Journal of Applied Input-Output Analysis, Vol.2, No.l, 1994

The Oil Saving Efficiency of Recycling Technology

for Waste Plastics1
By
Toyoaki Washida*

Abstract

After the first oil crisis many companies in Japan started on projects to recycle waste
plastics by transforming them into oil. These projects, however, were disrupted after thefall of oil price in the successive periods of the oil crisis. This disruption was mainly caused
by inefficiency of the recycling technology in those days.

Recently a new technology forrecycling, which uses artificial zeolite as catalyst, has been developed and an experimental
plant has been constructed. Although the technology has high efficiency in transforming
waste plastics into oil, it cannot produce value added. However we have to understand thedifference between the efficiency for value and for material. In this paper, we investigatedthe oil efficiency of the technology.

The oil efficiency was measured by the quantity ofoil which was directly and indirectly necessary to produce one unit of oil by recycling

waste plastics. We use the 1985 Input-Output Table and a linear programming model isconstructed.

Since waste plastics are produced as joint products, we cannot avoid to use

linear programming models. The result showed that recycling technology had high efficiency

in saving oil. If the total of the waste plastics generated in Japan would be processed bythis technology, the amount of oil savings would be 7.57 million Kl which would be just
4% of the total amount of oil used in 1985.

1.

Introduction

The total waste plastics discharged by households and by industries in 1988 is 8 x 10et in
Japan2. Since plastics support our materialistic life from every aspect, we do not expect thisamount to decrease substantially. On the one hand it is clearly wasteful to discharge the plastics
which contains energy with high density. On the other hand when waste plastics is discharged

as solid materials, they take up much space and accelerate the use of land fills.

To burnthem in facilities which can generate electricity is an effective way to save energy. It releases,

however, some types of pollutants in the air. Especially if the waste plastics include chlorine (Cl)they possibly generate hazardous organic chlorine compounds depending upon the conditions ofburning. Moreover the release of carbon dioxide (CO2) is unavoidable. Thus we have to seek

alternative ways to deal with them3.
The way which has the strongest potential is to transform them into oil which is the original
resource of plastics.

After the first oil crisis in 1973 many companies in Japan started on

projects to recycle waste plastics to reproduce oil. These projects, however, were disrupted after
the fall of oil price in the successive years. This disruption was mainly caused by inefficiency
Manuscript received May 25, 1994. Revised September 26, 1994.

* Faculty of Economics, Wakayama University

2This paper was presented in the 10th International Conference on Input-Output Techniques, Seville, Spain,
1993. I thank the anonymous referee for helpful comments.

2t means metric ton (= tonne) throughout this paper.
3 See Pearce(1990) and Washida(1992).

The Oil Saving Efficiency of Recycling Technology

39of the recycling technology in those days. Recently a new technology for recycling, which uses
artificial zeolite as catalyst, has been developed and an experimental plant has been constructed.
Although the technology has high efficiency in transforming waste plastics into oil, it cannot
produce value added in the progress. We have to pay attention to the difference between theefficiency for value and for material. We shall investigate in this paper, the oil efficiency of thistechnology. The oil efficiency is measured by the quantity of oil which is directly and indirectly
necessary to produce one unit of oil from recycling waste plastics. We use data from the 1985
Input-Output Table and a linear programming model is constructed. Since the waste plastics
are produced as joint products, we cannot avoid the use of linear programming model.

2.

Theoretical Framework of Technology Assessment

Since we use the input-output table, every quantity is basically measured in monetary unit,
unless it is specifically mentioned that other unit is used. Let the number of sectors be n andthe number of goods be m. In this stage they do not include waste plastics and their recycling

sector.

Let A = (a,;) be a m x n input coefficients matrix. We do not necessarily presume

m = n. dij means the amount of the ith products required to operate the jth industry for one

unit of activity. We assume that aXJ- includes the service by fixed capital equipment and it does
not include imported products.

Let B = (a,;) be the m x n output matrix and b{j denotes

the amount of the ith products produced by the jth industry for one unit of activity. In our
analysis, since we deal with joint production this matrix cannot be a diagonal one. We cannot
avoid using joint production model to analyze the efficiency of recycling technology, as wastematerials are inevitably produced as joint products. Let g = (gj) bean dimension row vectorof import coefficients.

The gj means the amount of imported products required for one unitof activity of the jth industry. The import of materials requires the same amount of exports
measured in monetary unit, and we assume that exports and imports are in balance.

