Journal of Applied Input-Output Analysis, Vol.1, No.l, 1992

Induced Technical Progress and Structural Adjustment:

A Multi-Sectoral Model Approach to Japan's Growth Alternatives1
By
Shuntaro Shishido* and Osamu Nakamura*

Abstract

Induced technical progress, distinguishing neutral and biased factors, is estimated on a sectoral

basis and then incorporated as endogenous variables into a large scale multi-sectoral econometricmodel of Japanese economy with the Leontief type input-output framework. The sectoraltechnical progress is explained by neutral non-price factor, neutral price factor (or barometer ofmarket competition), and biased factors induced by relative factor prices. Two growth alternatives

are explored with the model with a special emphasis on (a) import promotion and (b) increased

leisure in the context of induced technical progress, output, and employment on a 64-sectoral basis.
The importance for growth of the increased competition by imports is emphasized as its policy
implication.

1. Introduction
Recent empirical studies on technical progress on a sectoral basis have indicated substantial
differences in terms of levels and speeds among different sectors in almost all industrialized or semiindustrialized nations. A relatively slower pace in the primary sector and a faster growth in thesecondary, especially in high technology sectors, are commonly observed, though there are marked
differences among countries according to the stage of development, factor endowment, market
performance, educational and cultural background, government policies on technology, etc.

However, impacts of such sectoral technical progress on different sectors in terms of relative
prices, output, employment, investment, and foreign trade have not been specifically formulated
and anlyzed in an integrated system where interdependence among different sectors is explicitly andconsistently taken into account.

Furthermore, a feedback mechanism from these economic changes to sectoral technical progresshas not been analyzed on a quantitative basis, so that the degree of inducement in sectoral technicalprogress cannot be specified in an integrated system.

This paper aims to explicitly incorporate sectoral changes in technical progress in terms of totalfactor productivity (TFP) in the framework of the Leontief model with 64 sectors. The paper thenattempts to endogenize these technical changes in order to analyze the interdependence between

technical progress and conventional economic variables, especially factor prices.

In the latter part of the paper our multi-sectoral model is simulated for two alternative scenarios[(a) import promotion and (b) increased leisure] to evaluate the Japanese growth alternatives for
medium term, during 1990 and 1995. Special emphasis is placed upon policy impacts on sectoraltechnical progress and structural changes in output, employment, and foreign trade. The importance
Manuscript received September 21, 1990. Revised January 21, 1992.

* International University of Japan'The authors are indebted to Kiyo Harada for research assistance. The research was in part supported by the National
Institute for Research Advancement.

2

Journal of Applied Input-Output Analysis, Vol.1, No.l, 1992

of the impacts of foreign competition upon the promotion of domestic technical progress (ornegative impact of protectionism), is emphasized in the context of this scenario. The second
alternative scenario, with special reference to leisure, is discussed. This is compared with the firstscenario in terms of technical progress and policy implications, etc.

2. Model2
The model presented in this paper is a large scale multi-sectoral econometric model based on a
Leontief framework which has been developed by the International University of Japan (previously
by the University of Tsukuba) since 1985. The model is an annual dynamic econometric model with64 sectors and about 3500 equations, consisting of seven sub-blocks: (1) wages, (2) technical progress

and prices, (3) macro-economic variables, (4) final demand, (5) output and input, (6) value added
and its components, and (7) social and demographic variables.
The main features of the present version, JLM-G1, can be summarized in the following.
First, the annual model consists of sectoral variables, such as output, intermediate input,
employment, capital stock, capacity output, output prices, export and import prices, wages and user
costs of capital, and technical progress. These are integrated within a Leontief type input-output

framework with a 64 x 64 technical coefficient matrix and a 64 x 22 final demand matrix. Whatdistinguishes the present model from the ordinary multi-sectoral model with a Keynesian typemechanism is an annual updating system of an input-output (or technical) coefficient matrix basedon an algorithm named V-RAS Dl which is a dynamic version of the static V-RAS used at the

beginning of this research project.3 Given technical progress, or total factor productivity (TFP) andprimary factor prices, such as wage rates, user cost of capital and import prices on a sectoral basis,
both saving (s) and substitution (r) parameters as well as output prices can be estimated simul
taneously through RAS computation procedure. Note in this case that a rectangular technicalcoefficient matrix, including several rows for primary inputs, is employed instead of the ordinary
square matrix so as to link the inverse of TFP (1/TFP) to the s parameter for each input column.

Accordingly, the method enables us to evaluate the Leontief type forward effect of the output pricereduction caused by technical progress generated in a specific sector.
Second, by means of this updating system of technical coefficient matrix and forecasts on final
demand variables, the input-output table can be compiled for each year in both real and nominal
terms. This type of information has proved to be highly useful for business, in particular, as

medium-term information for marketing and cost-profit analysis.
Third, the interdependence between sectoral output and prices can be analyzed explicitly with thisgeneral-equilibrium type model, since almost all quantity variables are made price-sensitive withrespect to private consumption, foreign trade, intermediate and primary inputs, and technicalprogress which will be discussed later in more detail.

Fourth, the model also covers macroeconomic variables including those on fiscal and monetary
policy instruments, money flows, interest rates, taxes and transfers, income distribution etc.
Accordingly, the Keynesian type analysis can also be made on the dynamic multipliers as well as

sectoral analysis in a consistent framework of the Leontief system.
2Original model based on a 548x409 technology I-O matrix, was a statics type growth model [7], [9]. The model wasthen transformed into an annual econometric model with a dynamic adjustment mechanism. For use of this model see[1] [2].
3In V-RAS Dl, annual changes in (r) and (s) parameters were estimated in the formula of dynamic adjustment of lagged
explanatory variables on the basis of their annual time series. The static version was built on five-year intervals, assuming
a static equilibrium. For details, see F.G. Adams and S. Shishido [1] and Shishido et al. [7] and [9].

Induced Technical Progress and Structural Adjustment:

3

Finally, since the previous version of the JLM-F8 model4, a demographic block has been newly
added so that the information on labor supply and population structure can be analyzed by sex andby each cohort, mostly grouped by five years. The interdependence between economic variables andthese demographic variables can be explicitly analyzed. Technical progress can also be studied incontext to these socio-demographic variables, especially aging, sex, educational background, etc.

3. Impacts of Technical Progress on Sectoral and Macroeconomic Changes
As mentioned in the previous section, technical progress in terms of TFP has an important role inthe model in determining both quantity and price variables at both the sectoral and macroeconomic
level. Figure 1 illustrates the model's causal flows. Technical progress in a specific sector first reduces
the cost and the price of the output, thus causing the expansion of demand, whether intermediate,

final, or external, and increasing the output, employment and investment of the sector concerned.

This is a bright side to technical progress at the microeconomic level. It also tends to produce anindirect, secondary impact on industries using such newproducts, e.g. telecommunication based on
glass fiber system. The prices of such "using" sectors tend to fall as an indirect impact of technicalprogress. Forward linkage or spill over of technical progress through such price cuts is particularly

noteworthy as observed in Japan's micro-electronic revolution since the late 1970s.5 Capital, energy
and labor costs of electronic and related sectors have been dramatically reduced.
In contrast to this positive side of technical progress, there is a negative impact on employment,
capital service, and raw materials and fuels. The broken line in the Figure 1 denotes this negative(Macro)(Sectors)
Expansion
Technical

Cost

Price reduction
using sectorsofprogress,• Private consumption-^—• Business investment H^^

I

expenditure

reductionPriceintermediate
domestic^)f► Demand reduction incompetitive

demandlExpansionof output

Expansion of exports(secondary
effect)►Employment

reduction I

Employment

expansion j

Business[Foreign

effectindustries

I

demandfinal

exports

investment •countries]

Expansionof imports^

positive

effectFigure 1 Causal Flows of Technical Progress

4 See F.G. Adams and S. Shishido [2],5SeeShishidoetal.*[7], [9].

I

reduction -Demand expansion

negativeof effective
demand4

Journal of Applied Input-Output Analysis

flow which can also be observed for competitive sectors, e.g. natural fiber substituted by synthetic
fiber, and fossil fuels, such as coal and petroleum, substituted by atomic or solar energy. The net

positive impact of technical progress, after offsetting these negative ones, can be analyzed in themodel along the direction of backward linkage. A complicated interaction between these forward
and backward linkage effects (or price and quantity impacts), as induced by technical progress, canbe properly analyzed in the Leontief type system of the present model.

