D5 Annex report WP 2: ETISDatabase methodology ... - ETIS plus

D5 Annex report WP 2: ETIS­Database methodology
development and database user manual – Socio economic
data V2.1
CONTRACT N°: GMA2/2000/32051­SI2.335713 ETIS­BASE
PROJECT N°: 2.1.1/9
ACRONYM: ETIS­BASE
TITLE: Core Database Development for the European Transport policy Information System (ETIS)
PROJECT CO­ORDINATOR: NEA Transport Research and Training BV
PARTNERS:
­ Nouveaux Espaces de Transport en Europe Application de Recherche
­ Istituto di studi per l’integrazione dei sistemi
­ Universität Karlsruhe (TH)
­ MDS Transmodal Limited
­ MKmetric Gesellschaft Fuer Systemplannug MBH
­ Technical Research Centre of Finland
­ Eidgenoessische Technische Hochschule Zuerich
PROJECT START DATE: 1­12­2002
Date of issue of this report: 27­05­2004
DURATION: 33 Months
Project funded by the European Community under the
‘Competitive and Sustainable Growth’ Programme
(1998­2002)

D5 Annex report WP 2: ETIS­DATABASE METHODOLOGY DEVELOPMENT
AND DATABASE USER MANUAL – SOCIO ECONOMIC DATA
CONTENTS
page
1 INTRODUCTION ...............................................................................5
2 OBJECTIVES AND STRATEGIC ASPECTS.....................................7
3 SETTING THE FRAMEWORK ..........................................................9
3.1 Introduction.................................................................................................9
3.2 Structure for socio economic indicators to be included.................................9
3.3 Variables to be included and the way to estimate default value...................10
4 STRUCTURING OF SOCIO ECONOMIC, SPATIAL AGGREGATES13
4.1 Demography..............................................................................................13
4.1.1 Level 1: Country level ...............................................................................13
4.1.2 Level 2: Regional level..............................................................................14
4.2 Main macro economic aggregates..............................................................15
4.2.1 Level 1: National level ..............................................................................15
4.2.2 Level II: Regional level .............................................................................19
4.3 Economic sectoral indicators .....................................................................19
4.3.1 Level I: National level ...............................................................................19
4.3.2 Level II: regional level ..............................................................................24
4.4 Other socio economic indicators ................................................................24
4.4.1 Level I: National level ...............................................................................24
4.4.2 Level II: Regional level .............................................................................29
5 DATA NEEDS AND NEW BOTTOM UP CONSTRUCTION OF
INDICATORS...................................................................................31
5.1 Information available.................................................................................31
5.1.1 Demography..............................................................................................31
5.1.2 Main national macro economic aggregates.................................................31
5.1.3 Economic sectoral indicators .....................................................................31
5.1.4 Other socio economic indicators ................................................................32
5.2 New methods for construction local socio economic indicators ..................32
5.3 The testing case.........................................................................................35
6 CONCLUSION.................................................................................39
ANNEX A
SOCIO­ECONOMIC RESOURCES
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1 INTRODUCTION
The present report represents the WP 2 annex report of deliverable D5 of the reference database
development within the ETIS project1. The objective of this report is to present an inventory of
relevant data sources and to collect pilot data on a CD including a user manual of data access.
Within ETIS socio economic data have to be structured in a consistent framework so that the
other work packages can find in the socio economic database the indicators they need to
characterise a socio economic environment.
Although the objectives and structure of D5 have been coordinated and harmonised so that this
document is presented in a similar way for all WP of ETIS, its content will reflect this
specificity of WP2 within the ETIS reference database development.
These objectives are summarised as follows:
· Determine the variables to be included
· Describe the methodology to obtain the variables and to fill the remaining gaps
· Describe the data collection
· Describe the testing phase performed, lessons learned and its results
· List the sources to be considered
The testing phase data will concern demographic and economic data at national and regional
level; the user manual to accede to these data, printed on a CD, will also be presented in the
chapter IV.
The last chapter concerns specific demands addressed to WP2 by other WP and in particular
WP for freight and passenger modelling.
1 The full title of the reference database part of ETIS project is ETIS­BASE ­ `Core Database Development for the European
Transport policy Information System (ETIS)’
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2 OBJECTIVES AND STRATEGIC ASPECTS
The work on the ETIS reference database responds to key action 2, ‘Sustainable Mobility and
Inter­modality’, objective 2.1 ‘Socio­economic scenarios for mobility of people and goods’,
task 2.1.1/9, ‘Development of a European Transport policy Information System (ETIS) as a
basis for transport planning and policy formulation’. The task is separated into three sub­tasks.
The ETIS reference database addresses sub­task 2, ‘the development of a reference database for
the modelling element’.
The objectives of ETIS reference database are:
1. To contribute to the building of a consensus view of the reference pan European transport
modelling data set.
2. To develop an open methodology to generate a version of such a set from existing
international and national sources.
3. To produce a first compilation of the data set by applying the methodology mentioned
above, as on­line database.
During the kick­off of the project it has been decided by the European Commission that within
this project the work should focus on:
1. the development of an ETIS for TEN­T policies,
2. the procedures and data should face especially a monitoring of the TEN­T corridors,
3. the geographic scope has to be adjusted to the forthcoming 10 new members,
4. the PAN European scope has to be defined along the geographic hemispheres,
5. the degree of detail in general can be reduced including a concentration upon a few
indicators mentioned in the white paper,
6. the results have to be available for further use within the GETIS system,
7. the work tasks and responsibilities have to be adjusted in respect of the new focus and the
limited budget.