Let avector e be a basket which expresses the composition of products exported in 1985. It is a mdimension column vector and it is normalized as |e| = 1. It shows that one unit export has to
Let (/beam dimension vector expressing the final

be performed with a distributed form e.

demand for domestic products, and dm+i be the amount of final demand for imported products.

Let c' = (c'j) be a n dimension row vector expressing the amount of imported crude oil requiredby one unit of activity for each industry 4. Moreover we use a slightly different c = (cj) vector.
Let the kth industry produces crude oil. Then the difference between c' and c is only in the kthelement, that is, c* = c'k + 1 and Cj — c'jj ^ k.
First let us specify the primary problem which does not include the recycling industry of
waste plastics. The problem is to minimize input crude oil required to produce final demand.
The problem is as follows.

Minimizec' x + x^ — exs.t.

(B-A)x-exn+l

>

d

—gx

+£n+i

>

dm+i

x > 0,

zn+! > 0,

where x is an activity vector and zn+i is the amount of export. The objective function expresses
the total of imported and domestically produced crude oil. Since one unit of crude oil meansthat at least one unit of crude oil has to be extracted from the external of this economy (=natural environment), the objective function expresses the total crude oil resources exploited forsustaining the final demand d and dm+i.
4 The amount of crude oil is measured by physical terms throughout this paper.

40

Journal of Applied Input-Output Analysis, Vol.2, No.l, 1994

The first equation of the constraint conditions shows that the demand for domestic products
have to be less than that of supply. This is a m dimension vector equation. The second
equation shows that the total import has to be less than total export. The last equation is thenonnegativity conditions for variables.
Since the system is specified by a linear programming problem, the output configuration

has normative characteristics and we cannot say that the actual output configuration tends
to converge on the configuration given by this problem as an optimal solution. However theobjective of this analysis is not to show how the actual configuration is given, but to show
the criterion of technology assessment. In other words, our methods are to show whether therecycling technology of resources is effective under an optimal condition.
Next, the dual system of the problem is as follows.
Maximize

vd + vm+ic/m+is.t.

v(B-A)-vm+lg

<

c

-ve

+vm+i

<

0

v > 0,

vm+i > 0>

where v is a value vector measured in crude oil and vm+i shows the oil value of imported
products. The objective of this problem is to maximize the total oil value of the final demand
vector. The first vector equation shows that the output products for each industry cannot fix
the oil value more than the total oil value of input materials and services. This is an equation
for the conservation of the value.
It is unnecessary to show whether both problems have optimal solutions, for our analysis is
not theoretical but empirical. Owing to the duality theorem, if both problems have solutions the

maximum of the former problem coincides with the minimum of the latter problem5. Althoughboth solutions are closely related we mainly pay attention to the solution of the dual problem,
for the value vector can evaluate the basket of products from the viewpoint of macroscopic oil

efficiency.

Vi can be interpreted as the amount of crude oil which is directly and indirectly

required by additional one unit increase of the final demand for the products6, that is,Acx

Now let an+2 be the input vector required to produce one unit of oil by recycling.

van+2 shows the amount of oil charged by using this recycling technology.

Then

If the oil valueof waste plastics is zero and 1 > van+2 holds, then it means that the oil produced by therecycling technology is greater than the oil necessary for recycling.

Thus v functions as afundamental criterion to measure the efficiency of recycling technology.

We shall investigate

this point again after the specification of the problems which directly include the recycling
sector of waste plastics.

Let an+2 be the input vector of the recycling sector used above, and xn+2 be the working
level of the sector. xn+2 is measured by the amount of oil recycled by the sector. Let p be then dimension row vector which elements show the amount of waste plastics jointly produced byeach industry and pn+2 b.e the amount of the waste plastics required for one unit production ofoil. Let dm+3 be the amount of waste plastics discharged by the household. Finally let N be
the amount of input crude oil outside the economy. Then the problem is specified as follows.
Minimize
5 See Gale(1960)
6See Dorfman, Samuelson and Sollow(1958)

N

The Oil Saving Efficiency of Recycling Technology

41

s.t.
A \

—gx

—

J

>

0

+£n+i

-ex

zn+2

px

+N

-\

X > 0,

Zn+1 > 0,

Zn+2 > 0

The objective is to minimize the input crude oil. The first equation shows the supply and demandbalance for domestic products. The second shows the trade balance. The third equation showsthat the crude oil cannot be saved more than the amount recycled. Here we assume that therecycled oil is completely substitutable for crude oil. The fourth equation shows the supply anddemand condition for waste plastics.
Then we can specify the dual problem as follows.

Maximize

vd+ vm+idm+i - vm+3dm+3s.t.

