G-SEC WORKING PAPER No.5
Interdependence of Economy
and Environment in East Asia using
EDEN Data Base-Focusing on Korea
Naoko Takenaka ∗April, 2006

Abstract
There is concern that Asia will be one of the regions with the greatest burden on the
global environment as forecasts point to a continuing increase in energy consumption as theregion’s economic activity expands and its population grows sharply. It is therefore extremely
important to look at trends in East Asia when considering environmental issues on a world scale.
So I use EDEN Data Base, the only table in the world to estimate Economy and Environment
with common format in East Asia to clear the interdependence both of them. In this paper, atfirst, I introduce of EDEN Data Base and previous researches using this data base and thenfocusing on Korea, I extend estimation on EDEN Data Base to the 2000 version using theprovisional 1995 version and shed light on the actual state and changes in economic andenvironmental interdependence for three target years.

∗

Research Assistant, Global Security Research Institute, Keio University, E-mail:nao27tkn@parkcity.ne.jp

1. Introduction
The earth is burdened by many environmental issues including Global warming,
Acid rain, Marine pollution and Desertification, and the fact that it is facing a crisis that
presents the ultimate adversity, especially from the 1980s, is now irrefutable. This
critical situation has become a common perception shared in many countries. As themodern society in which we live enjoys the benefits of economic development,
environmental destruction is accelerating on a global scale. Along with implementing
environmental measures at the local level, international collaboration is also essential,
and we are indeed facing the situation in which conservation of the earth must be
considered on an international dimension. There is concern that Asia, home to morethan about 60% of the world’s population, will be one of the regions with the greatest
burden on the global environment as forecasts point to a continuing increase in energy
consumption as the region’s economic activity expands and its population grows
sharply. For example, in 1980 East Asia accounted for about 15% of the world’s CO2
emissions, but by 1995 this had grown to roughly one-quarter, while in emission
quantity, the region’s emissions have been growing at a much faster pace than the world
total with a 1.9-fold increase compared to the world’s 1.2-fold increase. It is therefore
extremely important to look at trends in East Asia when considering environmental
issues on a world scale. Here I will ascertain the state of economic and environmental
interdependence in East Asia using EDEN Data Base developed in a common format toclarify the condition of the environmental load in East Asia. Only EDEN Data Base1990 has been released, so the first aim of this paper is to extend estimation on EDEN
Data Base to the 2000 version using the provisional 1995 version especially focusing on
Korea. Then, using the 1990, 1995 and 2000 version of EDEN Data Base (hereinafterreferred to as the three target years), the second aim is to shed light on the actual state ofand changes in economic and environmental interdependence for the three target years.
This paper is composed as follows. In Chapter 2 I touch on the background andan overview of EDEN Data Base, and estimation conditions, and introduce previous
research using this Data Base. In Chapter 3, I draw up the 2000 version for Korea, andlook into the Economic and Environmental interdependence over the three target yearsof 1990, 1995 and 2000.

12. Overview of EDEN Data Base and Previous research
2-1

Overview (background and estimation condition)
EDEN (Economic Development and Environmental Navigator) was drawn up by

Keio Economic Observatory in collaboration with statistics authorities in various
countries to clarify the effect that economic growth and changes in interdependence in
East Asia has on the environment and energy supply and demand as a part of the JSPS
(Japan Society for the Promotion of Science) Research for the Future Program 1 . With
the extensive and long-term expertise of Institute of Developing Economies (IDE),
which has prepared the Asian International Input-Output Table, this Data Base enables
international comparisons that estimate energy and environmental fields. The target
countries are nine countries and regions; Japan, Singapore, Taiwan, Korea, Malaysia,
Thailand, Philippines, Indonesia, China, and in East Asia 2 , and the target years are thetwo years of 1990 and 1995. As of March 2006 only the 1990 version with 35-sector
tables has been released, and some researchers have made several reports on analysis
cases using the 1990 version. The project had set the initial goal of completing andreleasing the estimations of the 1990 and 1995 versions, but in view of time restrictions
and accuracy, while estimations for the 1995 version have started, they have not reached
the stage of public release, and because of the analysis extension over multiple years,
public release is some time in the future. 3
1 JSPS for the Promotion of Science, ‘Inter-disciplinary Studies for Sustainable Development in

Asian countries’ (Representative; pf. Yoshioka, Keio Economic Observatory) (1997-2001).
2 Singapore: National University of Singapore, Taiwan:Taiwan Research Institute, Korea: Korea

Energy and Economic Institute, Malaysia :Department of Statistics, Thailand :National
Economic and Social Development, Philippines :National Statistical Coordination,
Indonesia :Central Board of Statistic, China: State Statistical Bureau, Japan :IDE(the name atthat time). The target countries include countries that are usually classified in Southeast Asia,
but in this chapter, they are listed under the collective term of East Asia.
3 As mentioned above, the target years of EDEN Data Base is 1990 and 1995, but the project

ended with the completion of estimations and the release of the 1990 version, so the 1995
version exists only as a provisional version. I will therefore extend estimations to the 2000
version considering the release of the 1995 version and also 2000 Input-Output tables in various

2

EDEN Data Base is composed of five tables as table 1 4 and the estimation
process of this Data Base shows figure 1. A table integrates the Input-Output tables ofvarious countries into 76 common EDEN categories 5 , and is expressed in thosecountries’ respective currencies. 6 B table is the energy substance input table, and lists
energy substance quantity used in each sector and final demand sector for each of the 22energy types 7 . C table is the energy consumption table, and lists only the energy
substances in B table that are consumed as fuel 8 . D table is a calorie table that converts
the figures in C table to calories. Therefore B and C tables list units peculiar to eachenergy type, while D table lists calories, so this allows a direct lateral comparison foreach country in absolute quantity and percentage distribution. Lastly, E table is the CO2

countries. In addition, the author belonged to the project WGI, which was responsible for EDEN
Data Base estimations.
4 See Kiji(2002) for more detail information about EDEN Data Base.
5 The number of basic sectors in Input-Output tables varies considerably from country tocountry, so, taking into account each country’s sectors, EDEN set 76 sectors so there would be acommon sector classification for the target countries (Appendix 1).
6 There are two format types for the Input-Output tables: competing import type and non-competing import type according to how imports are handled. In EDEN Data Base, considering
the analysis aim, the ISARD non-competing import type, in which domestically produced goods
and imported goods are completely differentiated and imports are classified by country and bysector, is preferable, but EDEN Data Base has adopted the competing import type format sincein reality it is not possible to obtain accurate data regarding input and output from the target
countries.
7 Refer to Appendix 2 for 22 Energy types.
8 This excludes B table energy substances that are consumed as raw material (e.g., coal for cokeproduction, crude oil for petroleum refining). The raw material / fuel consumption ratio was not
obtained by all target countries, so the values for the countries where it was obtained have beenused instead.

3

/ SO2 generation table, and it converts carbon and sulfur generation estimated fromcarbon / sulfur content ratio based on D table into CO2 and SO2. 9

2-2

Previous research using EDEN Data BaseThis section will introduce research cases using EDEN Data Base. 10 The analysis

is broadly classified into “analysis of the current state of the East Asian Economy andEnvironment”, which is fact finding analysis from EDEN Data Base itself, and “Others”,
which is applied analysis using EDEN Data Base.

1 Analysis of the current state of the East Asian economy and environment
Analysis of the current state of the East Asian economy and environment using
EDEN Data Base consists of single country analysis that analyzes each country, thenfinally makes a cross-sectional comparison; and international link analysis that links
trade statistics to examine the interdependence between countries.

1)

Single country analysis — Comparison of economic structure, energy
consumption structure, and CO2 /SO2 generation structure of each country
Leading examples of single country analysis include Kiji (2002), Kim et al.

(2002) and Takenaka (2002).
Kiji (2002) conducts a country-based comparison of energy consumption andCO2 / SO2 total generation and percentage distribution in Asian countries, and estimates
generations per capita, per value added and per energy consumption unit, and direct andindirect generation for each industry. First, the paper classifies the region into the fivecountries/regions of Japan, Korea, China, Taiwan, and five Southeast Asian countries,
9 EDEN Data Base regards energy generation to which removal activities have been extended as

emission, so generation and emission are differentiated. The rate of removal is clear in somecountries such as Japan and China, so here it is possible to estimate emission separately.
10 This also includes analysis cases using EDEN Data Base 1995, which, as mentioned before, has

not completed estimations but is still at the provisional stage.