The reference database of ETIS will serve a various series of TEN­T policy issues: the level of
detail and the variables will be appropriate for this purpose. It will allow obtaining in an
accurate way the performance and the impacts (environmental, economic) of transport, as well
as the traffic at specific nodes or links of the networks. But the internal structure of the database
will allow proceeding easily to any aggregation in order to get a compact view of transport
performance (vehicle­kms etc) and effects (emissions level, energy consumption by mode etc).
The work organisation of ETIS reference database is established in close co­operation with the
external promotion 2 and contacts of ETIS. As part of this external promotion, support to the
development of the ETIS reference database is an essential element.
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There are several aspects on which synchronisation of the two projects take place:
· 4 workshops specifically related to the development of the ETIS reference database
· Open Conferences in which dissemination of results takes place
· Participation to the ETIS Steering group
· Testing of the system with pilot users, i.e. also testing of results of the development of the
ETIS reference database
· Dealing with specific issues like legal and organisational aspects.
In addition the ETIS reference database will be incorporated in the ETIS software tools 3 . The
two most important outputs of the reference database development that serve as input to the
system tools being developed are:
1. The metadata concerning indicators and data sources serve.
2. The final reference ETIS database
Furthermore in order to make it possible for the software tool developers to continue their work
while the reference database is being developed working material is being delivered which has
also been used in the TEN­STAC project. Intermediate results from the reference database
development will be delivered as soon as it comes available. ETIS reference database
construction will, where possible, use the results of GETIS (GIS data) and TEN­STAC
(indicator definitions and use of a selection of the input data) and find co­operation where
possible.
The ETIS reference database project, ETIS promotion and external contacts project and ETIS
software tools project 4 have come up with a common and better harmonised focus during
meetings from November 2003 up to January 2004 in order to be able to come up at the end of
the three projects with one consistent and unique ETIS product. This product is a pilot and it is
expected that one will continue to maintain and to develop the ETIS tool to the interest of the
European transport policy.
2 Promotion work is covered by the ETIS­LINK project
3 ETIS software tools are covered by the ETIS­AGENT project
4 respectively ETIS­BASE, ETIS­LINK and ETIS­AGENT, the trilogy of ETIS projects
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3 SETTING THE FRAMEWORK
3.1 Introduction
The distinction between supporting indicators and performance indicators does not really apply
to WP2 where data collected or estimated are not transport data but socio economic data used as
inputs for transport evaluation purpose.
Therefore the focus is put on the organisation of socio economic data, which covers a large
range of domains so that access to information is facilitated and default value can be estimated.
3.2 Structure for socio economic indicators to be included
A basic choice made to structure the database is to privilege the spatial dimension with three
basic levels:
· national level
· regional level
· local level.
The national level corresponds to national socio­economic aggregates which are well defined in
national statistics with a fairly good harmonisation at European level as well as at the world
level, although the details available are much more limited for non EU countries. The new
acceding countries can already be considered as the EU countries since an important
harmonisation effort has already been made within EUROSTAT adaptation of the statistical
concepts and data collection. A special mention must also be made for Mediterranean countries
with the MEDSTAT programme aiming at coordination and collection of statistics for
Mediterranean countries.
The regional level is more difficult to define; as a first approximation the European NUTS II
level can be considered as regional level although the NUTS II level does not always
correspond to what is called the administrative region with different appropriate names or
dimensions according to the history of the countries.
Therefore the NUTS III level will also be considered at this second level of spatial
desegregation, with a particular effort made for characterising a “regional” level for non EU
countries; this will be in particular very useful for new “neighbours” of European Union since
the European networks and corridors which are the main focus of first ETIS BASE application
must also improved connections with these “new neighbours”.
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The data at the NUTS III level are in general much less detailed than at the NUTS II level but
they are very useful for network assignment of freight traffic and quite necessary for network
assignment of passenger traffic since most of this passenger traffic is short distance traffic.
The second stage of desegregation will be organised as follows (sections)
(1) demographic information
(2) economic aggregates
(3) sector information
(4) other socio economic information.
A third dimension of the structure of the database is the geographic “scope” which will be
analysed with the following differentiation (scope)
(a) EU scope
(b) Neighbour countries with possible sub levels
(c) Rest of the world.
3.3 Variables to be included and the way to estimate default value
In many data sources and, in particular, in EUROSTAT details at NUTS II level are subdivision
of details provided at NUTS III level and this property is quite useful where some data are
missing, because NUTS II estimations can always be extended to NUTS III level as a first
approximation.
In WP2, the problem of missing data will be faced using this property of “embedded” definition
of statistics nomenclature when possible; this property which has been just mentioned for
relations between NUTS II and NUTS III can obviously be also applied between NUTS II and
NUTS I (or NUTS O) and this was a major reason for privileging the spatial level as first
dimension of database structuring.
The third level, which is the “local” level, is also sometimes difficult to define rigorously; the
reference to NUTS IV or NUTS V level is a possibility with NUTS V level associated to major
agglomerations in dense populated area. Therefore when such definition does not exist and in
particular in non EU countries, then the reference to “urban database” can be made.
Such approach will then have three consequences in the WP2 database structuring:
­ First it becomes clear that local information corresponding to this third level will mainly
concern information on population which is often a quite good indicator for spatial
distribution of activities and generation of traffic.