V(B - A)

-Vm+ig-l>m+2C+Vm+3P< <t>-ve

V > 0,

Vm+i > 0,

Vm+2 > 0,

Vm+3 > 0,

where vm+2>vm+3 are the value of oil and waste plastics, respectively.
vector composed only by 0 elements.

<f> is the m dimension

Since it is impossible for the economy to be sustained

without input of crude oil the minimized TV has to be positive. Owing to the duality theorem
the last equation in the dual problem holds the strict equality in the optimal solution.

Thismeans vm+2 = 1, that is, the oil value of the oil itself is 1.
As mentioned above let us examine how the value system v and vm+i in the model without
the recycling sector works for the evaluation of the recycling technology. Now let us assume thefollowing equation.

van+2 > 1

(1)

In other words, the total oil value of the input factors to produce one unit oil in the recycling

sector is greater than 1. Let v* and v^+t- (i=l,2,3) be the optimal solution in the dual problem
inclusive of the recycling sector. Then we can easily show that the following equation can neverbe satisfied.

v*d + t4+1dm+i - C+3<*m+3 < vd + vm+1dm+1(2)

The proof is as follows. Now assume t;m+2 = 1, vm+3 — 0 and let us consider v, vm+i (i=l,2,3).
If (1) is satisfied then v,vm+i (i=l,2,3) has to be a feasible solution of the dual problem inclusiveof the recycling sector. Moreover if (2) is satisfied the problem has the feasible solution which
value of the objective function is greater than the optimal solution.

This is a contradiction.

Therefore (2) can never be satisfied.
The right hand side of (2) expresses the oil necessary without the recycling sector and the left
hand side expresses that with the recycling sector. Therefore the fact that the above equation
is not satisfied means that we cannot save the oil input by introducing the recycling technology
from a macroscopic view.

Thus the following equation has to be satisfied so that the recycling sector saves the macro
input of crude oil.

van+2 < 1

(3)

42

Journal of Applied Input-Output Analysis, Vol.2, No.l, 1994

Table 1: Product and Input Flow
Waste Plastics

Sorting, washing, crushing
Recycling Plant

Product

1

Electricity

1,100

Other Costs

14,000t

Kwh¥

Fuel Oil200

Kg

Electricity

400

Kwh

Zeolite

2,000¥

Other Costs

2,000

¥

Recycled oil

800

Kg

Although (3) is a necessary condition, it is not a sufficient condition.

In other words, evenif (3) holds, we cannot exclude the case that the oil necessary with the recycling sector is notdifferent from that without the sector. However, we can say that the case is quite rare as we haveinvestigated in the previous part of this section. Therefore (3) can be the important criterion
for assessing new technologies.

It is true that we can directly judge the recycling efficiency by solving the problem inclusiveof the recycling sector. Yet to use the criterion (3) has some advantages. For example, let us
consider the case that we have some alternative technologies for recycling. If we use (3) as thecriterion it is not necessary to solve each problem for each technology. Since we already havethe vector v by solving the linear programming problem without the recycling sector, we simply

need to calculate the total value the input coefficient and to compare the value with 1. Moreover
we can extend the methods into the assessment of more general technologies. In other words not

only for recycling technologies we can assess whether a new technology has oil saving efficiency
or not by the same procedure as described above.

3.

Specification of the Recycling Technology

First let us simply describe the recycling technology of waste plastics which is working as anexperimental plant in Japan. The kinds of waste plastics which can be processed by the plant
are polyethylene, polypropylene and polystyreen. The four major plastics include, in addition,
polyvinyl chloride, which in this stage of technology cannot be processed, for the plant cannot

absorb chlorine gas without damage to the plant. However we assume that the recycling plant
can process the waste plastics of polyvinyl chloride with minor change that cannot affect theestimation of the technology.

These raw materials have to be broken into pieces before they

are taken into the plant. The materials are heated up to about 400 centigrade and transformed
into gas, which passes through artificial zeolite as catalyst and is finally transformed into oil.

The ratio of the materials and the product is 10:8 measured by weight. The ingredients of the

product are gasoline 50%, kerosene 25% and light oil 25%.
Next we shall estimate the input coefficients of the recycling technology except for fixedfacilities of the plant. Table 1 shows the components of input and output flow of the technology
per 1 t of waste plastics to be processed by the plant. We assume that the fuel oil 200 kg is
substitutable by the same amount of recycled oil. Then the recycled oil valued by the price in1985 amounts to ¥ 32,755. The total cost of electricity amount to ¥ 36,534.

