &
Infrastructure
Ageing
Commuting
Skills
Labour market
Participation
Benchmark 1: National
Looking at selected regions in Spain . . . . . . .
Productivity
Specialisation
Employment rate
Commuting
Age
Activity rate
La Coruña
Lugo
Orense
Pontevedra
Principado de Asturias
Cantabria
Álava
Guipúzcoa
Vizcaya
Comunidad Foral de Navarra
La Rioja
Huesca
Teruel
Zaragoza
Comunidad de Madrid
Avila
-40%
-20%
0%
+20%
+40%
Burgos
León
Comparing
GDP per capita of the region to the national average:
Palencia
Percent contribution
of each component
What
is the contribution
of each component
to the percent difference?
Salamanca
Presentation to the OECD Territorial Development Policy Committee, November 27, 2003
Benchmark 1: National
Looking at selected regions in Spain . . . . . . .
Productivity
Specialisation
Employment rate
Commuting
Age
Activity rate
La Coruña
Lugo
Orense
Pontevedra
Principado de Asturias
Cantabria
Álava
Guipúzcoa
Vizcaya
Comunidad Foral de Navarra
La Rioja
Huesca
Teruel
Zaragoza
Comunidad de Madrid
Avila
-40%
-20%
0%
+20%
+40%
Burgos
León
Comparing
GDP per capita of the region to the national average:
Palencia
Percent contribution
of each component
What
is the contribution
of each component
to the percent difference?
Salamanca
Presentation to the OECD Territorial Development Policy Committee, November 27, 2003
Benchmark 1: National
Looking at selected regions in Spain . . . . . . .
Productivity
Specialisation
Employment rate
Commuting
Age
Activity rate
La Coruña
Lugo
Orense
Pontevedra
Principado de Asturias
Cantabria
Álava
Guipúzcoa
Vizcaya
Comunidad Foral de Navarra
La Rioja
Huesca
Teruel
Zaragoza
Comunidad de Madrid
Avila
-40%
-20%
0%
+20%
+40%
Burgos
León
Comparing
GDP per capita of the region to the national average:
Palencia
Percent contribution
of each component
What
is the contribution
of each component
to the percent difference?
Salamanca
Presentation to the OECD Territorial Development Policy Committee, November 27, 2003
Benchmark 1: National
Looking at selected regions in Spain . . . . . . .
Productivity
Specialisation
Employment rate
Commuting
Age
Activity rate
La Coruña
Lugo
Orense
Pontevedra
Principado de Asturias
Cantabria
Álava
Guipúzcoa
Vizcaya
Comunidad Foral de Navarra
La Rioja
Huesca
Teruel
Zaragoza
Comunidad de Madrid
Avila
-40%
-20%
0%
+20%
+40%
Burgos
León
Comparing
GDP per capita of the region to the national average:
Palencia
Percent contribution
of each component
What
is the contribution
of each component
to the percent difference?
Salamanca
Presentation to the OECD Territorial Development Policy Committee, November 27, 2003
Benchmark 1: National
Number of regions by main determinant of regional economic performances in selected OECD member countries
Total
Country
High
Performance
Specialisation
EmployActivity
Productivity ment rate Commuting Age
rate
Low
Performance
Specialisation
Australia
5
0
4
0
0
0
Austria
10
0
4
0
5
Belgium
2
0
1
0
Czech Rep.
1
0
1
Denmark
3
0
Finland
3
France
1
3
0
3
0
0
0
0
8
0
1
25
0
12
0
10
0
3
35
1
0
0
9
0
6
0
3
0
0
11
0
0
0
0
13
0
12
1
0
0
0
14
1
0
1
0
1
12
0
7
0
5
0
0
15
1
1
0
1
0
0
17
0
9
1
1
0
6
20
13
0
4
0
8
0
1
83
2
59
0
13
0
9
96
Germany
12
0
10
1
0
0
1
37
1
21
1
0
0
14
49
Hungary
4
0
2
0
1
0
1
15
0
0
0
13
0
2
19
Ireland
2
0
1
0
1
0
0
6
0
4
0
2
0
0
8
Italy
55
4
12
10
2
0
27
48
0
19
9
9
0
11
103
Japan
6
0
3
0
2
0
1
41
15
19
0
5
0
2
Korea
8
n.a.
7
0
1
n.a.
0
8
n.a.
6
1
n.a
1
16
Netherlands
4
0
2
0
2
0
0
8
0
4
0
4
0
0
12
Norway
2
1
0
0
1
0
0
17
1
13
0
2
0
1
19
Poland
10
2
8
0
0
0
0
34
17
3
4
0
0
10
44
Spain
18
0
9
7
0
0
2
34
1
15
7
0
0
11
52
Sweden
3
0
0
1
1
0
1
18
0
7
1
3
0
7
21
UK
US
44
0
13
1
19
0
11
89
0
32
1
41
0
15
133
88
0
53
0
0
0
35
677
13
616
1
0
0
47
765
n.a. = not available.
Source: IDENTIFYING THE DETERMINANTS OF REGIONAL PERFORMANCE (GOV/TDPC/TI(2002)1/REV1)
EmployActivity
Productivity ment rate Commuting Age
rate
#
47
Benchmark 2: OECD Average


Regional variables are compared to
the OECD Average
Effects of performance factors are
measured as US $ PPP

Above average = “Gains”

Below average = “Losses”