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­ Secondly, when confronted with the difficulty of zoning definition of the local level the
techniques of “raster” cells can be used so that an estimation of local spatial distribution
of activity can be made in correlation with local spatial distribution of population or
employment
­ Thirdly that the GIS tool will be very useful, so that local impacts, assignment of local
traffic can be made more rigorously using geocoded data; sensitive areas and population
concerned can be, for example, very well referenced through GIS database.
As far as data sources are concerned these three levels will in generally depend upon different
types of database, modes of collection, or methods of estimation, although there is some
convergences between regional and national information available within EU due to efforts
made for regionalisation of information.
In WP2 a special effort will then be made to extend the European information available in
EUROSTAT to information for non EU countries, at regional level for neighbour countries and
at national level for countries which are further away.
Another type of effort will be made for a more generalised use of local information by
introduction of GIS techniques for socio economic information used and not only for network
description, as it will be done in other work packages.
Another major point concerning ETIS and organisation of the socio economic database is that
within each spatial level the same structure of information will be used within what will be
called “sections” or “subsections” so that the total database consistency is strengthened with
possibilities open to “bridge” information between, different sections such as employment and
GVA.
This is in particular the case for World Bank sources for non EU countries and the case of
CORINE LAND COVER source which provide important geocoded statistics on sensitive
areas, location of industry and tourism attractiveness.
To conclude the presentation of this specific domain of the socio economic of ETIS BASE it
must be stressed:
· The field covered is probably wider than for other data sets in ETIS in particular as far
as geographic scope is concerned including non EU states and the rest of the world
· The differentiation between supporting and performance indicators is of limited interest
as already pointed before and in particular in the first inventory of data of WP1 where a
fairly large denomination was used concerning socio economic type of information: the
details have been progressively précised after feedback with needs of other work
packages.
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However there is, also an open debate on the boundaries between the socio economic
environment and the transport system which influence the way to address transport modelling:
where are the limits between economic modelling and transport modelling?
This is for example illustrated by the difference of structures between the SCENES model and
the NEAC model for freight.
On the one side there is a trade “economic” model which is extended to a transport model:
basically there is a transformation of trade flows expressed in monetary value in traffic flows
expressed in tons or number of vehicles.
On the other side there is a direct connection between socio economic indicator and transport
flows expressed in tons.
These different approaches induce different requirements for socio economic inputs, with
sometimes the necessity to use outputs of socio economic models as inputs to transport models:
in this case the socio economic mechanism are externalised. Another important illustration of
such situation is the “motorisation model”, very important for passenger mobility appraisal,
which can be considered as an external socio economic model, reflecting an important feature of
modern societies.
Taking into account this specific position of socio economic information in ETIS, the question
of data gap will be often treated in relation with this general organisation of the database so that
“default” value can be used with reference to a more global spatial level (with, in general, more
detailed information/or using demographic information as indicator of distribution of added
value: this is a kind of “top down” estimation.
Reversely when GIS database such as CORINE LAND COVER will be available, socio
economic indicators for a zone can be constructed from geocoded information using “raster
technique”, and a coverage of the zones by rasters.
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4 STRUCTURING OF SOCIO ECONOMIC, SPATIAL AGGREGATES
The macro economic aggregates are relevant for the analysis of main evolutions of transport
related to increase of mobility and trade. A special focus has to be put on EU integration,
enlargement and to a context of globalisation which affect market sizes and behaviours.
For these aggregates, time services are often essential in order to understand main structural
changes of past decades, changes which are difficult to introduce explicitly in transport models,
which are often calibrated on “cross sectoral statistics, for a base year.
The sources of macro economic and demographic aggregates are differentiated according to
geographic “scope”, for which different types of sources are available. At the level of EU,
EUROSTAT is the main source but this database has many components and facets so that more
precision must be provided in order to accede to relevant information. For non EU countries an
investigation is made to find relevant sources for the different “sections” mentioned earlier.
However the socio economic data must also be useful for the understanding of the spatial
distribution of flows, at regional level which is in particular relevant for network
implementation.
For EU countries the regional level will be NUTS II or NUTS III defined in EUROSTAT. For
other countries a reference has to be chosen which will correspond when it is possible, to
administrative entities so that statistics can be attributed to such zone, this will be the case for:
­ Mediterranean area
­ Russia,
­ Balkans,
­ And the rest of the world.
If the definition of zones has stabilised within EU + CEEC area, within EUROSTAT there is a
problem of homogeneity of zones as well as a question of definition of zones outside this area
for analysis of extension of European networks, in particular towards Mediterranean countries
and Russia
4.1 Demography
4.1.1 Level 1: Country level
Population is in general a well­known information with fairly reliable projections using
demographic models based on age pyramid and fertility rate. However migration flows are more
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difficult to apprehend, and have a significant influence on evolution of population and
consequently on mobility. Therefore a special effort will be made to introduce available data on
immigration.
Sub sections
- Total population per country
- Population by sex and age group
- Emigration and immigration as well as their distribution per country of origin or
destination
- Education: pupils and students by level of education and sex.
Main sources
The main sources are:
- For EU, acceding countries and Mediterranean countries: EUROSTAT,
- Other specific sources must also be mentioned such as “Plan Bleu” source for
Mediterranean countries
- For the rest of the world UN, World Bank
Questions to be addressed in using demographic data
Demographic models for projection of population can be used as a fairly reliable framework of
reference for long term analysis. Demographic data and structure of population per age group
and revenue are also very useful for motorisation modelling.
However there is a difficulty to estimate migration flows which influence more and more the
mobility data evolution of countries.
