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Policy guidelines for regions falling under the new regional competitiveness and employment objective for the 2007 - 2013 period in the fields of the knowledge economy and the environment, in line with the Lisbon and Gothenburg objectives
Call for tenders by open procedure N° 2004 CE 16 0 AT 039
Policy guidelines for regions falling under the new regional competitiveness and
employment objective for the 2007 - 2013 period
Vol. II Coutry Report. DENMARK
Prepared for: European Commission December 2005 DG REGIONAL POLICY Conception and analysis, accession negotiations unit
CSIL, Centre for Industrial Studies- Milan
EPRC, European Policies Research Centre and FAI- Fraser of Allander Institute, University of Strathclyde - Glasgow
DMIO, Department of Management and Industrial Organisation, Marche Polytechnic University - Ancona
Mazars & Guérard, Evaluation & Pilotage des politiques publiques-Paris
Country Expert: Mr. Hallgeir Aalbu, EuroFutures-Stockholm
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DISCLAIMER
This report was produced by a consortium led by CSIL-Centre for Industrial Studies (Milan) for
the Regional Policy Directorate General and represents the views of the contractor. These views
were produced in order to provide analytical support for the Commission services. They have
not been adopted by the Commission and do not necessarily represent the view of the
Commission itself or the Directorate General for Regional Policy.
The Team takes full responsibility for the data, information and judgments expressed in the
present report.
CSIL - CENTRO STUDI
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Reg. Soc. Trib. Milano n. 197622
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TABLE OF CONTENTS
EXECUTIVE SUMMARY.................................................................................................5
1 Scope and methodology ...........................................................................................9 1.1 Aim of the report ...................................................................................................9 1.2 Methodology for context analysis.............................................................................9 1.3 Structure of the report ......................................................................................... 10
2. General economic conditions ................................................................................13
3. Innovation and knowledge economy ....................................................................17
4. Accessibility..........................................................................................................19 4.1. Access to transport infrastructure ......................................................................... 19 4.2. Access to telecommunications and information technologies .................................... 24
5. Environment and risk prevention ..........................................................................27 5.1 General analysis .................................................................................................. 27 5.2 Specific Features ................................................................................................. 28
6. Implementation of Structural Funds .....................................................................29
7. Policy priorities assessment .................................................................................31 7.1. Findings from the statistical analysis ..................................................................... 31 7.2 Findings from the field analysis ............................................................................. 32
ANNEX I: Methodology for transport indicators ........................................................39
ANNEX II: Telecom indicators levels.........................................................................43
ANNEX III: Methodology for environment indicators ................................................45
ANNEX IV: Bibliography and sources of information .................................................49
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LIST OF ACRONYMS
CIS Community Innovation Survey
DG Regio Directorate General of Regional Policy of the European Commission
ERDF European Regional Development Fund
EKC Environmental Kuznets Curve
EPO European Patent Office
ESPON European Spatial Planning Observation Network
FA Factor Analysis
GDP Gross Domestic Product
ICT Information and Communication Technology
INRA International Research Associates (Europe)
NUTS Nomenclature of Territorial Units for Statistics
PC Personal Computer
PCA Principal Components Analysis
PPS Purchasing Power Standards
R&D Research & Development
SF Structural Funds
TLC Telecommunication
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EXECUTIVE SUMMARY
This Report offers an assessment of economic conditions and policy priorities for the regions falling under
the new Competitiveness and Employment Objective 2007-2013.
It is structured as follows:
1) the report presents some statistical data on the general economic conditions of the country.
2) a statistical analysis on the three ERDF themes: a) Innovation and the Knowledge economy; b)
Accessibility; c) Environment and Risk Prevention.
3) a discussion of the current experience with Structural Funds and some implementation issues.
4) a set of policy priorities as perceived by the team of independent experts. The methodology, sources of
data and description of indicators are explained in detail in Vol. I of the Report, that should be duly
considered.
Contributors to the Report include: the statistical team, the core team, thematic experts and the country
experts. The final version has been prepared under the responsibility of the core team (Milan).
Eligible Regions: the whole country is eligible, and considered as one NUTS II.
ß General Economic Conditions
Population density in Denmark is very close to the reference average of EU Competitiveness
regions. The national average for the share of employment in the primary sector is slightly
above the EU benchmark, while the share of employment in manufacturing is 16% lower of
the reference average.
In terms of economic performance the country ranking is high. GDP per capita is slightly higher
than the benchmark, unemployment well below, GDP growth similar to the average EU eligible
region, but productivity per employee growth is higher.
The most vulnerable part of the country are the islands, including Bornholm (50,000
inhabitants). The stronger economic area is the capital city, surrounded by a large commuting
area (most of Zealand).
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ß Innovation and knowledge economy
The innovation potential of Denmark can be ranked as intermediate. R&D expenditure is over
the benchmark, and the number of patents applications is relatively high, and the share of
firms’ turnover due to new products, as well. Employment in hi-tech manufacturing is well
below the benchmark, while employment in hi-tech services is higher. The share of population
with tertiary education is very high.
ß Accessibility
Multimodal transport accessibility and connectivity to transport terminals by car is ranked
intermediate. Trends of passenger transport in the country are very close to the EU-15
average. For freight transport, the pattern is different, with an increasing role of railway,
usually declining elsewhere. However there is 15 years scenario of the rail mode for the
country, and an increase for cars and trucks. Pipelines play an important role for the transport
of commodities The TEN-T priority projects of interest for Denmark include the Oresund fixed
link, the Ferner Baelt/Ferhmarnbelt railway, and the Baltic Motorway of the sea.
ICT/TLC indicators are high, as in other Nordic countries, on all dimension, including household
with internet access, holding a computer, and with broadband access (the latter more than
three times the benchmark).
ß Environment and risk prevention
The overall ranking for the country indicators in this area is intermediate. For energy
sustainability, efficiency and self-sufficiency are over the benchmark, while renewable
resources play a limited role. The environmental impact of transport may be lower with more
non fuel transportation than what is available. Rural and natural assets show an adequate
degree of protection, but e quite low degree of wilderness. Natural risk is low but technological
risk, while below the benchmark, is not negligible.
ß Implementation of Structural Funds in the current programming period
The country is currently eligible to the current Objective 2, with a multi-regional programme
covering one tenth of the population. In terms of current priorities, around one half are
targeted to the productive environment (mainly SMEs, tourism, RTDI, each with around 15%).
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Around 27% is going in human resources, 9% in ICT and the remaining in very small
measures in transport, energy, environment, social infrastructures, environment, etc.