OECD Territorial Level 2
Regional differences in real GDP per capita, 2000 - Europe
OECD average = 23,833 US $ (PPP)
Between 10,000 and 15,000 US $ above the average
Between 5,000 and 10,000 US $ above the average
Less than 5,000 US $ above the average
Less than 5,000 US $ below the average
Between 5,000 and 10,000 US $ below the average
Between 10,000 and 15,000 US $ below the average
More than 15,000 US $ below the average
0
250
Kilometres
500
Gains and losses in GDP per capita due to sectoral
specialisation, 2000 - North America
Gains: more than 1,000 US $
Gains: between 500 and 1,000 US $
Gains: less than 500 US $
Losses: less than 500 US $
Losses: between 500 and 1,000 US $
Losses: between 1,000 and 3,000 US $
Losses: more than 3,000 US $
0
1,000
2,000
Gains and losses in GDP per capita due to average
productivity, 2000
Europe
Gains: more than 10,000 US $
Gains: between 5,000 and 10,000 US $
Gains: less than 5,000 US $
Losses: less than 5,000 US $
Losses: between 5,000 and 10,000 US $
Losses: more than 10,000 US $
0
250
Kilometres
500
Gains and losses in GDP per capita due to
employment rates 2000
Europe
Gains: more than 1,000 US $
Gains: between 500 and 1,000 US $
Gains: less than 500 US $
Losses: less than 500 US $
Losses: between 500 and 1,000 US $
Losses: between 1,000 and 2,000 US $
Losses: more than 2,000 US $
0
500
Kilometres
1,000
Gains and losses in GDP per capita due to age of
population 2000 - North America
Gains: more than 3,000 US $
Gains: between 2,000 and 3,000 US $
Gains: between 1,000 and 2,000 US $
Gains: between 500 and 1,000 US $
Gains: less than 500 US $
Losses: between 500 and 1,000 US $
Losses: more than 1,000 US $
1,000
Kilomètres
2,000
Gains and losses in GDP per capita due to
participation rates 2000 – Japan
Gains: more than 2,000 US $
Gains: between 1,000 and 2,000 US $
Gains: less than 1,000 US $
Losses: less than 1,000 US $
Losses: between 1,000 and 2,000 US $
Losses: between 2,000 and 3,000 US $
Losses: between 3,000 and 5,000 US $
Losses: more than 5,000 US $
0
5
10
Benchmark 3: Regional Type
OECD Regional Typology
3 criteria:
1. Population density:
a community is rural if density < 150 inhabitants
< (500 in Japan)
2. % of population in rural communities:

> 50%  Predominantly Rural (PR)

< 15 %  Predominantly Urban (PU)

Between 50 and 15 %  Intermediate (IN)
3. Urban centre:

> 200K Rural  Intermediate

> 500K Intermediate  Urban
GDP per capita by regional type
In most OECD countries
PU > IN > National Average > PR
Exceptions:
Canada
Finland
Greece
Ireland
Korea
US
IN < NA
How much is explained by the Typology ?
GDP per capita
National Average
Rural Average
Regional Type
Rural Region
Region
Specific
Regional
Type
How much is explained by the Typology ?
Ireland
Slovak Rep.
Czech Rep.
Norway
France
Finland
Sweden
Austria
Denmark
USA
Hungary
Portugal
Japan
OECD
Greece
Spain
Mexico
Italy
Belgium
Germany
Netherlands
U.K.
Canada
Australia
Korea
81%
77%
76%
69%
69%
69%
66%
66%
65%
63%
63%
62%
60%
56%
56%
55%
55%
22%
38%
35%
35%
32%
48%
45%
44%
GDP per Capita
Differences from national averages explained by the OECD Regional Typology
From 0% to 25%
From 25% to 50%
From 51% to 75%
From 76% to 100%
GDP per Capita
Differences from national averages explained by the OECD Regional Typology
From 0% to 25%
From 25% to 50%
From 51% to 75%
From 76% to 100%
GDP per Capita
Differences from national averages explained by the OECD Regional Typology
From 0% to 25%
From 25% to 50%
From 51% to 75%
From 76% to 100%
0
500
Kilomètres
1,000
GDP per Capita
Differences from national averages explained by the OECD Regional Typology
From 0% to 25%
From 25% to 50%
From 51% to 75%
From 76% to 100%
0
250
Kilomètres
500
GDP per Capita
Differences from national averages explained by the OECD Regional Typology
From 0% to 25%
From 25% to 50%
From 51% to 75%
From 76% to 100%
0
500
Kilomètres
1,000
How much is explained by the Typology ?
Productivity
60%
Age
57%
Specialisation
54%
Commuting
53%
Activity rate
51%
Employment
rate
51%
Issues for Future Research
1.Regional GDP:

Not available in New Zealand and
Switzerland.

Only for Large Regions (TL2) in Australia,
Canada, Mexico, Turkey and USA.

Methodology for Small Regions (TL3) is
controversial.
Issues for Future Research
2. Employment by Industry:

Only 3 macro sector for Small
Regions (TL3)

Effect of specialisation is
underestimated
Issues for Future Research
3. Average Productivity is
the main factor of
competitiveness:



Statistics on capital and infrastructure
are rare.
Effects of technology and skills cannot
be introduced in this framework.
Social capital and information spillovers
are hard to measure.
Issues for Future Research
4. Rural/Urban works better in
some countries than in
others:


OECD Typology need to be refined.
Inclusion of geographic indicators
(distance, land use).
Further Information

OECD Regions at A Glance 2005

OECD Website:
www.oecd.org/gov/territorial
indicators