As for the macroeconomic impact, as shown in the right side of the figure, technical progress ofa specific sector creates the expansion of private consumption due to increased real disposable
income and business investment as a result of increased profit expectation. As widely recognized,
the latter variable is particularly important in analyzing the business cycle from Schumpeterian
dynamics on technical progress. The greater becomes the macroeconomic impact, the stronger

technical progress tends to occur in a cluster in the related industries, as in the case of microelectronics.
Regarding foreign trade, technical progress tends to strengthen competitiveness through pricereduction, thus stimulating exports as shown in the figure. This is a typical case of forward linkage.
On the other hand, there is another case in reducing imports as a negative effect of technical progress(e.g. reduced imports of iron ores substituted by new synthetic material). In both cases, the trade
surplus tends to increase with a negative impact on foreign countries, especially if the macro
economic impact of technical progress and the induced imports is not strong enough to offset therise in trade surplus. In most cases, however, technical progress is likely to occur as a cluster witha strong induced investment, as pointed out by C. Freeman et al.,6 and a fairly positive, expan

sionary effect is usually observed on the world trade as well.7
4. Factors Inducing Technical Progress
We have concentrated so far on the effects of technical progress on sectoral and macroeconomic
variables. The next question is how such technical progress is induced by economic variables.

Although there have been many attempts to formulate endogenized technical progress,8 few
contributions have been made using TFP as a quantitative measure of technical progress in theframework of the multi-sectoral model.
In view of fairly wide fluctuations of relative prices, including factor prices, and significantly

growing differentials of technical progress between different sectors in the Japanese economy since1970, we attempted to estimate TFP functions directly for all sectors of the economy by using thefollowing hypothesis.

First, in our theoretical hypothesis, technical progress in terms of TFP is assumed to be accounted
for by three factors: (a) exogenous factor or non-price factor based on remarkable productinnovation or revolutionary scientific technology and vintage of capital stock which can affecttechnical progress irrespective of the price changes, (b) net output price factor, which is negatively
or positively related to technical progress, depending on the degree of market competition, and (c)biased price factor in favor of saving a specific factor (or input) per unit of output. Besides thesethree factors, R&D expenses, which are increasingly important in Japan, are not explicitly
included in our formula, because of the lack in database consistency. But they are implicitly

6See C. Freeman et al. [4].
7See S. Shishido et al., [7] and [9].
8See H.P. Binswanger and V.W. Ruttan [3], D.W.J Jorgenson and B.N. Fraumeni [5], and H. Wago [11].

Induced Technical Progress and Structural Adjustment

5

involved in our model, as mentioned later. As the database becomes more consistent, it is to be
directly included in our formula in the near future.

As easily noticed, factors (a) and (b) are well known, neutral technical progress in the Hicksian
sense, but factor (b) needs to be further explained. Here, net output price is defined asp*//?*, theratio of output price (px) to total unit cost (pz). In the case of perfect competition with no profit,
pzZ=pxXholds, where Z is total input, and A"output, both in real terms, and TFP = X/Z, or
r. In usual cases with a highly competitive market, the decrease in net output price due to thedecline in output price or increase in factor prices (e.g. wage rate, capital cost, etc.), tends to exert
a strong pressure to technical advancement or cost reduction, thus accelerating technical progress.
In other words, as the market becomes more restrictive due to some entry barriers, there is a
growing tendency where the parameter of this factor (b) nears zero or even turns negative, as
discussed later.

In factor (c), a biasedness in technical progress has been discussed by many economists, as inrobotics for labor saving, softwares for capital and energy saving, etc.
Considering these three factors, our TFP function was estimated using the following formula.

In TFP = c + X In (px/pz) + a In (w/pk) + 0 In (pr/Pk) yiv + y2t(1)

where pk = user cost of capital, w = wage rate, pr = input price of intermediate input (including
energy), v = vintage factor, £ = time.

The sign conditions of this equation are: \<0 for competitive sector, X>0 for non-competitive

sector, a^O, ]3^0, 71 >0 and 72 >0. In context to our theoretical hypothesis, 71 and 72 relate tofactor (a), non-price neutral factor; X relates to factor (b), neutral price factor; and a and /3 imply

factor (c), factor price indicating biasedness. Since a homogeneity constraint of degree zero is
imposed on factor (c), the parameter of pk is implied to be -{a + 13).
In the following, we first take up the meaning of parameters and in the context to biased
technical progress and later discuss X.
With respect to the property of the production function underlying these parameters, we impose
no restrictions in our model such as those in Cobb-Douglas, CES, or Translog, except the

restriction of homogeneity of degree zero for demand elasticity of factor price, as mentioned
above. This implies that we are assuming a fairly flexible and generalized formula of a nonhomothetic type in our production function. The technical progress function in equation (1),therefore, is derived from the following unit factor demand function based on such generalformula of the production function. Unit factor demand (Fi/X) for a specific factor in the

Leontief mode thus is made dependent on factor prices (/?,) and time trend (t) as shown below.
(In our empirical expression, Fi = K,L,R. pj = w, pk, pr, as in equation (1).)

jp/?i, ln/72, ...\npn, t)

df/dlnPj = ej

?e' = °

(2)
(3)

(U = 1. 2.....I.)(4)

Considering business behavior in the real world, the demand elasticity for many factors e//, i.e.

demand elasticity of a factor / with respect to a factor pricey, is preferably assumed to be affectedby two aspects: (a) short-term factor adjustment efj, and (b) long-term factor adjustment withbiased technical progress efj. (See Appendix for detail.) While the former relates to current
production, the later relates to strategic costs, such as R&D expenditures, investment adjustment

6

Journal of Applied Input-Output Analysis, Vol.1, No.l, 1992

costs, overhead expenses, etc., which are more or less based on long-term management strategy

at the head office level. In aggregating equation (2) to obtain total unit factor cost or an inverseof TFP, it is convenient to assume a symmetry condition of the rate of substitution au for efj anda non-symmetry one for efj. This implies that for short-term factor adjustment weighted verticalaggregation of efj gives zero value for each factor price, as shown below.

24 = 0(5)j°l = aft(6)

el = coM(7)S«M = 0(8)

where o)t denotes cost share of factor /.

Accordingly, equation (7) indicates that, as far as efj is concerned, there is no reason to expectthat total unit factor cost, l/rs (= S uf In Ff/X) is dependent on relative factor prices,
although in current production each factor input is likely to be adjusted in response to relative factor
price changes in the short-term.

For long term business decisions, as shown below, a weighted vertical aggregation of efj provides
no-zero values for technical progress rL in the absence of a symmetry condition as in the
short-term.

S4 = 0(9)

S u^u * °0°)-In/ = SakJlnpy+XJttfa,1-/(11)

Ilirning back to equation (1), the TFP function, it now becomes clear that the factor priceparameters a, /?, exactly correspond to 2 wfe,y, implying the long-term responsiveness to relative
factor prices in business decisions for technical progress.

Next, we modify the above model in order to dynamize its adjustment process under a more
realistic assumption. This is an attempt to introduce parameters X, 71 and y2 into equation (1).
The neutral price factor, X, is of great importance as it can identify the competitive condition ofa specific sector of the economy according to X -^- 0. As shown in Figure 2, highly competitive sectors
tend to indicate a negative value for X, while oligopolistic or protected sectors show a positive value.

Since 1/TFP, or total unit cost, can be regarded as an average cost (AC) at given factor prices,
a competitive industry tends to reduce AC by adopting new technology or improving the production
process, when the market price of its output falls for some reasop or other, e.g. new entry of foreigncompetitors or decline of domestic demand, etc. The equilibrium point then moves from P to Q andboth output and TFP increase correspondingly, as shown in Case A in Figure 2.