Then we have to match these components to the classification of the 1985 Input-Output Table

in Japan. Since the. electricity is treated as an independent product in the Input-Output Table,
we can make it correspond to the product in the table as a cost directly. We make the artificial
zeolite correspond to the sector of the other industrial inorganic chemicals in the input-output
table. The other costs are distributed among elements using the input vector of the sector of

The Oil Saving Efficiency of Recycling Technology 43

the petrochemical basic products in the Input-Output Table which is normalized to make thesum equal to 1. Before making the normalized vector, we eliminate the elements for the otherindustrial inorganic chemicals, oil products, products related to petrochemical basic products

and electricity from the vector, for these elements are already included. The configuration islisted in the first column of the table in Appendix A. We finally have the input coefficient vector,
i.e. an+2) vector by these elements divided by the nominal value of recycled oil.
Finally we have to estimate the coefficients related to the supply and demand of waste

plastics. Since waste plastics does not have stable evaluation by markets we have to deal with
the quantity of waste plastics in physical term. The amount of waste plastics required to produce

one unit of recycled oil can easily be calculated by the relationship in Table 1. The amount ofwaste plastics discharged by each industry is estimated as follows.

As mentioned in the firstsection, total industrial waste plastics amounts to 282 x !06t in 1985. However we do not haveinformation about how much of the amount is partly attributed to each industry.

Therefore

we assume that each industry discharged waste plastics in proportion to the input of plastics.

We distribute the total 282 x 106t to each industry in proportion to the input of plastics. The
output coefficient is obtained by dividing it by the activity level of the industry.

We assumethat waste plastics discharged by households amount to 10% of the total waste materials of

4,344.9965 x 106t in 1985.

4.

Processing of the Input-Output Table

We use the 1985 Input-Output Table of Japan, where one unit is treated as 100 million yen.

Although our analysis is primarily based on the 183 sectors integrated table, we utilize the datafrom the 529 x 408 basic table, when necessary.
The integrated table includes the products, iron scrap and non-ferrous metal scrap, which
are not produced as main products by any sector. We assume that these products are produced
as joint products by industries. Clearly all sectors have the potential to produce these products.
Since we pay attention to the flow of crude oil in this analysis, we should avoid treating
petroleum refinery products as a single kind of products. We assume that the petroleum sector
jointly produces gasoline, jet fuel oil, kerosene, light oil, heavy oil A, heavy oil B and C, naphtha,

LPG, and other petroleum refinery products. These data are listed in the basic table. Thus thetotal sector number is 181, and the total product number is 191 in our model.
Except for the petroleum refinery sector, the working level of each sector is measured by theamount of main product. The working level of the petroleum refinery sector is measured by theamount of gasoline produced.
Now let us show how to construct matrices and vectors from the input-output table. First,

the input coefficient matrix A is the sum of an intermediate input coefficient matrix A! and acapital service coefficient matrix C, that is, A — A! + C. The matrix A is obtained by dividing
the input elements by the activity level of each sector.

To make the C matrix, we distributethe depreciation of fixed capital by normalized vector which is obtained by the fixed capitalformation matrix in 1985. In the fixed capital formation matrix, products are classified into thebasic classification employed by the basic table and sectors are classified by an 84 sectors table.
It is easy to integrate the basic classification into ours. To disintegrate the sector classification,

we assume that similar sectors, which are treated as same sectors when the 183 table is integrated

into the 84 table, have the same proportion of various fixed capital. Then we divide the elements
by the activity level of each sector.
The column vector of the output coefficient matrix for each sector includes the element 1 forthe main products of the sector and non-zero elements for the iron scrap and non-ferrous metal

scrap which are joint products divided by the amount of the main product, and all the otherelements are zero. As stated above, since the activity level of the petroleum refinery sector is44

Journal of Applied Input-Output Analysis, VoL2, No.l, 1994

measured by the production level of gasoline, the element for the gasoline is 1 and the otherelements of joint products are proportional to this level.
The import row vector g is the sum of the column elements of the import matrix for eachsector divided by the activity level. The export column vector e is constructed by normalizationof the export vector in the final demand part of the integrated table. The row vector c of crude
oil input coefficient is constructed by dividing the crude oil input for each sector by the activity

level and by making the element of domestic crude oil sector 1.

Moreover, as an exception,

the crude oil input is measured by the physical term, Kilo liter KL Finally the final demand

vector for domestic products d can be obtained directly from the table and the final demand forimported products dm+i is the sum of imported products.

5.

