International material resource dependency in an input...
Transcript of International material resource dependency in an input...
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands
----- draft April 2012, please do not quote -----
International material resource dependency
in an input-output framework
Bouwmeester, Maaike C. a#
a University of Groningen, Faculty of Economics and Business
Postbus 800, 9700 AV Groningen, The Netherlands
Abstract
Strategic resource interests coupled with increasing resource depletion have contributed to a
rising concern with resource security. Governments issue reports to identify strategic material
resources and actively design strategies to ensure the supply of natural resources and re-use of
materials already in the economy. We assess natural resource use, trade linkages and material
dependence among 43 countries and the RoW region as represented in the EXIOPOL
database. Material resource requirements along the international supply chain are quantified
using an environmentally extended international input-output model, which allows
considering direct and indirect, domestic and international resource use. We focus specifically
on fossil energy carriers, metals and mineral resource use. Dependency on foreign resource
suppliers is examined by looking at the natural resources required directly and indirectly in
satisfying final demand by country. Of particular interest is the extent to which these
resources are imported and whether the majority of the imports is sourced from a small or
large set of trade partners. Three measures of resource dependency are analyzed. Resource
dependency is measured as total material requirements (direct and indirect) per unit output.
International material dependency is defined as the percentage of the material requirements
that is sourced abroad. Finally, we also consider the concentration of international material
dependency; when resources are mainly imported from one or a few trade partners, countries
may want to reconsider whether strategic interests should be factored into their procurement
strategies.
Keywords: international input-output, environmental accounting, material resources,
dependency,
# Corresponding author: Tel +31-50-363.7974 Fax +31-50-363.7337 E-mail: [email protected]
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1. Introduction
In our globalized world, production chains have become increasingly fragmented. Production
process are not only split up, but often even relocated to different countries (Hummels et al.,
2001). Fragmentation of production allows countries to specialize in the production activities
in which they have a competitive advantage, decreasing overall production cost of the final
product. It has also increased the interdependence and the complexity of international trade
relations.
Unlike capital that can be accumulated or a labor force that can increase, natural
resources cannot be produced. The material basis of the global economy and the distribution
of natural resource extraction are described in Behrens et al. (2007). However, in case a
country is not endowed with natural resources, it will have to obtain the resources needed for
production through international trade. Unstable economic trade relations with another
country may be harmful to the economy in case it concerns primary suppliers of essential
natural resources. Fully depending on other countries for the supply of natural resources is
seen as undesirable, especially after the two main oil crises of the 20th century and the
increasing scarcity of natural resources.
Governments have started to seriously acknowledge that access to raw materials is
key to a well-functioning and internationally competitive economy. The European
Commission (2008) has launched an initiative to secure the reliable and undistorted supply of
raw materials due to its importance to the EU’s competitiveness. Recently, an update has been
communicated to report results of ongoing actions to identify critical raw materials, and in
areas of trade, development, research, resource efficiency and recycling (European
Commission, 2011). Following suit, the Council of the European Union (2011) published a
list of conclusions that supports the initiative and encourages the European Commission in its
proposed actions. In Prins et al. (2011) it is asserted that the rising prices of resources are not
so much related to stock depletion, but are an effect of badly functioning markets and
policies. The economic and political dimensions of resource scarcity also receive much
attention in the EU’s communications, in which a large role is foreseen for diplomatic
relations.
In this paper we investigate the issue of the dependency of countries on imported
material resources from abroad. The focus of the present analysis is on four types of metals,
chemical/fertilizer minerals and fossil energy carriers. For the metals, we included: iron ores,
aluminum/bauxite ores, copper ores and precious metals ores. The last category is already
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scarce, and the first three have a large chance to become scarce in the near future (British
Geological Survey, 2011)1.
To satisfy demand, producers may need to import raw materials or intermediate
inputs in which these resources are embodied. International trade data can convey the country
of origin of materials, when the trade flow relates directly to raw materials. In contrast,
information about the origin of the raw materials is unavailable when it concerns intermediate
inputs that may already have crossed borders several times, before they are incorporated in a
final product. In case of an advanced electronic device, several different metals and minerals
may have been incorporated into the final product at different stages of the production process
located across multiple countries.
Assessing the full dependence on imported raw materials requires taking into
account all materials used directly and indirectly in producing the products imported by a
country in order to meet final demand. Input-output tables and related models allow for
calculating the direct and indirect effects of an increase in final demand on total output.
Extending input-output tables with environmental information results in a framework that is
very suitable for analyzing the relationship between economic activities and the pressure on
the environment caused by these activities (De Haan and Keuning, 1996). In this paper, we
use environmental information on material resources used per unit output to analyze material
dependency.
Including international trade linkages into an environmentally extended input-output
table (EE IOT) enables the analysis of international integration and the dependency of
production. It also enables tracking the origin of products consumed in a country and which
resources have been used in the production process. For example, it can be established
whether the Japanese cars contain more or less material resources than cars produced in the
United States. In addition, it can be investigated which countries actually extract these
resources. One of the debates this type of information has fuelled is whether a country is
responsible for the extraction of natural resources or the countries to which the products are
exported to (Peters, 2008; Serrano and Dietzenbacher, 2010).
Countries should be aware of their vulnerabilities with respect to raw materials and
identify bottlenecks in order to avoid future problems with their productive system. Especially
fossil energy carriers are, at least in the foreseeable future, the driving force of any economy.
Apart from environmental concerns in terms of emissions, the resource itself is also becoming
scarcer. Changing to another energy system may be a solution, but this switch may heavily
strain the material resource base (Kleijn & van der Voet, 2010). A strategy of diversifying
1 The level of detail of the available data prevents us from studying rare metals and minerals.
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imports over the countries which have natural resource endowments may decreases risks
associated with natural resource dependency.
In the next sections the methods used are discussed followed by a description of the
data available from the EXIOPOL database. Next, we report on the countries and sectors for
which an increase in final demand generates the most additional extraction of the three types
of resources. This indicates the dependency of a sector on material resources. Second, we
investigate the extent to which this additional demand is generated in other countries, which
shows how dependent a country is on foreign suppliers of the material resources. In addition,
the concentration of the international dependency is analyzed as an important aspect of the
factual dependency. Finally, a correlation analysis is undertaken to see to what extent these
three measures are related for individual sectors. The last section of this paper concludes and
provides an outlook.
2. Methods
An input-output model describes how supply x follows demand with the following identity:
= +x Ax f . Where x is total output, A the matrix of direct input coefficients2 and f the vector
of final demand3. Solving the model for output gives ( )−
= −1x I A f , where (I – A)
-1 is the
Leontief multiplier matrix of direct and indirect industry output requirements per unit of final
demand. In the Leontief quantity model, from which the backward multipliers are derived, the
assumption is made that prices are fixed in the short term. Another assumption in IO
modeling is that input coefficients do not change regardless of output, final demand, or other
relevant changes. The structure of the economy is taken to be constant, at least in the short
term.
The environmental extensions are given as a matrix of direct impact coefficients
[ ]kjd=D , of which each element represents the amount (in physical units per dollars’ worth
of output) of the environmental factor k used in the production of sector j. These
environmental extensions can be emissions, pollution, raw material, land use, water use, etc.
The total requirement of environmental factors Ex can be calculated as:
2 The derivation of an input-output model from supply and use tables (SUT) requires an explicit
assumption regarding the production technology of secondary and/or by-products of industries,
whereas this assumption is hidden in input-output tables. To obtain the industry by industry A matrix as
introduced here, the industry technology assumption has been used.
3 Bold letters denote vectors, bold capital letters matrices.
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1( )E −
= = −x Dx D I A f 1
For an international input-output table the same equation holds, where x is now a vector of all
individual country sub vectors Rx , for all countries R. The matrix [ ]R
kjd=D is the
concatenated matrix of all individual country matrices RD . The matrix [ ]RS
ija=A is the
input coefficient matrix of all domestic RRA matrices and all bilateral matrices
RSA , where R
and S are the country indices and i and j are sector indices. The vector f is the stacked vector
of all individual country final demand vectors Rf .
The total requirement of environmental factors Ex signifies the dependency of a
sector on material resource inputs. The requirements may be partially sourced domestically,
but especially for the countries that do are not endowed with material resources, these
requirements will be imported. The extent of dependency on foreign suppliers for material
resources is measured by the requirement of imported environmental factors over the total
requirement.
In addition, the Herfindahl index will be used to look at the concentration of the
environmental requirements over the countries from which a sector imports. This highlights
an important aspect of dependency; importing from multiple sources will make a country less
dependent on one particular supplier. The index can be represented as given by equation 3,
where k is the index representing the different resources.
2
,
R RS
ki ijS ikj R RS
R S ki ij
i R S
d l
Hd l
≠
≠
=
∑∑
∑ 2
Each country has potentially 42 trading partners. For 42 observations, the value of the
Herfindahl index would equal to 1/42 ≈ 0.0238 in case each of the environmental multipliers
is exactly the same for each trade partner. This corresponds to full diversification over
countries from which a particular country demands its imports and embodied resources. When
a country only imports the embodied resources from one trade partner the value of the
Herfindahl index will be equal to 1. The higher the value of the Herfindahl index the more
dependent a country is on one, or a few countries, to fulfill its demand for embodied
materials.