Less competitive, oligopolistic or protected sectors tend to adjust their output in the face of thefall in market price, still keeping their high profit. The equilibrium point moves from P to Q withhigher AC or 1/TFP, as shown in Case B. This behavior of a downward adjustment of output will
be continued until the output price reaches the level of A, the lowest point of the AC curve. Since
R&D expenses also depend on profit in these types of industries, the fall of output price tends todiscourage their effort to improve technology. Schumpeterian hypothesis (Mark II) holds exactlyInduced Technical Progress and Structural Adjustment

7

B. Non Competitive Market Case

A. Competitive Market Case

AC

'>V\

MC

j^kj-Q.

AC

/

-

D
>v

\

X
\
X
v

MR

•D'

'MR
X

Figure 2 Cost-Price Relationin this case,9 since the price increase with higher profit encourage R&D efforts, enabling a
reduction in AC of 1/TFR If the expected maximum profit is sufficient, the sector attempts not
only to expand its output, but also to move the AC and MC curves downward by accelerating its

technical progress.
Second, a modification of the neutral factor in technical progress function is made in the context
of 71 and 72 of equation (1). 71 represents vintage factor of capital stock which is approximatedby the ratio of business investment to capital stock during the past several years. In a sense thisfactor could be regarded as factor augmentation for capital input accompanied by a long time lag.

72, therefore, is a pure non-price parameter of time, representing an innovation of revolutionary
technology, invention of a new product, TQC and management improvement, etc., as noted
earlier.

5. Empirical Results on Induced Technical Progress
For empirical implementation of the theoretical model in the previous section, we made aregression analysis of sectoral TFP on the basis of annual data developed for our multi-sector
model, JLM Gl, for the sample period of 1970 through 1983.
As summarized in Table 1 the result of the regression analysis relates to 58 sectors, covering

almost all sectors of the economy on a 64 sectoral basis. (See Table 2 for further details.) Regarding
the sign of X, competitive position, more than half of the sectors indicate negative signs, suggestingthat competitive sectors exceed non-competitive sectors in number. The secondary sector, i.e.

manufacturing industry, dominantly shows negative signs implying that about two-thirds of this
sector is highly competitive because of its heavy dependence on the international market.
Particularly noticeable is the concentration of negative signs in high technology sectors and lightmanufacturing sectors which are now under keen competition with the Asian NIES. Generalmachineries, electronics, automobiles, other transport equipment (mostly shipbuilding), textiles,

and apparels are typical examples. Less competitive or oligopolistic sectors show positive signs as
usually expected. They are mostly primary sectors, and hlaf of the tertiary sectors, such as
9See J.A. Schumpeter [6].

8

Journal of Applied Input-Output Analysis, Vol.1, No.l, 1992

Table 1 TFP Functions: Parameters with Positive or Negative Values
in Terms of the Number of Sectors
X(sign)

+

(3

a

0

+

0

+

3
27

Primary

7

1

1

5

3

1

Secondary

10

22

2

17

17

0

Tertiary
Total

1-ot-jS
0

+

4

2

5

6

1

10

71

72

0

+

+

3

1

5

2

23

1

7

13

7

7

1

3

7

5

12

2

1

4

11

0

7

5

24

30

4

25

27

6

42

12

4

19

37

2

19

20

Note: In TFP = a + X In -A- + a In o> + (3 In pr + (1-a-jS) In pk + y^v + y2\

construction, public utilities, finance and other services.

Regarding parameters a, j8, and l-a-/3, biased responses factors in technical progress, the results
show significantly positive signs for /?, relating to material price (including energy price), and strong
negative signs for (l-a-/3), the capital cost. Sectors with positive signs for a, the response parameterof wage rate, account for only about fifty percent. The a's positive signs, however, are dominant
in the primary sectors and high technology sectors, while an opposite tendency is observed in thetertiary sectors. Exceptionally, the positive signs of l-a-0, the capital cost, are indicated for capitalintensive industries such as mining, beverage and tobacco, oil refineries, iron and steel, electric
power, and railway transportation. This is highly in accordance with the factor intensity based on
their technology.

Non-price neutral factors, 71 and 72, also turn out to be significant, but their numbers are rather
limited, about one-third of the total, respectively. Vintage effects 71 are indicated in rather slow
growing sectors and some of them are not highly significant as shown in Table 2. This probably
represents the fact that fast growing or high technology oriented sectors tend to always maintainyoung vintage capital stock employing new technology because of their rapid pace of investment.

It is also because technical progress in these sectors tends to depend more on R&D rather than on
the vintage effect.
With respect to X2, purely neutral factor for technical progress, rapid rates of increase of about

3 to 6% are indicated for high technology sectors, trade, and finance, while a modest growth of
1 to 3% is observed for some of the food processing, textiles, apparels, etc. While 72 is limited in
number, it should be emphasized that its impact on the entire economy becomes increasingly
important in view of their growing share in Japan's economy.
Table 3 focuses on manufacturing sectors, distinguishing three types: (1) high technology(machineries and chemicals), (2) capital-intensive (iron and steel, non-ferrous metals, coal andpetroleum products, and cement) and (3) others. In summary, the high technology sectors' TFP ishighly competitive, labor and material saving, and capital using. Capital-intensive sectors show arather reversed tendency, although parameter signs are mixed. They are characterized as lesscompetitive and capital saving. Other sectors indicate a similar pattern to high technology sectors,
but parameter signs are weaker.

Finally, in the context of the conventional Leontief type analysis of direct and indirect dependence
on primary factors, parameter can be further broken down into primary factor parameters of wage

rate, capital cost and import price under the homogeneity constraint as noted before. This meansthat on a primary factor price basis TFP =/* (w, pki pm), where pm is import price of raw materials

and fuels. Although not explicitly estimated, it can be safely stated that, as far as biasedness isconcerned, Japan's technical progress as a whole is characterized as labor and import saving, andcapital using. This conclusion suggests two important macroeconomic policy implications:
1) Relatively lower capital cost through monetary or tax incentives will accelerate technicalTable 2 TFP Functions
J3

SECTOR

C

1.

-2.60

(3 7)

(9)

2.

-1.76

.39

-.02

4.

-22.94

.67

.07

5.

.57

6.

1.34

7.

-3.76

6.

-1.35

9.

-3.68

12.

-32.4515.

-41.83

16.

-1.89

17.

4.95

18.

-83.2119.

-37.3420.

-19.1821.

-47.0222.

-18.64

28.

-1.13

29.

-.92

30.

-.82

31.

-.26

32.

3.27

33.

-4.47

-.23

(-4.8)(2.0)
t-1(:i5!)(ii??).16(2.7)-1. 16

.03

.31

1.83

35.

-4. 02

.25

.59

2.16

36.

-1. 52

-.20

.18

.78

1.95

37.

3. 16

.52

.89

1.28

38.

95

dffc

(--*ff)

.71

1.60

39.

41

-.29

.06

.23

.95

2.39

40.

-24. 03

-.48

.98

2.45

41.

-58. 68(if!)1"1 (3°!)
(i°?)

.68

1.66

42.

1. 29

(3°J,

(:321)-f-81(:4°42)(-i2!)

2.78

.94

2.06

.43

0.38

45.

-114. 25

-.28

.76

2.14

46.

-4. 28

.25

.38

2.05

47.

-3. 53

(iff)

.47

0.46

48.

-1. 11

.64

1.91

49.

-43. 20

(iff)

.72

2.44

50.

10. 10

.85

1.93

51.

33

.58

1.81

52.

-2. 29

-.52

t-1

.01

(ifl)

-.22

(ill)

-.02

-.15

(ifl)
(i?o)

.03

( .3)

(:6 lh

2. 08

43.
44.

-49. 80

-.13

.31

1.45

53.

-51. 47

-.23

.70

1.91

54.

-7. 17-.16(-'if?)-.19

1 (if!)

.15
-.66

.81

1.98

55.

4. 19

.90

2.54

56.

6. 94

.57

1.84

57.

-24. 58

.94

1.82

58.

-1. 40

.77

-.13

<■;»

-.45

1.51

.98

1.52

60.

1.04

63.

1.09
1.06

(i!o)

.32

.90

.23

-.39

.94

-4. 31

59.