ß Policy priorities for discussion
The key message of the analysis is that in Denmark the ERDF can offer a contribute focussing
on the priority Innovation and the knowledge economy, in combination with a limited allocation
to ICTs for SMEs. Transport accessibility and environment and risk protection, are only for very
specific projects to be considered for ERDF funding, given the limited funds available.
While the innovation indicators in the Denmark are already goods, the country needs a
competitive jump top face global competition. A balanced combination of funding of RTDI
capacities, stimulation innovation in SMEs and promoting entrepreneurship seems advisable,
while the scope for new financial instrument or incubators is very limited.
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1 Scope and methodology
1.1 Aim of the report
The aim of this Country Report is to offer the European Commission an overview of the
strengths, weaknesses, opportunities and threats faced by the regions eligible for the new
Competitiveness objective 2007-2013. It focuses on the three ERDF themes listed in the draft
regulation, and it has been prepared as a background document, with a view to supporting the
Commission in its own policy priorities analysis and negotiation with the Member States.
As a part of a comprehensive study on 19 countries including 167 regions, the present Country
Report is designed as a summary assessment of some key issues. It is a preliminary
assessment that should be completed by a much more detailed structural and policy analysis
needed at a later stage for the preparation of the Operative Programmes. Moreover, as
explained in detail in Vol. I (Statistical Analysis), and as requested by the Terms of Reference,
the present report is based mainly on standardised regional statistics and a common cross-
county approach. This has obvious advantages in terms of comparisons and benchmarking, but
is not designed to fully capture specific features based on local data, and this fact should be
duly considered when using it as a reference.
1.2 Methodology for context analysis
The analysis at regional level presents the following sections: general economic structure,
innovation and the knowledge economy, accessibility, environmental and risk prevention. For
each section a brief description is given according to a short list of indicators with the following
characteristics:
- they are consistent and available at NUT2 level;
- they are relevant for the ERDF thematic approach;
- they are, as far as possible, policy-oriented.
The choice of this set of indicators comes from the need to provide guiding principles for policy
priorities, rather than to develop comprehensive regional statistical data. For this reason it
should be clear that they give some highlights of the major trends in the regions and do not
offer a complete picture of all the needs and weaknesses experienced by the regions.
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The rationale of the data processing is the following:
- for each aspect (economic structure plus three themes) a linear composite indicator
is created and the region is ranked in comparison with all the other eligible regions;
- for each theme (except Environmental risks) the degree of correlation with the
economic performance is investigated, by means of a correlation analysis.
The basic idea is to discuss the main thematic trends in the regions, with respect to the ERDF
eligible interventions, in the light of the economic structure and trends and the relative
position of the regions as compared to a given benchmark (the EU eligible regions average).
This reading of the data helps to discover combinations of, for example, High Innovation and
Low Economic Performance, that may suggest the existence of unexploited potential, hence an
opportunity to invest more on transfer and adaptation than on R&D or tertiary education per
se. This analysis is included in Sections 2 to 5.
This set of information is then discussed from a more qualitative point of view on the basis of
inputs coming from an assessment of the current SF programming period and lessons learnt in
the field analysis carried out by the national expert.
1.3 Structure of the report
Section 2 briefly summarises the general economic conditions for the eligible regions, using the
following average annual data (2000-2002): regional population and its national share,
population density, employment share of manufacturing, a ‘rural/urban’ and a ‘presence of
manufacturing’ classification; and 1995-2002 averages for GDP per capita, rate of
unemployment, growth of GDP, labour productivity growth per employee, and economic
performance ranking. The latter ranking is crucial in the analysis. It is based on a linear
combination of two factors (‘levels’ and ‘growth’) arising from a factor analysis (see Vol. I for
details). Each data set is presented in comparison with a benchmark given by the average of
the EU 168 regions eligible for the objective. Often some additional macroeconomic
information is also included.
The following section is on Innovation and Knowledge Economy. It presents regional average
annual data (mostly 1995-2002) on R&D expenditure as a share of GDP, EPO applications per
million inhabitants, percentage of employment in high-tech services, share of population with
tertiary education, share of firms’ turnover due to new products (CIS data), and an overall
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classification based on a factor analysis. Regions are classified High, Intermediate or Low
performing in innovation with a combination of these data.
Section 4 is about Accessibility. It presents data on TLC and ICT (share of firms with Internet
access and websites and share of households with a PC and access to the Internet) and data
on transport indicators (the ESPON multimodal accessibility potential and connectivity to
terminals by car). The analysis is supplemented by recent and forecasted trends in travel
demand by mode (DG TREN data and scenario at 2020 (Tremove). A multi-index analysis is
given in the Annex.
Section 5 looks at Environment and Risk prevention. This includes standardised data on energy
sustainability (electricity efficiency, self-sufficiency, renewable sources and ranking); the
environmental impact of transport (vehicle density, non-fuel transport, anthropic degree,
urban/rural typology); natural and technological risk (flood hazard potential, burnt areas and
polluting sites). The reader should note that these data cannot cover specific sub-regional
environmental risks, but consider regional averages.
Section 6 gives a quick overview of the current 2000-2006 programming period, based on a
financial breakdown by re-classified priority and some qualitative comments based on the
evaluation results.
The last section is about the policy priorities assessment. The first part of it presents the
results of a correlation analysis between Economic Performance and Innovation, Access, and
Environment summary indicators. A similar cross-reading is given for Economic Performance,
Accessibility and Environment, while the presence of high Natural or Technological Risks is
considered as a critical issue per se.
After this combined reading of performance and structural data, the following section is more
qualitative, and based on other sources of evidence, including interviews with stakeholders,
official documents, evaluation reports, academic research, and the personal assessment by the
country expert. This leads to the suggestion of some indicative regional policy priorities, based
on the available evidence, to be checked at a later stage when the national frameworks and
regional programmes are available.
The report ends with a brief discussion of some implementation issues.
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2. General economic conditions
Denmark, differently from other small Northern countries in terms of surface (such as
Benelux), has a lower density of population, which scores around the reference average of the
168 eligible regions. Overall, the region has an intermediate degree of rurality/urbanization
and an intermediate presence of manufacturing activities.
Tab. 1 Structural indicators
Population
(thousands)
Population
density
Share of
primary sectors
on total
employment
Share of
manufacturing
on total
employment
Rural/urban
classification
Presence of
manufac-turing
Denmark 5,356 124 3.57 17.02 Intermediate Intermediate
EU eligible regions 313,711 129 3.34 20.18 Source: Eurostat –see vol. I
Tables 2-3 highlight the features of the high economic performance of Denmark. First, the per
capita GDP stands above the reference average, while the dynamics of GDP is slightly inferior.