4.1.2 Level 2: Regional level
Sub sections
- population at NUTS II and NUTS III
- population by sex and age group at NUTS II
- emigration and immigration at NUTS II.
Main sources
The main sources are:
- REGIO for Europe
- MEDSTAT for Mediterranean area, Balkans
- Rest of the world: cities database (geocoded).
- Population of cities as “proxy” for distribution of activities.
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Question to be addressed
For many countries population is not available at regional level: in this case estimation can be
made using geocoded cities database; this has been done for some countries in Mediterranean
area in order to complete a regional population database in the area. Such databases are essential
to distribute activities with countries at a regional level and thereafter to distribute traffic flows
according to such indicator.
4.2 Main macro economic aggregates
4.2.1 Level 1: National level
These aggregates are essential to relate general economic activity to transport activity and in
particular to international transport within and outside EU.
Form a technical point of view the choice of the indicator must be expressed in real terms so
that correlations with “material” exchanges (trade of goods) or physical movements, the “trips”
become more relevant and independent fluctuations of currencies or inflation.
Sub sections
The most important socio economic indicator is the GDP. In EUROSTAT the reference base
year for GDP is 1995 and its yearly evolution is most of the time expressed in terms of relative
change. For our purpose import and exports of countries are also relevant indicators to
characterise EU integration or internationalisation of trade, although they are not often used in
transport models as input variables.
- GDP (real, constant euros base 95)
- Import/exports (real or as % of GDP) with distinction between EU and non EU
countries (with eventually further distinction for non EU countries)
- Industrial production index
Main sources
- For EU, acceding countries and Mediterranean countries: EUROSTAT,
- Within EUROSTAT special mention must be made to COMEXT which provides
import and export on a country to country basis with detailed products
nomenclature in Euros and tons per mode: therefore COMEXT can be considered
as a socio economic database but also as one of the most important transport
database.
- For the rest of the world UN, World Bank
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Questions to be addressed in the use of macro economic aggregates
- First it is necessary to recall there are relations between macro economic aggregates
(production, import, export, consumption, investment) for economic development
which have to be taken into account. These relations show in particular how the
international trade influences more and more the GDP growth of countries. They
show also that imports and exports grow faster than GDP and that these aggregates
can fluctuate very much from one year to another (see table for recent years). These
relations are accounting relations, but they can also reflect the choice of a type of
macro economic model taken as reference for the development of the socio
economic context (See Figure 4.1)
- A second constraint mentioned concerns the choice of indicators which has to
reflect, as much as possible, material exchanges ; this is why index of industrial
production is often chosen rather than GDP (which includes services) for freight in
the perspective of estimation of freight flows in tons: however this indicator is less
often available and most of the time expressed in relative annual change (see Figure
4.2)
- A final remark is the necessity to initiate indicators for EU integration dynamic,
enlargement and development of world trade. The following graph on EU trade
shows clearly that new members of EU have a more rapid growth of intra UE trade
(see Figure 4.3)
Figure 4.1
Relations between macro economic aggregates
Economic growth (real)
Private
consumption
Public
consumption
1995 1996 1997 1998 1999 2000 2001 2002
1,8 1,9 2,0 3,2 3,6 3,0 2,2 1,2
0,8 1,6 1,0 1,5 2,0 1,9 2,0 2,2
Investments 2,9 1,8 3,0 6,5 5,2 4,7 ­0,2 ­2,1
Export 8,0 4,9 10,1 6,6 5,3 12,1 2,4 0,7
Import 7,3 4,1 9,3 10,0 7,3 11,4 1,5 ­0,2
PIB 2,4 1,6 2,5 2,9 2,8 3,4 1,5 1,0
Source: European Commission ­ ECFIN
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Figure 4.2
Comparison between PIB, industrial production index and transport volume for
France
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Figure 4.3
Twenty years of EU integration
15,0
COMMERCE INTRA­UE PAR ÉTAT MEMBRE (Croissance des exportations, base 1980)
13,0
11,0
9,0
7,0
5,0
3,0
1,0
­1,0
B/L DK D EL E F IRL I NL A P FIN S UK UE­15
1990 2,2 2,3 2,4 2,3 3,8 2,5 3,0 2,7 2,2 2,9 4,7 2,2 2,1 2,0 2,3
2000 4,4 4,5 4,0 2,7 10,9 4,7 11,0 4,5 4,9 6,0 9,7 4,7 4,0 4,3 4,7
15,0
COMMERCE EXTRA­UE PAR ÉTAT MEMBRE (Croissance des exportations, base 1980)
13,0
11,0
9,0
7,0
5,0
3,0
1,0
­1,0
B/L DK D EL E F IRL I NL A P FIN S UK UE­15
1990 1,7 2,2 2,1 1,0 2,2 1,8 3,1 2,0 1,6 2,1 2,1 1,8 1,9 1,5 1,9
2000 4,6 4,6 4,7 3,5 5,4 4,1 24,4 4,7 4,3 5,6 4,6 5,1 4,6 3,2 4,4
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4.2.2 Level II: Regional level
Sub sections
- GVA for NUTS II and NUTS III zones
- Employment
Main sources
- REGIO for Europe
- National statistics for non EU countries
4.3 Economic sectoral indicators
4.3.1 Level I: National level
Sub sections
Structural change in the economy and evolution of specific sectors influence both volume of
traffic and transport demand requirements expressed in terms of reliability and quality. To
reflect these changes of structure several types of sectoral indicators must be considered.