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3. Data
We use the international EE IOT for the year 2000 as constructed by the EXIOPOL project
team.4 The objective of the project is to enable the estimation of environmental impacts and
external costs of industry activities and consumption activities of countries in the European
Union. These environmental impacts include greenhouse gases emitted, pollutants discarded,
and resources used as inputs to production (Tukker et al. 2009). The construction of the
EEIOT is a core element of the project, because it has been identified as the most suitable
database for environmental policy analysis (Wiedmann et al., 2007; Wiedmann, 2009).
The EXIOPOL database, which has as core an environmentally extended IO
framework, contains satellite accounts for 186 environmental factors. The focus on the
environment also called for more detail in the sectors that are mostly involved in generating
or using these environmental factors. Agriculture, food products, mining and energy have
been disaggregated into multiple subsectors. By covering around 80 per cent of world GDP,
adding sectoral detail and the incorporation of bilateral trade, the EXIOPOL database caters
directly for the need of harmonized and improved data for EE IOT analysis (Tukker et al.,
2009).
The full EXIOPOL database consists of the supply and use tables (SUT) of 43
countries5 and an aggregated ‘Rest of the World’ (RoW). The supply and use tables
maintained by Eurostat (referred to as the ESA-95 tables) are used as basis for the supply and
use tables of the European Union countries. These tables have been disaggregated in industry
and commodity classification to 129 industries and products, still in a squared set-up of the
SUT. See for a more detailed description of the construction methods (Wood et al., 2010).
The tables are linked to each other via bilateral trade flows using a methodology that
combines information on origin and destination of trade flows from trade statistics with the
aggregated trade data in the SUT. In the process of regaining consistency after combining
these two data sources, the data are also revalued from cost-insurance-freight prices of the
purchasing country to basic prices of the producing country. (For a full description of the
methodology see (Bouwmeester and Oosterhaven, 2008). It has to be noted that although
several information sources are combined to construct a full international SUT, these tables
do not represent full information. The database also contains input-output tables that have
resulted from input-output modeling of the supply and use tables.
4 EXIOPOL is the acronym for: a new environmental accounting framework using externality data and
input-output tools for policy analysis. The project website is www.feem-project.net/exiopol, last
accessed 27-04-2010. The data will be made available through www.exiobase.eu.
5 See the appendix tables for a full list of the countries included.
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All supply and use tables are extended with satellite accounts of social and
environmental variables. The environmental extensions focused on in this study are the
materials that are known as scarce or will become scare in the future. We report results for 1)
iron ores, 2) aluminum and bauxite ores, 3) copper ores, 4) precious metal ores, 5) chemical
and fertilizer minerals, and as aggregate category 6) fossil energy carriers6. In order to
aggregate the information of fossil energy carriers, the data in kilograms has been converted
to energetic values by applying general calorific values7. For more information on the
environmental extensions data construction, see (Lutter et al., 2011).
Not all countries are suppliers of material resources. It may be that the materials are
not present at all within a country’s territory as a natural resource. Alternatively, it may be
that there are material resources, but only in a limited amount or hard to retrieve, making it
economically uninteresting to mine the materials. Three countries do not extract any of the six
types of materials analyzed here: Luxembourg, Malta, and Switzerland. For fossil fuels, the
following countries do not mine coal or extract oil or gas8; Belgium, Cyprus, Luxembourg,
Malta, Portugal and Switzerland. Iron ores are extracted by 25 individual countries and the
RoW region. Aluminium and bauxite ores are extracted by 13 countries and the RoW. Copper
ores are extracted by 21 countries and the RoW. Precious metals are extracted by 27 countries
and the RoW region. Chemical and fertilizer minerals are extracted by 35 countries and the
RoW.
In Table 1, the top three of countries with the most domestic extraction, as well as the
top three of countries with the most material use per million € output are represented9. For
fossil fuel carriers, chemical/fertilizer minerals, copper and precious metals the RoW is the
6 The results are based on the environmental extensions of that represent domestic extraction. Unused
domestic extraction related to these materials is not included in the analysis, as these material flows do
not enter the economic system.
7 The different fossil energy carriers are each again mixes of carriers with different calorific values, in
addition, calorific values also differ for the same carrier, e.g. natural gas depending on country and
region of extraction. For each group of energy carriers we use a general calorific value, to arrive at an
energetic value for fossil energy carriers, which is more informative than a simple aggregate based on
weight. The fossil energy carriers included, and the calorific values used are: hard coal 25 MJ/kg,
lignite/brown coal 10 MJ/kg, crude oil 42 MJ/kg, natural gas 38 MJ/kg, natural gas liquids 38 MJ/kg,
peat for energy use 8 MJ/kg. These values are determined based on (International Energy Agency
2003) and information provided by prof.dr. H.C. Moll in personal communications.
8 In case an environmental extension is recorded while the SUT record no output by the specific
industry, the value of the environmental extension is disregarded in the analysis presented here.
9 See Appendix 2, Table 1 for the table of resource use in kilogram per € output for all countries
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largest extractor of materials, however its ranking in terms of the use of materials per euro
output of the related mining industry is for fossil energy carriers 23nd
, for chemical/fertilizer
minerals 15th, for copper ores 5
th and for precious metals ores 4
th. China ranks first total
domestic extraction of iron ores, and third on the quantity of iron ores used to produce the
output of the mining industry of iron ore. China uses much iron ore and its mining industry is
apparently also not very efficient. The same holds for chemical/fertilizer materials and copper
ores in the United States. The values for the domestic extraction used per € output is relatively
large for India in case of aluminum/bauxite ores and for Brazil concerning copper ores.
Table 1: Domestic extraction used
fossil fuel carriers GMJ*
% fossil fuel carriers MJ / €
1 Rest of the World 106 34 1 Hungary 2469
2 United States 52 16 2 South Africa 1609
3 China 37 12 3 Greece 1361
chem./fert. minerals MMT*
% chem./fert. minerals kg / €
1 Rest of the World 62 28 1 Romania 71
2 United States 51 23 2 Russian Federation 41
3 China 34 16 3 Finland 16
iron ores MMT % iron ores kg / €
1 China 224 21 1 Indonesia 182
2 Brazil 210 19 2 India 158
3 Australia 172 16 3 China 157
aluminum/bauxite ores MMT % aluminum/bauxite ores kg / €
1 Australia 121 51 1 India 238
2 Rest of the World 46 22 2 France 81
3 Brazil 14 7 3 Hungary 46
copper ores MMT % copper ores kg / €
1 Rest of the World 767 44 1 Brazil 609
2 United States 380 22 2 United States 359
3 Indonesia 119 7 3 Bulgaria 325
precious metal ores MMT % precious metal ores kg / €
1 Rest of the World 403 53 1 Bulgaria 95
2 United States 89 12 2 France 64
3 Australia 74 10 3 South Korea 51
* GMJ = Giga Mega Joules, MMT = Million Metric Tonne
4. Results and discussion
In this section an analysis is presented of the dependency of countries on trade partners to
fulfill their demand for embodied materials. To focus the discussion of the results, we
selected the industries that on a world scale demand the most additional resources per Euro of
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output. For this purpose we have created a simple world supply and use table and a vector
with the total material use per ‘world’ sector10
. For these selected industries we computed the
share of the international environmental multiplier in the total environmental multiplier as a
measure of dependency on trade partners to fulfill the demand for embodied resources. Next,
we also look at the Herfindahl index of the international multipliers to determine the
concentration of dependency. Finally, a correlation analysis is undertaken to see whether
higher international dependence of countries is related to a higher concentration of
international dependence. This would indicate that the sector may be very vulnerable to the
effects of increasing scarcity of material resources.
Due to the large amount of sectors; 129 sectors in each of the 43 countries included in
the dataset, we have chosen to focus our analysis to the sectors that on average (as ‘world’
total) have the highest resource use per € of demand for that sectors’ output. See Table 2 for
the ranking of the industries and the related value of the environmental multiplier for each of
the material groups considered. For each material group the sector which mines or extracts
that resource is associated to the largest environmental multiplier (i.e. the industry that ranks
first in Table 2 for each material). Fossil fuel carriers are extracted by sector i10, sector i11.a,
sector i11.b and sector i11.c. More interesting are the sectors in the table that are not directly
related to the mining of the material resources. As can be expected, the second largest users of
domestic resources per unit of final demand are the directly downstream sectors that produce
products of the materials. For example, for copper ores, the second largest user is i27.44 –
copper products. The quantity of material resources used per unit of final demand for the
downstream sectors quickly decreases; other inputs gain in importance. In Appendix 2 –
Table 2 the detailed breakdown of the environmental multipliers per country can be found.
10 To make a real world table, all international trade flows would have to become part of the domestic
transactions matrices.
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Table 2: Largest environmental multipliers per material for the ‘world’
Megajoule / kilogram of additional domestic extraction per additional € demand
rank fossil energy carriers chemical/fertilizer minerals iron ores
1 p10 721 p14.3 4 p13.1 39
2 p11.b 352 p26.e 0.3 p27.a 2
3 p11.a 259 p26.d 0.1 p12 0.5
4 p40.11.a 240 p12 0.1 p27.5 0.4
5 p23.20.a 164 p27.43 0.1 p13.20.13 0.3
rank aluminum/bauxite copper ores precious metals
1 p13.20.13 6 p13.20.11 116 p13.20.14 28
2 p27.42 1 p27.44 11 p27.41 2
3 p27.5 0.4 p12 2 p26.c 0.2
4 p12 0.1 p27.41 1 p12 0.2
5 p28 0.03 p37.1 0.5 p26.a 0.2 Note: See Appendix 1 for the sector classification codes and labels.