Moreover, the employment performance has not affected the growth of productivity: in fact,
while the rate of unemployment is remarkably below the reference average, the dynamics of
labour productivity is more sustained.
Tab. 2 Economic performance indicators
GDP per capita Rate of
unemployment
Growth of GDP Growth of GDP per
employed person
Overall
Denmark 25,617 4.61 2.26 1.23 High
Average of EU
eligible regions
24,162 6.42 2.34 0.99
Sources: Eurostat and DG Regio – see vol. I
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Tab. 3 Economic performance indicators (European eligible regions=100)
GDP per capita Rate of unemployment Growth of GDP Growth of GDP per employed
person
106 72 96 124 Sources: Eurostat and DG Regio – see vol. I
As the whole country is one NUTS2 region, we will not discuss internal disparities within
Denmark. The most vulnerable part of Denmark consists of a number of smaller island
communities. Bornholm is the largest of these islands with 50,000 inhabitants. After some
years with moderate growth, the capital region has been the fastest developing part of the
country during recent years.
Measured by per capita incomes, Danish living standards have been in the top handful of OECD
countries for several decades. Moreover, Denmark has paid great attention to its social goals
such as income equality and environmental sustainability. Twenty years of comprehensive
reforms have put the economy on a robust footing without any short-term macroeconomic
imbalances. Denmark’s performance has been built on the foundation of a well functioning job
market, openness to trade and a comprehensive welfare system.
According to commuting data Denmark had 34 travel-to-work areas in 2000. This is 12 less
than in 1992. This increased commuting is a consequence of a more specialised workforce,
growing mobility, geographical diversity of new housing and rising housing prices in the cities,
which makes it more attractive to live in the surrounding area. In addition, most new jobs
have been created in the cities in recent years. The increased level of commuting has a
positive impact on the regional balance in Denmark. Thanks to increased commuting part of
the income growth has moved from the places of work in the cities to households in the
surrounding areas.
The commuter region around Copenhagen, which now covers most of Zealand, has grown
exceptionally fast in the 1990s. Holding 40 percent of the population in Denmark, this region is
the largest commuter region in the country. Also, the commuter regions around Århus, Vejle
and Aalborg have grown significantly. Approximately two thirds of the population live in the
commuter regions around the four largest cities in Denmark. The smallest commuter regions
are single municipalities located on islands, such as Læsø, Ærø and Samsø.
There is a trend towards concentration of young people in the large cities. Many young people
move to the cities to get an education. In the period 1990-2002 the commuter regions around
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the large cities experienced the highest rise in population figures. By contrast, in several
geographically marginal areas population figures have fallen because people move away.
There are not very large regional differences in disposable income per capita in Denmark. The
commuter region of Copenhagen performs above the national average in terms of both earned
income and disposable income. On Zealand and in a belt across Central Jutland the earned
income per capita is just above or below the national average. Three commuter regions –
Nakskov, Langeland and Læsø – have a disposable income per capita that is more than 10
percent below the national average. The regional balance in disposable income has largely
been stable during the last decade whereas there is a growing unbalance in earned income per
capita has somewhat decreased. This situation is mainly due to the relatively low growth rate
in the marginal areas. The regionally balanced disposable income per capita is the result of
regional income redistribution, through taxation, compensation and transfer systems.
The annual average employment growth rates were in 1994-2002 largest in city regions like
especially Copenhagen, Århus, Aalborg, Vejle, Kolding and Holbæk. Outside the large urban
areas the employment rate were not as high and in some parts of the country the employment
rate decreased; Bornholm, southern Funen, Lolland-Falster, Frederikshavn, Lemvig and
Haderslev. The relatively slow development in marginal areas is primarily caused by declining
employment in agriculture and fisheries, and in the related processing industry. The decline
has generally affected the whole country but it was mostly seen in the marginal areas due to
the processing industry’s relative importance to these areas.
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3. Innovation and knowledge economy
Denmark does not reach a high level in the ranking of innovation and knowledge economy
indicators, but stands in the average. However, as table 4 shows, its position derives from two
differentiated behaviours. While the R&D and EPO indicators point towards a not brilliant
performance, confirmed by a low level of high-tech manufacturing, the situation is different in
high-tech tertiary activities, whose presence is fairly good; beside that, the share of population
with tertiary education is more than satisfactory.
Denmark is characterized by a high degree of user-driven innovation, i.e. innovating activities
generated trough interaction with customers. The country does not have many large and
research-based companies, as its affluence more come from trade and small-scale industries
than from high-tech manufacturing companies.
Moreover, according to the recent European Innovation Scoreboard, Denmark is above the EU
average and is expected to “move ahead”.
Tab. 4 Indicators of innovation and knowledge economy
R&D
expenditures
on GDP
EPO application
per million
inhabitants
Percent. of
employment in
high-tech
manufact.
Percent. of
employment in
high-tech
services
Share of
population with
tertiary
education
Share of
turnover due to
products new to
the firms
Overall
ranking
DK 2.09 167 1.02 4.12 31.77 41.00 Intermediate
EU Elig
Regions 1.70 136 1.49 3.23 24.81 35.21
Sources: Eurostat and Community Innovation Survey – see vol.I
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4. Accessibility
4.1. Access to transport infrastructure
Concerning the access to transport infrastructure, the situation of Denmark appears as
intermediate (see table 5). In fact, considering its morphology and territory characteristics (a
small region with an average density, with most of the population concentrated in a few urban
centres), the intermediate endowment of secondary roads allowing access to primary nodes
qualifies the situation of this country as non critical in the field of transport infrastructure. A
similar situation arises for multimodal potential accessibility
Tab. 5 Indicators of access to transport
Connectivity to transport terminals by car Multimodal potential accessibility
Intermediate Intermediate
Source: ESPON.
Consequently, a recommendation for policy measures in this area does not emerge for
Denmark.
Transport context
Apart from bus and coaches, which in the last six years1 show a declining trend (opposite to
the positive one registered on average in the EU 15), the Danish passenger transport demand
trends are all very close with the European average values. This is not the case of freight
transport, where the data show a significant positive trend for the railway mode, which on the
contrary is declining on average in Europe, and a much more moderate trend in road haulage.
Modal shares are more favourable to non road modes for passengers, while for freight the very
high percentage reached by the pipeline mode is partially distorting the comparison with the
EU values.