.55

0

c-s*!)1"1 (:i°6)M.44 t-1
(3.2)

(4?l)

-.12

(iff)
(-4")
(iff)
(ifj)
(ifl)
(-'">
<:i?i>1"1 (323)1"' (--iff)1"(IS,(-1?5)(ifl)(:i13-)

(if?)

.33

(:i24°)(" -9)(4.1)

t-2(1-QT-/9).59(-1.0)(- .6)-.84(-1.5)-.41(-2.3)

TIME DUMMY

.36

.12

-.33

(-V?i)
-.31

t-1

V

.39

c!i)

-.54

-10.0327.

Is!?)(-2.9)
.07

-4.30

26.

(iff)1-1-.66^
1.32 t-1(-4.8)
(6*4)

1.59

34.

0

(:3368)

J.33^

3.23
25.

(15*3)

(266)

12.84

23.

(ill)

(2 .0)(~-i")(-2.8)SECTOR

1.72

-.39

.07

.18

(1.4)

-1.18

D.W.

.60

t-%

(iV- ("-32.5)• 85(*652)
5^5)-29.70

14.

R2

-.08

( .6)

(3.5)

-38.9213.

(l-or£)-117. 45-. 004(2?f)(3?!)1"1 (iff)

(338)

t-1
t-1

(3.%
("ifi)1"1
-.50

t-1

"(iff)1'1(Vl)1'1 (iff)

R2

D.W.

-.43

.79

1.06

.14

.69

1.75

.18

.62

1.08

.40

.90

2.47

-.32

.89

1.97

-.29

.89

2.41

(-1.8)

(1.8)

(4.0)

(:i!I)

(3?8)

-.09

-1.41

(256*)(16%(146)(i?3°)(i!i)(4* 26)t-1(:3?f)
(-7 %
&%

-.09

(-3.4)(- .7)-.72(-3 45)

(if!)
(293)

(i79)
(2!!)
(1.4)

.06

.93

0.58

-.21

(5?))

(4.1)

(l")

."96

2.27

.72

1.59

.86

2.69

.73

2.06

.25

.87

2.02

.25

.92

1.90

(4 23?)

-.27

(7°3)

-.38

-.14

.20

-.11

(#19)

.31

-.01

(

.07

.8)

t-1
.02

(2.2)

(i1?)1"2(4°3)(32!)1"2 (?°5
.20

(3.6)

t-2

(2?l)

.74

1.S4

.90

2.13

.90

1.82

.82

1.43

.93

1.87

.82

2.23

(2?0)
(-*°4)

-.32

.51

0.80

-.90

.27

1.10

.93

1.97

o!i)

.02

.71

0.75

-.14

(3H2)

(-32.7)

.54

1.48

-.09

-.05

(?4)

(- .8)

(9.7)

.66

34

(4.3)

. 03

.03

-.19

(2*0)

(4?i)

-.59

-.38

(3.1)

-.59 t-1

-.06

1.18

t-1

(-5 %1"1 (i!o)
-.41

0.98

.97

(i1?)

-.13

j 53

.60

-.61

-.30

(-1.4)

t-I

-.70

.16
(2.0)

\&

.44

1.72
2.65

t-1

-jijt-i (1%
t-1
(V?)
C'b
(ifo3)(i?l)1"1(-'°8)
(i7?)
(l.D

.96
.99

.14

(3.6)

(-1.3)

TIME DUMMY

.23

lill
-.22

V

(^S)1"2(3"l)1"2 (6?36)(i?6°)1"2

1 General crops

2. Industrial crops

7 Coal mining

8 Iron ores

14 Grain products

textiles

20 Chemical textiles

paper

26 Printing and publishingchemicals31

3. Livestock for textiles

9 Nonferrous metallic ores
21

Petroleum products

4 Other livestock and service

10 Crude petroleum

15 Manufactured sea loods
Other textiles

22 Wearing apparel

27. Leather products

32 Coal products

11

16 Other foods

6 Fisheries

12 Other minings

18 Tabacco

23 Wood and wood products

28 Rubber products

33 Cement

5. Forestry

Natural gas

17 Beverages

24 Furniture

29 Basic and intermediate chemicals

34 Other ceramics

35 iron products

and forgmgs
13 Meat and

19 Natural

41

37 Aluminium (including secondary)Electrical machinery

42 Automobiles

38 Other non-ferrous products

43 Aircraft

47 Housing construction

25 Pulp andconstruction

51. Electric power

52 Gas30 Final

56 Railways

57 Trucks and buses

36 Rollings, casting

services

48 Industrial construction

53 Water and sanitary service

58 Other transportation

62 Public services 63 Other services

39 Metal products

44. Other transport equipment

46 Miscellaneous manufacturing

64 Unallocated40 Machinery

45 Instruments and related products
49 Public construction

54 Wolesale and retail trade

59 Communications

a.
in

E

(2.8)

Sectoral Classification Japandairy products

C

50 Other

55 Real estate

60 Finance and insurance

61 Government

10

Journal of Applied Input-Output Analysis, Vol.1, No.l, 1992

Table 3 Technical Progress in Manufacturing Sectors
in Terms of Parameters of TFP Functions

Xa

1. High technology-+

2. Capital intensive±+

3. Others

0

1-a-jS±

Note: See Note in Table 1 ( + ) denotes weakly positive.

progress of the economy as a whole; and 2) Material saving tendency in our study seems tp strongly

suggest a remarkable performance in energy saving, especially that of crude oil. The tendency will
have to be further strengthened in view of global considerations on energy and environment.
6. Simulation Analysis on Import Promotion and Increased Leisure
The new version of our multi-sectoral model (JLM Gl) incorporating endogenized TFP functions,as discussed above, has been used for various alternative scenario analyses. In the following we
present two important scenarios to evaluate the impacts of (a) import liberalization and (b)increased leisure in the context of sectoral technical progress, output, employment and prices aswell as macroeconomic growth alternatives including GNP, the current account balance, the rateof inflation, etc.

Before discussing alternative forecasts, we shall briefly describe the results of baseline forecast.

In order to evaluate normal growth patterns, the model was simulated for the period 1990 to 1995
on the assumption that exogenous variables tend to grow along each trend in recent years, as

shown in Table 4. World trade was assumed to grow around 4% and exchange rates to graduallyrise from ¥150 in 1990 to ¥133 in 1995 in terms of the yen against the dollar. Regarding macro-economic policy, fiscal expenditures such as public consumption and investment were assumed to
grow on the normal trend, about 3.1% and 4.7% respectively. In light of the recent Structural
Impediments Initiative Talk between Japan and the United States, the growth for public
investment is fairly modest. The discount rate of the Bank of Japan was assumed to continue atthe recent level. Despite recent new developments, the oil price was assumed to grow modestly.

Table 4 Exogenous Variables (Base Line Forecast)Rate of change (%)
1990

1991

1992

1993

1994

1995

1. World trade (/Ww)
2. World import price (Pmw, $)

5.3

4.0

3.9

3.8

3.7

3.6

2.0

2.0

2.0

2.0

2.0

2.0

3. Crude oil (Pmio, $)

11.6

-0.8

0.5

0.4

0.4

0.3

4. Exchange rate index (REX)*

5.

do.

(Y/$)*

2.39
150.0

2.47

2.52

145.0

142.0

2.58
139.0

2.63

2.69

136.0

133.0

6. Government investment (/g65)

7.4

4.7

4.7

4.7

4.6

4.6

7. Government consumption (Cg)

-0.3

3.1

3.1

3.1

3.1

3.1

8. Official discount rate (IN)*

5.16

5.25

5.25

5.25

5.25

5.25

9. Corporate tax rate (/V)*

0.49

0.47

0.45

0.43

0.43

0.43

* denotes level.

Table 5 Macroeconomic Variables (Base Line Forecast)

as

1989

1990

—

.iapam

1991

XCHG

MnnPi

XCHG

f

1992

si

XCHG
A.7

REAL

PE3S

Z3HS

3.0

DEFL

Z.3

-WHOLES AL£_aitXC£
LA30* FO*CE

0.1

RATE

US

2.88902.4

3.0369

I A-B-X..0235-

50.416-12.2

51.791

5.4

56.014_nX4.3-45._
54.0202.9578_aA.M.t

CBP

3FOOL
3G

D R2.LUS

WAGE

RATE

57.450

W

2.7
11.1

5CHG

1994

125..63

9.5.. 8 3°.