4

which includes Malaysia, Thailand, Philippines, Indonesia and Singapore and analyzes
energy consumption and CO2 / SO2 generation for each country / region, then states thatconsidering the energy and environmental issues facing East Asia, China’s presence isof paramount importance when looking at total generation. On the other hand, whenlooking at per capita figures, Japan stands out, and when considering per value added
amount 11 figures in the same way, China requires the greatest energy consumption andCO2 / SO2 generation to create the same value added unit — respectively, 2.3 times, 3.0
times and 9.1 times as great as that needed by Japan. CO2 generation per energy
consumption unit (it excludes Electric power) is lowest in Indonesia, and high in China
and Taiwan. SO2 generation is low in Japan and Singapore, and particularly high in
China. Such disparity is thought to arise mainly from the different types of energy
consumed in each country. 12 The energy consumption composition in each country
under the five energy classifications(the type of Coal, Oil, Gas and others) shows that in
China coal with its high level of CO2 / SO2 generation accounts for 75%, and in
Singapore petroleum accounts for more than 90%, while in Japan, dependence is spread
across many energy types. If look at direct and indirect CO2 generation per domestic
production unit for each sector 13 , in Japan there is a significant difference between
direct and indirect generation in machinery and equipment sector, with indirect
generation more than 18 times as great as direct generation. A similar trend can also beseen in Korea, Taiwan and Singapore, confirming the broad base of machinery andequipment industry within the country. And similar trends can be seen in coal productsin Singapore and Taiwan, petroleum refinery products and other services in thePhilippines, and petroleum refinery products and eating and drinking places in
Malaysia.
11 The paper uses figures substantiated with purchasing power parity indices calculated from

GDP statistics. See Kiji(2002)p.32.
12 Specifically, natural gas and LNG, whose main components are methane and ethane, have low

CO2 generation relative to calorific value, whereas coal, whose main component is carbon andwhich also has high sulfur content, has high CO2 / SO2 generation (See kiji(2002)p.35). So thedisparity in generation per energy consumption unit arises depending on the type of energy
used domestically.
13 Twenty independently set industrial classifications are used.

5

Kim et al. (2002) compares the actual state of energy use and sectors with highenergy consumption in nine countries, and, focusing on Light industries and Heavy
industries, estimates CO2 generation per calorie amount by industry, and the direct andindirect induced CO2 generation for each sector. First, the paper classifies energy into
four energy types(the type of Coal, Oil, secondly energy and others), and ascertains thestate of energy use by country taking into account the condition of each country’s
energy resource holdings, especially focusing on Japan and Korea. Energy use
composition shows that China has particularly high coal consumption, while the othereight countries are all high in petroleum consumption. One characteristic that can beseen is that the use of non-petroleum energy types is also high in Japan and Korea. The
reason for this is that both countries rely heavily on imports for their energy resources,and having learned from their experience of the oil crises, they have been pushing ahead
with energy diversification since the 1970s. A comparison of the high energy
consumption sectors 14 reveals a common trend in all countries is that thermal power
and private-sector consumption are high energy consuming sectors. Similar to Kiji
(2002), the paper analyzed energy consumption and total CO2 / SO2 generation for eachcountry to examine generation per capita and household consumption. Looking at percapita CO2 to household consumption, we can see that generation is high in countries
with relatively high income, such as Korea, Japan and Singapore. The paper also
analyzed energy consumption and CO2 / SO2 generation focusing on the three sectors of
textiles, which is a typical Light industry, iron and steel, which is a Heavy industry, andthermal power, which is a high energy consumption industry. For CO2, the textile
industry in China and Korea generate almost as much as the iron and steel industry, andconsidering textile products are major exports of both countries, there is a strong needfor environmental measures not just in the Heavy industries, but in the Light industries
as well. CO2 generation in the iron and steel industry is high in China, Japan andTaiwan, but low in Malaysia and other Southeast Asian countries. CO2 generation inthermal power is much higher in China and Japan, but because of an anticipated rise inpower demand in Asian countries, the paper highlights the need for a range ofcountermeasures such as reviews of each country’s energy mix. The paper also attempts
an index representation linking energy consumption and CO2 / SO2 generation with
14 In addition to the 76 industries, the final consumption sector is also analyzed.

6economic activity: specifically, 1) energy consumption and CO2 / SO2 generation per
output unit, and 2) energy consumption and CO2 / SO2 generation per calorie unit ofenergy consumption, and 3) directly and indirectly induced energy consumption andCO2 / SO2 generation per final consumption unit. In China, 1) CO2 generation per
output unit is more than 20 times as high as in Japan 15 . In 2) generation per calorie unitof energy consumption, the difference between countries is greater in SO2 generation
than in CO2 generation, with China, the highest, four times as high as Japan, thelowest 16 . This is thought to stem from the difference in energy type composition, andwhere the energy type is the same, from differences in sulfur content rate between
countries. The paper points out that in SO2 generation over the three industries oftextiles, iron and steel, and thermal power, the Light industries generate more than the
Heavy industries and thermal power in China, Korea and Taiwan, and here, too,highlights the need for environmental initiatives in the Light industries. At the end, thepaper estimates induced CO2 generation for each industry. These estimates indicate thateven in the same sectors, induced CO2 generation is substantially different from country
to country. The paper gives the following four reasons for this: 1) differences among
countries in the goods that can be purchased with the same sum of money, 2)differences in product mix, 3) differences in energy mix, and 4) differences in
production technology.
Takenaka (2002) focuses on the energy consumption structure (total consumption,energy structure, highest energy sector) and household sector in the target countries, andclarifies the characteristics of each country’s household energy consumption structure.
The paper carries out a simple simulation estimating energy consumption resulting fromchanges in the calorific value per energy unit to examine future trends in energy
consumption. Similar to Kiji (2002), the paper compares energy consumption in ninecountries, and points out that considering China accounts for 48% and Japan for 32% of
total East Asian energy consumption, for a combined total of 80%, both countries have

15 Here the paper uses dollar value for output converting each country’s currency using a single

exchange rate, so care should be given to the result in the aspect that it does not use purchasing
power parity.
16 Japan is low because of the widespread use of desulfurization technology at the fuel stage.

7

a major influence on environmental issues in East Asia. It also classifies energy
consumption into production sector and household consumption sector, and gives theenergy consumption ratio for each by country. The household energy consumption ratio
differs depending on the country, but those with a high ratio are Malaysia, Indonesia
and Korea with 20% followed by JAPAN with 13%, while the lowest are Taiwan andSingapore with 5%. It is therefore understood that household consumption as apercentage of energy consumption is low in Singapore and Taiwan, and high in Korea,
Malaysia and Indonesia. Next the paper sheds light on differences in the energy
composition in each country through an international comparison of energy type.
Among the characteristics to emerge are that Japan has a high electric power ratio, but
at the same time it depends on a comparatively diverse range of energy types; Singapore,
Taiwan, Korea and Philippines have a high fuel oil ratio; of the ASEAN countries,
Malaysia has a high petroleum fuel and natural gas ratio, while Thailand has a strong
dependence on diesel oil; and Indonesia depends heavily on plant-based fuel oil, while
China is the only country that is heavily dependent on coal. Sectors with the highest
level of energy consumption (includes household consumption) are power, gas andwater, household consumption, and transportation in Japan and Korea, and power, gas
and water, and transportation in Taiwan, Thailand, and Philippines. In Singapore, thehighest are petroleum refinery and coal products, and in China, cement and othernonmetallic mineral manufacture. Indonesia is the only country where household
consumption is the highest energy consumer, while timber and wooden products, andwooden furniture are also high energy consuming sectors. Next the paper focuses on thehousehold consumption sector to determine the total amount and structure of energy
consumption. An international comparison of energy type in the household consumption
sector shows that in Japan, Singapore and Thailand, the main energy types are gasoline
and electric power. In Korea and China coal-based sources are the main energy type,with other coal products in Korea and coal in China. Plant fuel ranks high in Thailand
and Indonesia. City gas ranks high only in Japan, Singapore and Korea, three countries
with high income levels. Lastly, Takenaka (2002) conducts a simulation on changes incalorific value per energy unit. Calorific value per energy unit is necessary data for
estimating the D table, which has been converted into calories from the C table, andvaries greatly by country. From its estimate of each country’s energy consumption

8

based on cases where the calorific value per energy unit is 1) at the level of Japan, and2) at the highest and 3)at the lowest levels in East Asia, the paper points out that, taking
into account the “flying-geese” pattern, there are many opportunities for developing
countries to learn from developed countries, and each country must obtain informationfrom Japan and other developed countries in East Asia on their past experiences not justin the economy, but also regarding the environment, and make every effort to lower the
degree of future uncertainty about environmental issues as much as possible, and takethe path of sound economic development processes.