1 European Commission, Directorate General for Energy and Transport, Eurpean Union Energy and Transport Figures, 2003.
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Tab. 6 Trends in travel demand – pkm 1990 = 100
Years Cars Bus and coaches Railway Urban rail Air
1970 70 49 80
1980 80 78 78
1990 100 100 100 na 100
1995 114 114 99 126
2000 124 98 110 178
2001 123 97 114 185
2001 EU 15 120 112 115 115 182 Source: EC –DGTREN.
Tab. 7 Trends in travel demand – tkm 1990 = 100
Years Road haulage Railway Inland waterways
1970 51 98
1980 83 94
1990 100 100 100
1995 108 115
2000 130 122
2001 129 120
2001 EU 15 143 95 117 Source: EC –DGTREN.
Tab. 8 Modal shares by mode of land transport – Passengers - 2001
Cars Bus and coaches Railway Urban rail Powered two wheels
Denmark 79.3 12.2 7.5 - 1.0
EU 15 80.4 8.8 6.5 1.0 3.2 Source: EC –DGTREN.
Tab. 9 Modal shares by mode of land transport – Freight - 2001
Road Rail Inland waterways Pipelines
Denmark 73.2 8.6 0 18.3
EU 15 75.5 13.1 6.8 4.7 Source: EC –DGTREN.
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Trends projections2
Baseline trends in transport demand, emissions and vehicle stock are derived from the
Tremove study3 for the period 2005-2020 and are used as background scenario for the
regional analysis. Expected trends in modal shares are more road oriented: Denmark would
experiment a reduction of the role played by the rail mode both for freight and for passengers,
at least in the business as usual scenario. In the absence of specific transport policies aiming
to a reduction of the use of private cars and trucks, these two modes are expected to increase
their role in the future. Coherently, the forecast show a consistent increase in trucks fleet,
although this data is biased as for the Netherlands the international component of the road
haulage sector.
Fig. 1 Trends in model shares. Percentage change 2005-2020. Modal shares
0% 20% 40% 60% 80% 100%
Car
Train
Coach
Urban PT
Plane
Slow
Trucks
Train
IWW
mod
es
%
2.020
2.005
Source: Tremove.
2 Trends have been derived from the Tremove database, data cannot be compared with the past trends presented in the previous section as the transport modes as well as the type of flows considered are different. Nevertheless they represent a likely trend in the absence of specific transport policies.
3 Tremove 2 Model has been developed by K.U Leuven and Transport &Mobility Leuven together with WSP, TRT, TRL, INFRAS and COWI, on behalf of DG ENV (2005).
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Fig. 2 Road vehicles stock
100
120
140
160
180
200
220
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Year
Car
Trucks
Source: Tremove.
Fig. 3 Trends in transport emissions
Emissions
25
50
75
100
125
150
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
CO2 N2O Nox
PM VOC
Source: Tremove.
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Regional analysis
Map 1 TEN-T priority projects
DK00DK00
Two rail and road TEN-T priority projects run through the Danish territory,
- the Oresund fixed link, completed in 2000, a railroad link across the Danish straits
from Copenhagen to Malmo with a four lane motorway running above a double track
railway. The new link consist of a four km tunnel under the sea, a four km long
artificial island and a 7,5 km bridge, the world longest cable-stayed bridge for road
and heavy rail. The project involved, as accompanying measures, the construction
of new road and rail access routes and a new railsation at the Copenhagen airport.
- The Ferner Baelt/Ferhmarnbelt railway, the construction of 19 km fixed rail and road
link, either a bridge or a tunnel or both, through the Fehmarn Straits between
Germany and Denmark.
Furthermore, also the Motorway of the Baltic Sea is expected to improve maritime connection
between Denmark and the Baltic and central European member States.
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4.2. Access to telecommunications and information technologies
Denmark is not dissimilar from other Nordic countries, showing a high communication and
computing culture. It is a heavy user of TLC and IT technology, where it invests more than the
European average (6.50% of GDP). It is known for having both a high computing and
communication culture and it shows a strong infrastructure in Information and Communication
Technology, in general, according to the traditional indicators: at the 2d level for fixed and
mobile telephony (with respectively, 60 to 69 fixed lines and 80 to 89 subscribers per 100
inhabitants), and at the 1st for PC availability and Internet access (with more than 50 PC and
50 Internet users per 100 inhabitants).4
Denmark is by all means amongst the good performers, within the Competitiveness Objective
regions, and show high access to ICT across the whole spectrum of indicators, both from the
supply and from the demand side, and with reference to mature as well as emerging and
innovative access typologies.
Table 10 depicts the situation in terms of access to TLC and ICT, where Denmark, as other
North European countries, scores high. Particularly, this performance is led by the investment
leadership of firms, which record both high levels of Internet access and web sites, and by a
sustained household adoption, with more than two thirds of units having a PC and almost 55%
access to the Internet.
Tab. 10 Access to TLC/ICT
Share of firms
with Internet
access
Share of firms
with a Web site
Share of
households with
PCs
Share of
households with
Internet access
Share of
households with
broadband
Internet access
Overall ranking
Denmark 97.0 75.0 67.7 54.3 16.6 High
EU eligible Regions 86.01 56.33 49.29 35.19 5.05 Sources: ESPON and INRA – see vol.I
4 See Annex II
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A note must be added on this respect, because Denmark stands out also as an interesting case
in which households compare relatively better than firms within the whole universe or eligibile
regions.
Tab. 11 Ranking of Denmark by access to TLC/ICT
Share of firms
with Internet
access
Share of firms with
a Web site
Share of
households with
PCs
Share of
households with
Internet access
Share of
households with
broadband Internet
access
Ranking 7 6 4 3 4 Sources: ESPON and INRA– see vol.I
Denmark is an outstanding example of well-balanced co-evolution; it is a country where both
economic performance and ICT uptake and access record a high level and are balanced. If an
effort may be exercised on ICT it might be directed towards accelerating the development of
supply-side ICT and increasing the access by firms.
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5. Environment and risk prevention
5.1 General analysis
The overall situation of Denmark with respect to environment and risk prevention does not
appear critical in any respect, especially considering its high level of economic performance. In
details, Denmark has an intermediate degree of energy sustainability, transportation impact,
natural assets, a low degree of natural risk and an intermediate degree of technological risk.
As a result, Denmark’s situation qualifies as non critical in the areas of environment and risk
prevention.
Tab. 12 Indicators of energy sustainability
Electricity efficiency Electriciy self-sufficiency Renewable sources of
electric energy
Overall ranking
Denmark 3.834 0.346 0.093 Intermediate
EU Eligible Regions 3.646 0.254 0.202 Source: EUROSTAT – NEW CRONOS (Regio) – see vol.I
Tab. 13 Indicators of transportation impact
TR1
Vehicles density
TR2
Non-fuel transportation
TR3
Traffic intensity
Overall ranking
Denmark 0.054 0.009 -0.279 Intermediate
EU eligible Regions 0.218 0.031 0.400 Source: EUROSTAT – NEW CRONOS (Regio) – see vol.I 1) Every transport indicator - TR1, TR2 and TR3 – should be interpreted according its own dimension (and colour in column chart). Indicators cannot be compared with each other because of the difference in scales used. See Annex. The value of the traffic intensity indicator (TR3) could be some time negative because of the method of normalization used to calculate it. Such a normalization method allows us to summarize the two heterogeneous variables which make up the indicator (“total number of driven intra-regional trips/Total Area” and “Total number of kilometres made by journeys produced-generated by the region/Total Area). Values produced by normalization are relative and not absolute values.