Solution without the Recycling Sector

First we solved the problem in which the recycling sector of waste plastics was not implemented.
As discussed in the theoretical analysis, we can evaluate the recycling technology with the value
vector of crude oil which can be obtained from the model without the recycling technology.

The calculation was performed by the revised simplex method of linear programming. The

value of the objective function in the optimal solution amounts 195,695xlO3Kl. This meansthat in order to produce the final demand basket in 1985, this amount of crude oil has to be
input to the economy at the minimum. On the other hand, the actual amount of crude oil input

to the Japanese economy in this year is about 219,300xl03/C/. The difference between the two
numbers suggests that the Japanese economy have the potential to save crude oil input.
Let us investigate the optimal solution vectors. The table in Appendix B shows the structureof the solution.

The first column shows the optimal production configuration.

The second

column shows the amount of excessive production for each sector in the optimal solution. The
third column shows the dual solution vector, which its elements of measure the crude oil value
for each products and they are measured in physical term Kl.

In the table we can confirm that the values of the products excessively supplied are zero. This
fact is derived from the duality theorem of linear programming. Actually among the products

jointly produced by the petroleum refinery sector, all values of the products except for naphtha
are zero because of excessive production. This means that naphtha is the most scarce productamong the petroleum refinery products for the Japanese economy in 1985. Of course, for theactual production, since these joint products are slightly substitutable, the economy can avoid
this rigid situation.

The other excessive production appears for the sector of two wheel motor vehicle and thesector of watches and clocks. This result is related to the joint production of scrap. The sector of

two wheel motor vehicle produces iron scrap with high proportion, on the other hand, the sectorof watches and clocks produces non-ferrous scrap with high proportion too. Since the scarcityof these kinds of scrap is rather high for the production of the final demand, these sectors are
actually transformed into those of the scrap production as main products in our model. Thisshows the inefficiency of the actual economy from the view point of the saving of crude oil.

Now let us evaluate the recycling technology by means of the dual solution as theoreticallyexamined in the previous section. We employ the following notations.
s : Recycled oil per ton of waste plasticsr : Intermediate input vector per ton of waste plastics/ : Depreciation of fixed capital per ton of waste plastics
k : Proportion vector of fixed capital, normalized as \k\ = 1
v : Crude oil value vector

The Oil Saving Efficiency of Recycling Technology

45

Table 2: Summary of calculation
Depreciation

Input of crude oil

Rate of saving

Activity level of

Value of wasted¥/<

xl03A'/%

recycling sector 106¥

plastics Kl/t

0187,920

3.973

378,8540.673264

20,000188,126

3.868

379,1930.655553

100,000

188,9473.448

380,556

0.584393

300,000

191,0282.385

384,005

0.404235

500,000

193,1461.303

387,5170.220781

700,000

195,303

0.200

391,095

0.033940

800,000

195,6950005, r, and k are already given in the section for technology specification, v is gven as the dual
solution of the model without the recycling technology. However p is not specified explicitly yet.
First let us investigate the t which satisfies the following equation.

s = rv + tkv(4)

Let t* be t which satisfies the above equation7. This equation means that the amount of produced
recycled oil is just equal to the total crude oil value of the technology which can produce it.
As suggested in the theoretical part, in this case the recycling technology can save the input of

crude oil as the total of society. On the other hand, if the depreciation of fixed capital of thistechnology is less than <*, the technology is efficient, for it can save the input of crude oil. We
can easily calculate t* and,t* =735,939.
In other words, if the depreciation of fixed capital for recycling It of waste plastics is less than

¥ 735,939, then the technology is efficient. The rational depreciation is now estimated to beabout ¥ 20,000 for It of waste plastics, and this t* is very large. Therefore, we can expect highlevel of saving efficiency of crude oil by this technology.

6,

Estimation of the Oil Saving Efficiency

Let us investigate how much we can save crude oil with the recycling technology for waste

plastics. Although we have to make the model include the recycling technology, we have notspecified the depreciation of fixed capital for the technology which is denoted as t in the previous
chapter.

We try to catch how the efficiency of the technology would change by making thedepreciation shift to different levels. The alternatives of the depreciation are 0, 20,000, 100,000,
300,000, 500,000, 700,000, and 800,000 per It of waste plastics. The summary of calculation isshown in Table- 2. We can confirm that the depreciation exceeding the critical level t* = 735,939
make it impossible to save crude oil.

Since the normally expected level of the depreciation is

20,000, at that level the amount of saving of crude oil is about 7.569 xlO6 if/8, which is 3.9% for
the total input of crude oil to the Japanese economy.