2)International link analysis
EDEN Data Base is prepared under a common format for nine countries, so

adding processes linked by trade statistics enables us to ascertain an international
interdependence in the Economy and Environment not just for a single country but inrelation to multiple countries. Takenaka (2002) is a typical international link analysis. It
adopts an East Asia trade matrix for quantifying the international interdependence ofEast Asian countries in CO2 generation associated with economic activities in the
countries / regions with the aim of drawing up a chart giving an overview of East Asian
countries regarding environmental load, such as what goods demand by which country
will in turn cause what industries in which country to generate CO2.

2

OthersTypical applications of analysis using EDEN Data Base include 1) environmentalload in the open ocean, 2) trade and the environment, and 3) household energy
consumption analysis.

1)

Environmental load in the open ocean
Washizu et al. (2002) estimates CO2 caused by East Asian open oceantransportation, that is, goods transportation between countries, using the 1990 version.
Single-country input-output tables only indicate energy consumption by that country’s
own national transportation organizations (ships, air transport and so on) over a one9

year period as a total amount, so they cannot reveal the environmental load arising fromtrade between two given countries. In addition to international link analysis, Washizu etal. (2002) estimated the environmental load accompanying open-ocean transportation.
However, the analysis only looked at ships within multiple transportation organizations.
Technical information on ocean-going ships used in export / import was not available,
so the estimations had a number of constraints, such as assuming the rate of fuelconsumption is the same as that of coastal ships, and that the CO2 basic unit does notchange according to the exporting / importing country, and as a result 17 , the paper foundthat for the nine countries as a whole, CO2 generation associated with goods production
amounts to 3.8 billion tons, and generation in the open ocean ranges from a maximumof 37.89 million tons to a minimum of 21 million tons, so it can be said that CO2
generation in the open ocean accounts for between 0.5% and 1.0% of total CO2
generation from goods production. By country, CO2 generation associated with goods
production is highest in China with 2.15 billion tons, followed by Japan with 980
million tons, while for CO2 generation in the open ocean, in exports Indonesia is thehighest with 13.09 million tons, and in imports Japan is the highest with a maximum of
15.91 million tons. As for generation induced by domestic final demand, China induces
1.78 billion tons, and Japan 950 million tons. Countries with a high overseas leakage(induction to other countries or the open ocean) are Singapore with 51.4%, followed by
Malaysia with 27.3%, and Thailand with 19.5%, while, conversely, countries with low
overseas leakage are China with 0.5% and Korea with 7.2%. Looking at Japan, Korea
and China by sector, we can see that induction to other countries is high in electric
power, gas and water supply, and also in Heavy and chemical industry products such as

17 CO2 generated by ship transportation is worked out by obtaining the consumption of each fueltype from the consumption percentage distribution of each fuel type from the fuel consumption
obtained from the fuel consumption rate for the weight of goods to be transported,transportation distance, and type of ship, then multiplying this by the CO2 basic unit.

10iron and steel. On the other hand, in ASEAN, emissions are high in crude oil andnatural gas, and timber and wooden products. 18

2)

Trade and environment (The influence on economy and environment by
FTA)
Trade forms the foundation of the economic system, and has brought

development to the world’s nations through mutual economic exchanges. Within this, it
is absolutely vital to strive for sustainable development that respects the perspectives ofboth trade and the environment and seeks their coexistence. As the finite nature ofresources becomes more obvious, the expansion of trade is becoming increasinglyconnected with various aspects of the environment and environmental policy, and there
is concern that trade expansion and the concomitant economic growth may have an
adverse impact on the environment and hinder sustainable development. And as it now
stands, trade expansion through the deepening of international interdependence overrecent years is affecting the Economy and Environment not just in one’s own country,
but in other countries as well. Takenaka et al. (2004) envisages trade expansion in twocases of WTO membership and free trade agreements, and analyzes the relationshipbetween the associated economic growth and environmental load 19 .
First, using the 1995 version, Takenaka et al. (2004) verifies the hypothesis that
trade liberalization in China may contribute to a lowering of the environmental load as ameans of clarifying the economic and environmental effect on China and Japan when
China undergoes trade liberalization premised on China, which has enjoyed remarkable

18 Future analysis will expand transportation organizations to include air transportation,

develop trade data in an identical unit, and, especially regarding ships, obtain technicalinformation on ocean-going and coastal ships.
19 Refer to Takenaka et al. (2004)p.159-162 for more detail about the relation between trade andenvironment. Shinozaki et al. (1997) is used as a reference for analysis method. The analysis
quantifies the environmental load resulting from an exogenous change with a fixed grossdomestic expenditure scale, and does not take into account the effects from income, prices, etc(See Takenaka et al. p.176).

11

growth in recent years, joining WTO. Specifically, the paper seeks the induced amountof CO2 and SO2 generation through the Leontief open model, assuming that China andJapan, which represents all other countries, are the only two countries in the world, andthat trade liberalization in China will result in an increase in China’s export of relatively
cheap goods, i.e. labor-intensive goods, and, conversely, an increase in its import ofrelatively expensive goods, i.e. labor-saving goods 20 . The result shows an increase in
output in both countries, but whereas the induced generation increases in China, it falls
in Japan. Combining the two, output increases, and the induced amount of CO2 and SO2
generation decreases about 1% each, indicating that China’s trade liberalization will
have the effect of expanding production in both countries, while contributing toward a
reduction in both countries’ environmental load. So while it cannot be claimed
categorically that trade liberalization in China will contribute toward a reduction in theenvironmental load, the paper confirmed that there is indeed a strong possibility that it
could. By sector, in China there is considerable CO2 generation increase in textile
products, whose production expanded due to increased exports, and in chemical
products, whose production increased through an indirect effect, and a notable decreasein iron and steel industry, non-ferrous metals, and power and heat supply services,
whose production dropped with the increase in imports. On the other hand, in Japan
there is a considerable CO2 generation increase in iron and steel industry, whose
production increased with the increase in exports, and in coke and other coal products,
and power and heat supply services, whose production increased due to an indirect
ripple effect, and a considerable decrease in air transport, and apparel and leather
products, whose production fell with the increase in imports. Combining the twocountries, CO2 generation rose substantially in textile products and chemical products
largely as a result of the effect of increased production in China, and fell substantially iniron and steel industry, and power and heat supply services, whose production
decreased in China.
Second, Takenaka et al. (2002) analyzes the direct and indirect effect of CO2
generation on the economies and environment of Japan and Korea assuming that an

20 Purchasing power parity index was used as a judgement standard in sector selection (SeeTakenaka et al. (2004)p.164).

12

FTA removing tariffs has been signed between the two countries, specifically, a JapanKorea FTA that removes Japanese and Korean tariffs. The analytical framework of thispaper is a combination of a kind of the integrated simulation model of AIM/CGE (Asia)
and Input-Output analysis using with EDEN Data Base. As a result, Japan-Korea FTA
would increase the GDP from 0.15% to 0.6% and also increase CO2/SO2 generation ineach country from 0.17% to 0.25%. A simulation result says that in total effects of bothcountries the additional environmental load in the degree of increase in CO2/SO2
generation would be expected lower than that of estimated degree of their economic
expansion of both countries. Then the formation of FTA could be evaluated even as anenvironmentally sound agreement.

3)

Analysis of environmental load accompanying Household consumption
Focusing on Japanese household consumption, Takenaka (2005) analyzes

household energy consumption from the perspective of its relationship with 62
household expenditure items for 1990 and 1995. 21 Considering recent international
environmental policies, Japan, which was obligated to reduce emissions especially with
the Kyoto Protocol coming into force, is at the stage of translating plans for reducing
emissions into action, and against this backdrop, we are ourselves obligated to reduce
emissions caused by the household sector, which is still trending upward. So empiricalanalysis is being carried out based on the idea that understanding the current state is thefirst step toward reducing emissions. Analysis started with an estimation of thehousehold consumption converter by laying out the household consumption vector of A
table on a matrix of 62 expenditure items x 76 products, and in addition to changes in
21 The paper does a similar analysis for Korea as well, and there are plans to expand this to other

East Asian countries. Washizu (1996) and Washizu (2001) are examples of analysis with eight
major expenditure items for 1990 and 1995 using another database. This chapter deals only withanalysis using EDEN Data Base, so it does not touch on Washizu (1996) and others aimed at
ultimately drawing up environmental household accounts using other data. The 62 household
expenditure items in Takenaka (2005) are expenditure classifications designed to correspond toboth the SNA and Household expenditure survey systems. For 1995, however, the provisionalversion of EDEN is used.

13the industrial structure, it clarifies the relationship between the environment and theconsumption lifestyle that reflects consumer preferences.