Tab. 14 Indicators of natural/rural assets
Degree of protection Wilderness degree Anthropic degree Urban/Rural typology Overall ranking
Denmark 0.100 0.122 0.055 3.345 Intermediate
EU eligible Regions 0.088 0.310 0.103 2.819 Source: IRENA Database and ESPON-CORINE Landcover Database – see vol.I
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Tab. 15 Indicators of natural and technological risk
Natural risk Technological risk
Flood hazard potential Share of burnt areas Overall ranking Polluting sites density Overall ranking
Denmark 0.000 0.000 Low 0.367 Intermediate
EU eligible Regions 0.763 1.622 0.447 Source: ESPON Database and EPER-EEA – see vol.I
5.2 Specific Features
Electricity efficiency and renewable energy
Denmark demonstrates an electricity efficiency similar to the Union average (around 3.8
million euros GDP produced for every gigawatt hour consumed), while electricity self-
sufficiency is slightly higher than the Union eligible regions average, and the share of
renewable sources is quite far from the EU average level.
As the composite indicator of energy sustainability shows, the Danish overall ranking is
intermediate.
Transport and environment
The non fuel transportation share is quite low (0,009), compared to the EU average.
Furthermore, traffic intensity and vehicles density indicators show very low values.
In synthesis, the transportation impact on environment is intermediate.
Natural resources assets and management
Denmark natural resources endowment, in terms of sites under Habitat and Birds Directive is
very similar to the average observed at the Union level, although the wilderness degree is
lower. The anthropic degree and the urban density indicators assume intermediate values.
Risk Prevention
The probability that natural negative events occur is very modest (values equal to zero
registered by the flood hazard potential and the burnt areas indicators), while, as regards the
technological risk, the polluting sites density indicator (sites under IPPC Directive) assumes an
intermediate value, quite near the Union average one.
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6. Implementation of Structural Funds
In the current period it is benefiting a multi-regional objective 2 support, covering around 10%
of the total population.
The overall aim is the reconversion and development of areas facing structural problems.
Particular emphasis is given to RTDI and ICT, and secondarily to human resources.
During the previous programming period the region achieved an employment growth more
than elsewhere and a stronger growth in knowledge intensive and high-technologies industries.
According to data from the mid term evaluation approved projects for the current period are
forecasted to create 2,800 new jobs, 143% of the target.
Fig. 4 EU Contribution by typology area – Denmark, Objective 2 (2000-2006)
Productive environment Human resources Basic infrastructure Technical assistance
Source: our processing of DG Regio data (programme complements).
Objective 2 has a Structural Funds contribution of 197 million Euro, moreover Denmark
benefits from an Objective 3 programme (413 million Euro)5 and a fishery special support (230
5 Real prices.
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million Euro). Together with Equal, Urban, Leader and Interreg support, Denmark receives a
total contribution from Structural Funds equal to 931,74 million Euro6.
Community added value of Structural Funds in Denmark are mostly leveraging of other
investments and attracting inward investments.
6 It includes also an additional amount of almost 33,24 millions EURO (total for Objectives 2 and 3 and Fisheries programme) in the framework of the performance reserve.
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7. Policy priorities assessment
7.1. Findings from the statistical analysis
Denmark is a high income country which has successfully implemented an employment-rich
model of development without a strong high-tech potential in secondary activities. However,
the level of education of the population appears satisfactory, and the diffusion of TLC and ICT
technologies is high, both among firms and households. Finally, the degree of transport
connectivity is intermediate and the environment and risk prevention side does not present
clear criticalities. As a result, Denmark can benefit from a policy directed at maintaining the
current path of development, preventing the emergence of potential areas of critically not yet
clearly manifested, such as the technological base and the secondary networks of transport.
Tab. 16 Economic performance versus innovation & knowledge economy, access to ICT and
access to transport.
Economic performance Innovation and knowledge economy Access to TLC and ICT Access to transport
Ranking Joint analysis Ranking Joint analysis Joint analysis
High Intermediate Uncorrelated High High performers Non problematic region Source: our processing.
Tab. 17 Economic performance versus environment and risk prevention
Economic
performance
Energy sustainability Transport impact Natural/rural assets
Natural risk Technological risk
High Intermediate Intermediate Intermediate Low Intermediate Source: our processing.
If we focus on entrepreneurship, Innovation and ICT, Denmark has an excellent economic
performance, especially in the Innovation sector. Nevertheless, in the future, the globalization
will challenge the Danish competitiveness. It is a matter of fact that Danish enterprises are
very good in adapting to the market, building cooperation network and introducing innovation
in the productive process as well in the product itself. The threat comes by the lack of a strong
research-base. Since the Danish enterprises are mostly SMEs, they could not afford to invest in
pre-market research and the innovation is mostly customer-driven.
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7.2 Findings from the field analysis
National analysis
Denmark is one single NUTS 2 region, and there will most likely be only one national Objective
Competitiveness programme and one Objective Territorial Cooperation programme in the next
programming period.
Denmark’s strong entrepreneurial traditions explain a considerable part of the country’s
favourable economic situation. The challenge for the future is to maintain this position as a
commercial centre. Especially Copenhagen’s location provides an advantage for the location of
Nordic and North European headquarters. A continued focus on entrepreneurship and
innovation as a source of international competitiveness is therefore a logical way forward.
Denmark has identified four “growth drivers”: human resources, innovation, new technology
and entrepreneurship. Policies for economic growth will be focused on these four drivers. The
main challenges for policies are:
• Human resources. Denmark has a good level of basic education and a flexible
workforce, but relatively few have a higher education. Research based education is not
used much utilised by the enterprises.
• Innovation. Danish enterprises are strong in market-based innovation and they do learn
from each other. They do however tend to compete on price rather than on new
products, and the cooperation with research and higher education is not well developed.
• New technology. Denmark has a good ITC infrastructure and is in the forefront
regarding ITC use in businesses. A more advanced use is less well developed, however,
as few companies are utilising ITC for customer support, e-learning etc.