In the case of the ¥ 20,000/< depreciation, the activity level of the recycling sector for waste

plastics is ¥ 379,193xl06, which equivalents to 8.683xlO6#/ in terms of crude oil. This meansthat if the depreciation could possibly be zero, then we could save 8.683xl06/<7. However,
7The variables can be related to the input coefficient vector an+i, i.e., r + tk = an+2/Pn+2 and also s —l/pn+2- Since we need the variable t the new notations are introduced.

8The amount is derived by 195,695 - 188,126.

46

Journal of Applied Input-Output Analysis, Vol.2, No.l, 1994

in actual we can only save 7.569xl06A7. The difference 1.114xlO6/<7 is consumed directly or
indirectly by the recycling process of waste plastics. The difference is unexpectedly small.

The activity level of the recycling sector for waste plastics increases as the depreciation
increases. This means that the increase in depreciation causes the increase in activity levels of
the other sectors and the increase in waste plastics jointly produced. Therefore the recycling
sector has to increase the activity level to recover from technological inefficiency as much as it
can.

Finally, the value of waste plastics decreases as the depreciation increases. This shows directly
the deterioration of the technology. At the point of zero activity level of recycling sector, sincewaste plastics is excessively produced, the value of waste plastics becomes zero too.

7.

Concluding Remarks

Our empirical study for the recycling technology for waste plastics shows that this technology
has high efficiency in saving the total input of crude oil for the Japanese economy. On the other

hand, the technology still does not have the ability to produce value added. In this stage ofprogress, the technology has to be in the area of increasing returns to scale. Therefore economic
policies to promote the use of recycling technology for waste plastics in many fields of theeconomy are required.

The Oil Saving Efficiency of Recycling Technology

47

Appendix A
The list is for the products which are input to the recycling sector as intermediate products or
fixed capital.
Intermediate