There is a large variation in the individual country multipliers as shown in Appendix
2 – Table 2. For fossil energy carriers this can be due to the composition of the energy
carriers. The net calorific value of the different types of fossil energy carriers has been
crudely applied to aggregate the carriers. Specifically for the different types of coal used by
sector i10 – coal and lignite; peat, the range of net calorific value can be rather large. For each
of the three main extractive sectors, i10, i11.a, and i11.b, we find quite large variation in the
environmental multipliers. However, for the downstream sectors i40.11.a and i23.20.a most
multipliers are relatively close to the World average.
For chemical/fertilizer minerals, Finland, Greece, Lithuania, Romania, Russia, and
the United States have high multipliers for the related mining sector i14.3. Only Lithuania and
Romania have comparatively large multi pliers for sector i26.e – other non-metallic mineral
products. Greece and Romania and Lithuania still use more than a kilogram per € final
demand in sector i26.d – cement, lime and plaster.
China, India, Indonesia and the Slovak Republic all require more than 100 kg metals
per euro of extra final demand for output of sector i13.1; iron ores. This is about four times as
much as the world average. Final demand related to sector i27.a results in the largest
additional amounts of iron used in China and Brazil, of 8 kg/€ and 6 kg//€. Basic
manufacturing of iron and steel in these countries requires more ores per euro of final
demand. For the other metal ores the picture is rather similar in terms of variation, with the
exception of India for aluminum ores and Brazil for copper ore, which seem to be outliers.
The multipliers per country-sector can be broken into a domestic environmental
multiplier and an international environmental multiplier. The international environmental
multiplier as percentage of the total multiplier is a measure of the dependence of a country on
foreign suppliers. It shows the share of additional demand for materials that has to be satisfied
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from suppliers abroad. The higher this percentage the more dependent a country is on foreign
suppliers. In Appendix 2 – Table 3 to Table 8 the international multiplier percentage is given
per material for each country for the five sectors that require, on a world scale, the most
additional material resources when demand for its products increases. These tables also show
the Herfindahl index (HI) calculated based on the international multipliers.
A combination of a high international environmental multiplier combined with a high
value for the Herfindahl index can indicate a vulnerable supplier relationship for a specific
material resource and the sector that requires the material in its production process. Table 3
below shows the results for the sectors that are the runner up to the extractive sector in terms
of quantity used per € of final demand.
From Table 3 it can be seen that most small European countries have a high
international multiplier percentage, which is consistent with the European open market.
However, the Herfindahl index for the East-European countries is in general higher than the
Herfindahl index for the West-European countries. The concentration of supplier relations is
especially high for fossil energy carriers, even though 37 of the countries included in the
dataset extract fossil fuel carriers domestically. This would suggest that especially for Estonia
and Latvia, it might be wise to diversify their supplier relations more, as these counties score
high on the international dependence and on the concentration of suppliers. Only a few
countries extract aluminium/bauxite ores, so most countries fully rely on imports of these
ores. In addition, the concentration of suppliers is rather high – especially given the reliance
on imports, for Mexico, Norway, Poland, South Africa, Spain and Sweden. For copper ores
the countries that are most vulnerable are China, Germany, Luxembourg, South Korea and the
U.K. Regarding precious metals, France, Indonesia, Lithuania and South Africa might want to
investigate their supplier relations.
In Table 4 the coefficients of determination are presented. These values show for the
five ‘heavy use’ sectors for each of the three material groups how much of the variation in the
one variable can be explained by the variation of the other. In other words, a high coefficient
of determination shows whether the total material multipliers (tm), the extent of international
dependency (id), measured as percentage international material multiplier in the total material
multiplier and the Herfindahl index (hi) of the international multipliers correlate over the
countries.
Most relations between the total resource multiplier and international dependency
enter with a negative sign. Countries that use much material resources per unit of final
demand apparently use domestically extracted resources. This may be a matter of
specialization; the availability of domestic resources may stimulate the development large
specialized sectors that focus on mining or making products of the ores that are abundantly
available. Also, if a resource is abundantly available it may result in inefficiency in using the
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resource, especially if the natural supply seems unlimited. The most interesting coefficient of
determination, the one between the international dependency measure and the Herfindahl
index of the international multipliers, does not show very strong results. Sector i11.b – natural
gas and services, sector i14.3 – chemical and fertilizer minerals and sector i13.1 – mining of
iron ores show the highest coefficients. Sector i13.20.13 – aluminum ores and i37.1 –
recycling, are also related to high coefficients, but these relationships have a negative sign.
5. Conclusion and outlook
These first results indicate that international dependency on material resource suppliers differs
much from sector to sector. Especially for sectors that are of strategic importance to the
functioning of the economy at large, it is important to investigate the extent of dependency
and the concentration of dependency. A start of the analysis of dependency has been made in
this paper, but the matter is definitely in need of further investigation.
As expected, the sectors that extract the resources are the most resource intensive
sectors in terms of physical material used per Euro of output generated. Resource intensity
quickly decreases when a sector only uses intermediate inputs in which materials are
embodied. However, in case this intermediate input is vital for production, the quantity
embodied is not directly relevant, as production will halt without it. In this sense, the
international dependency measure is relevant, irrespective of the total material use of a sector.
Although there is not a single sector that shows large dependency across all countries, some
country-sector pairs are associated with full international dependency and a high
concentration of the suppliers. For the sectors we investigated this is observed for all six types
of materials. In addition, for the metal ores on average only half of the 43 countries and RoW
extract these materials, limiting the possibilities for changing suppliers or decreasing the
concentration of supply.
The EXIOPOL database offers a wealth of information. However, no direct
information about the scarcity of natural resources per country is included, while this directly
influences the topics discussed in this paper. The environmental multipliers vary widely. In
highly aggregated international IO tables this can be expected due to the fact that very
different sectors can be lumped together. However, in the EXIOPOL project much effort has
been put in detailing the sectors that are important from an environmental and natural
resource perspective. To still find such varying multipliers is an issue for further investigation
about the characteristics of the database and the quality of the data.
Generalizing in term of dependency and concentration appears to offer rather weak
results. This implies that we cannot identify a sector that is generally vulnerable, independent
of the country the sector is present in. Although a general claim cannot be made for a specific
sector, for some counties and sectors the dependence on a single country to supply the
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resources is rather large. In this paper we have made a start in creating a picture of the
relationships between raw material suppliers and the final users of the embodied minerals.
Table 3: Selected sectors, % international multiplier of total multiplier and Herfindahl index
fossil energy carriers chem./fert. minerals iron ores
i40.11.a i26.e i27.a
inter % HI inter % HI inter % HI
Australia 2 1 23 0.2 13 0.3
Austria 100 0.5 100 0.2 100 0.2
Belgium 100 0.4 99 0.3 100 0.2
Brazil 31 0.2 53 0.3 0.2 0.1
Bulgaria 18 1 24 0.3 25 0.3
Canada 59 1 26 0.2 42 1 China 1 0.5 8 0.2 4 0.3
Cyprus - - 100 0.3 - -
Czech Rep. 6 1 99 0.2 100 1 Denmark 98 0.4 100 0.2 100 0.1
Estonia 100 1 100 1 100 0.3
Finland 83 0.4 9 0.1 100 0.3
France 76 0.2 86 0.1 100 0.2
Germany 8 0.1 68 0.1 100 0.2
Greece 2 0.4 1 0.3 28 0.2
Hungary 11 1 100 0.4 100 0.5
India 2 0.2 75 0.3 1 0.2
Indonesia 10 1 87 0.2 99 0.2
Ireland 36 0.2 100 0.1 100 0.1
Italy 100 0.2 100 0.2 100 0.3
Japan 100 0.3 41 0.2 100 0.3