However beyond this general consideration it is necessary to address more precisely the
question of the sectoral breakdown so that proper ad equation is made between structural
change in the economy and consequences for transport.
- Added value per sector (see Figure 4.4)
- Employment per sector
- Import/export per sector: value and tons
- Specific information for energy sector and fuel price.
Main sources
- EUROSTAT for EU and in particular COMEXT,
- For the rest of the world: World Bank
- Fuel price: IRU (See Figure 4.5)
Questions to be addressed
- A first problem is the choice of sectors which means, not only the definition of the
level of desegregation, the choice of type of nomenclature: do we privilege
economy or transport nomenclatures (NACE or NSTR)? how relevant the NSTR
is? (Figure 4.6 and Figure 4.7)
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- Beyond this problem there is indeed the fundamental question of the choice of the
type of model for freight modelling:
(a)
(b)
a trade model from which transport flows in tons are derived (SCENES
option)
a transport model which relates directly transport flows in tons with economic
indicators (NEAC option).
In the first case we need to explicit tables of correspondence between economic nomenclature
and transport nomenclature, since the economic model will be formulated using the first set of
definitions of variables and the transport outputs with the second set.
In the second case this is not necessary if correlations between economic variables and transport
variables are satisfactory.
However the level of the sector the question of competitiveness between countries becomes
essential. This is why in option (a) a complete economic model can be integrated with transport
model; in option (b) the economic mechanisms are externalised and sectoral indicators are
inputs of the transport model.
In option (a) an approach which has been privileged is to use input output national data per
sector so that an international competition dynamic can be introduced: this is particularly
interesting at a period of Europe enlargement with significant differences for personnel
productivity between countries.
Figure 4.4
Structure per sector for EU 15 and acceding countries % annual growth
EU­15 Acceding countries
1990­2000 2000­2010 2010­2020 1990­2000 2000­2010 2010­2020
Gross Value Added 2 2,5 2,4 1,6 3,9 3,8
Industry 1,4 2,4 2,4 1,2 4,1 3,5
. Iron and steel ­1,0 0,1 0,2 1,5 2,4 1,6
. Non ferrous metals 1,2 3,3 2,6
. chemical 2,1 2,6 2,5 5,6 6,6 4,6
. Non metallic minerals 0,4 1,7 1,8
. Paper. Pulp. Printing 1,9 2,3 2,2
. Food drink tobacco 1,6 2,3 2,3
Construction 0,3 1,8 2,0 ­1,0 3,7 3,9
Services 2,4 2,7 2,5 2,8 4,3 4,2
Agriculture 1,2 1,1 1,0 0,5 1,3 1,5
Energy sector 2,2 1,3 1,7 ­2,3 0,7 0,9
Source European Energy and Transport ­ Trends to 2030
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Figure 4.5
Fuel prices (in European Countries)
Country Currency 95 lead free 98 lead free Diesel
Austria 0.90 0.98 0.75
Belgium 1.07 1.08 0.79
Bulgaria BGN 1.25 1.55 1.10
Croatia HRK 6.47 6.66 5.43
Czech Republic CZK 24.93 29.48 22.97
Denmark DKK 8.53 8.75 7.04
Estonia EEK 9.50 10.00 9.00
Finland 1.07 1.10 0.77
France 1.03 1.05 0.82
Germany 1.07 1.11 0.86
Greece 0.81 0.89 0.69
Hungary HUF 232.50 241.50 208.00
Ireland 0.91 1.05 0.83
Italy 1.08 0.89
Latvia LVL 0.42 0.44 0.36
Lithuania LTL 2.39 2.50 2.30
Luxemburg 0.87 0.89 0.64
Netherlands 1.22 1.27 0.83
Norway NOK 9.30 9.43 8.75
Poland PLN 3.50 3.70 2.92
Portugal 0.96 1.03 0.71
Romania ROL 24'900.00 ­ 21'800.00
Russia RUB 10.50 11.20 8.70
Slovakia SKK 34.40 37.00 32.90
Slovenia SIT 189.70 193.00 166.80
Spain 0.83 0.92 0.70
Sweden SEK 9.76 10.06 7.95
Switzerland CHF 1.36 1.40 1.42
Ukraine UAH 2.25 2.60 2.25
United Kingdom GBP 0.77 0.82 0.79
USA USD 0.43
Yugoslavia YUM 49.30 53.70 41.50
Source: IRU – 2004, Week N o 14, 2004.