3. Korea-the current state of economy and environment in three target
years
Here I will expand EDEN Data Base in the three target years in Korea, andexamine changes in the current state of the Economy and Environment. 22 As mentioned
in Chapter 2, only the 1990 version of EDEN Data Base has been completed andreleased, while the 1995 version is still undergoing estimation, and the 2000 version has
not even reached the estimation stage. This paper therefore uses the 1995 provisionalversion assuming the already released 1990 version is correct, and after considering thestate of precision, extends this to the 2000 version. Here I judged precision for domestic
production from the extent to which it corresponds to the transactions table for the 2000
input-output table estimated independently by each country, and for CO2, from theextent to which it differs from general statistics on the five-yearly rate of increase. As
there is only limited information on total amounts, for both countries the 2000 version
was drawn up with specific assumptions on more detailed sector-by-sector generation.

3-1

Preparation and overview of EDEN Data Base 2000
Here I will prepare three-year data for Korea. When confirming the provisional

1995 version of EDEN Data Base, regarding A table, I confirmed from Korea’s inputoutput table that there is a match with the 76, so I judged there were no problems.
Regarding CO2, the rate of increase from 1990 to 1995 was 1.46, and considering theincrease rate in general statistics 23 was 1.49, it is judged to be a close match. I will
therefore extend the estimation to the 2000 version using information from both years.
First, I integrate the transaction table (2000 Input-Output table in Korea, Bank of Korea)
22 Of all the countries included in EDEN Data Base, Korea most closely resembles Japan interms of the state of statistics preparation, and because Korea was the first to release the basic
transactions table for the 2000 Input-Output table, it has been chosen for analysis.
23 Refer to Handbook of Energy and Economic Statistics in Japan.

14

so that it corresponds to EDEN 76. While there are slight variations in the 2000 version
such as a sector reorganization in communication and broadcasting and the new
establishment of a software-related sector 24 (table 3), I prepared A table by integrating
the 2000 transaction table into EDEN 76 with the 1995 sector categories as a reference.
Regarding CO2, in general statistics 25 the rate of increase from 1995 to 2000 is
1.19 times, and, similarly, 1.7 times from 1990 to 2000, so substituting both EDEN year
versions, I forecast that Korea’s CO2 generation in 2000 on an EDEN base is 444,661–
452,595(1000t-CO2). At the same time, looking at changes in the CO2 generation
coefficient, the rate of change from 1990 to 1995 is 0.7 times, indicating an average
improvement in CO2 generation efficiency of 30%. Therefore, assuming similar
technological advancements took place and efficiency improved by a uniform 30% ineach sector from 1995 to 2000, CO2 generation will be 450,449(1000t-CO2), which iswithin the forecast range 26 . However, I assume that 1995 values will be maintained for
15 sectors 27 in which the CO2 generation coefficient increased from 1990 to 1995. From
this, I prepared the 2000 CO2 generation table (E table) on an EDEN base 28 , anddeveloped a three-year database on Korea’s Economy and Environment.

24 Korea changed to compliance with the 1993 SNA system from the 2000 input-output table.

Therefore, care is needed when comparing with other years.
25 See footnote 24.
26 It can be conversely ascertained that CO2 generation efficiency improved by an average ofabout 30% from 1995 to 2000.
27 The 15 sectors (such as Dairy farming and livestock raising, Non-edible crops, Coal, Metal

ores mining, Spinning and weaving, Printing and publishing, Timber and Wooden products,
Coke and other coal products, Other fabricated metal products, Other power and so on) arethose sectors in which the CO2 generation coefficient increased from 1990 to 1995.
28 Separately, I also estimated 2000 substituting the 1995 value for CO2 generation coefficientwith the assumption that there was no change in the technological structure from 1995 to 2000,
and it was ascertained that this would result in a CO2 increase of 1.6 times, while technologicaladvancements would keep the increase in CO2 generation for 2000 down to 1.19 times.

15

3-2

ResultUsing EDEN Data Base for the three target years, I will determine interdependence

in Korea’s Economy and Environment 29 .

1)-1 Economic scale
Figure 3 shows changes in economic level over the three target years from adomestic production perspective and changes in per capita economic scale. Korea’s
domestic production jumped from 418 trillion won in 1990 to 1,392 trillion won in 2000,
a 3.32-fold increase in economic scale over the ten-year period. The rate of increase was
especially high from 1990 to 1995 at about 2.0 times, so Korea’s economic scale
expanded more in the first half of the 1990s than it did in the second half. The per capita
economic scale rose from 9.76 million Won in 1990 to 18.65 million Won in 1995, anincrease of 1.91 times, and to 29.63 million Won in 2000, an increase of 1.58 times30 . I
can therefore say that the increase was higher in the first half of the 1990s, and the percapita increase in domestic production rose about 3.03 times over the ten-year period.

1)-2 Industrial structure (Import and Export, Value added)
Here I will look at the industrial structure over the three target years. Figure 4
shows the industrial ratios for the three target years in 7 categories 31 . Broadly, it showsa decrease in the ratio of Primary and Secondary industries, and an increase in the ratioof Tertiary industries. Primary industries accounted for 5.1% in 1990, but this fell to

29 This is a nominal analysis in this section; substantive analysis is a future issue. In particular,

in the latter half of the 1990s Korea experienced the impact of the Asian crisis, so care isnecessary when using the analysis results.
30 The population of Korea is 42.9 million people in 1990, 45.1 million people in 1995 and 47.0

million people in 2000.
31 To clarify the overall feature, I integrated EDEN 76 to 7, Primary industry, Secondary(Mining) (Light) (Heavy) (Others) industry, Tertiary (Power & Transportation) (Others)
industry. To divide Light and Heavy industry, I refereed to Keio Economic Observatory (1974).

16

3.8% in 1995, and further to 2.75% in 2000. Secondary industries maintained thehighest ratio through the three target years, though it fell from 60.3% in 1990 to 53.7%
in 2000. One exception to this downward trend is Heavy industry, and it is the only
Secondary industry category that showed an increase, rising from 30.9% in 1990 to34.8% in 2000. In Tertiary industries, a notable increase was “others”, jumping from
34.5% in 1990 to 43.4% in 2000. The industry with the highest ratio among the sevenindustrial categories was a Secondary industry (Heavy) in 1990 and 1995, but in 2000, a
Tertiary industry (Others) rose above the Heavy industry. Looking at changes in
Korea’s industrial structure over the ten years from 1990 I can see that agriculture, andMining and Light industry sectors fell, while Heavy industry and the Tertiary industries
enjoyed a prominent rise, and that the service industry has overtaken the Heavy industry
and now occupies the position of Korea’s leading industry.
Next I will examine this by sector. Table 4 lists the top ranking sectors indomestic production. In 1990 the five main sectors in Korea were buildings, commerce,
motor vehicle, other electrical machinery, and real estate services, and while the sectors
in the top five did not change in 1995, the percentage share of other electricalmachinery, motor vehicle, and real estate services rose, and that of buildings andcommerce fell slightly. In 2000 a change took place in the main sectors, with otherelectrical machinery taking over as the sector with the highest percentage at 8.9%, andfinancial and insurance services, a Tertiary industry (Others), rose to take its place inthe top-ranking sectors. Table 5 lists the sectors with a high rate of increase in domestic
production. From 1990 to 1995 the increase rate of repair of motor vehicles, andknitting was particularly high, while business services, gas supply, and precision
instruments also enjoyed high rates of increase. From 1995 to 2000 eating and drinking
places increased 7.2 times, while the increase rate for postal telecommunication services
was also high, and gas supply, repair of motor vehicles and knitting have continued
their high rate of increase from the early 1990s. The ten-year rate of increase from 1990
to 2000 shows that repair of motor vehicles is highest at 41.3 times 32 , followed by

32 Regarding repair of motor vehicles, the basic classification in the Korean input-output tablehas undergone significant changes in the name of sectors and details from 1990 to 1995, so careis necessary when using this.

17

knitting with 28 times, eating and drinking places with 19.3 times, and gas supply with
11.9 times. Overall, over the ten years output has increased in 71 sectors other than cokeand other coal products, leather and leather products in the Light industry, and metalores mining, coal, and crude oil and natural gas in Mining industry.
As can be seen in the Korean economy over the three target years, economic scale
over the ten-year period expanded 3.3 times, and the per capita economic level also rose
more than 3.0 times, confirming that Korea developed substantially in the 1990s. In
particular, the pace of expansion was much greater in the early 1990s than in the latter
half of the decade. As for the industrial sector, the ratios of the Primary industries andLight industry fell, while the ratios of the Heavy industry and service industry rose.
Characteristic features of the decade are that in Heavy industry, other electricalmachinery became the main industry in 2000, and in the service industry, eating anddrinking places enjoyed a high rate of increase, and commerce, real estate services, andfinancial and insurance services became the main industries in 2000.