Latvia 98 1 100 1 100 0.3
Lithuania - - 100 1 100 0.3
Luxembourg - - 100 0.5 100 0.2
Malta - - 100 0.4 100 0.2
Mexico 35 0.4 48 0.3 38 0.5
Netherlands 99 0.3 85 0.1 100 0.2
Norway 83 0.2 100 0.5 70 0.3
Poland 4 0.4 100 0.2 100 0.4
Portugal 100 0.4 88 0.2 99 0.3
Romania 30 1 15 0.3 96 0.3
Russia 1 1 25 0.2 48 1
Slovak Rep. 98 0.4 100 0.3 94 0.5
Slovenia 4 0.1 100 0.4 100 0.2
South Africa 1 0.2 97 0.2 93 0.2
South Korea 93 0.2 70 0.4 100 0.3
Spain 63 0.4 86 0.2 97 1
Sweden 83 0.3 84 0.1 43 0.2
Switzerland - - 100 0.2 100 0.2
Taiwan 100 0.2 87 0.2 100 0.3
Turkey 55 0.4 43 0.2 80 0.2
U.K. 30 0.2 100 0.4 100 0.2
U.S. 1 0.4 14 0.4 29 0.3
RoW 20 0.2 16 0.3 66 0.3
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
14
Table 3: Selected sectors, % international multiplier of total multiplier and Herfindahl index
aluminum/bauxite copper ores precious metals
i27.42 i27.44 i27.41
inter % HI inter % HI inter % HI
Australia 0.3 0.2 6 1 0.2 1
Austria - - 100 0.5 - - Belgium - - 100 0.4 - - Brazil 26 0.4 11 0.4 1 0.4
Bulgaria - - 2 1 1 1 Canada 100 0.4 0.2 1 97 0.3
China 50 1 100 1 57 0.5
Cyprus - - 99 0.2 - -
Czech Rep. - - - - - - Denmark - - - - - - Estonia - - - - - -
Finland - - 100 0.4 100 0.2
France 99 0.5 35 0.3 99 1
Germany 100 0.3 100 1 - - Greece 39 1 - - 85 0.2
Hungary 14 0.2 100 0.4 - -
India 10 1 87 0.5 15 1 Indonesia 62 1 77 0.4 100 1
Ireland - - - - 45 0.2
Italy 100 0.2 100 0.3 98 0.2
Japan 100 0.3 100 0.4 98 0.4
Latvia - - - - - - Lithuania 100 0.2 100 0.4 100 1
Luxembourg 100 0.4 100 1 100 0.2
Malta 100 0.3 100 0.2 100 0.4
Mexico 100 1 47 1 42 1
Netherlands 100 0.5 - - - - Norway 100 1 100 0.3 - -
Poland 100 1 9 0.5 98 0.2
Portugal - - - - 100 0.4
Romania 100 0.4 31 0.4 1 0.2
Russia 78 0.5 49 1 21 1 Slovak Rep. 100 0.2 - - 20 0.2
Slovenia 100 0.2 - - - - South Africa 100 1 96 0.3 98 1
South Korea - - 100 1 - - Spain 100 1 87 0.5 15 1 Sweden 100 1 39 1 58 0.5
Switzerland 100 0.3 - - - - Taiwan - - 100 0.3 100 0.4
Turkey 26 0.2 79 0.4 1 0.2
U.K. 100 0.3 100 1 - - U.S. 97 0.3 16 0.3 18 0.3
RoW 79 1 29 0.3 42 1
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
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Table 4: Coefficients of determination as percentage (R2 – % of variation explained)
fossil enery carriers chem./fert. minerals iron ores
id hi id hi id hi
i10 tm (-) 22.3 3.8 i14.3 tm (-) 7.3 0.3 i13.1 tm (-) 13.0 (-) 4.0
44 id 2.4 44 id 15.4 24 id 14.2
i11.b tm (-) 2.6 (-) 4.3 i26.e tm 0.1 43.7 i27.a tm (-) 32.0 9.3
44 id 18.0 44 id 5.4 43 id 0.5
i11.a tm (-) 3.1 3.8 i26.d tm (-) 14.6 8.8 i12 tm (-) 0.3 (-) 4.3
44 id 2.0 44 id 5.4 16 id 0.0
i40.11.a tm (-) 23.4 (-) 7.3 i12 tm (-) 11.4 0.8 i27.5 tm 53.1 (-) 0.5
44 id 0.2 44 id 11.5 30 id 0.6
i23.20.a tm (-) 0.4 (-) 27.5 i27.43 tm (-) 20.7 (-) 22.3 i13.20.13 tm (-) 0.5 11.0
44 id 0.3 44 id 0.3 16 id 1.3
aluminum/bauxite copper ores precious metals
id hi id hi id hi
i13.20.13 tm (-) 8.7 19.5 i13.20.11 tm (-) 11.5 (-) 0.2 i13.20.14 tm (-) 3.6 19.9
16 id (-) 14.2 26 id 0.1 30 id (-) 0.4
i27.42 tm (-) 29.6 0.5 i27.44 tm (-) 19.6 15.9 i27.41 tm (-) 18.9 21.7
31 id (-) 1.9 33 id (-) 7.3 29 id (-) 4.1
i27.5 tm 0.6 26.1 i12 tm (-) 20.6 (-) 7.6 i26.c tm (-) 19.0 16.9
30 id (-) 7.5 16 id 1.1 44 id 2.0
i12 tm 0.0 4.7 i27_41 tm (-) 26.5 0.4 i12 tm (-) 21.3 0.2
16 id (-) 1.3 29 id (-) 4.4 16 id (-) 3.1
i28 tm (-) 4.3 58.3 i37.1 tm (-) 58.0 (-) 10.4 i26.a tm (-) 20.0 6.8
44 id 4.1 31 id (-) 24.8 44 id (-) 0.0 Note: the numbers in italics beneath the sector code indicate the number of countries that have a total
multiplier recorded and that have been included in the calculation of the coefficients of determination.
Acknowledgements
This work is part of the EXIOPOL project (A New Environmental Accounting Framework
Using Externality Data and Input-Output Tools for Policy Analysis, http://www.feem-
project.net/exiopol), which is an integrated project funded by the European Union, under
Framework Programme 6, Priority 6.3 Global Change and Ecosystems, Grant agreement no.
037033-2. The author would like to thank all EXIOPOL partners for their cooperation, and
prof. dr. Sangwon Suh, prof. dr. Tukker and prof. dr. J. Oosterhaven for their comments.
The author would like to acknowledge the support by prof. dr. H.C. Moll, who shared his
expert opinion on the average calorific values of fossil energy carriers.
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
16
References
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Hummels D., Ishii J. and Yi K., 2001. The nature and growth of vertical specialization in
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Lutter S., Giljum S., Acosta J., Wittmer D., Kuenen J. and Pulles T., 2011. Documentation
(technical report) of data sets compilation for environmental extensions. , EXIOPOL
Deliverable DIII.2.b-2 and DIII.3.b-2.
Peters G.P., 2008. From production-based to consumption-based national emission
inventories. Ecological Economics, 65:13-23.
Prins A.G., Slingerland S., Manders A.J.G., Lucas P.L., Hilderink H.B.M. and Kok M.T.J.,
2011. Scarcity in a sea of plenty? Global resources scarcities and policies in the European
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500167001.
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evaluation of approaches. Ecological Economics, 69:2224-2232.
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Tukker A., Poliakov E., Heijungs R., Hawkins T., Neuwahl F., Rueda-Cantuche J.M., Giljum
S., Moll S., Oosterhaven J. and Bouwmeester M., 2009. Towards a global multi-regional
environmentally extended input-output database. Ecological Economics, 68:1928-1937.
Wiedmann T., 2009. A review of recent multi-region input-output models used for
consumption-based emission and resource accounting. Ecological Economics, 69:211-222.
Wiedmann T., Lenzen M., Turner K. and Barrett J., 2007. Examining the global
environmental impact of regional consumption activities -- Part 2: Review of input-output
models for the assessment of environmental impacts embodied in trade. Ecological
Economics, 61:15-26.
Wood R., Hawkins T., van Bree T. and Poliakov E., 2010. Development of Harmonized
Supply and Use Tables for the EXIOPOL Database, and, Consumption Activities and Waste
in EXIOBASE. , EXIOPOL Deliverable DIII.2.a, DIII.3.a, DIII.2.c.2 and DIII.2.c.3.
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
18
Appendix 1: sector classification
i01.a Cultivation of paddy rice
i01.b Cultivation of wheat
i01.c Cultivation of cereal grains nec
i01.d Cultivation of vegetables, fruit, nuts
i01.e Cultivation of oil seeds
i01.f Cultivation of sugar cane, sugar beet
i01.g Cultivation of plant-based fibers
i01.h Cultivation of crops nec
i01.i Cattle farming
i01.j Pigs farming
i01.k Poultry farming
i01.l Meat animals nec
i01.m Animal products nec
i01.n Raw milk
i01.o Wool, silk-worm cocoons
i02 Forestry, logging and related service activities (02)
i05 Fishing, operating of fish hatcheries and fish farms; service activities incidental to fishing (05)
i10 Mining of coal and lignite; extraction of peat (10)
i11.a Extraction of crude petroleum and services related to crude oil extraction, excluding surveying
i11.b Extraction of natural gas and services related to natural gas extraction, excluding surveying
i11.c Extraction, liquefaction, and regasification of other petroleum and gaseous materials
i12 Mining of uranium and thorium ores (12)
i13.1 Mining of iron ores
i13.20.11 Mining of copper ores and concentrates
i13.20.12 Mining of nickel ores and concentrates
i13.20.13 Mining of aluminium ores and concentrates
i13.20.14 Mining of precious metal ores and concentrates
i13.20.15 Mining of lead, zinc and tin ores and concentrates
i13.20.16 Mining of other non-ferrous metal ores and concentrates
i14.1 Quarrying of stone
i14.2 Quarrying of sand and clay
i14.3 Mining of chemical and fertilizer minerals, production of salt, other mining and quarrying n.e.c.
i15.a Processing of meat cattle
i15.b Processing of meat pigs
i15.c Processing of meat poultry
i15.d Production of meat products nec
i15.e Processing vegetable oils and fats
i15.f Processing of dairy products
i15.g Processed rice
i15.h Sugar refining
i15.i Processing of Food products nec
i15.j Manufacture of beverages
i15.k Manufacture of fish products
i16 Manufacture of tobacco products (16)
i17 Manufacture of textiles (17)
i18 Manufacture of wearing apparel; dressing and dyeing of fur (18)
i19 Tanning and dressing of leather; manufacture of luggage, handbags, saddlery, harness and footwear (19)
i20 Manufacture of wood and of products of wood and cork, except furniture; manufacture of articles of straw and
plaiting materials (20)
i21 Manufacture of pulp, paper and paper products (21)
i22 Publishing, printing and reproduction of recorded media (22)
i23.1 Manufacture of coke oven products
i23.20.a Manufacture of motor spirit (gasoline)
i23.20.b Manufacture of kerosene, including kerosene type jet fuel
i23.20.c Manufacture of gas oils
i23.20.d Manufacture of fuel oils n.e.c.
i23.20.e Manufacture of petroleum gases and other gaseous hydrocarbons, except natural gas
i23.20.f Manufacture of other petroleum products
i23.3 Processing of nuclear fuel
i24 Manufacture of chemicals and chemical products (24)
i25 Manufacture of rubber and plastic products (25)
i26.a Manufacture of glass and glass products
i26.b Manufacture of ceramic goods
i26.c Manufacture of bricks, tiles and construction products, in baked clay
i26.d Manufacture of cement, lime and plaster
i26.e Manufacture of other non-metallic mineral products n.e.c.