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AUSTRIA
BELGIUM
BULGARIA
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Figure 4.6
A: SCENES Transport flows and correspondence to NSTR
Transport Model Flow NST/R group Group of Goods Handling
category
1­ Cereals and agricult. Products 00 01 04 05 06 09 17 18 1 3 4 5 part of 6 7 General cargo
2 – Consumer food 02 11 12 13 16 Part of 2 Part of 6 Unitised
3 – Conditioned food 03 14 Part of 2 Part of 6 Unitised
4 – Solid fuels and ores 21 22 23 41 45 46 8 11 12 Solid Bulk
5 – Petroleum products 32 33 34 10 Liquid Bulk
6 – Metal products 51 52 53 54 55 56 13 General Cargo
7 – Cement and manuf. Build mat. 64 69 14 Unitised
8 – Crude building materials 61 62 63 65 15 Solid Bulk
9 – Basic chemicals 81 83 17 part of 18 Solid Bulk
10 – Fertil,, plastic and oth. Chem. 71 72 82 84 89 16 part of 18 19 General Cargo
11 – Large Machinery 91 92 939 part of 20 General Cargo
12 – Small Machinery 931 part of 20 Unitised
13 – Miscell. Manufact. Articles 94 95 96 97 99 21 22 23 24 Unitised
Figure 4.7
B: SCENES Transport flows and correspondence to NSTR
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4.3.2 Level II: regional level
Sub sections
- GVA per sector at NUTS II level ( 3 main sectors)
- Employment per sector at NUTS II (as an alternative proxy for sectoral spatial
distribution)
Main sources
- REGIO for Europe
- National statistics for non EU countries
Main questions to be addressed
The main socio economic indicator for spatial distribution between regions are not necessarily
the most appropriate for projections of interregional traffic flows; this is again the problem of
the difference between “cross­section” calibration and use of such calibration for projection
purpose. One example to illustrate this difference is the following; the regional sector
employment might be a good indicator for spatial distribution of a given product but it can
induce wrong interpretation when used for projection of regional flows: productivity increase
and economic performance of a sector does not go necessarily in parallel with employment
increase and in many cases the correlation is even negative.
4.4 Other socio economic indicators
4.4.1 Level I: National level
Sub sections
- Employment/unemployment
- Household: number, size, disposable income and consumption
- Motorisation rate
- Tourism: number of arrivals/departures, nights spent by residents, number of beds.
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Main sources
- EUROSTAT
- OMT for tourism
- IRU for motorisation rate
- FORESIGHT monitoring system for non transport policies (which influence
transport)5
- EUROBAROMETER to characterise acceptability and attitude toward transport.
- World fact book.
Questions to be addressed
First there is the estimation of motorisation rate from demographic data, as well as revenues,
and prices for use of a car which is an important indicator for passengers mobility and modal
choice; in this case we consider the motorisation rate as external socio economic indicator. But
there is also the question of monitoring so called “structural indicators”, which are of relevance
for assessment of impact of transport policy:.
- Structural indicator on exclusion and cohesion (EUROSTAT) (Figure 4.8)
- Data available on attitudes and opinions of European population which become
more important with development of public consultations for construction of new
infrastructures; these information on attitude also take into consideration attitude
towards environment
- Information of “non transport” policies which influence transport (see
FORESIGHT project) with in particular the rate which can be attributed to public
services and public transport in different countries.
5
FORESIGHT is a research project of the Vth Framework coordinated by ICCR (Austria)
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Figure 4.8
Structural indicator on exclusion and cohesion
STRUCTURAL INDICATORS DEFINITIONS
Generic Topic Indicator Number and Name Definition
General
economic
background
a1 GDP per capita
a2 GDP growth rate
b Energy intensity of the economy
c1 Labour productivity
c2 Labour productivity (per hour worked)
d Inflation rate
e Real unit labour cost growth
f Public balance
GDP per capita in Purchasing Power Standard (PPS)
(EU­15=100)
Growth rate of GDP at constant prices (base year
1995)
(Gross inland consumption of energy)/GDP
(kilogram of oil equivalent)
GDP per person employed (EU15=100)
GDP in PPPs per hour worked relative to the EU
(EU15=100)
Annual percentage change in Harmonized Index of
Consumer Price (HICP) (annual average)
Growth rate of the ratio: compensation per employee
in current prices divided by GDP per total
employment in current prices
General government net balance as percentage of
GDP
Employment
Innovation and
Research
Economic
reform
1.1 Employment rate
1.2.1 Employment growth
1.5.1 Unemployment rate
2.1 Public expenditure on education
2.2.2 R&D expenditure
2.3 ICT expenditure
2.6 Share of exports of high­tech products in
total exports
3.1.a Intra­EU trade integration
3.1.b Trade integration
3.2 Business investment
3.3.a Relative price levels
Employed persons aged 15­64 as a share of the total
population aged 15­64
Annual change in the total employed population
Total unemployed individuals as a share of the total
active population
Total public expenditure on education as a percentage
of GDP
Business enterprise expenditure on R&D
ICT expenditure as a percentage of GDP
Share of exports of high­tech products in total exports
(Intra­EU exports of goods + intra­EU imports of
goods) / (2 * GDP)
(Total exports of goods + total imports of goods) / (2
* GDP)
Gross fixed capital formation by the private sector as
a percentage of GDP
Relative price levels of private final consumption
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STRUCTURAL INDICATORS DEFINITIONS
Generic Topic Indicator Number and Name Definition
including indirect taxes (EU­15=100)
3.4.b1 Industry electricity prices
3.4.b2 Household electricity prices
3.4.c1 Industry gas prices
3.4.c2 Household gas prices
Price level and evolution in electricity, Industry users,
(in euro per kWh)
Price level and evolution in electricity, Households,
(in euro per kWh)
Price level and evolution in gas markets, Industry
users, (in euro per Giga­Joule)
Price level and evolution in gas markets, Households,
(in euro per Giga­Joule)
Source: Cambridge Econometrics
STRUCTURAL INDICATORS ­ EU TOTAL
Level Average Annual Growth 6 Level
General Topic Indicator (levels) Units (levels) 1999 1991­94 1995­99 2000­05 2005
Economic
Background
a1 GDP per capita EU15=100 100 0.0 0.0 0.0 100
a2 GDP level Euro (1995) bn 7213 1.0 2.3 2.7 8524
b Energy intensity kgoe 200 ­1.4 ­0.9 ­2.4 176
c1 Labour productivity EU15=100 100 0.0 0.0 0.0 100
c2 Labour productivity
(per hour)
EU15=100 100 0.0 0.0 0.0 100
d Consumer prices 1995=1.0 1.15 2.4 3.2 1.9 1.29
e Real unit labour cost Index 0.48 ­0.9 ­1.0 ­0.4 0.47
f Public balance % of GDP ­0.6 ­0.3 0.9 ­1.2 ­5.0
Employment 1.1 Employment rate % of working
population
62.1 ­1.2 0.6 0.6 66.0
1.2.1 Employment millions 153.0
5
­1.2 1.1 1.0 164.0
5
1.5.1 Unemployment rate % of labour force 9.1 1.0 ­0.4 ­0.4 6.2
Innovation and
Research
2.1 Public expenditure on
education
% of GDP 5.2 0.2 ­0.1 ­0.0 5.0
2.2.2 R&D expenditure Euro (1995)m 1.9 0.0 0.0 4.9 2.8
6
% pa, except for variables expressed in % terms, for which pp change is used.