1)-3 Influence and sensitivity coefficients
Here I look at changes in the degree of interlinkage between industrial sectors
through the influence and sensitivity coefficients. The influence coefficient is anindicator for measuring the backward linkage effect, and allows us to determine thedegree of direct and indirect influence one industry has on the economic activities ofother industries. The sensitivity coefficient is an indicator for measuring the forward
linkage effect, and it enables us to determine the extent to which a product of a given
industry is demanded by other industries, including those in its own sector, as anintermediate input product. By combining both indicators, I can ascertain theinterdependence among industrial sectors within a single country. In general, whenanalyzing the influence and sensitivity coefficients, I look at placement in four
quadrants with coefficient 1 as the standard. Industries falling under the high influence
coefficient first or fourth quadrants have a high direct or indirect raw material input ratefrom various industries, and are broadly based with a relatively high degree ofprocessing requiring many intermediate goods. Industries falling under the high18

sensitivity coefficient second or third quadrants have a broad array of demand sectors
and a high intermediate demand ratio. 33
Figure 5 shows the influence and sensitivity coefficients for the seven industries
over the three target years. In all three target years, Secondary industry (Light) and
Secondary industry (Heavy) are in the first quadrant, only Tertiary industry (Others) isin the second quadrant, and only Secondary industry (Others) is in the fourth quadrant,
while Primary industry, Secondary industry (Mining) and Tertiary industry (Power andtransport) are in the third quadrant. Light industry and Heavy industry are both in thefirst quadrant, and are positioned as key industries in Korea, but comparing the twocoefficients, I can see that Light industry has a higher influence coefficient, while,
Heavy industry has a very high sensitivity coefficient. In both industries, though, thecoefficients dropped from 1990 to 2000, although only slightly, so theirinterdependence with other industries can be said to be on a weakening trend. On theother hand, Tertiary industry (Others) in the second quadrant is characterized by a very
high sensitivity coefficient, and while there was no change in the influence coefficientfrom 1990 to 2000, the sensitivity coefficient rose, positioning it close to the highest
ranking Heavy industry. It is therefore an industry with an increasing interlinkage
among industries by way of intermediate demand. Although the influence coefficient of
the third quadrant Primary industry and Secondary industry (Mining) rose, their
sensitivity coefficient is on a downward trend. From the above figures on the status of
the seven industries in influence and sensitivity coefficients, I can say that the Light andHeavy industries are still key industries in Korea, but both are falling in bothcoefficients, and their interlinkage with other industries is trending downward. In
contrast, I can see that Tertiary industry (Others) rose significantly in sensitivity
coefficient, signifying a strengthening interlinkage by way of intermediate demand. I
will now look at the relationship between influence and sensitivity coefficients by eachof the 76 industries, focusing on Light industry, Heavy industry, and Tertiary industry

33 From the above, industries in the first quadrant are high in both coefficients, and are above

average in the degree to which they influence and are influenced by production in industry as awhole when final demand occurs. They can be said to be key industries for economic growth,and should be developed with greater priority than other industries (See Ezaki(1985) ).

19

(Others). Table 6 lists the top ranking sectors in both coefficients for the three target
years. The influence coefficient is high in Light industry such as meat and meatproducts, and dairy products, and Heavy industry such as iron and steel products. It isnotable that in 2000 motor vehicle joined the top ranking group in influence coefficient,while in the sensitivity coefficient, other chemical products was the top ranking
industry for all three target years, and Tertiary industry (Others) such as commerce, andfinancial and insurance services, and iron and steel are in the top group of industries.
Table 7 lists sectors whose placement on influence and sensitivity coefficientschanged. What should be noted here is that eating and drinking places, which falls
under Tertiary industry (Others), rose above 1 in both coefficients in 2000, moving fromthe third quadrant to the first quadrant, positioning itself as a key industry. The
influence coefficients of coal, and repair of motor vehicles rose, moving them to thefourth quadrant in 2000, the sensitivity coefficient of postal and telecommunication
services rose, while the sensitivity coefficients of other chemical products, buildings,
and road transport fell. The influence coefficients of the five sectors of tea and coffee,
beverages, cement, glass and glass products, and air transport rose in 1995, moving
them to the fourth quadrant, but in 2000, they fell again, moving them back into thethird quadrant. Similarly, printing and publishing rose in the sensitivity coefficient in1995 to move into the first quadrant, but it again fell in 2000, and moved back into thefourth quadrant. The greatest change was seen in timber and wooden products — bothcoefficients rose in 1995 to position it as a key industry, but in 2000 the sensitivity
coefficient dropped, and it became a fourth quadrant industry. Overall, the number offirst quadrant industries rose from 15 in 1990 to 16 in 1995, but then fell to only 14 in
2000. In particular, in Light industry, timber and wooden products, and printing andpublishing became first quadrant industries in 1995, but moved back in 2000, while in
Heavy industry, the sensitivity coefficient of other chemical products fell in 2000,
pushing it out of the group of key industries. As mentioned earlier, over the sevenindustries, the above is thought to be one of the factors contributing to a drop in bothcoefficients from 1990 to 2000 in Light industry and Heavy industry.

202)-1 CO2 Generation
Next I will look at CO2 generation over the three target years from E table. Figure 6
shows CO2 generation by Korea, and CO2 generation per capita and per domestic
production unit. First, in total amount (right axis), CO2generation totaled about 250
million tons in 1990, but increased 1.46 times to about 373 million tons in 1995, andfurther increased 1.20 times to about 450 million tons in 2000. Therefore, the rate ofchange from 1990 to 2000 is 1.77 times, and is higher in the first half of the 1990s thanin the second half. Generation per capita shows that it increased 1.39 times from 1990 to
1995, and 1.15 times from 1995 to 2000, for a total increase of 1.61 times over the tenyear period. In contrast, CO2 generation per domestic production unit dropped to 0.73
times from 1990 to 1995, and to 0.72 times from 1995 to 2000, for a total drop to 0.53
times over the ten years. From the above, on a total amount base the rate of increase of
CO2 generation fell in the second half of the 1990s, but increased 1.7 times over the ten
years, and while per capita generation increased 1.6 times, per domestic production unit
generation was roughly halved over that period. It can therefore be said that in terms ofabsolute amount, the environmental load increased, but from the perspective of
production efficiency, the environmental load is tending to improve.
Figure 7 shows CO2 generation by each of the seven industries. Overall, theTertiary industry, and especially Power and transport, has generated the highest amountin all three target years, followed by Secondary industry, and Primary industry, and over
the ten-year period, the generation ratio of the Tertiary industry increased from 58.6%
to 69.2%, while the generation ratios of the Primary and Secondary industries fell. In
particular, Heavy industry dropped significantly from 26.7% to 20.7%, while the shareof Tertiary industry (Power and transport) rose above 50%. Tertiary industry (Others)
also rose from 14.6% to 18.2%.
Next I will look at CO2 generation by each of the 76 industries. Table 8 lists thesectors that generate large amounts of CO2. In all three target years thermal power has
generated the most CO2, accounting for 29% of total generation in 1995 and 2000. In
1990 the top ranking sectors were the transport sector, namely road transport and watertransport, cement, and commerce, and in 1995 the ratio for iron and steel, a Heavy
industry, increased, so the top five in 1995 were thermal power, road transport, water21

transport, cement, and iron and steel, accounting for more than 52% of total CO2
generation. In 2000 the ratio of eating and drinking places, and other power increased,
and with the other three of thermal power, water transport, and road transport, the top
five in 2000 account for more than 53% of total generation. Table 9 lists the sectors
with high rates of increase in CO2 generation. From 1990 to 1995 the increase rate forrepair of motor vehicles is highest at 8.4 times, and as mentioned earlier, this isconsidered to be due to an increase in production volume. Also characteristic is theincrease in generation by other fabricated metal products and eating and drinking
places. From 1995 to 2000, the five sectors with the highest increase in CO2 generation
were eating and drinking places, gas supply, repair of motor vehicles, knitting, andpostal and telecommunication services, all of which recorded high rates of increase in
output. Looking at changes from 1990 to 2000, repair of motor vehicles shows thehighest increase in generation, followed by eating and drinking places, knitting, and gas
supply. Therefore, looking at trends in Korea’s CO2 generation from EDEN Data Baseover the three target years, I can see that CO2 generation increased 1.7 times through the
1990s, and that the rate of increase was higher in the first half of the 1990s than in thesecond half. Per capita generation increased 1.6 times, but generation per domestic
production unit fell by about 50%, so while on a total amount base, generation increased,from the perspective of production efficiency, these figures show a comparatively
strong improvement. By sector, there is a marked increase in generation by Tertiaryindustry, and especially in 2000, in addition to thermal power, road transport, andwater transport, CO2 generation by eating and drinking places, which is classified a
Tertiary industry and enjoyed a substantial increase in production itself, stands out.
Moreover, in 1995 and 2000, the top five sectors alone generated more than 50% of thetotal amount, so the sectors that generate CO2 are relatively limited.