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sector classification – continued
i27.a Manufacture of basic iron and steel and of ferro-alloys and first products thereof
i27.41 Precious metals production
i27.42 Aluminium production
i27.43 Lead, zinc and tin production
i27.44 Copper production
i27.45 Other non-ferrous metal production
i27.5 Casting of metals
i28 Manufacture of fabricated metal products, except machinery and equipment (28)
i29 Manufacture of machinery and equipment n.e.c. (29)
i30 Manufacture of office machinery and computers (30)
i31 Manufacture of electrical machinery and apparatus n.e.c. (31)
i32 Manufacture of radio, television and communication equipment and apparatus (32)
i33 Manufacture of medical, precision and optical instruments, watches and clocks (33)
i34 Manufacture of motor vehicles, trailers and semi-trailers (34)
i35 Manufacture of other transport equipment (35)
i36 Manufacture of furniture; manufacturing n.e.c. (36)
i37.1 Recycling of metal waste and scrap
i37.2 Recycling of non-metal waste and scrap
i40.11.a Production of electricity by coal
i40.11.b Production of electricity by gas
i40.11.c Production of electricity by nuclear
i40.11.d Production of electricity by hydro
i40.11.e Production of electricity by wind
i40.11.f Production of electricity nec, including biomass and waste
i40.12 Transmission of electricity
i40.13 Distribution and trade of electricity
i40.2 Manufacture of gas; distribution of gaseous fuels through mains
i40.3 Steam and hot water supply
i41 Collection, purification and distribution of water (41)
i45 Construction (45)
i50.a Sale, maintenance, repair of motor vehicles, motor vehicles parts, motorcycles, motor cycles parts and
accessories
i50.b Retail sale of automotive fuel
i51 Wholesale trade and commission trade, except of motor vehicles and motorcycles (51)
i52 Retail trade, except of motor vehicles and motorcycles; repair of personal and household goods (52)
i55 Hotels and restaurants (55)
i60.1 Transport via railways
i60.2 Other land transport
i60.3 Transport via pipelines
i61.1 Sea and coastal water transport
i61.2 Inland water transport
i62 Air transport (62)
i63 Supporting and auxiliary transport activities; activities of travel agencies (63)
i64 Post and telecommunications (64)
i65 Financial intermediation, except insurance and pension funding (65)
i66 Insurance and pension funding, except compulsory social security (66)
i67 Activities auxiliary to financial intermediation (67)
i70 Real estate activities (70)
i71 Renting of machinery and equipment without operator and of personal and household goods (71)
i72 Computer and related activities (72)
i73 Research and development (73)
i74 Other business activities (74)
i75 Public administration and defence; compulsory social security (75)
i80 Education (80)
i85 Health and social work (85)
i90.01 Collection and treatment of sewage
i90.02.a Collection of waste
i90.02.b Incineration of waste
i90.02.c Landfill of waste
i90.03 Sanitation, remediation and similar activities
i91 Activities of membership organisation n.e.c. (91)
i92 Recreational, cultural and sporting activities (92)
i93 Other service activities (93)
i95 Private households with employed persons (95)
i99 Extra-territorial organizations and bodies
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Appendix 2: additional result tables
Table 1: Domestic extraction used – MJ or kilogram per € output by country, ordered
Fossil energy carriers Chem./fert. minerals Iron ores
1 Hungary 2469 Romania 71 Indonesia 182
2 South Africa 1609 Russia 41 India 158
3 Greece 1361 Finland 16 China 157
4 Bulgaria 1205 US 16 Slovak Rep. 121
5 Czech Rep. 1166 Greece 14 Sweden 97
6 Russia 1131 Lithuania 14 Brazil 81
7 Estonia 1057 Mexico 9 Australia 60
8 India 963 Canada 8 Greece 59
9 Poland 707 Bulgaria 8 South Korea 43
10 Romania 643 Slovak Rep. 6 Mexico 41
11 Indonesia 573 France 5 US 35
12 China 472 South Korea 4 RoW 33
13 Germany 425 Belgium 4 Canada 31
14 South Korea 419 Czech Rep. 4 Bulgaria 29
15 Australia 407 RoW 4 Turkey 25
16 Turkey 373 Spain 3 Spain 20
17 Spain 336 Australia 3 Romania 15
18 US 326 Italy 3 South Africa 12
19 Slovenia 321 Germany 3 Norway 8
20 France 289 India 3 Russia 7
21 Brazil 242 China 3 Japan 1
22 Austria 225 Japan 2 Portugal 1
23 RoW 221 Hungary 2 Austria -
24 Slovak Rep. 210 South Africa 2 Belgium -
25 Denmark 201 Turkey 2 Cyprus -
26 Canada 194 Brazil 2 Czech Rep. -
27 Mexico 188 Sweden 2 Denmark -
28 Norway 186 Norway 2 Estonia -
29 Finland 185 Netherlands 1 Finland -
30 UK 183 Denmark 1 France -
31 Ireland 157 Cyprus 0.3 Germany -
32 Netherlands 155 Taiwan 0.3 Hungary -
33 Italy 153 Portugal 0.3 Ireland -
34 Lithuania 137 Indonesia 0.2 Italy -
35 Japan 86 UK 0.2 Latvia -
36 Sweden 46 Austria 0.1 Lithuania -
37 Latvia 40 Estonia - Luxembourg -
38 Taiwan 22 Ireland - Malta -
39 Belgium - Latvia - Netherlands -
40 Cyprus - Luxembourg - Poland -
41 Luxembourg - Malta - Slovenia -
42 Malta - Poland - Switzerland -
43 Portugal - Slovenia - Taiwan -
44 Switzerland - Switzerland - UK - Note: - means no domestic extraction.
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Table 1 continued: Domestic extraction used – kilogram per € output by country, ordered
Aluminium/bauxite ores Copper ores Precious metals
1 India 238 Brazil 609 Bulgaria 95
2 France 81 US 359 France 64
3 Hungary 46 Bulgaria 325 South Korea 51
4 Australia 32 Indonesia 173 RoW 49
5 Greece 20 RoW 124 Australia 44
6 Brazil 16 China 119 Brazil 37
7 US 11 Russia 110 Hungary 30
8 Turkey 9 Mexico 92 Spain 30
9 Indonesia 9 Australia 89 Indonesia 30
10 RoW 6 Spain 86 US 27
11 China 1 Romania 72 Sweden 23
12 Russia 0.3 Sweden 69 Russia 21
13 Italy 0.1 Turkey 54 China 18
14 Austria - France 47 Japan 18
15 Belgium - Poland 46 South Africa 14
16 Bulgaria - Japan 41 Ireland 13
17 Canada - South Africa 40 Canada 12
18 Cyprus - India 30 Turkey 12
19 Czech Rep. - Canada 29 India 6
20 Denmark - Portugal 4 Romania 5
21 Estonia - Finland 1 Mexico 4
22 Finland - Cyprus 0.3 Italy 3
23 Germany - Austria - Slovak Rep. 2
24 Ireland - Belgium - Finland 1
25 Japan - Czech Rep. - Norway 0.5
26 Latvia - Denmark - Greece 0.5
27 Lithuania - Estonia - Portugal 0.4
28 Luxembourg - Germany - Poland 0.2
29 Malta - Greece - Austria -
30 Mexico - Hungary - Belgium -
31 Netherlands - Ireland - Cyprus -
32 Norway - Italy - Czech Rep. -
33 Poland - Latvia - Denmark -
34 Portugal - Lithuania - Estonia -
35 Romania - Luxembourg - Germany -
36 Slovak Rep. - Malta - Latvia -
37 Slovenia - Netherlands - Lithuania -
38 South Africa - Norway - Luxembourg -
39 South Korea - Slovak Rep. - Malta -
40 Spain - Slovenia - Netherlands -
41 Sweden - South Korea - Slovenia -
42 Switzerland - Switzerland - Switzerland -
43 Taiwan - Taiwan - Taiwan -
44 UK - UK - UK -
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
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Table 2: Environmental multipliers by country –MJ or kilogram per € demand
Fossil energy carriers Chem./fert. minerals Iron ores
i10 i11.b i11.a
i40.
11.a
i23.