• Entrepreneurship. There are entrepreneurial traditions and business services are
available, but only few new businesses becomes growing companies. Only a limited
number of start-ups are based on spin-offs from R&D.
Given this focus on the four growth drivers and the lessons learned from the current
programming period, our assessment on the view in Denmark concerning the 10 main
priorities for future Structural Fund support are as follows:
• Promoting innovation and R&D will be one of the Danish priorities for the next
programming period. The focus on SMEs fits the Danish situation well.
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• Promoting entrepreneurship is another of Denmark’s main priorities. Again, Denmark
will agree with the SME focus.
• Secondary networks is of relevance in some parts of the country only, notably on the
most remote islands where links to mainland Denmark are always discussed.
• Information society will also be a prioritised area of intervention, with a focus on the
use of the opportunities provided by ITC infrastructure (rather than on the
infrastructure itself).
• Investment in infrastructure linked to Natura 2000 are of less importance for the
discussion on regional policy and the use of Structural Funds.
• Regarding promoting the integration of cleaner technologies and pollution prevention
measures in SMEs there is an interest in the commercial potential of environmental
technologies – but more as a business opportunity than of concern for the environment
itself. Measures for such purposes would probably be placed under the “innovation and
business support” label rather than under “environment”.
• Rehabilitation of derelict industrial sites is not an important topic in Denmark.
• Supporting measures to prevent natural and technological risks are not an important
topic in Denmark when regional development and competitiveness are discussed, but it
might be of interest from a business opportunity perspective. Measures for such
purposes would probably be placed under the “innovation and business support” label
rather than under “environment”.
• Promotion of urban sustainable public transport is of less importance for the discussion
on regional policy and the use of Structural Funds.
There is an interest for development and use of renewable energy in the commercial potential
of environmental technologies – but more as a business opportunity than of concern for the
environment itself (e.g. Denmark’s leading position in windmill technology). Measures for such
purposes would probably be placed under the “innovation and business support” label rather
than under “environment”.
Since the Objective Competitiveness programme will be of limited size in Denmark, and since
the development situation is relatively balanced across the country, funding will have to be
concentrated to issues where they make a difference.
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There are of course a large number of good purposes where funding could be spent, but the
use of ERDF funding (as extra money on top of national efforts) will have to be discussed on
the basis of resources available in national budgets. That is why e.g. integration issues and
labour market issues are regarded as less important for Objective Competitiveness and
Employment.
The proposal for Denmark is to focus strongly on innovation and entrepreneurship.
Concentrating in a single thematic is a consequences of the financial dimension of EU
contribution since the Objective 2 program will be of limited size in Denmark comparing with
the available national resources. It is also to say that, based on the analysis above,
Environment and Accessibility do not represent an imminent and clear threat for a balanced
development. Denmark does not have much contaminated sites, and only limited natural and
technological risks. Further more, the country has for many years been one of the leading in
production of wind power. Urban transport is not seen as a major constraint to economic
development, neither is secondary links to TEN transport.
The decision to focus on innovation is consistent with the National Development Strategy
which is based on the so called “four drivers”: Innovation, ICT, Human resources and
Entrepreneurship”. The National Strategy aims to maintain the comparative advantage in the
innovative business sector with two priorities: Use of Knowledge and Entrepreneurship. The
four drivers are the main pillars to achieve these priorities. Environment and Accessibility will
be taken account as cross-cutting themes together with rural and urban development. It
means that the Program could implement a single intervention which might be environmental,
but this should have a very innovative nature (or e.g. linked with ICT or Entrepreneurship). In
other words, funding could nevertheless be used for purposes within the environmental,
energy or transport sectors, but then based on goals for the enhancement of competitiveness
and employment rather than focusing on these sectors themselves. The Danish development
strategy in represented in the scheme below:
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Given the structure of the business sector, the innovation strategy will have its core in the
support to the SMEs. One specific action will be strengthening the links between SMEs and
research and higher education. As a consequence, the future management of the SF will be
strictly coordinated and the ESF and EDRF will be included in the same strategically framework
(see the above scheme). Another specific action will concern the promotion the use of ICT by
SMEs.
Regional level
The whole Denmark is eligible as a NUTS2 region under the new programming period 2007-
2013. Although Denmark presents a very high degree of regional balance, there are still some
marginal areas relatively underdeveloped with respect to the rest of the country. Marginal
areas are mainly located along coastal areas in the following Danish counties (amter):
• Nordjylland (Skagen, Hjørring, Frederikshavn, Læsø)
• Southern part of Funen island (Svendborg, Ærø, Langeland)
• Storstrøms (Lolland-Falster
• Bornholm island (regional municipality)
• Municipalities in other counties (Tønder, Grenå, Mors and Samsø)
The marginal areas comprise 15 small and medium-sized regions (minor towns and their
hinterlands), comprising approximately 9 per cent of the country's total population. All of the
Rural/ Urban Development Accessibility Environment ……………
Hum
an R
eso
urc
es
Innova
tion
Entr
epre
neurs
hip
ICT
Use of Knowlegde Entrepreneurship
Maintain Innovative Comparative Advantages
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small commuter regions rank in this group. These regions can also be distinguished from the
other regions of Denmark by a variety of socio-economic factors. Employment in the service
sector, income per capita, employment growth and education levels are all below the national
average. Decrease in population is one of the most serious issues and the main strategy
adopted by the government is to raise travel allowances for commuters from these areas in
order to stimulate settlements there.
These areas share the issue of declining fishing opportunities and the urge to restructure this
industry or to convert industrial competencies to new productions and new businesses.
The relatively slow development in marginal areas concerns also the agricultural sector, and in
the related processing industry. This decline has particularly affected marginal areas because
these industries are of relatively greater importance to them than to the rest of Danish
regions. However, challenges faced by marginal areas vary significantly.
Whereas in terms of GDP per capita there are not significant disparities with the rest of
Denmark, in terms of earned income per capita the difference is higher so that the
performance of these areas is usually 10-20% below national average. Growth of earned in
income per capita has been high enough to reduce the gap with the rest of Denmark in four of
these areas (Morsø, Samsø, Ærøskøbing and Tønder). Other areas are actually increasing their
gap (Nykøbing-Falster, Frederikshavn, Nakskov, Grenå, Marstal, Rønne and Skagen). Skagen
represents a special case. The region was among the most prosperous regions ten years ago,
whereas today it lies at the bottom.
Employment in the primary sector is above national average. The average unemployment rate
in Objective 2 regions was 8.1% in 1999 compared to the national average of 5.8%. Several
marginal areas witnessed a decline in agriculture and fisheries and in the food, beverages and
tobacco industries that alone reduced employment rates by more than 0.5 per cent annually in
the period 1994-20027. Employment rates dropped especially in Bornholm, southern Funen,
Lolland-Falster, Frederikshavn, Lemvig and Haderslev.