1.9
0 ..7

137.139.7.. 231

.1. 3_
5.6
2...4_
2.7
1. 5__

6530.40.2

1.3

133.5155.205_0.56514.50.0

3.1286_L-.023B
52.6431263JL.. —D...4

3.0

3.2337DL.O.
-6.0.1.01.4.

-A-4-U17T.

•0.2

6541.0L2.6JJ... _0...3.
2.3

1.27.0.3..
3.41442.7_=0...Z
21.5

7...02S.2
78.623

0 . 4 _.
12.5__0 . 6
3.1

=1563.4..
61.741
t..25.4.4

3.1
O..l_

57.5174 ^ ?7no-GA3SS—NATTDMALCOMS-SONPROFITFXP-£f<DlXURr

1989

1990

19^4Q?T?nniii.

CNP

2560.62636.1

I?

75369.

81199.

XCHG

^Y

XCHG

1993

2317.7

4.9

1994
23 67.43 .

ft. 0_

3100.64.93252.5

4.9

INVT-SOVSRNMENT

3UI1CV

4.6.4.1_ _6182.3_

305.900.0305.900.0305.900.0305.900.0

Q.Qppnn.nnnn0.+A

0-DQ0jQ

0..O.

L..0

0 -.0 0 0 0

0 m 0_

66376.
74203.
-JL07.40.__7.Z363-

11.8
10.1

79492.
B465-7-*

7.1
8.J.

5.5

94568.

8.9

100399.

3.5

95243

4.6_

99871.

XCHG
.3

1994

1995

3X6033337566.

CNP OS

IPOS__L3ycs-3FSTnF<mXHDS?s* 2_4-._25A3-4-

INVES-GOVERNM.ST

IGOS

25560.

28745.

.8X84-—X0.6_
31369.
9.1-30XXS-33485.

6.4

5.0XX0.
102486.

6-3

3OSX6-.

2.8

3 2.450._6.735464.

7.9
3.0_

72671.
_6.4_828 .

2.9
4.. .40.0000EOS

70605.
2X15.

O.JDOOO.

4571.253003.
112648.
3.4322.
39828.

5.9

37501.

2-2

3335..S

2Z.5.4.4 6*3.. 00.0
327.00-0 .000 O_ _O..O
4.3
75323.

327.000.0

O..OOO.Q__0.0

327.000.000067_46 6 ... _4.1

7.0813._6.4_5.085335.
7.4511-80684.

General Footnote to Table 5

GNP and its components are in either current billion yen or 1980 billion yen. Demographic variables(NL,N) are in ten thousand people. Unemployment rate and interest rate are in %. Current accountbalance (CBP) is in billion US dollars. Wage rate is in 100 thousand yen per year.
Total factor productivity (TQ)
logarithm.

305.90

7.4
_4.3
5.7

4296.2

5.8^
5.3

O...O_

0.0

6.4

95434.

0.0^0 • 0327.004037.8

4J43X.

6.4

327.00n- jo Q0D

JGOS

1993

6.5

4A

in

34116.

31170.
.435.9-;

XCHG

4.0_
4.9

354.92.

23446.
4.7
2.736. 6—33 ..4.

GROSS -NAXIONAL EXPFNOU.URE. aY-CAT.£CORY_(.CURR-YJXCHG
1990
XCHG
1991
1992
1939
L63.46L
122901
3566.63352.16.43150.53794.9•XQL.1 1 421J.36*3_ __4.4B35.
73692.
85190.
8.0
70086.
90663.

XCHG

107999.

27162.
7.4
L452-2~=35 . 1

INVESTHENT-3USN

MPT

1995

246159.
3411.925289.
_223X.D
305.90

CONS-MOMPROFIT

2_. 8__.29-209._6525..

INVES-GOVERNMNT_IJ4 VE-S LOR Y^2A I V.T-

is an index

XCHG

4.0

93117.

_I.MVESnA£SXI)£.MXl_

INVT-SOVERNMENT

XCHG.7.6X5 .
32333.,_CaSS=30V.£RNM£-HXINVESTMEST-BJSN

P.. 2_CATFGORJL-L

1991

4..6_—2JQ.965 L-

4.9

XCHG

463902.

9.4..J_47.
6511.7

-0.3

1995

1 .5

415331.

20.. 33.
131.02

XCHG

5.3

5...6_53J_035.
4.6439265.
1-5122...65.

397054.
_XXS..JO3
128.72.O^St
UNEMPLOY1993
S 23A6.2.

i
3

4.9

I

XCHG
6.8_
6.4
5.8_

9.9
5.8_
6.2
13 . .4_
0.0
0.0_.

5.8
5.2_.

3

|

I

E

12

Journal of Applied Input-Output Analysis, Vol.1, No.l, 1992

Table 6 Output for Selected Sectors(Base Line)(1980 Bil Y)

1990

1995

(0/0)

1. General crops

7,986

7,304

-1.8

5. Forestry

1,412

1,232

-2.7

13. Meat and dairy products

5,392

6,441

3.6

15. Manufactured seafood

2,939

3,302

2.4

21. Other textiles

6,855

8,073

3.3

30. Final chemicals

9,871

13,8487.0

21,891

27,210

4.4

31. Petroleum products

36. Steel

16,21917,241

1.2

40. General machinery

35,95953,0838.1

41. Electrical machinery

55,62587,220

9.4

42. Automobiles

25,39836,577

7.6

47. Housing construction

20,803

26,7485.2

5.2

51. Electric power

11,126

14,36054. Wholesale & retail trade

71,58997,147

6.3

57. Road transportation

10,825

12,5683.0

63. Other services

55,86364,7183.0

Total

721,536

930,608

5.2

As shown in Table 5, Japan's economy in this base line forecast grows at 4.4 to 5.8% during 1990
and 1995. The growth rate seems to be fairly normal in view of the recent performance of 4.6 to

5.7% during 1987 and 1989. The index of GNP deflator tends to increase gradually at 1.9 to 2.4%
but is relatively stable by the international standard. The current account balance, however, tends
to grow again after a small decline in 1989 and 1990. This is rather against recent growing optimism

on this variable, although it is likely to be overvalued if the recent rising tendency by foreign direct
investment is fully taken into account. The adjusted amount, nevertheless, would be rather limited,since there are some indications that the foreign direct investment has already hit its peak in 1989.
Population and labor force estimates for the coming six years are 0.5 to 0.2% and 0.3% respectively.
This deceleration in the demographic growth rate is a recent feature mostly due to the fast pace of
aging of population. This tendency provides a basis for our second scenario on increased leisure.

As for the sectoral level, Table 6 indicates changes in output only for selected sectors. In response
to macroeconomic growth, structural changes in output level are particularly noticeable for final
chemicals, general machinery, electrical machinery, and automobiles. Most of the other sectors,

representing each industry, shows a 4 to 6% of growth, which is near the average growth rate of

5.2%. A fairly stagnant growth is observed for textiles, food processing, steel and road transportation, while negative growth is noticeable for general crops and forestry.

Regarding TFP of the selected sectors in Table 7, electrical machinery shows the highest rate of
2.9%, while other sectors, such as general machinery, wholesale and retail trade, also indicate therelatively higher rate of growth of technology. General crops in agriculture also shows a higher rateof 1.8%, which, however, is based on heavy agricultural price support of the government.

6.1. Impacts of Import Promotion10
The Japanese current account, though having declined slightly in 1989 and 1990, still continues
to have a huge surplus and it is likely to grow again according to our base line forecast, as noted
before.

10For manufacturing sectors based on different assumptions, see S. Shishido and O. Nakamura [8], and for details on
automobiles, see S. Shishido [10].