20.a
i14.3 i26.e i26.d
i13.1
i27.
a i12
Australia 784 147 179 195 170 3 0.1 0.05 61 4 0.1
Austria 236 151 818 237 142 0.2 0.2 0.05 - 0.3 -
Belgium - - - 47 63 5 0.2 0.1 - 0.4 -
Brazil 1001 278 254 304 157 2 0.5 0.05 81 6 0.1
Bulgaria 1475 127 492 771 344 9 1 0.4 29 2 0.1
Canada 1455 192 158 406 163 8 0.3 0.04 31 2 0.04
China 697 120 296 279 174 3 1 0.3 157 8 0.1
Cyprus 10 - 8 - 287 0.3 0.1 0.1 - - -
Czech Rep. 1279 190 4803 467 347 4 0.1 0.03 0.1 3 0.2
Denmark - 159 225 140 186 1 0.1 0.03 - 0.2 -
Estonia - 45 - 19 178 0.2 1 0.2 - 1 -
Finland 215 - - 377 177 17 0.4 0.2 - 3 -
France 473 389 25774 158 135 5 0.04 0.01 - 1 0.1
Germany 541 244 68733 143 184 3 0.1 0.03 - 1 -
Greece 1591 166 237 517 201 14 1 2 59 1 -
Hungary 2780 1870 33994 202 83 2 0.4 0.1 - 3 -
India 1180 1403 439 416 218 3 0.3 0.2 158 4 -
Indonesia 613 500 634 503 169 0.2 0.2 0.01 182 0.5 -
Ireland 262 402 29 135 140 0.03 0.03 0.02 - 0.04 -
Italy 20 191 9038 53 191 3 0.03 0.02 - 1 -
Japan 1483 73 35 246 116 2 0.2 0.1 2 2 0.1
Latvia 67 - - 69 160 0.01 1 - - 1 -
Lithuania 34 29 191 - 278 16 10 1 - 0.3 -
Luxembourg - - - - - 0.1 0.1 0.1 - 0.4 -
Malta - 6 4 - 82 0.1 0.1 - - 1 -
Mexico 1179 50372 149 353 104 9 0.3 0.2 42 2 0.00
Netherlands 0 185 13103 39 204 1 0.2 0.1 - 1 -
Norway 227 149 205 3 155 2 1 0.3 8 1 -
Poland 704 - - 269 58 0 0.00 0.00 - 3 -
Portugal - - - 86 202 0.3 0.1 0.05 1 1 -
Romania 768 934 634 436 332 79 3 2 21 4 -
Russia 2182 3870 633 439 288 41 0.1 0.03 12 4 0.1
Slovak Rep. 507 532 2775 443 404 7 0.3 0.1 121 4 -
Slovenia 327 - - 230 114 0.5 0.2 0.05 - 0.5 0.00
South Africa 1796 54508 85 490 153 2 0.3 0.03 12 0.1 0.02
South Korea 430 - - 256 149 5 0.2 0.1 43 3 -
Spain 402 150 7163 340 162 3 0.01 0.01 20 2 0.1
Sweden 60 - - 133 182 2 0.04 0.01 97 0.5 -
Switzerland 9 3 9 - 210 0.02 0.1 0.01 - 0.1 0.00
Taiwan 41 113 21 417 160 1 0.4 0.2 3 1 -
Turkey 462 122498 223 277 161 2 0.4 0.2 26 2 -
UK 349 202 184 174 140 1 0.2 0.1 - 1 -
US 1069 236 271 438 166 16 0.2 0.1 35 1 0.03
RoW 232 492 254 67 183 4 0.2 0.2 34 1 0.3
World 721 352 259 240 164 4 0.3 0.1 39 2 0.5 Note: - means no value.
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
23
Table 2 continued: Environmental multipliers by country –kilogram per € demand
Aluminium ores Copper ores Precious metal ores
i13.
20.13
i27.
42
i27.5 i13.
20.11
i27.
44
i12 i13.
20.14
i27.
41
i26.c
Australia 32 16 - 89 49 0.03 45 26 1
Austria - - 0.1 - 4 - - - 0.02
Belgium - - 0.1 - 4 - - - 0.01
Brazil 18 0.1 0.01 609 1 0.1 60 1 1
Bulgaria - - - 326 93 2 128 34 0.2
Canada 0.00 2 0.04 29 21 0.02 12 0.01 0.01
China 1 0.4 0.2 119 17 0.02 19 0.02 0.02
Cyprus - - - 0.4 1 - - - 0.01
Czech Rep. 0.00 - 0.03 2 - 0.04 0.00 - 0.01
Denmark - - - - - - - - 0.01
Estonia - - - - - - - - 0.02
Finland - - 0.04 1 32 - 1 0.01 0.01
France 83 1 0.03 47 0.04 0.1 80 2 0.2
Germany - 1 0.1 - 14 - - - 1
Greece 20 3 - - - - 0.5 0.00 0.02
Hungary 46 3 - - 1 - 30 - 0.1
India 238 3 0.02 30 20 - 6 0.4 0.00
Indonesia 10 4 - 188 2 - 32 0.2 0.1
Ireland - - - - - - 13 0.01 0.01
Italy 0.1 0.2 0.00 - 0.04 - 3 0.00 0.01
Japan - 1 3 41 11 0.1 18 5 0.1
Latvia - - 0.1 - - - - - 0.02
Lithuania - 0.2 0.00 - 1 - - 0.1 0.01
Luxembourg - 0.2 0.02 - 1 - - 0.01 0.01
Malta - 0.3 0.00 - 0.03 - - 0.03 0.01
Mexico - 1 0.00 92 31 0.01 5 2 0.3
Netherlands - 0.4 - - - - - - 0.01
Norway - 1 0.04 - 6 - 0.5 - 0.01
Poland - 2 0.03 47 3 - 0.2 0.01 0.02
Portugal - - 0.1 4 - - 0.4 0.02 0.00
Romania - 3 - 85 59 - 7 2 0.03
Russia 1 1 0.03 110 9 0.01 27 2 0.1
Slovak Rep. - 0.3 0.04 - - - 2 0.1 0.04
Slovenia - 0.2 - 0.01 - 0.00 - - 0.02
South Africa - 6 0.3 40 1 0.02 14 0.1 0.01
South Korea - - 0.00 0.02 31 - 51 - 0.05
Spain - 1 0.01 86 6 1 30 6 0.01
Sweden - 1 0.03 70 17 - 24 2 0.01
Switzerland - 0.2 - - - 0.01 - - 0.2
Taiwan 0.02 - 0.2 0.01 4 - 0.00 0.3 0.01
Turkey 9 1 - 54 21 - 12 1 0.1
UK - 0.3 0.02 - 1 - - - 0.01
US 11 0.2 0.04 359 14 0.2 29 1 0.1
RoW 6 0.02 0.01 138 0.2 2 50 0.1 0.02
World 6 1 0.4 116 11 2 28 2 0.2 Note: - means no value.
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
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Table 3: International environmental multiplier as % of total environmental multiplier –
Herfindahl index of international multipliers – fossil energy carriers
Fossil energy
carriers
% international multiplier Herfindahl index of intern. multipliers
i10 i11.b i11.a
i40.
11.a
i23.
20.a i10 i11.b i11.a
i40.
11.a
i23.
20.a
Australia 1 1 1 2 72 0.57 0.55 0.56 0.56 0.71
Austria 2 5 1 100 91 0.24 0.25 0.24 0.47 0.63
Belgium - - - 100 100 - - - 0.36 0.21
Brazil 1 2 2 31 32 0.32 0.55 0.53 0.20 0.90
Bulgaria 10 47 7 18 98 0.87 0.87 0.89 0.63 0.99
Canada 0 1 1 59 57 0.22 0.21 0.21 0.82 0.29
China 0 5 2 1 21 0.46 0.59 0.59 0.45 0.70
Cyprus 100 - 100 - 100 0.52 - 0.47 - 0.87
Czech Rep. 3 28 0 6 94 0.75 0.68 0.65 0.56 0.77 Denmark - 1 0 98 40 - 0.17 0.15 0.41 0.72
Estonia - 100 - 100 100 - 0.91 - 0.79 0.95
Finland 5 - - 83 100 0.43 - - 0.44 0.35
France 20 1 0 76 100 0.16 0.26 0.19 0.20 0.39
Germany 1 2 0 8 99 0.18 0.20 0.22 0.14 0.27
Greece 1 12 1 2 99 0.49 0.51 0.42 0.44 0.68
Hungary 3 3 0 11 89 0.43 0.73 0.64 0.61 0.63
India 0 0 1 2 44 0.45 0.53 0.55 0.25 0.96
Indonesia 1 1 2 10 29 0.41 0.66 0.82 0.70 0.79
Ireland 29 7 97 36 100 0.21 0.69 0.67 0.21 0.85
Italy 82 1 0 100 100 0.41 0.31 0.27 0.16 0.53 Japan 1 10 13 100 100 0.43 0.51 0.28 0.32 0.69
Latvia 39 - - 98 100 0.79 - - 0.94 0.62
Lithuania 29 100 14 - 100 0.63 0.93 0.88 - 0.90
Luxembourg - - - - - - - - - -
Malta - 100 100 - 100 - 0.32 0.33 - 0.50
Mexico 1 0 0 35 1 0.24 0.21 0.27 0.36 0.22
Netherlands - 3 0 99 100 - 0.54 0.32 0.32 0.35
Norway 1 0 0 83 6 0.17 0.16 0.16 0.24 0.38
Poland 0 - - 4 60 0.39 - - 0.41 0.49
Portugal - - - 100 100 - - - 0.41 0.61
Romania 8 5 9 30 51 0.85 0.89 0.88 0.71 0.70
Russia 0 0 0 1 4 0.63 0.92 0.60 0.81 0.94 Slovak Rep. 8 91 15 98 100 0.77 0.98 0.98 0.41 0.95
Slovenia 2 - - 4 99 0.27 - - 0.14 0.40
South Africa 0 0 3 1 64 0.38 0.39 0.27 0.23 0.94
South Korea 2 - - 93 100 0.28 - - 0.22 0.72
Spain 4 6 0 63 100 0.37 0.58 0.17 0.40 0.66 Sweden 14 - - 83 100 0.18 - - 0.26 0.35
Switzerland 100 100 100 - 100 0.48 0.45 0.54 - 0.97
Taiwan 91 4 38 100 100 0.43 0.34 0.57 0.23 0.69
Turkey 4 0 3 55 90 0.41 0.35 0.47 0.36 0.72
UK 1 1 1 30 19 0.15 0.34 0.20 0.22 0.51
US 0 2 2 1 56 0.33 0.42 0.40 0.39 0.53 RoW 1 1 1 20 9 0.17 0.56 0.34 0.18 0.42 Note: - means no value, 0 indicates a value smaller than 0.5
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
25
Table 4: International environmental multiplier as % of total environmental multiplier –
Herfindahl index of international multipliers – chemical/fertilizer minerals
Chem./fert.
minerals
% international multiplier Herfindahl index of intern. multipliers
i14.3 i26.e i26.d i12
i27.