2)-2 Induced CO2 generation by final demand item
Next I will look at CO2 generation by final demand item 34 . Figure 8 shows theratio of CO2 generation for each final demand item (Private consumption expenditures,
34 This is level of dependence for each final demand item, and it enables us to determine which

final demand items are depended on in the direct and indirect generation of CO2.

22

Government consumption expenditures, Gross domestic fixed capital formation,
Increase in Stocks, and Export) for each year. Overall, CO2 generation derived fromconsumption (Private and Government) is the highest amount in each year, accounting
for about 47% of total generation, and there has been little change seen in this ratio over
the ten year period. On the other hand, the ratio derived from investment, especiallydomestic fixed capital formation, is decreasing, while CO2 generation from exports
increased from 30% in 1990 to 39% in 2000. Consequently, I can see a structuralchange in that about half of the CO2 generation in Korea in the 1990s was fromconsumption, while generation accompanying production aimed at export has been
increasing.
The above is on a total amount base, but similarly, Figure 9 shows induced CO2
generation by final demand item for each of the seven industries. By final demand item,in all years the four industries of Primary industry, Secondary industry (Light), Tertiaryindustry (Power and transport) and Tertiary industry (Others) have a high induced CO2
generation through consumption, Secondary industry (Others) is the only industry withhigh induced CO2 generation through investment, and the two industries of Secondary
industry (Mining) and Secondary industry (Heavy) have high induced CO2 generation
through exports. By industry, Primary industry in particular has high generation fromconsumption, and through the 1990s its ratio percentage was in the high 60s. Secondary
industry (Mining) has a relatively strong tendency to be dispersed among the final
demand items, but among them, the export ratio is high, rising from 38% in 1990 to
53% in 2000. Secondary industry (Light) has a high generation through consumption,with the ratio increasing in 1995 while the export ratio decreased, and in 2000,
consumption is again the main factor, though the export ratio strengthened. Like
Secondary industry (Mining), Secondary industry (Heavy) has a strong tendency to bedispersed, but the import ratio increased, and in 2000 more than half of generation isfrom production for export. As mentioned earlier, Secondary industry (Others) is the
only industry in which generation resulting from investment accounts for more than90%. Until 1995 in Tertiary industry (Power and transport) generation throughconsumption accounted for more than half of induced CO2 generation, but in 2000 theexport ratio increased almost to the level of consumption. In Tertiary industry (Others)
generation through consumption in 2000 accounts for more than 70%, so generation23

resulting from consumption is increasing. From the above, I can see that overall as
mentioned before, the ratio through exports is increasing, but I can say this is attributed
to the rise in induced generation derived from exports within Secondary industry,
especially in Mining and Heavy industry. By the 76 industries, those whose main final
demand item newly shifted from consumption to export during the 1990s include
petroleum refinery products, coke and other coal products, iron and steel, iron and steel
products, motor vehicles, and other transport equipment, while those whose generationfrom export increased substantially are the six industries of coke and other coalproducts, ship building and repairing, other transport equipment, machinery andequipment n.e.c., railway transport, and other transport and transport-related services,and I can say that because of the increase in induced CO2 generation from export inthese sectors, the export ratio of the Heavy industry sector as a whole rose.

2)-3 Induced CO2 generation associated with an increase in final demand
Focusing on the three industries of Secondary industry (Light), Secondary
industry (Heavy) and Tertiary industry (Others) from among the seven industrial
classifications, Figure 10 shows changes by year in directly and indirectly induced CO2
generation when final demand in each of the industries expands by about one trillion
Won 35 . Even assuming final demand in each of the industries expanded by the same
scale, there are differences in the induced CO2 generation, however, a common
characteristic among all three industries is that 1995 is less than 1990, and 2000 is lessthan 1995. In particular, generation by Light industry and Tertiary industry (Others) in2000 is half of that in 1990, and, similarly, generation by Heavy industry in 2000 is
38% of that in 1990, so even with the same scale of demand increase, I can say that2000 is in a more environmentally friendly condition. This is considered to be due toimprovements in technological efficiency. Comparing a breakdown of CO2 generation
among the three industries, in Light industry, the generation ratio for Light industry
itself is the lowest, and CO2 generation also arises in Tertiary industry (Power andtransport) and Heavy industry, and Primary industry. However, this own-industry
35 One trillion Won correspond to 0.55% of final demand in 1990, 0.26% in 1995 and 0.17% in

2000.

24

generation ratio is rising each year, and in 2000, 48% was generated by Light industry
itself. On the other hand, Heavy industry has the highest own-industry generation ratio,
and more than 60% is generated by the Heavy industry itself, and the remaining 25% isgenerated by Secondary industry (Power and transport), and Tertiary industry (Others).
Heavy industry’s own-sector generation ratio, however, has been falling each year,
whereas the generation ratio for Tertiary industry (Power and transport) and Tertiaryindustry (Others) is increasing. Tertiary industry (Others) generates 50% in its own
industry, and the remainder is generated by Tertiary industry (Power and transport), andHeavy industry, and this own-industry ratio is, like the Light industry, trending upward
year by year. This result reflects the degree of interdependence among the sevenindustries, and as was made clear by placement in the influence and sensitivity
coefficients, it is thought that the main factors for reductions in CO2 generation in eachindustry include a weakening interdependent relationship with the Heavy industry,
which is especially technologically inefficient regarding the environment, i.e., it has ahigh generation coefficient, and conversely, a rising interdependent relationship withthe low generation coefficient Tertiary industry (Others).

4. Conclusion
In this paper I prepared a database for environmental analysis over the three target
years for East Asia, one of the regions that are the main factors in the environmentalload, and especially Japan and Korea, and ascertained the characteristics of theinterdependence in the economy and the environment.
In Chapter 2 I discussed the background to the preparation of EDEN Data Baseand an overview, and looked at previous research. The main aspects of this were factfinding analysis using EDEN itself, and empirical analysis applying EDEN. Regarding
the former, only the 1990 version has been released, so the analysis covered thesituation in a single fiscal year. As for the latter, EDEN Data Base was used also inanalysis for clarifying the issue of environmental load in the open ocean, which is quite
substantial but has yet to be studied extensively because of a lack of data, the issue of
trade and environment under a growing need to determine the environmental load,
which is no longer a single country base but takes into account multiple countries,

25

associated with a deepening international interdependence against the current
globalization backdrop, and the issue of consumption lifestyle and the environment toascertain the current state of environmental load in the household sector, which,domestically, is on an increasing trend.
In Chapter 3 I first developed data in a common format over the three target years,
focusing on Korea. As the 1995 provisional version is quite accurate, I extended theestimations to the 2000 version based on the 1990 and 1995 versions. At this stage,
however, sector-based generation figures are not available, so judging from the total
amount, I drew up these figures assuming a 70% improvement in environmental
technology for each sector from 1995 to 2000. Through this, I was able to determine thecharacteristics of the structure of and changes in the economic and environmental
interdependence over the three target years, and not just for the single year of 1990. As
a result, economic scale in Korea expand 3.3 times as domestic production and morethan 3.0 times as domestic production in per capita from 1990 to 2000. In particularly,
the rate of increase was higher in the first half of the 1990s than last half. As for theindustrial structure over the three target years, the ratio of Primary and Secondary
industry decrease and Tertiary industry increase. But one exception to this down ward
trend is Heavy industry, and it is the only Secondary industry category that showed anincrease, especially Other electrical machinery and apparatus became main industry in
Korea as domestic production. In Tertiary industry, a notable increase was “Others”,
jumping from 34.5% in 1990 to 43.4% in 2000, the rate of Eating and drinking place,
Commerce, Real estate services, Financial and insurance services especially wereincreased and then Tertiary industry (Others) rose above Heavy industry. Next I look atchanges in the degree of interlinkage between industrial sectors through Influence andSensitivity coefficients, Light and Heavy industries are still key industries from 1990 to
2000, but both coefficients slightly dropped, so their interlinkage can be said to be on aweakening trend in three target years. Sensitivity coefficient of Tertiary industry rose,so it could be increased interlinkade among industry by way of intermediate demand.
We will now look at the relationship between influence and sensitivity coefficients byeach of the 76 industries. In Light industry, Timber and Wooden products, Printing andpublishing became key industry in 1995, but drooped out again in 2000. In Heavy
industry, Other chemical products drooped out from key industry in 2000. On the other26