Induced Technical Progress and Structural Adjustment

13

Table 7 TFP for Selected Sectors(Base line)
1990

1995

1. General crops

.7266

.7954

1.8

5. Forestry

.9889

.9619

-0.6

13. Meat and dairy products

1.02171.0551

0.6

15. Manufactured seafood

1.10901.1815

1.3

21. Other textiles

.7366

.7741

1.0

30. Final chemicals

1.3713

1.4635

1.3

31. Petroleum products

1.1212

1.0935-0.5

36. Steel

1.34581.36430.3

40. General machinery

1.1976

1.31191.8

41. Electrical machinery

1.30811.51092.9

42. Automobiles

1.1085

1.11390.1

47. Housing construction

1.13901.1688

0.5

.6358

.6137

-0.7

54. Wholesale & retail trade1.2932

1.4037

1.7

57. Road transportation

1.07501.1358

1.1

.8245

.7752

-1.2

51. Electric power

63. Other service(0/0)

In order to reduce it and to eliminate international frictions we need an alternative policy
scenario aiming at highly dynamic fiscal, trade and structural policies. Here we assume a combined

policy of (a) substantial import promotion of foods and manufacturings, (b) domestic demand
promotion by active fiscal policy, especially through public investment, and (c) price reduction in
the distribution system through deregulation and government guidance.

Regarding import promotion, we temporarily assume a more than 50% cut of current accountsurplus, i.e. about $35 billion reduction by 1992. In nominal terms of the yen this amounts toapproximately ¥5 trillion, or a 15% increase in the 1989 imports. The breakdown of this additional
increase are food imports amounting to 5% and 10% of domestic production of agricultural foodand processed food, respectively, and a 35% increase in manufacturing imports.11 In accordancewith this adjustment, the constant terms of import function were shifted upward. The increased

amounts are sustained until 1995.
Public investment is assumed to be boosted additionally by 2.4% of GNP, about ¥9 trillion

annually in 1980 prices. This aims to not only offset deflationary impacts of import liberalizationfrom a macroeconomic point of view, but also to minimize social frictions due to structuraladjustments caused by imports. Accordingly, it also covers various capital expenditures on
retraining and vocational facilities to enhance the mobility of employment and to encourageregional development for promoting employment in rural areas.12

The third policy measure concerns the government's price reduction in the distribution system
to eliminatte differentials between domestic and imported products. Since it is difficult to quantify
the amount of the direct policy impact, we temporarily assume that the constant terms of sectoral

output price equations are reduced by 5% for food and 3% for non-food manufactured products.
The result of our combined policy package is shown in Table 8 for macroeconomic anddemographic variables. Real GNP is shown to increase by 1.1% in 1990 and 3.4 to 3.8 during 1991

"Sectors selected for import promotion are 1, 13, 14, 15, 16, 17, 18, 21, 22, 24, 27, 30, 35, 36, 40, 41, 42, 43, 44, 45, and46. (For Sector Numbers see Table 2.)l2In the context of the Structural Impediments Initiativese Talk, the U.S. government also urged Japan to adopt a similar
policy measure to promote imports and social infrastructure. But the amount suggested was modest, as compared withthis simulation.

Table 8 Import Promotion Scenario: Macroeconomic Variables_SELECIED_£CONOMIi:_lNDlCA.tORS_==._JAPAN .MDDELt .VERSION ..Gl_
1989
mati

REAL
flMP

1990

SUE

CONS

DEFL

_WHOLESALE.-PJUCE-

LABOR

1991

FORCE

4055.

1.1

=3^310-3.043=2.9-2.5=3.135-0.129=3.4
0.0

pnPIII ATTOMUNEMPLOr
RAMK

RATE

I PSnn0.0000-0.0202n.nnnn

-n-

BFDOL

RATE

-19.10-37.9

0.

12865.
=.4.569-4.232

3.4
-J.9

1992

1.JL
3.7

=3.623—=3.fl-3.4=3.32.1—.=4.1

XCHG__5.43.1.
14811.

1993

15824.

XCHG

3.3-?-aa7=2.

-4.084-3.2-3.725-2.8-3.407-2.

_=3.20362.520=3.4
1.0_=2.95 3=3=3.429

=3.6

1.855

0.0

47.2150.7

i7.q?nn-ii7-fl^7

n.i-0.0757-2.5-0.1128-3.6-0.1327-4.1=.0.125.0=1..8=0..0J3.6=Q.2_

D.D.40J.

I-30.53=38.9.6.

-54.5
S9-9

-33.18»B491 ,

-63.0
53.. 8_-36.31-64.0

61.246I

0.9_2J.. o&a

n.7

-0.1324-4.0-0.1267-3.7

1.032.0.
0..5-41.10 -53.8

0.0210-44.14

-56.1

33.ii
-0.8

5JL.1.

0.0000=-4J16JD.
-0.3975^3253.

W-0.4528-0.8-0.1687-0.3

0.13590.2:r.8.19_2_,
0.4266

5.0..30.7

H3.15J?,
0.6557TO

n.nnnnn.nnnu

n.o

n.nnn

o.n

~q«ooq7o.q

0.00110.0

0.00120.0

0.0009CanSS

NATTflMAI

1989
CONS-NONPROFIT

-0.7

0.00

-B.G

t;n\/T

WAS6

US

3ATP

CBP

XCHG
0.2

HCPI ATHR

PERS

XCHG

«pm

PXPFMnTTIIRP

1990

RY

C ATPCORV, t flO

Y >

%CHG

1992

%CHG

0 «.o

ftu.s

n.4

CNP

0.00000.00000.0

rr.

n.nnnnn.nnnn

n.n

XCHG

1993

XCHG
2-8

1994

XCHG

1995

7499 .1\.2

0.0

0.00000.0

0.00000.0

0.00000.0

0.0000l._4

45JL3...

2.2

0.00000.0

0.00000.0

0.0000n.nnnnn.no.onoo0.0

0.0000

0

0.3

3
XCHG

ft3J£jo

1937

INVESTMENT-BUSN
TMtfp^-gp^Tn EM T.L

32*1

INVES-GOVERNMNT

INVT-30VERNHENTEXPORTSmattonai

1989
0.0000

XCHG

0.00000.0-4i7_n-i^i-1183.

-1.5

CONS-MONPROFITCONS-S aVERMMEN tCNPOSINVESTMENT-BUSS

IPOS

INVES-SOVERNMNT

_1HOS
IGDS

0.0

n.o

4428.2
v?n. ft

JGOS

0.00000.00000.0n\ NK4nr>

nTnnnnn.nnnnQ..Q

0.

-1046.

I »fVgs|fng v-pg j yT

INVT-GOVERNMENTEXPORTSEDS
dOS

See general

4 7.3

10.6 2. 0.

0.0

0.0000.A.OJDOJQ

Q...Q

O.QOOO

0.0

0.00301118.6_4X11.3

1.4
5.6

1561.6
j663 11.9

997.7

BY CAIEGORY—t CURfiLJTJ
1991
XCHG
1992

PxPPM

1990

9137.012 • 00.0000-7.Q-7B17.

-1.0

-304.

-0.1

1994
1690.

XCHG
0.5

0.00000.0

0.00000.0

0.00000.0

0.0000

0.0

-S

-0.8

-1*9.5

-0.3

-711.

-0.8

20.
_3 771.1

0.0
10.9

1543.
3094.89469.2468.3
0.00000.0000
94.

1.6
10.0
26.7
14.6
0.0
0.0
O.I

1951.3

6.3-

XCHG

9050.028.8

9160.1

27.4

Iflii.749.4

0.00000.0

B9S.1
0.00000.0-1.6-0..0000
-731.

0•0
-1.0

Q...Q.OQO
372.

JL.XL
0.5

0.D_^_Lfl2O^_3-.2-363!6 -h

6 . tt50 82,

15. V7

footnote at the end of Table

5.

1.1

-S74&.

1993

XCHG

1597.
2_74A*P
9721.5336.9
0.00000.0000
-332.

1995

XCHG

2796.

0.8

0.0000

0.0

0.1

189.8

0.4

1.6
g.._5
25.9
8.6

1850.
ZidtUl9950.4327.0
0.00000.0000
-340.

1.6
7.1
25.0
7.3
0.0
P_._Q_
-0.4

0.0
0.0
-0.4

>

I.