43 i14.3 i26.e i26.d i12
i27.4
3
Australia 0 23 53 54 58 0.22 0.24 0.28 0.22 0.21
Austria 45 100 100 - 100 0.16 0.16 0.15 - 0.10
Belgium 8 99 98 - 87 0.27 0.32 0.31 - 0.17
Brazil 6 53 46 34 55 0.32 0.33 0.31 0.30 0.32
Bulgaria 1 24 16 36 23 0.32 0.25 0.24 0.16 0.17
Canada 0 26 19 37 49 0.18 0.17 0.18 0.24 0.18
China 0 8 6 18 23 0.17 0.18 0.18 0.18 0.17
Cyprus 1 100 100 - - 0.20 0.28 0.22 - -
Czech Rep. 5 99 97 97 97 0.21 0.20 0.19 0.18 0.14
Denmark 17 100 99 - 96 0.40 0.22 0.21 - 0.24
Estonia 100 100 100 - - 0.84 0.85 0.83 - -
Finland 1 9 6 - 89 0.15 0.15 0.16 - 0.15
France 0 86 78 90 93 0.14 0.15 0.14 0.14 0.17
Germany 4 68 55 - 92 0.10 0.11 0.10 - 0.12
Greece 0 1 0 - 9 0.22 0.27 0.20 - 0.14
Hungary 2 100 100 - - 0.40 0.44 0.42 - -
India 0 75 67 - 73 0.38 0.29 0.37 - 0.39
Indonesia 1 87 87 - 96 0.23 0.16 0.15 - 0.26
Ireland 100 100 100 - 100 0.12 0.10 0.12 - 0.13
Italy 2 100 97 - 98 0.13 0.20 0.18 - 0.23
Japan 0 41 21 40 96 0.20 0.16 0.15 0.25 0.18
Latvia 100 100 - - - 0.74 0.62 - - -
Lithuania 13 100 100 - 87 0.98 0.98 0.98 - 0.97
Luxembourg 100 100 100 - 100 0.50 0.49 0.48 - 0.12
Malta 100 100 - - 100 0.36 0.36 - - 0.18
Mexico 4 48 17 81 73 0.27 0.26 0.26 0.41 0.27
Netherlands 13 85 80 - 99 0.15 0.14 0.14 - 0.15
Norway 18 100 100 - 100 0.45 0.45 0.45 - 0.45
Poland - 100 100 - 100 - 0.23 0.18 - 0.18
Portugal 13 88 80 - 96 0.23 0.23 0.20 - 0.17
Romania 0 15 7 - 10 0.30 0.31 0.31 - 0.26
Russia 1 25 25 41 44 0.33 0.22 0.23 0.22 0.29
Slovak Rep. 2 100 99 - 97 0.27 0.27 0.26 - 0.21
Slovenia 100 100 100 100 100 0.38 0.37 0.33 0.15 0.17
South Africa 0 97 97 94 94 0.21 0.22 0.28 0.17 0.21
South Korea 4 70 65 - 95 0.38 0.35 0.36 - 0.20
Spain 0 86 84 97 83 0.16 0.18 0.16 0.20 0.20
Sweden 4 84 72 - 93 0.15 0.14 0.13 - 0.19
Switzerland 100 100 100 100 100 0.27 0.20 0.18 0.18 0.20
Taiwan 43 87 85 - - 0.21 0.21 0.21 - -
Turkey 2 43 21 - 46 0.19 0.18 0.18 - 0.16
UK 65 100 100 - 99 0.36 0.36 0.35 - 0.28
US 0 14 16 8 57 0.43 0.39 0.33 0.27 0.43
RoW 0 16 16 18 18 0.22 0.33 0.33 0.28 0.28 Note: - means no value, 0 indicates a value smaller than 0.5
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
26
Table 5: International environmental multiplier as % of total environmental multiplier –
Herfindahl index of international multipliers – iron ores
Iron ores % international multiplier Herfindahl index of intern. multipliers
i13.1 i27.a i12 i27.5
i13.
20.13 i13.1 i27.a i12 i27.5
i13.
20.13
Australia 0 13 16 - 23 0.32 0.30 0.22 - 0.16
Austria - 100 - 100 - - 0.17 - 0.17 -
Belgium - 100 - 100 - - 0.16 - 0.18 -
Brazil 0 0 1 2 5 0.14 0.14 0.16 0.14 0.14
Bulgaria 1 25 72 - - 0.39 0.31 0.29 - -
Canada 0 42 48 76 53 0.42 0.63 0.47 0.20 0.36
China 0 4 13 18 11 0.26 0.28 0.22 0.29 0.24
Cyprus - - - - - - - - - -
Czech Rep. 100 100 100 100 100 0.45 0.52 0.42 0.34 0.45
Denmark - 100 - - - - 0.15 - - - Estonia - 100 - - - - 0.33 - - -
Finland - 100 - 100 - - 0.34 - 0.23 -
France - 100 100 100 100 - 0.25 0.18 0.20 0.27
Germany - 100 - 100 - - 0.23 - 0.17 -
Greece 0 28 - - 76 0.16 0.18 - - 0.17
Hungary - 100 - - 100 - 0.50 - - 0.41
India 0 1 - 4 8 0.20 0.23 - 0.23 0.20
Indonesia 0 99 - - 100 0.39 0.24 - - 0.18
Ireland - 100 - - - - 0.14 - - -
Italy - 100 - 100 100 - 0.31 - 0.18 0.19
Japan 4 100 100 100 - 0.27 0.34 0.25 0.21 - Latvia - 100 - 100 - - 0.34 - 0.35 -
Lithuania - 100 - 100 - - 0.33 - 0.41 -
Luxembourg - 100 - 100 - - 0.20 - 0.19 -
Malta - 100 - 100 - - 0.15 - 0.14 -
Mexico 0 38 75 74 - 0.47 0.49 0.20 0.24 -
Netherlands - 100 - - - - 0.22 - - - Norway 0 70 - 99 - 0.15 0.28 - 0.16 -
Poland - 100 - 100 - - 0.40 - 0.31 -
Portugal 6 99 - 100 - 0.28 0.30 - 0.28 -
Romania 32 96 - - - 0.29 0.29 - - -
Russia 31 48 65 53 47 0.98 0.96 0.90 0.78 0.83
Slovak Rep. 0 94 - 96 - 0.41 0.49 - 0.42 - Slovenia - 100 100 - - - 0.20 0.20 - -
South Africa 0 93 84 90 - 0.16 0.17 0.17 0.19 -
South Korea 0 100 - 100 - 0.31 0.34 - 0.29 -
Spain 1 97 99 98 - 0.47 0.61 0.24 0.37 -
Sweden 0 43 - 81 - 0.15 0.17 - 0.18 - Switzerland - 100 100 - - - 0.20 0.17 - -
Taiwan 100 100 - 100 100 0.47 0.28 - 0.21 0.29
Turkey 0 80 - - 84 0.18 0.19 - - 0.17
UK - 100 - 100 - - 0.24 - 0.22 -
US 0 29 36 69 24 0.32 0.32 0.28 0.19 0.24
RoW 1 66 62 62 67 0.31 0.26 0.28 0.28 0.24 Note: - means no value, 0 indicates a value smaller than 0.5
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
27
Table 6: International environmental multiplier as % of total environmental multiplier –
Herfindahl index of international multipliers – aluminum/bauxite ores
Aluminium/
bauxite ores
% international multiplier Herfindahl index of intern. multipliers
i13.2
0.13
i27.
42 i27.5 i12 i28
i13.2
0.13
i27.