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STRUCTURAL INDICATORS ­ EU TOTAL
Level Average Annual Growth 6 Level
General Topic Indicator (levels) Units (levels) 1999 1991­94 1995­99 2000­05 2005
2.3 ICT expenditure Euro (1995)m 5.6 5.3 6.2 0.6 6.2
2.6 Share of exports of
high­tech products
% 18.9 ­0.3 0.9 0.6 22.7
Economic Reform 3.1. b Trade integration % 16.3 ­0.1 0.4 0.7 21.2
3.1.a Intra­EU trade
integration
% 9.6 0.2 0.3 0.6 14.7
3.2 Business investment % of GDP 18.0 ­1.0 0.2 0.2 19.4
3.3.a Relative price levels EU15=100 100 0.0 0.0 0.0 100
3.4.b1 Industry electricity
price
3.4.b2 Household
electricity price
Euro per kWh 6.3 ­1.3 ­2.9 0.0 6.4
Euro per kWh 10.5 0.3 ­0.9 2.5 11.7
3.4.c1 Industry gas price Euro per Giga­joule 3.5 ­2.5 ­1.4 2.1 5.5
3.4.c2 Household gas
price
Euro per Giga­joule 6.7 ­0.5 0.8 1.6 8.4
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4.4.2 Level II: Regional level
Sub sections
- Number of households
- Motorisation rate at NUTS II and III
- Tourism: number of arrivals, number of beds at NUTS II
Main sources
- EUROSTAT for EU,
- IWW (SCENES),
- OMT for tourism
- MEDSTAT for Mediterranean countries
- PLAN BLEU for Mediterranean area
Main questions to be addressed
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5 DATA NEEDS AND NEW BOTTOM UP CONSTRUCTION OF
INDICATORS
In WP2 a new approach of socio economic indicator construction can be explored based on new
GIS tools or GIS models. The basic principle relies on the possible availability of geocoded
socio economic characteristics but mainly concerning physical characteristics of the space
which takes a growing importance in transport policy concern.
An illustration of these new needs and opportunities is given by the evaluation made in TEN
STAC concerning the impact of new priority projects (or corridors).
These types of socio economic data refer to local socio economic context.
Several types of data needs expressed by other WP could be addressed using such method as it
has been stressed by WP4 on passenger modelling to characterise attractiveness of geographic
zones for tourism.
This context is important for local generation of traffic, assessment of local impact of TEN
policy as well as for appraisal of infrastructure capacity where conflicts might arise between
local and interregional traffic for use of infrastructure.
5.1 Information available
Main information available are:
5.1.1 Demography
­ population in towns and communes
5.1.2 Main national macro economic aggregates
­ Implementation of types of industries for more precise analysis of freight access to
network
5.1.3 Economic sectoral indicators
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5.1.4 Other socio economic indicators
­ Location of sensitive areas which are protected
­ Topographic and climate information.
5.2 New methods for construction local socio economic indicators
From the methodological point of view there is the opportunity of more intensive use of GIS for
evaluation of policy and projects and development of raster and buffer methods for modelling
and assessment of environmental impact (corridor approach for TEN T priority experience of
TEN STAC) for example raster analysis to better understand conflicts between traffic flows of
different origins for use of infrastructure and development of congestion (passengers and
freight, local and interregional). It can also be used to assess impact of transport using socio
economic local information such as population concerned. (Figure 5.1).
“Buffer” analysis cans, on the other hand be used to assess conflicts between corridor and
protected area; it points out, for example, how far a priority corridor is from protected area
(Figure 5.2)
However there are limits in local information availability concerning in particular land use
policy factors such as price of land, or local policy context.
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Figure 5.1
Rasters which form an envelop of TEN priority projects
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Figure 5.2
TEN­T priority projects and buffer zones for analysis of conflicts
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5.3 The testing case
A first testing case has been realised within phase 2 of the reference database development with
an application to demographic data.
These demographic data have been reorganised according to the structure presented in part I
according to different dimensions: spatial level, content in sections and geographic scope.
These dimensions are the lines and columns of matrices which characterise the organisation of
this database. The cells of the matrices inform about the availability of the information, and
when available, provide direct access to it.
For the pilot case the matrices can be presented as follows with in line the sections (and
subsections) and in columns the spatial level and the geographic scope.
In the following tables the cross means that the data have been collected in relevant sources and
implemented on a CD.