hand, Eating and drinking place in Tertiary industry became key industry in 2000. Next
we look at CO2 generation, the total amount of CO2 generation in Korea increased 1.7
times through 10 years and increased 1.6 times as per capita, too. On the other hand,
CO2 generation per domestic production unit decreased half in 2000 from 1990, so it
can be said that Environmental load in Korea increased as a total amount but decreased
as a production efficient. As for each industries, Tertiary industry only increased. As forCO2 generation by final demand item, CO2 generation derived from consumption is thehighest through ten years, on the other hand, the ratio derived from exports increased,
especially for Heavy and Mining industry. As for EDEN 76 sector, Petroleum refinery
products, Coke and other coal products, Iron and steel products, Other transport
equipment, Other electrical machinery and apparatus, include Heavy industry are
increased derived from export. Finally, I will see the directly and indirectly induced
CO2 generation by the expansion of each final demand as a same scale, focusing on thethree industries of Light industry, Heavy industry and Tertiary industry (Others). The
induced CO2 generation in three industries decreased in 2000 from 1990, and it can besaid that 2000 is in a more environmentally friendly condition because of the generation
ratio of Heavy industry decreased but the ratio of Tertiary industry increased in threeindustries. So the change of interdependency among industry and improvement oftechnological efficiency regarding the environment brings the environmentally friendly
situation in Korea.
I started analysis with the preparation of EDEN Data Base for Korea for the threetarget years, and examined structural changes in the economic and environmental
structure over the three target years. At this stage information on sector-based
generation for 2000 is not available, so judging from the total amount in general
statistics, I carried out the analysis assuming, for convenience, a 30% improvement inenvironmental technology for each sector. As a future issue, I need to review thecoefficient for each sector by collecting detailed data on environmental and production
technology to draw up a more accurate 2000 version. EDEN Data Base is the only tablein the world to estimate the economy and environment in nine countries in East Asia
using a common format. Under the current state of EDEN Data Base release, I can only
carry out a cross-sectional comparison of the nine countries for 1990, but I am seeking
to establish the estimation methods in this paper as the basis of extended estimations,27

and where possible, undertake extended estimations of the 2000 version in a similarmanner for countries other than Korea so I can carry out time series and cross-sectional
analysis over the three target years for the nine East Asian countries.
Environmental load is incidental to economic activities, and considering thebackdrop of an international interdependence among countries and industries, resolving
this issue requires policy intervention based on international collaboration. EDEN Data
Base used in this paper is an analysis tool for quantitative analysis of theinterdependence between economic activities in the business sector in various countries,
and the environmental issues that arise incidental to these activities, and by clarifying
the state of the global environment, which is taking on a rapidly growing presence inworld awareness with the expanding economic activities, it is an invaluable databasewhen considering global preservation. Unfortunately, though, only the 1990 version of
EDEN Data Base has been released, so it has as yet not reached the multipurpose use
stage. I am hoping to develop EDEN Data Base versions for each year in each country
as soon as possible, and from this, consider methods of dealing with global
environmental issues whose resolution is a matter of great urgency.

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Washizu A., andYamamoto, Y.(2002)., “Asian Interdependency from CO2－applicationof EDEN Data base 1990”, In Japan Society for the Promotion of Science, “Interdisciplinary Studies for Sustainable Development in Asian countries, Working
GroupⅠ, Keio Economic observatory, Economic development and Environmental30

preservation in Asia “Vol.1, Estimate and application of EDEN Data Base”: Keio
University Press, Ch.5, pp.145-170.

31

Table 1: Structure of EDEN Data Base
Unit

Intermediate Demand

Final Demand

A

Transaction table

Respective currencies

76×76

76×5

B

Energy substance input table

Specific physical unit

22×76

22×5

C

Energy Consumption table

Specific physical unit

22×76

22×5

D

Calorie Table

Calories

22×76

22×5

E

CO2・SO2 generation table

ton

2×76

2×5

Source: This table is an excerpt from Kiji(2002)p.25.

Figure 1: Outline of EDEN Data Base32

Figure 2: Estimation process of EDEN Data Base

Table 2 : Outline of previous analysis-single country
Kiji(2002)

Kim et al.(2002)

Takenaka(2002)

Sector

20

76

48

Energy545Features

The paper uses figures

Mainly focusing on Japan

Mainly focusing on Household sector

substantiated withand Korea, and Light andcarries out a simple simulation estimatingpurchasing power parity

Heavy industry.

energyconsumption

resultingfromindices calculated fromchanges in the calorific value per energy

GDP statistic

unit to examine future trends in energy
consumption.

Source:Author makes this figure referring to Kiji(2002), Kim et al.(2002), and Takenaka(2002)

33

Table 3 : The list of change sector in 2000 from 1995
1995

2000

Unrefined liquors and rice wine.3173

Section deletion.

Mineral and spring water.3177,Manufactured ice.3178

Integrate to Spring water and manufactured ice.0084.

Engines and turbines.4001

Change name, International combustion engines
turbines.0226.
Separate and new establishment Machinery for－

manufacturing semi conduct.0244 from Misc.machineryand equipment of special purpose.

Other electronic signal equipment.4112

Change name, Flat digital display.0255.

Telegraph and telephone.6402

Separate Telephone.0347 and High-speed network
services.0348 a

Broadcasting(private non-profit).6404 ,Separate Terrestrial broadcasting.0350 and Cable

Broadcasting(commercial).6405

broadcasting.0351.

Depositoryinstitutions.6501,

Separate Central bank and banking institutions.0352,

Non-depository credit institutions.6502

Non-bank depository institution,0353 and Other financial
brokerage institutions.0354.
Separate Computer soft wares development.0364 from－

Computer programming, data processing, and othercomputer related services.

Research and news syndicated services.6617

Change name, Information provision services.0368.

Source: Author makes this table referring to The Bank of Korea(2003).

34

Figure 3: Korea-Economic scale in three target years

1600000

35000

1400000
1200000

Domestic product

30000

Domestic product per capita

25000

1000000

20000

80000015000

60000010000

4000005000

200000
0

0

1990

1995

2000

Unit: Domestic product-One billion won, Population-One million people.

Figure 4: Korea-Industry structure in three target years

2000

1995

1990
0%

10%

Primary
Secondary(Heavy)
Tertiary(Others)

20%

30%

40%

50%

Secondary(Mining)
Secondary(Others)

60%

70%

80%

90%

100%

Secondary(Light)
Tertiary(Power&Transport)

Source: Author makes this figure from EDEN Data Base(A Table).

35

Table 4 : Korea-Top ranking sectors of Domestic Products(%)
1990

1995

2000

1

Buildings

7.38

Buildings

6.61

Other electrical machinery

8.98

2

Commerce

6.62

Other electrical machinery

6.05

Real estate services

5.88

3

Motor vehicle

4.38

Commerce

5.89

Commerce

5.01

4

Other electrical machinery

4.30

Motor Vehicle

4.71

Financial and insurance services

4.55

5

Real estate services

3.97

Real estate services

4.61

Motor vehicle

4.25

Source: Author makes this table from EDEN Data Base(A Table).

Table 5 : Korea- Top sectors with a high rate of increase in domestic production
1995 / 1990

2000 / 1995

2000 / 1990

1

Repair of motor vehicles

12.62

Eating and drinking place

7.25

Repair of motor vehicles

41.31

2

Knitting

9.00

Gas supply

3.61

Knitting

28.00

3

Business services

3.59

Repair of motor vehicles

3.27

Eating and drinking place

19.34

4

Gas supply

3.29

Knitting

3.11

Gas supply

11.92

5

Precision instruments

2.84

Postal telecommunication services

3.09

Petroleum refinery products

7.54

Source: Author makes this table from EDEN Data Base(A Table).

36

Figure 5 : Korea-Influence and Sensitivity coefficient for 7 industry
1.8
1990
1995
2000

1.6
1.4
1.2

2nd(Heavy)

3rd(Others)

1.0

Primary

2nd(Light)

3rd(Power)

0.8
0.6

2nd(Mining)

0.4

2nd(Others)

0.2
0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

Source: Author makes this figure from EDEN Data Base(A Table),Note: Horizontal axis-Influence coefficient, Vertical axis-sensitivity coefficient.