42 i27.5 i12 i28
Australia 0 0 - 6 9 0.32 0.22 - 0.24 0.22
Austria - - 100 - 100 - - 0.23 - 0.23
Belgium - - 100 - 100 - - 0.29 - 0.27
Brazil 0 26 43 8 47 0.42 0.36 0.38 0.42 0.38
Bulgaria - - - 100 100 - - - 0.21 0.26
Canada 100 100 100 100 100 0.29 0.43 0.38 0.32 0.33
China 10 50 71 74 72 0.79 0.85 0.83 0.79 0.83
Cyprus - - - - 100 - - - - 0.31
Czech Rep. 100 - 100 100 100 0.24 - 0.23 0.22 0.22
Denmark - - - - 100 - - - - 0.28
Estonia - - - - 100 - - - - 0.28
Finland - - 100 - 100 - - 0.28 - 0.26
France 2 99 97 99 99 0.58 0.46 0.25 0.29 0.28
Germany - 100 100 - 100 - 0.31 0.21 - 0.21
Greece 0 39 - - 44 0.40 0.83 - - 0.64
Hungary 0 14 - - 77 0.27 0.24 - - 0.23
India 0 10 61 - 47 0.78 0.89 0.69 - 0.86
Indonesia 0 62 - - 87 0.71 0.96 - - 0.95
Ireland - - - - 100 - - - - 0.27
Italy 0 100 100 - 100 0.21 0.22 0.21 - 0.21
Japan - 100 100 100 100 - 0.29 0.94 0.29 0.92
Latvia - - 100 - 100 - - 0.27 - 0.27
Lithuania - 100 100 - 100 - 0.25 0.22 - 0.23
Luxembourg - 100 100 - 100 - 0.35 0.34 - 0.31
Malta - 100 100 - 100 - 0.27 0.23 - 0.25
Mexico - 100 100 100 100 - 0.62 0.32 0.31 0.30
Netherlands - 100 - - 100 - 0.47 - - 0.25
Norway - 100 100 - 100 - 0.51 0.26 - 0.34
Poland - 100 100 - 100 - 0.62 0.29 - 0.27
Portugal - - 100 - 100 - - 0.39 - 0.37
Romania - 100 - - 100 - 0.35 - - 0.31
Russia 61 78 80 76 81 0.43 0.49 0.43 0.39 0.41
Slovak Rep. - 100 100 - 100 - 0.20 0.21 - 0.20
Slovenia - 100 - 100 100 - 0.21 - 0.22 0.20
South Africa - 100 100 100 100 - 0.97 0.96 0.90 0.95
South Korea - - 100 - 100 - - 0.54 - 0.55
Spain - 100 100 100 100 - 0.66 0.30 0.31 0.46
Sweden - 100 100 - 100 - 0.60 0.33 - 0.31
Switzerland - 100 - 100 100 - 0.33 - 0.31 0.26
Taiwan 100 - 100 - 100 0.30 - 0.94 - 0.94
Turkey 0 26 - - 96 0.27 0.23 - - 0.22
UK - 100 100 - 100 - 0.35 0.37 - 0.24
US 1 97 98 76 98 0.34 0.27 0.29 0.30 0.25
RoW 0 79 85 55 95 0.71 0.81 0.79 0.71 0.87 Note: - means no value, 0 indicates a value smaller than 0.5
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
28
Table 7: International environmental multiplier as % of total environmental multiplier –
Herfindahl index of international multipliers – copper ores
Copper ores % international multiplier Herfindahl index of intern. multipliers
i13.
20.11
i27.
44 i12
i27.
41 i37.1
i13.
20.11
i27.
44 i12
i27.
41 i37.1
Australia 0 6 28 18 - 0.48 0.77 0.41 0.48 -
Austria - 100 - - 100 - 0.49 - - 0.44
Belgium - 100 - - 100 - 0.36 - - 0.40
Brazil 0 11 3 60 - 0.40 0.37 0.39 0.30 - Bulgaria 0 2 4 3 3 0.82 0.61 0.39 0.46 0.46
Canada 0 0 44 14 66 0.59 0.58 0.41 0.36 0.46
China 0 100 57 85 - 0.53 0.61 0.44 0.49 -
Cyprus 8 99 - - 88 0.20 0.20 - - 0.20
Czech Rep. 100 - 100 - 100 0.94 - 0.23 - 0.30
Denmark - - - - 100 - - - - 0.26
Estonia - - - - 100 - - - - 0.30
Finland 29 100 - 100 100 0.42 0.39 - 0.37 0.35
France 0 35 100 100 100 0.26 0.27 0.27 0.25 0.30
Germany - 100 - - 100 - 0.56 - - 0.31
Greece - - - 100 100 - - - 0.24 0.24
Hungary - 100 - - 100 - 0.39 - - 0.28
India 0 87 - 95 - 0.40 0.49 - 0.33 -
Indonesia 0 77 - 80 - 0.52 0.39 - 0.37 -
Ireland - - - 100 100 - - - 0.27 0.27
Italy - 100 - 100 100 - 0.33 - 0.26 0.30
Japan 0 100 100 100 100 0.60 0.45 0.70 0.71 0.37
Latvia - - - - 100 - - - - 0.36
Lithuania - 100 - 100 100 - 0.40 - 0.27 0.24
Luxembourg - 100 - 100 100 - 0.52 - 0.47 0.48
Malta - 100 - 100 100 - 0.21 - 0.30 0.32
Mexico 0 47 71 63 - 0.97 0.97 0.70 0.80 -
Netherlands - - - - 100 - - - - 0.38
Norway - 100 - - 100 - 0.29 - - 0.33
Poland 0 9 - 1 2 0.34 0.47 - 0.42 0.45
Portugal 0 - - 100 100 0.35 - - 0.38 0.40
Romania 12 31 - 41 - 0.46 0.45 - 0.38 -
Russia 0 49 48 43 - 0.95 0.98 0.50 0.86 -
Slovak Rep. - - - 100 100 - - - 0.38 0.25
Slovenia 100 - 100 - 100 0.36 - 0.34 - 0.42
South Africa 0 96 90 90 - 0.26 0.33 0.25 0.33 -
South Korea 100 100 - - - 0.48 0.67 - - -
Spain 0 87 98 95 90 0.34 0.49 0.34 0.32 0.42
Sweden 0 39 - 62 60 0.78 0.84 - 0.41 0.54 Switzerland - - 100 - 100 - - 0.35 - 0.33
Taiwan 100 100 - 100 - 0.26 0.35 - 0.28 -
Turkey 0 79 - 97 79 0.31 0.36 - 0.42 0.35
UK - 100 - - 100 - 0.60 - - 0.19
US 0 16 2 9 - 0.28 0.27 0.27 0.26 -
RoW 0 29 5 41 - 0.31 0.31 0.22 0.32 - Note: - means no value, 0 indicates a value smaller than 0.5
Final WIOD Conference, April 24-26, 2012, Groningen, The Netherlands ~ draft April 2012 ~ please do not quote
29
Table 8: International environmental multiplier as % of total environmental multiplier –
Herfindahl index of international multipliers – precious metals ores
Precious
metal ores
% international multiplier Herfindahl index of intern. multipliers
i13.
20.
14
i27.
41 i26.c i12 i26.a
i13.
20.14
i27.
41 i26.c i12 i26.a
Australia 0 0 4 3 2 0.35 0.91 0.78 0.43 0.17
Austria - - 100 - 100 - - 0.42 - 0.39
Belgium - - 100 - 100 - - 0.28 - 0.24
Brazil 0 1 1 8 1 0.21 0.39 0.20 0.27 0.19
Bulgaria 1 1 5 3 10 0.98 0.96 0.24 0.28 0.26
Canada 0 97 89 96 87 0.63 0.29 0.17 0.60 0.19
China 0 57 24 39 30 0.73 0.49 0.25 0.30 0.22
Cyprus - - 100 - 100 - - 0.18 - 0.17
Czech Rep. 100 - 100 100 100 0.30 - 0.33 0.33 0.33
Denmark - - 100 - 100 - - 0.29 - 0.32
Estonia - - 100 - 100 - - 0.44 - 0.42
Finland 1 100 100 - 100 0.31 0.20 0.27 - 0.34
France 19 99 100 99 100 0.81 0.83 0.80 0.19 0.76 Germany - - 100 - 100 - - 0.57 - 0.57
Greece 1 85 100 - 100 0.17 0.18 0.48 - 0.35
Hungary 0 - 26 - 38 0.26 - 0.32 - 0.33
India 0 15 92 - 99 0.23 0.70 0.26 - 0.19
Indonesia 0 100 16 - 9 0.93 0.78 0.58 - 0.48
Ireland 0 45 88 - 97 0.21 0.21 0.21 - 0.21
Italy 1 98 100 - 100 0.21 0.17 0.14 - 0.14
Japan 0 98 92 44 97 0.36 0.41 0.39 0.22 0.42
Latvia - - 100 - 100 - - 0.45 - 0.45
Lithuania - 100 100 - 100 - 0.68 0.43 - 0.48
Luxembourg - 100 100 - 100 - 0.19 0.38 - 0.42
Malta - 100 100 - 100 - 0.38 0.15 - 0.23
Mexico 13 42 27 70 27 0.77 0.71 0.72 0.33 0.70
Netherlands - - 100 - 100 - - 0.21 - 0.48
Norway 0 - 98 - 97 0.22 - 0.31 - 0.29
Poland 6 98 88 - 87 0.34 0.23 0.35 - 0.36
Portugal 0 100 100 - 100 0.24 0.43 0.16 - 0.15
Romania 0 1 26 - 34 0.16 0.16 0.21 - 0.22
Russia 2 21 49 35 40 1.00 0.99 0.89 0.70 0.83
Slovak Rep. 0 20 31 - 40 0.35 0.24 0.36 - 0.42
Slovenia - - 100 100 100 - - 0.29 0.32 0.28
South Africa 0 98 80 62 72 0.52 0.96 0.34 0.56 0.22
South Korea 0 - 89 - 88 0.15 - 0.73 - 0.65 Spain 0 15 47 59 44 0.16 0.85 0.16 0.48 0.16
Sweden 4 58 97 - 95 0.48 0.48 0.25 - 0.24
Switzerland - - 100 100 100 - - 0.17 0.14 0.16
Taiwan 100 100 100 - 100 0.26 0.43 0.19 - 0.19
Turkey 0 1 7 - 10 0.18 0.19 0.20 - 0.20
UK - - 100 - 100 - - 0.25 - 0.29
US 1 18 67 29 59 0.35 0.35 0.35 0.20 0.31
RoW 0 42 31 14 76 0.31 0.78 0.33 0.67 0.39 Note: - means no value, 0 indicates a value smaller than 0.5