Induced Technical Progress and Structural Adjustment75

to 1993 and 3.5% for the last two years. In terms of the change in the rate of growth, the growthrate accelerates 1.1, 2.3, 0.3, 0.1% each year during 1990 to 1993 and slightly decelerates by 0.3%

in 1994. Except for 1991, the growth rate of real GNP stands at about 5.0 to 5.5%, which is notunrealistic in terms of recent performances. The exceptional 7% growth in 1991 represents an

initial shock of our policy package mostly due to a rise in public investment. The increased imports
exert a contractionary impact on the economy, since they rapidly grow until the third year, andstay at the same level until 1995. Surprisingly, exports also start to rise because of the fall in prices.

The current account balance, the most important target of this simulation, falls rapidly by $30 to$44 billion, as expected before. The average TFP at the macroeconomic level shows significantly
positive signs. Sectoral details are discussed later.
Table 9 Import Pronomion Scenario: Sectoral Output
1990

iCMG

iCHG

1992

1993

tCHG

0.0

XR02

1994

1995

SCHS

-583.10.000-3.123-3.6-1.726

-0.3

3.316

0.6

11.8900.00303.30000.0000OoO

n.nrtiin

2.1
0.0

XR04

0.3

-106.4-123.3-2.9-105.0-2.3

xaos

0. 3000-49.71o.o
0.0
0.3000-119.1-2.5-2.7
0.0 ..
3.0000.. _0.0 ....0.0000..
-58.76-2.3-53.66
-2.1

XR06

0.00

0.0000-62.29

n.oop

2-A19

1 .2

3.71 R

__0«0
-2.4

tarn

3.9

13.71*

5. 9

0.30000.0

13.5163.2

0*0000

n.n

-80.1

-1.7

0.0000. _o.o.. _.0.0000.
-42.63-1.8

IT-35924.7160.0000

4.3

-1.5
—1.6

0.0.

-73.9
.0.0000.

-1.6-42.84

7.7

9.513

4.1

15.879

6.5

0.3

XR08

0.0000O.OOOC0.0

0.0

0.00000.00300.0

0.00000.0

0.0030

0.3

XR09
XR10

0.00000.0000.
3.00000.0.. ..0.0000
0.0
0.00000.0.
0.0

0.0000__0.0__

0.00000.0

0.00000.0

0.00000.3

0.00000.00000.0

0.00000.0

0.00000.3.XR11

0.0000_.0.0000_0.0 ...-0.0000.

0.0_

0.0000 _. .0.0
264.1312.5

0.0000.
273.380.0_.o. 0000

0.0

0.0000_Q.3.....

13.1

261.9411.8

267.6611.*-384.7 -10.3-381.2-10.3-338.0-9.9

112.36-0.5
1.3._ ...139.. 91
52.2211.3

0.9-17.82-0.1

2.2_ 130.97

2.3

1.8

46.5851.6-3.1-121.5-12.52-U8__rl25.5_

XR120.00000.30

111.735.8

231.23

11.5

-3-1

Oall

0.0

-4-2

XR14

0.0

-165.2-4.3-292.1-7.5-359.5

-9.6

XR16

0.30

-44.77-0.3-27.83-0.2.1.2

164.21

1.3.-10.30.30

143. 50

2o7._ ._ 66.57

0.000

61.345

2.3

34.402

1.2-10.79

-2.8

XR22

-4.0
-15.440-0 _ __r 196.7-_j=3.1-233.3
0.0
-3.4

XR23

n-n

—262«d

r5.0..

XR24

0.00

104.51

2.6

XR17_._
XR18-70.30.112.69 . -1.9._._ 83.25
49.02036.7391.3*Q } 9

XR2O
XR21

0.00

r88.9 _-l »4-2.7-191.5. 166.9. .-.2.7..
167.994.0-15.05—112.4 _rl.7-177.6

-2.4

191-5

3.0

L83.47-12.61-3.9-13.31__rll4..7_-198.5

-3.2
-1.7
-2.7

-199.2-2.6-224.4

-2.3

65.6

1.0

59.6

0.8

32.6

4.5

197.454.0

193.73

0.4
3.9

2.1

224.15201.45

4.2

2.?
XR26

0.30

8.29

0.1

XR27

n.nn

XR28

0.00

rl3.39-90.06

-2.5
-3.7

XR29

0.0_

-112*0 . _-Q.7_

XR30

0.0

-111.4

vpt |

0«0

XR32
XR33

T-rOOQ

XR34

0.00

0.00

-l.l

148.1547-<*'»^
316.777.7

9.0-

102.13-1.3

1.5

111.71

1.3

108.191.2

118.291.2-2-R-18.02-3.3-18.68-3.4-17.62

-3.2

27.05

1.0

27.14
217.0.
-124.71.0-13.32-0.4-19.76-0.6

157 oO

0.9-175.8-1.6

157.937.9

335.98

4-7

A3-lfl>5-5

7.6

840.128.9

802.39315.3.

4.1.

2.3

5.9

1380.8.
1139.8

19.J

933.4

7.1

661.1.
1047.3n.nn-onnnO.O __iJ-a D.QQ 0

O.Q

o.nono656^6.

XR36

380.0

XR37

r\ _ noon

XR3S

0.30

34.56

1.2

325.66

XR39

0319-.0

"> ^7

RR2.7

0.7

2.1

124.56697.120.0— 1.3-15.275n.9nn

3.7

0.0—

264.9

0«4_

69.6.

-131.7
310-4

XA35

0

1.2

-12.18 ...^2.2..
-62.92
-2.3

-3.4

16.6

210.61

i.x

233.8

-1.0

-121.8l.l_

2.46.6.

l.l

-0.9

-95.4

-0.7

3.2

1001.83.7

10.2

207.849.2

232.299.6

7.0

62...620.

5.3

6.1..J74_

4.9

9.1

781.988.3

790.858.0

9.4

7_06..*_

9.4_.7.15. 6_

6.5

982.2

6.0

992.6

8.9
5.8

0.0

0.00000.0

0.00000.3

4.0

453.03

5.3

419.294.8

358.493.8

321.24

5.6

1061.46.5

1147.1

6.3

I24_i*.l_3.2
6.2

1405.03797^.2616.6

3.5
_6.±

4.2

2013.5

6.6 _1168.3
1780.04.5

1852.03.5

36X6-2

5.5

4270-46.0

4*26.72.2

1524.35.3

1427.64.61173.6

3.4

1384.43.8

0.00000.0

0.00000.0

0.0000

0.0

-6.02

-0.1

-1.44
I84_.i5_0.0.

1798.0

3.7

XR40

0.0

XP41

n.n

993-1

1-R

XR42

0.0

-16.0

-0.1

XP43

n-ooooflrnnoQ

o.n

O-OOOO0.0

q^oppo

0-0

XR44

0.00

-51.18-1.1-20.98-0.4-22.38

-0.5

3.13

0.1

TR4S

0-00

1OO.98

1 .9

176-023-1

135.3ft

2-3

166.562.7

165.25.

2.5

XR46

0.00

1.49

0.0

193.14

1.6

229.301.9

299.602.1

32S.38356.99

2.3

XR47

n.n

597-5

?-*•

19)3-3ft,6

2A25.411.1

2414.99.9_2128.7_

2.2
8.3

1916.6

7.2

XR4B

0.0

442.7

1.8

1276.84.91503.75.5

1751.46.1

1714.55.7

1762.45.5

3428.220-53429.6

19.7

0.0

518.2

3.0

1246.36.8

1355.77.1

1491.27.6

1462.47.1

1478.7

6.3

n-nn

&3-RR

2.7

393.601.3

25.226

1.2

0.3__.39.934
1739.5
1.2

0.8
1.8

n-o

XR5O
XR51

XR52
-XR53 .... ..

olooo

1.589

—0.000

5.694

0.1
O.I.

? 2 1 - 24

1 -9

375.9fc

3.0

348.040.7

23.778

1.3

23.5362.7
1.2

366.96.

12.979__.0.7.
1.71335.234.1681393.10- g_35.371.