Table 5.1
Population database for European member
EU ­ 15
Country Region Local
Population
Population at 1st January by sex and age
group
Population density X X
Births and deaths X X
Deaths by sex and age group X X
Crude birth rate
Crude death rate
Immigration by sex and age group X X
Emigration by sex and age group X X
Distribution of emigrants
X
X
X
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Table 5.2
Population database for New Member
New Members
Country Region Local
Population
Population at 1st January by sex and age
group
Population density X X
Births and deaths X X
Deaths by sex and age group X X
Crude birth rate
Crude death rate
Immigration by sex and age group X X
Emigration by sex and age group X X
Distribution of emigrants
X
X
X
X
X
Table 5.3
Population database for Candidate Country
Candidate Countries
Country Region Local
Population
Population at 1st January by sex and
age group
Population density X X
Births and deaths X X
Deaths by sex and age group X X
Crude birth rate
Crude death rate
Immigration by sex and age group X X
Emigration by sex and age group X X
Distribution of emigrants
X
X
X
X
X
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Table 5.4
Population database for Neighbouring and World
Western
Balkan
Countries
Neighbouring
Norway &
Switzerland
Country
World
CIS Med Country
Population at 1st January by sex and
age group
X X X X
Population
Population density
X
Births and deaths
Deaths by sex and age group X X
Crude birth rate X X X
Crude death rate X X X
Immigration by sex and age group
Emigration by sex and age group
Distribution of emigrants X X
Table 5.5
Country classification
EU ­ 15 be Belgium
dk Denmark
de Germany
gr Greece
es Spain
fr France
ie Ireland
it Italy
lu Luxembourg
nl Netherlands
at Austria
pt Portugal
fi Finland
se Sweden
uk United Kingdom
New Member cy Cyprus
cz Czech Republic
ee Estonia
hu Hungary
lt Lithuania
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lv
mt
pl
si
sk
Latvia
Malta
Poland
Slovenia
Slovak Republic
Candidate Countries bg Bulgaria
ro Romania
tr Turkey
CIS ru Russian Federation
ua Ukraine
Western Balkan Countries al Albania
ba Bosnia and Herzegovina
hr Croatia
mk Macedonia, the former Yugoslav Republic of
yu
Serbia and Montenegro
Med Maghreb dz Algeria
ma Morocco
tn Tunisia
Machrek eg Egypt
ly Libya
ps
sy
il
jo
lb
Palestinian Authority
Syrian Arab Republic
Israel
Jordan (Hashemite Kingdom of)
Lebanon
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6 CONCLUSION
D5 refines the structure of the socio economic components of the ETIS database, which concern
the socio economic environment of transport and therefore plays a specific role in the overall
organisation of ETIS.
The field covered by the socio economic information is open to a broad definition of the socio
economic environment of transport leaving the door open to new type of indicator within a
“section” which has been called other socio economic indicator.
However the structure adopted is fairly simple; it privilege spatial levels (national, regional,
local), the “content” items, the so­called “sections”, presented in an homogenous way for
different spatial levels and finally the geographic scope (EU, neighbour countries, rest of the
world) which often determine the statistical sources to be referred to. This systematic way of
presenting the information helps to fill the gap with “default” values, since the structure of
organisation also reflects a prioritisation of data: a missing value at a lower spatial level can
always be replaced by a value available at a more global level, an information on demography
can often be an indicator for distribution of employment, added value.
But not all the statistical sources required have been received yet. New techniques for filling the
gaps are also envisaged using “raster” cell technique or “buffer” technique of GIS methods
when detailed GIS database will be communicated to NESTEAR such as CORINE LAND
COVER to precise geographic implementation of industries or location of protected areas.
The question of performance indicators did not really concern the field of socio economic data,
since it addresses the outputs of the transport system; however the question of performance of
socio economic sectors or countries maybe sometimes of relevance for inputs or outputs of
transport models in order to better understand the performances of the transport sector; this is
why some common “structural indicators” of the economic and social system are also
mentioned and in particular indicators which have been used in the ECOFIN studies or in Plan
Bleu for Mediterranean area.
The testing case chosen for the D5 deliverable is concentrating on demographic data although
much of socio economic data have also been collected at regional level; the presentation used is
again fairly simple and should help the modellers to find socio economic data they want to
obtain, and that they have transmitted to NESTEAR: among these data most of them can
already be made available, most of the missing ones being related to the availability of GIS
database.
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ANNEX A Socio­Economic
Resources

D5 Annex report WP 2: ETIS­DATABASE METHODOLOGY DEVELOPMENT
AND DATABASE USER MANUAL – SOCIO ECONOMIC DATA
Socio­economic sources
1. New Cronos, Regio. Available
2. Comext 7 Available
3. Scenes 8 . Available
4. SABE. Available
5. Gisco. Available
6. Corine land cover. Ordered
7. World Bank Data & Statistics (by country) 9 . Ordered
8. IMF STATISTICS DOTS­ Direction of Trade Statistics. Ordered
9. WTO World Trade Organisation 10 . Ordered
10. OECD Main Economic Indicators 11 Ordered
11. Worldfact Book (CIA database) Available
7
http://europa.eu.int/en/comm/eurostat/serven/home.htm
8
www.iww.uni­karlsruhe.de/SCENES/
9
Cf. Website: http://www.worldbank.org/data/countrydata/countrydata.html.
10
Cf. website: http://www.wto.org/english/res_e/statis_e/statis_e.htm.
11
Cf. Website: http://www.oecd.org/document/54/0,2340,en_2649_33715_15569334_1_1_1_1,00.html.
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