Proportion of

Dual

Input

Fixed Capital

Solution

44.9370.00000

0.618663.7730.00000

0.4576Natural gas

0.000

0.000131.4515

Other textile products

5.436

0.00000

0.7985

Wearing apparel

1.399

0.00000

0.6433

Apparel accessories

25.8320.00576

1.0041

Wooden furniture and accessories

87.3990.00000

0.4443

Printing and publishing112.101

0.00000

0.9358Industrial soda chemical

2000.000

0.00000

2.5515

Other industrial inorganic Chemicals

436.0800.00000

0.9597

Coal products

57.7460.00000

1.9325

Other rubber products

7.534

0.00000

0.7022

Leather footwear

0.054

0.00000

1.0091

Miscellaneous leather products

0.538

0.00000

0.5212Other glass products

4.844

0.00000

0.6495

Ceramic, stone and clay products

0.000

0.000121.9539

Metal products for construction

SectorCoal and Lignite

0.000

0.00077

1.2116

Heating and cooking apparatus

13.7230.00000

0.0841Other metal products

0.000

0.01598

1.2493Engine and boilers

0.000

0.00391

1.3060Conveyors

0.000

0.00291

2.0079Refrigerators and air conditioning

0.000

0.010211.1483

Other general industrial machinery

0.000

0.000070.9604Mining and construction machinery

0.000

0.41238

0.9363Chemical machinery

0.000

0.00058

0.7810Industrial robots

0.000

0.068440.8210

Other special industrial machinery

0.000

0.00345

1.5670

Other general machines and parts

819.5810.00000

0.6166

Repair of general machinery

0.000

0.002200.4704

Office machines

0.000

0.002171.4154

Household electric appliance0.000

0.02398

0.9737

Computer and accessory device

0.000

0.00444

1.1231

Communication equipment

0.000

0.00094

0.8910Applied electronic equipment

0.000

0.02449

1.5684Heavy electrical equipment

0.000

0.042191.5007

Other electrical equipment

204.8820.00000

0.7129Repair of electric machinery

0.000

0.00396

1.2514Passenger cars

0.000

0.00365

1.4267

Trucks, buses and other cars

48 Journal of Applied Input-Output Analysis, Vol.2, No.l, 1994

0.000

0.00451

1.5267

Other trans, equipment and repair

1.023

0.00000

0.0000

Watches and clocks

0.753

0.04265

1.1878Other precision instruments

0.000

0.15855

0.8119New residential construction

312.7850.00000

0.6298

Repair of construction

0.000

0.06794

0.9734

Other civil engineering

36534.000

0.00000

1.8287

Electric power

9.956

0.00000

2.1624

Gas supply

306.9190.00000

0.8347

Water supply

238.3560.00000

0.1900

Other sanitary services

955.3080.083890.1862Wholesale trade

27.7700.001480.2192Retail trade

6507.731

0.00000

0.1244

Financial service

141.055

0.00000

0.1542

Insurance

858.8140.00000

0.1390Real estate agencies and rent

42.6770.00003

0.5459National railway transport 1

2.099

0.00000

0.4726

National railway transport 2

23.5180.00000

0.3621

Local railway and tramway

69.3160.00000

0.1856

Road passengers transport

458.038

0.007200.1768Road freight transport

104.298

0.00000

0.3377

Private self-passenger transport

65.9800.00000

0.3524

Private self-freight transport

168.3400.000100.3562

Coastal and inland water transport

12.0550.000160.1793

Transport service in harbor

116.8370.00002

0.4752

Air transport

71.5770.00056

0.3102

Storage facility service

6.512

0.00000

0.4012

Packing

41.0090.00000

0.1199Postal service

104.9970.00000

0.3979Telecommunication

0.269

0.00000

0.1809School education and research

7.158

0.00000

0.5163Self-education

44.1300.00000

0.2484Social and other education

155.9620.00000

0.2807

Research institute809.3020.00000

0.8206

Self-research

431.9360.00000

0.2018Other public service

25.0250.00000

0.3284Advertising agency

167.3710.00000

0.1767

Information services

100.5300.00000

0.5359

Office machines renting and leasing

631.9750.00000

0.2012Other business services

11.8940.00000

0.9299

Office supply

1080.864

0.00000

1.3633

Activities not elsewhere classified

The Oil Saving Efficiency of Recycling Technology

Appendix B
Optimal Output

ExcessDual

Configuration xlO4

SupplySolution

436.945—0.456635.865—0.5730

Potatoes and pulses

220.520—0.4553

Vegetables

105.641—0.3797

Fruits

28.925—0.6396

Other edible crops
Inedible crops

Sector
Cereals118.961—0.5987384.329—0.6856

Livestock-raising

25.028—0.7735

Sericulture

61.807—0.5046

Agricultural services

86.061—0.2864

Silviculture

125.262—0.2270Logs

24.801—

0.3425

Minor forest products

303.891—

0.3843Maine fisheries

19.083—0.6704Inland water fisheries
Iron and ore mining

0.467

—

0.666822.169—0.4988Non-ferrous metal ores

37.912—0.5037

Material ceramics

180.447—

0.3435

Gravel and quarry

2.221

—

0.5476

Other non-metal ores

49.808—0.6186

Coal and lignite

9.760

—

23.3240

Crude petroleum

18.432—0.4576Natural gas

220.480—0.6411

Slaughtering and meat processing

0.7170Meat foods

480.083—0.5945

Sea foods

466.677—

0.5816

Grain milling

686.315—0.6502

Vegetable and fruit products

618.279—

0.5801Other foods

388.994—

0.3137

Liquor268.161—

0.5720

Other beverages

174.761—

0.9719Feeds and organic fertilizer

271.852—0.2523

TobaccoRaw silk and fiber yarns

2i iD.ooo

213.883—

1.7753449.212—1.4256Fabrics

160.217—0.9872

Knit fabrics

177.173—

0.8298

Yarn and fabric dyeing

186.654—1.4515

Other fabricated textile

508.258—

0.7985

Wearing apparel

Apparel accessories

26.918—0.6433104.678—0.8375

Other ready-made textile products

455.028—0.7631

Timber, plywood and wooden chips

49

The Oil Saving Efficiency of Recycling Technology

203.952—

0.5489157.121—0.4132Pottery, China and earthenware

402.770—0.6495

Ceramic, stone and clay products

2054.164—

10.5713—185.3276

1898.799—

5.7606

Hot rolled steel

395.481—2.3157

Steel pipes and tubes

1304.684—

1.4882Cold-finished and coated steel

1112.768—

9.0666

Cast, fogged and other steel

508.952—

7.0315

Non-ferrous metals—

141.6316

288.127—

7.1367

Electric wires and cables

1025.639—

13.5915

Other non-ferrous metal products

390.046—

1.9539

Metal products for construction

334.120—

3.2396

Metal products for architecture

154.089—

1.2116

Heating and cooking apparatus

1466.635—

0.0841Other metal products

Cement products

Pig iron and crude stone
Iron scrap

Non-ferrous metal scrap

354.187—

1.2493Engines and boilers

292.100—

1.3060Conveyors

163.791—

2.0079Refrigerators and air-conditioners

999.088—

1.1483

Other general industrial machines

469.248—0.9604Mining and construction machinery

267.290—0.9363Chemical machinery
Industrial robots

81.915—0.7810856.168—

0.5149

Metal processing machinery

741.744—0.8210other special industrial machinery
Other general machines and parts