The business sector of the marginal areas is usually characterised by low-tech companies. The
demand for technology services, research partnerships, etc. is limited. Education levels are
also systematically lower in marginal areas. This represents an important reason for the
relatively low productivity and income levels of these areas. Notably higher educational
qualifications are underrepresented. The eligible regions face special environmental
7 The Danish Regional Growth Strategy, The Danish Government, May 2003
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restrictions. These include vulnerable environments such as coastal zones or small islands
which have limited land use and/or fresh water resources.
Implementation issues
As far as management and implementation is concerned there is a wish to increase flexibility
by reducing the number of budget lines for future Structural Fund programmes, as this will
make budget reallocations less necessary.
Denmark has in the past used integrated projects (called framework projects) as a way to
reduce the administrative burden for participants, i.e. applying a parallel to the lead partner
principle also in domestic programmes. This will probably be applied also in the next
programming period.
From 2007 Denmark will have a new structure for regions and municipalities. The number of
regions will be reduced to five (from 14 at present) and the number of municipalities to 98
(from 271). This will have an impact on Structural Fund management. Most likely will the
present ERDF arrangement be continued, i.e. that the regions propose projects for funding,
while the National Agency for Enterprise and Construction does a legal control and takes care
of payments. The regions can themselves organise their partnerships (“growth foras”) – and it
might be more than one for each region. The necessary legislation passed the parliament in
June 2005, but the details are still to be developed.
Following the national reform and establishment of five regions (instead of the previous 14),
regional development will be a responsibility of the new regional councils together with the
regional partnership. A probable solution is therefore to implement the Objective
Competitiveness programme trough the five regions. Each of them will have a “growth forum”
that will serve as the regional partnership.
ERDF and ESF funding will be combined as far as possible. Denmark has already moved the
ERDF implementation and the ESF implementation responsibilities to the same agency at
national level: the Agency for Enterprise and Construction (under the Ministry of Economic and
Business Affairs). This was done to enhance the coordination and cooperation between the
two.
This arrangement will probably be maintained also for the future. The idea is to let the funds
work in concert and to use the four drivers of growth (human resources, innovation, new
technology, entrepreneurship) as pillars for the programme, with equal opportunities,
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environment, urban and rural as cross-cutting integrated issues. The programme will then be
possible to implement all over the country, but of course with a different focus from region to
region and from city to city depending on the local challenges and opportunities.
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ANNEX I: Methodology for transport indicators
The multi-index approach
Finding a unique measure of the transport conditions in a given region, even if the analysis is
focused on one main aspect like accessibility, is a very difficult task. Both demand and supply
conditions play a role and both can be seen from different perspectives so that each indicator
is hardly more than just a limited point of view. For that reason, we decided to use different
indicators, namely three indexes:
- Infrastructure Usage Index - IUIj
- Accessibility Index - AIj
- Connectivity Index - CIj
The Infrastructure Usage Index measures the level of road and rail demand entering the region
and leaving the region (i.e. generated and attracted traffic excluding trips starting and ending
in the same region) in comparison to the supply of major roads and rails. The index is
computed separately for road and rail and for passenger and freight8 by taking the ratio
between the demand and the length of the main infrastructures (e.g. motorways, dual
carriageway roads, etc.). Thus four separate ratios are computed. Then the logarithm of each
ratio is computed and a weighted average of the four logs is computed where the weights are
the modal shares of road and rail on passenger and freight demand. The weighted average is
the Infrastructure Usage Index. The index is greater for zone where the ratio between demand
and supply is higher, that is where infrastructure are more exploited.
The Accessibility Index is a synthetic measure of multimodal potential accessibility. It is based
on the assumption that the attraction of a destination increases with its size (in terms of
population or GDP) and declines with distance, travel time and costs. The accessibility model
used in the ESPON study assumes the centroids of NUTS3 regions as origins and destinations
and, then, calculates the minimum travel time (with respect to different modes of transport,
that is by road, rail and air) between the various centroids. This indicator of potential
accessibility contains parameters that need to be calibrated so that it cannot be expressed in
8 Generated and attracted traffic is estimated from the results of the European transport model SCENES.
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familiar units. The higher is the index the higher is the accessibility. As a consequence, NUTS3
data are standardised to the average accessibility of the EU25 countries. NUTS2 indicators
have been computed by the Statistical Team by averaging NUTS3 data provided by the ESPON
database.
The Connectivity Index is expressed as the reciprocal of the hours needed to reach by car
different transport nodes (rail stations, motorways accesses, seaports and airports) starting
from the centroid of each NUTS3 region. Thus, regional centroids are taken as origins while
transport terminal as destinations. The higher is the index the higher is the connectivity. Again
such an indicator is available for NUTS3 European regions from ESPON and it has been
averaged by the Statistical Team to obtain NUTS2 indexes.
All three indexes provide a piece of the story and there is not a hierarchy among them. As the
analysis in section 2 will show, the Infrastructure Usage Index is somewhat correlated to the
Accessibility Index, in the sense that zones where the former is greater than the median
(showing a lower performance in terms of availability of infrastructures with respect to the
generated and attracted demand), also the latter is greater than the median (showing a better
performance in terms of accessibility). In other words, not surprisingly, the most accessible
zones tend to be attract and generate more demand, in relative terms, than less accessible
zones.
Furthermore, more than the numeric values, the most useful information is how the regions
within a country are ranked according to each index and especially which performs better and
which worse. When a region underperforms according to all the indexes, this is a hint that
some problems exist concerning accessibility, and vice-versa if a region overperforms.
Therefore, the analysis consisted in the following steps:
a) For each index the median across the NUTS2 regions of a given country has been
computed: MED(IUI), MED(AI), MED(CI). The median has been preferred to the mean
because in most of the countries the distribution of the indexes is strongly asymmetrical
and so the mean can be influenced by one or two very high (or low) values.
b) Each region in the country has been classified as underperforming or overperforming in
terms of each of the three indexes: underperforming have been considered those regions
where the index is lower than the median (for the accessibility and the connectivity index)
or, vice-versa, higher than the median (for the infrastructure usage index). This
classification allows to compare regions in terms of a specific index.