Table 6 : Korea-Top ranking sectors of Influence and Sensitivity coefficient
Influence Coefficient

1990

1995

2000

Sensitivity coefficient

1

Meat and meat products

1.67

Other Chemical products

3.29

2

Dairy products

1.52

Commerce

2.59

3

Not elsewhere classified

1.44

Financial and insurance services

2.34

4

Iron and steel products

1.38

Not elsewhere classified

2.04

5

Iron and steel

1.37

Iron and steel

1.98

1

Meat and meat products

1.59

Other Chemical products

2.98

2

Not elsewhere classified

1.41

Business services

2.90

3

Dairy products

1.39

Financial and insurance services

2.47

4

Dairy farming and Livestock

1.37

Not elsewhere classified

2.06

5

Iron and steel products

1.33

Petroleum refinery products

1.88

1

Meat and meat products

1.61

Other Chemical products

3.20

2

Not elsewhere classified

1.39

Financial and insurance services

2.61

3

Dairy products

1.37

Business services

2.60

4

Motor vehicle

1.34

Petroleum refinery products

2.54

37

5

Iron and steel products

1.30

Commerce

2.06

Source: Author makes this tabke from EDEN Data Base(A table).

Table 7 : Korea –Lists of sectors whose placement on Influence and Sensitivity
coefficients changed
1990

1995

2000

Ⅲ

Ⅳ

Ⅳ

Ⅲ

Ⅳ

Ⅲ

Timber and Wooden products

Ⅲ

Ⅰ

Ⅳ

Printing and publishing

Ⅳ

Ⅰ

Ⅳ

Other chemical products

Ⅰ

Ⅰ

Ⅳ

Buildings

Ⅰ

Ⅳ

Ⅳ

Road transport

Ⅱ

Ⅱ

Ⅲ

Air transport

Ⅲ

Ⅳ

Ⅲ

Eating and drinking place

Ⅲ

Ⅲ

Ⅰ

Postal and telecommunication services

Ⅲ

Ⅲ

Ⅱ

Repair of motor vehicles

Ⅲ

Ⅲ

Ⅳ

Coal
Tea and Coffee, Beverages, Cement, Glass and glass
products, Air transport

Source: Author makes this table from EDEN Data Base(A Table).

Figure 6 : Korea-CO2 generation (total, per capita and per domestic product)
500000450000400000350000300000250000200000150000100000
50000
0

12000
10000
8000

CO2 per Capita
CO2 per Domestic Products
CO2 generation

6000
4000
2000
0

1990

1995

38

2000

Source: Author makes this figure from EDEN Data Base(E Table),
Unit: CO2-1000t-CO2, Population-One million people, Domestic Products-10 trillion Won.

Figure 7 : Korea- CO2 generation in seven industries.

2000

1995

1990

0%

20%

40%

Primary
Secondary(Heavy)
Tertiary(Others)

60%

Secondary(Mining)
Secondary(Others)

80%

100%

Secondary(Light)
Tertiary(Power&Transport)

Source: Author makes this figure from EDEN Data Base(E Table).

Table 8 : Korea- List of the sectors that generate large amounts of CO2
1990

1995

2000

1

Thermal power

22.0%

Thermal power

29.4%

Thermal power

28.8%

2

Road transport

11.1%

Road transport

8.6%

Eating and drinking place

6.8%

3

Water transport

5.6%

Water transport

6.2%

Water transport

6.8%

4

Cement

5.4%

Cement4.2%

Road transport

6.7%

5

Commerce

5.4%

Iron and steel

4.2%

Other power

3.9%

Source: Author makes this table from EDEN Data Base(E Table).

Table 9 : Korea-List of the sectors with high rates of increase in CO2 generation
1995/1990

2000/1995

2000/1990

1

Repair of motor vehicles

8.41

Eating and drinking place

5.08

Repair of motor vehicles

19.26

2

Knitting

4.57

Gas supply

2.53

Eating and drinking place

13.39

3

Other fabricated metal products

3.09

Repair of motor vehicles

2.29

Knitting

9.96

39

4

Gas supply

2.94

Knitting

2.18

Gas supply

7.44

5

Eating and drinking place

2.64

Postal and telecommunication services

2.17

Other power

4.71

Source: Author makes this table from EDEN Data Base(E Table).

Figure 8 : Korea-The ratio of CO2 generation for each Final demand item
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
1990

1995

Private Consumption expenditures
Gross domestic fixed capital formation
Export2000
Government consumption expenditures
Increase in Stocks

Source: Author makes this figure from EDEN Data Base(A and E table).

Figure 9 : Korea- Induced CO2 generation by Final demand item in seven industries

100%
90%
80%
70%
60%

Export50%

Invest40%

Consumption

30%
20%
10%

1990

1995

Tertiary(Others)

Tertiary(P&T)

Second(Others)

Second(Heavy)

Second(Light)

Second(Mining)

Primary

Tertiary(Others)

Tertiary(P&T)

Second(Others)

Second(Heavy)

Second(Light)

Primary

Second(Mining)

Tertiary(Others)

Tertiary(P&T)

Second(Others)

Second(Heavy)

Second(Light)

Second(Mining)

Primary0%

2000

Source: Author makes this figure from EDEN Data Base(A and E table).

40

Figure 10 : Korea- Changes by year in directly and indirectly induced CO2 generation
when Final demand in each of the industries expands by about one trillion Won
800
Primary
2nd(Heavy)
3rd(Others)

700
600

2nd(Mining)
2nd(Others)

2nd(Light)
3rd(power&Transport)

500
400
300
200
100
0
Light

Light

Light

Heavy

Heavy

Heavy

3rd(Others)

3rd(Others)

3rd(Others)

1990

1995

2000

1990

1995

2000

1990

1995

2000

Source: Author makes this figure from EDEN Data Base(A and E Table).
Unit: 1000t-CO2.

41

Appendix 1 : EDEN 76 classification
1

Paddy

39

Iron and steel

2

Fruits40

Iron and steel products

3

Dairy farming and Livestock raising41

Non-ferrous metal products

4

Other edible crops

42

Metallic furniture and accessories

5

Non-edible crops

43

Other fabricated metal products

6

Agricultural services

44

Household electrical appliances

7

Forestry(Inc. Hunting)45

Other electrical machinery and apparatus

8

Fishing

46

Motor vehicle

9

Coal

47

Ship building and repairing

10

Crude oil and Natural gas

48

Other transport equipment

11

Metal ores miming

49

Precision instruments

12

Non-metallic ores mining

50

Machinery and equipment n.e.c

13

Dairy products

51

Other manufactured products

14

Meat and meat products

52

Thermal power

15

Other foods

53

Other power

16

Animal feeds54

Gas supply

17

Tea and coffee

55

Water, Steam & hot water supply, Sewage,
Sanitary services

18

Beverages

56

Buildings

19

Tobacco57

Civil engineering

20

Spinning and weaving

58

Commerce

21

Knitting

59

Railway transport

22

Wearing apparel and other fabricated60

Road transport

textile products
23

Leather and leather products

61

Water transport

24

Timber and Wooden products

62

Air transport

25

Wooden furniture

63

Other transport and transport relating services

42

26

Pulp, paper and paper products

64

Eating and drinking place

27

Printing and publishing

65

Hotels & other lodging place

28

Fertilizer

66

Postal and telecommunication services

29

Drugs and medicine

67

Financial and insurance services

30

Soap, detergent and toiletries

68

Real estate services

31

Other chemical products

69

Business services

32

Petroleum refinery products

70

Public administration

33

Coke and other coal products

71

Education

34

Rubber products

72

Medical and health services

35

Plastic products

73

Repair of motor vehicles

36

Cement74

Other repairs, n.e.c37

Glass and glass products

75

Other services

38

Other non-metallic mineral products

76

Not-elsewhere classified
Source: This table excerpt from EDEN Data Base.

Appendix 2 : 22 Energy classification
1

Coal

12

LPG

2

Coke

13

Other Petroleum fuels

3

Other Coal products

14

Naphtha’s

4

Crude Oil(Inc. Liquid oil)

15

Other Petroleum Products

5

Natural Gas

16

Total Electricity

6

Liquefied Natural Gas

17

Town Gas

7

Gasoline

18

Vegetable fuels

8

Jet Fuel

19

Industrial waste gas

9Kerosene20

Industrial or General Waste

10

Diesel Oil

21

Steam and Hot water supply

11

Fuel Oil

22

Natural energy

Source: This table excerpt from EDEN Data Base.

43

Appendix 3 : 76sectors for 7 Industry
7 Industry

EDEN 76

1

Primary industry

1,3,4,5,6,7,8

2

Secondary (Mining)

9,10,11,12

3

Secondary(Light)

13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,34,35,37

4

Secondary(Heavy)

28,29,30,31,32,33,36,38,39,40,41,42,43,44,45,46,47,48,49,50,51

5Secondary(Others)

56,57

6

Tertiary(Power & transport)

52,53,54,55,59,60,61,62,63

7

Tertiary(Others)

6,59,64,65,66,67,68,69,70,71,72,73,74,75,76
Source: The author makes this table.

44