971.922—1.5670627.658—

0.6166

Repair of general machine

501.835—0.4704

Official machines
Machinery for service industry

115.127—1.00191882.719—

1.4154

Household electric machinery

1053.280—

0.9737

Computer and accessory device
Communication equipment

514.697—

1.1231369.260—

0.8910Applied electronic equipment

1285.511—

0.9213

Semiconductor and IC

1064.891—

1.5684Heavy electrical equipment1479.873—

1.5007

Other electrical equipment

1900.266—

1.0195

Parts and accessory of electrical

266.573—

0.7129Repair of electric machinery

1645.065—

1.2514Passenger cars

907.248—1.4267

Trucks, buses and other cars

3436.517

3301.457

0.0000

Two wheel motor vehicle51

52 Journal of Applied Input-Output Analysis, Vol.2, No.l, 1994

5297.700—

1.6537

Parts of motor vehicle

592.044—0.9633

Repair of motor vehicle

627.373—

1.2382

Ships and its repair

141.776—0.5507

Railway cars and its repair

1.1997

Aircraft and its repair
Other transportation equipment

110.699—248.494—

1.5267269.605—

0.9337

Optical instruments

11229.882

8534.679

0.0000

Watches and clocks

463.756—

1.1878Other precision instruments

156.438—

1.4621

Toy and sporting goods

878.634—

1.2412Other manufacturing products

2261.725—

0.7761

New residential construction

2928.321—

0.8119New non-residential construction

748.234—

0.6298

Repair of construction

1375.572—

0.6179Public utility construction

1493.425—

0.9734

Other civil engineering

2383.849—

1.8287

Electric power

224.605—

2.1624

Gas supply

5.355

—

0.8587

Steam and hot water supply

354.368—

0.8347

Water supply

298.525—

0.1900

Other sanitary service

6299.191—

0.1862Wholesale trade

3169.599—

0.2192Retail trade

3370.751—

0.1244

Financial service

844.244—0.1542

Insurance

1396.257—

0.1390Real estate agencies and rent

2733.049—

0.3075

House rent

367.861—

0.5459National railway transport 1

73.738—0.4726

National railway transport 2

226.003—

0.3621

Local railway transport

534.862—0.1856

Road passenger transport

1313.971—

0.1768Road freight transport

577.131—0.3377

Self-passenger transport

604.554—0.3524Self-freight transport

695.555—

0.9607

Ocean transport

168.800—

0.3562

Coastal transport

251.819—0.1793

Transport service in harbor

277.670—0.4752

Air transport

168.887—

0.3102

Storage facility service

340.639—0.4012

PackingThe Oil Saving Efficiency of Recycling Technology

53

Other transport service

419.218—

0.2378

195.731—0.1199Postal service

796.163—0.3979Telecommunication

10.318—0.3473

Other services for communication

216.876—

0.2786

Broadcasting628.336—0.3622Public administration (central)

1113.921—

0.1481

Public administration (local)

1306.440—

0.1809School education and research

49.140—0.5163Self education

190.276—

0.2484Social and other education

168.491—

0.2807

Research institute731.037—0.8206

Self-research

1922.764—

0.4199

Medical service

261.313—0.2873Social insurance

691.255—

0.2018Other public service

589.809—

0.3284Advertising agencies

714.650—0.1767

Information service

258.461—

0.5359

Office machines renting

47.269—0.4185

Car renting

1889.949—

0.2012Other business service

959.084—0.2852

Amusement service

1526.646—

0.3151

Eating and drinking places

401.720—0.3404

Hotel and other lodging places695.456—

0.2712Other personal service

280.885—0.9299

Office supplies

1339.841—

1.3633

Activities not classified

7325.840—

1.7589

ExportReferences[1] Pearce, D.W. and R.K.Turner (1990), Economics of Natural Resources and the Environment, London, Harvester Wheatsheaf.

[2] Washida, T.(1992), Kankyou to energy no keizai bunseki (Economic Analysis of the Environment
and Energy), Tokyo, Hakuto Syobo.
[3] Dorfman, R., P.A. Samuelson and R.M. Solow (1958), Linear Programming and Economic Analysis,
New York, McGraw-Hill Book Company, Inc.

[4] Gale, D.(1960), The Theory of Linear Economic Models, Chicago, The Univ. of Chicago Press.