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c) For each region has been computed the ratio between the value of the index for that zone
and the median value computed above across all the zones of the country: AIj/MED(AI) and
CIj/MED(CI) for the accessibility and the connectivity index or, vice-versa, the ratio
between the median value and the value of the index for the zone: MED(IUI)/IUIj for the
infrastructure usage index. These ratios are greater than one for zone overperforming and
lower than one for the regions underperforming.
d) For each region the three ratios computed above have been summed. The higher is the
sum and the better the region performs. However, as the aim of the analysis is not
computing a super-index, the value of the sum is not really relevant in itself. Instead, the
average and the standard deviation of the sums have been computed. The zones where the
sum of the ratios is lower than the average minus one standard deviation (SUMj < Average
– DevSt) can be considered as highly problematic with respect to the average conditions in
the country. The zones where the sum of the ratios is lower than the average minus 75%
of standard deviation (SUMj < Average – 0.75*DevSt) can be considered as problematic
even if at a less extent. On the opposite side, zone where the sum is higher than the
average plus one standard deviation (SUMj > Average * DevSt) can be considered as those
with less problems concerning their accessibility.
This analysis mixes quantitative and qualitative indications to provide a comparative picture of
region’s performances. It should be stressed that the results make sense in relative terms
(e.g. comparing the regions each other) rather then in absolute terms. In other words, a
region can perform worse than other regions of the country but this does not mean that the
accessibility is absolutely poor; if the overall situation is good in the whole country, even
regions classified as underperforming can enjoy a good level of accessibility.
Multi index analysis
The multi index analysis is based on three different indicators:
- Infrastructure Usage Index - IUIj
- Accessibility Index - AIj
- Connectivity Index - CIj
Denmark consists of one region only at the NUTS2 level, therefore the multimodal index
analysis cannot be performed. However, from the results of the SCENES model, the
Infrastructure Usage Index could be computed for two NUTS3 regions, as reported in the
following table. Infrastructure Usage, Accessibility and Connectivity indexes are compared with
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the mean values of the two neighbouring countries, Netherlands and Sweden. Although the
three countries have different characteristics, and therefore their comparison should be
considered only as an indication, it is interesting to notice that the three indexes for Denmark
are all included between the high Nederland values and the low values of Sweden ones, and in
general more near to the Swedish values. It should be noted that, also from the point of view
of population density (122 inhabitants per km2), Denmark is very close to Sweden. From the
above information, the Denmark region appears to be in line with the average characteristics
of the area.
Indexes for Denmark compared with Sweden and Nederland
SCENES Region IUI AI CI
Hovedstadt & Ost f Storebaelt 32.6 91.8. 2.09°
Vest for Storebælt 28.0 91.8. 2.09°
Sweden Median/ Mean1 28.2 74.3 1.7
Nederland Median/Mean 43.8 123.7 4.3 1 The mean of the summary statistics exclude the Övre Norrland region.
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ANNEX II: Telecom indicators levels
Sources and definitions
The source is: ESPON project 1.2.2 Telecommunication Services and Networks: Territorial
Trends and Basic Supply of Infrastructure for Territorial Cohesion.
Main telephone lines per 100 inhabitants:
Level 1 = >70
Level 2 = 60-69
Level 3 = 50-59
Level 4 = 40-49
Level 5 = 30-39
Level 6 = <30
Cellular mobile subscribers per 100 inhabitants:
Level 1 = >90
Level 2 = 80-89
Level 3 = 70-79
Level 4 = 60-69
Level 5 = 50-59
Level 6 = <50
Estimated PC per 100 inhabitants:
Level 1 = >50
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Level 2 = 40-49
Level 3 = 30-39
Level 4 = 20-29
Level 5 = 10-19
Level 6 = <10
Internet (users per 10000 inhabitants):
Level 1 = >5000
Level 2 = 4000-4999
Level 3 = 3000-3999
Level 4 = 2000-2999
Level 5 = 1000-1999
Level 6 = <1000
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ANNEX III: Methodology for environment indicators
Sources and definitions
Indicators at regional level Nuts II
1 - Energy
Indicator Definition Year Source
EN1 GDP / total electricity consumption 2000 EUROSTAT – New
Cronos (Regio)
EN2 Total electricity production capacity/ total
electricity consumption
2000 EUROSTAT – New
Cronos (Regio)
EN3 (Total electricity production capacity –
Thermal power – Nuclear power)/ Total
electricity production capacity
2000 EUROSTAT – New
Cronos (Regio)
Energy
sustainability
Energy sustainability indicator + Energy
efficiency indicator
2000 EUROSTAT – New
Cronos (Regio)
2 - Transport
Indicator Definition Year Source
TR1 Vehicles Density: Total Number of
Vehicles/Total Area
2000 EUROSTAT – New
Cronos (Regio)
TR2 Non-fuel Transportation: Electricity 2000 EUROSTAT – New
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Consumption in the Transport Sector/ Total
Electricity Consumption
Cronos (Regio)
TR3 Traffic Intensity: (Total number of driven
intra-regional trips/Total Area) + (Total
number of kilometres made by journeys
produced-generated by the region/Total
Area)
2001 EUROSTAT – New
Cronos (Regio)
Transportation
impact
Traffic intensity sustainability indicator –
Clean transportation indicator
EUROSTAT – New
Cronos (Regio)
3 - Natural resources
Indicator Definition Year Source
NA1 Degree of protection: Area under Nature
Protection/Total Area
2003 Irena Database
NA2 Wilderness degree: (Forest Area + Semi-
Natural Area)/ Total Area
1996 Espon Corine Landcover
Database
NA3 Anthropic degree: Artificial surface/ Total
Area
1996 Espon Corine Landcover
Database
NA4 Urban-Rural typology 1996 Espon Corine Landcover
Database
Natural/rural
assets indicator
(factor score – lowest score)/ (highest
score – lowest score)*100
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4 - Natural hazard and Technological risk
Indicator Definition Year Source
RK1 Natural hazards with anthropic
implications-1: Regional flood hazard
potential
1996-
2002
Espon Database
RK2 Natural hazards with anthropic
implications-2: (Size of burnt areas/Total
area)*1000
2000 Espon Database
RK3 Polluting Sites Density: Number of
Installations under IPPC obligation (IPPC
Sites)/Total Area (hundreds Km2)
2000-
2001
Eper-EEA
Natural risk
indicator
[(RK1 – lowest value)/(highest value –
lowest value)*100] + [(RK2 – lowest
value)/(highest value – lowest value)*100]
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ANNEX IV: Bibliography and sources of information
Economic Survey of Denmark, 2005. OECD.
The Danish Regional Growth Strategy, The Danish Government, May 2003. Danish Ministry of
Economic and Business Affairs.
OECD: “Environmental performance (I cycle). Conclusions and recommendations, 32 countries
(1993-2000)”, OECD working party on environmental performance. November 2000.
International Energy Agency (IEA), “Energy balances”, IEA Energy Statistics, 2000.