21.875.—0.50.9
722.9

31.30525.0024801.4

5.5

2.7

2.7

XR54

0.0

-174.9-0.2

1.7

1100.7

n.o

-79-A

-n-i

444.R-

l-l

R9A. 7

7.1

1247-22.8

1439.3

3.1

1S29.0

3.3

XR56

0.00

-11.70

-0.4

-6.49

-0.2

0.4

13.55

0.4

14.42

0.4

0.30

61-99

0.6_ __ .213.54

1.9

0.3
2.5

14.49

XR57
XR58

0.00

6.58

0.1

106.68

1.7

10.52
?9i.n
185.052.7

198.982.8

206.88XR59

0.30-33.44-O.5

fcfl.5R

1.0

1 19.85l.&_158.00

2.0—193.32.

282.?5

2.4__2.65...88.

2.2__267.3_9_

2.1

2.8

227.142.9

2.4

244.5.4.

2.8

XR60

0.00

97.66

1.8

679.012.6

722.032.7

742.062.6

XR61

0.00000.0

0.00000.0

458.100.00000.0

0.00000.0

0.00000.0

0.00000.0

339.330.0000

2.8

-17.9

0.0

247.8

0.5

0.9

845.2

1.7

907.2

1.7

1096.0

2.0

0.0

50-3

O-1

745-0

1.3

1O96.&

1.7

103.391.1

327.89

3.2

4.3

994»B
519.58

}-6

0.00

4.6

551.684.5

624.51*.8

n.

4924,.

O.7

2O322-

2.6

448.3
1049-5469.0527231.

3.4

28100..

.3.4__2.7934..

3.2

XR62
XR64

0.4

1*8

1

0.0
1.7

...29919.... _3.2..

16

Journal of Applied Input-Output Analysis, Vol.1, No.l, 1992

Table 10 Import Promotion Scenario: Sectoral TFP
1989

1990

XCHS

1991

XCHG

1992

*CHG

1993

SCHG

199*

tCHG

1995

XCHS

TPP1

Q-noon-OrP19*-?.7—1.024A-1.1-0.Q73S-^«4-O.p*18-S.7-0.0373-5.0-0.0*36

-5.5

TFP2
_TFR3
TFP*
_TF.P5TFP60.00000.00030.00000*00000.00000.000b0.000J-0.0177=0.0023-0.0119

0.1
0.0
-2.9
r3.3
-1.3

3.001*
0.2
3.00000.0-0.0306-5.1=3.00*6 .-=0.5-3.0165-2.50.00130.0000-0.0*65=-0.0015-0.0166

0.2
0.0
-7.3
-Q-7
-2.6

0.0023
O.jOOOO-0.0320-n.nnn?
-0.01360.4.
0.0029D.O
Q..OO00.
-*.9-0.0186
O.O___=0.OOO*.
-2.1-0.0131

0.5
0..Q
-2.7
0.0
-2.0

0.003*
0.0000-0.0016=.0.0006-0.01360.5
0..0._-0.2-O.I..
-2.1

jgpy

rt-flf)f>Q

n-OftO7?>-T

i.fUQH1.^

Q.fll&Q

0.9

Q.Q1O3Q.&

Q.QO850.*0.00850.*TFP80.0000 * 0.0073

0. 0000 _^0. 0059

0.6

=0.5

-3.0125

1.0

0.00820.7= 3. 0Z5 l__r.l o l_rO. 0* 15_tlL • 7

0.00*0

rO.O* 280.3

0.00290.2

0.0028

0.2

TFP13
TFPll
TFP12
TCPH

0.00000..0000
0.00000*1)000

3.00003.30003.079*=A.jQL63A

0.0
0.0000__0.0 . ..0.0000
6.3
0.1666=0.*065Jt

0.0
0.3
3.*
=3*J1

=b • 7-O .0671

0.0
0«0
1*.9
-&.1

0.00300.0
0.0000__ 0.0
0.223*
17.7-O.OSfl 2-5.7

0.00000,00000.1859-0.0590

0.0
0.0
13.1
-5.7

-0.0532

0.0
0.0
9.8
-5.0

..IEP150.0000.^O.OObfc=0.6=3.01*0

r.1.2

rO.012.*-LI=0.0101=.0.9-0..0.1U)-0.9-O.|0.12.5-l..l_
-l.S

_J «9

TFPl*

0.00000.00000.00030.0398-0.0303-3.6-0.3352 -10.3-0.0861 -10.5-1 ,.Z_=P . P3A1

-0.1215 -I*.3=,L. 3-0.1279 -I*.5-0... 03.0*. _^U_l_
0.00000.0000 _0.1**3-0.15*6 -16.6

TFP16

0.0000-3.0132-!•*-2.0080-3.8-0.0123-1.2-0.0133-1.3-0.0178-1.7-0.016*_tEPlI
TFP18

0.00000.00000.00000.078*

0.0
1.3

J.0U6
3.0*853.*
1.1=0.0095
0.0*32=0.3 _=.0.0093
0.9
0.0297=.0.3
0.6

r 0 . 015_L_-1 • V
0.02660.5

tQ.Q08_8
0.0173

nP.8__
0.3

YppiO

Q-f-OOPO^>0t%^

1*Tl^QflfcSO«flt aQ^QQ^^Q^j»"^Q^QQQ^

0 • 0331* .5

0..029J-0.0008**0• ^

5.6-O.I~0«0036_LER2J-0.0007

—Qo2

3 ..7

0.0275—3.000*0.0-O.0.023. _^0*3
3.01301.3

0.0007=0.00*30.007*

0.1
=0.3
0.7

0.0001=.0*0027
0.0037

0.0
=.0.3
0«*

-0.0003=0.00240.00230.00580 .006 8

0.6
1o0

0.*
0 . 5.

0.00300 . 0013

0.3
0,50.0022
Q .0.080

0.2
0 , 9_=0.J&OL7__-J3.2
0.00780.6

0.00*00..00A6
0.0029=Q.AO30
0.00*3-0.3
0.3-0.0030
0.0063-0.3
0.*=JUPJU.6
0.0092-O..2_
0.6

TFP20

0. 0000&.03B00.3012

0.1

TFP22_J£P23
TFP2*

0.00000.0000O. 0000
0.0000-0.0005
0.00860.0209

0.0
0.9
2.0

TFP26
_I E£22
TFP28
tcp?q
TFP30

0.00000* 0000

5 .2

0.00290.3

0.00000 . 02B0-0.00363.3-0.*n-nnnn0.3000a. 00 00
0.01030.0
0.8

0.00*3

2. 0412.

im

3.5

0.00673,. 019J

0.6
2.2

O.OOOd
3.01390.0
1.0

0.00600.6

0.00100.00570.1

0.5

QaQ ^ **Q«QO2Q

3 • 9.

0.3

0.02800.0027-0.1-0.0005

0.0-0.0009=.O.3_j=0...OOU
0.2
0.0021

0.2

0.0028-0~. 1
3.6

-0.1
-0.2_
0.2

0.2

Tcp^i

fl-fiflrtn—n.non<fi.fl—*>.nrt?i-»n^.?

—fl.no>Q—on^—0.0033-q,i—o^po3^—Q «3—0.0036

—0.3

TFP32
.XER330.0000O.flOOQ

0.00030.01150.0
1^3-3.0555
0*0190-5.0
2.1

0.00000.0-3.0050^=0.6
3.02702.0-0.03390.0239-3.3
3-0

0.00000.0=0.0123 _^JL» 5
0.02351.7-0.08*9
CO 246-8.0
3.2-0.0253
Oj* 029.6

-2.5
3.1
0.0
-0.7
1.7

-0.0*67
0.. 031.0

0.0000=.0.0052
0.02*1

-*.7
3.2_

0.0
=_0.6_
1.8

TFP38_lf.PJ9
TFP*O

0.00000-J3000
0.0000.0.0000

0.003d0.*-0.0039 _=0.*
0.00000.0

0.0063=0.0029
3.0000

0.6
rJD-3
0.0

-0.0005
0.0-0.00*1=O.OO35-_=0.3__=0«0OS2
0.00000.0
0.00000.00*.*
0*3^
0.003J

-0.*
=.0.5
0.0

-0.0033=0.004*0.00000.00*0.

-0.3
=0..A
0.0
0.3

-0.0010
rJD.0032
0.0000-0.1=.0.3_
0.0

n.nm

1^4

1.1

o.o?aq7.9

0.0791TFP3*_LEPJ5
TFP36_IEP_*1
TFP*2

jcpfc.'x

0.00000.00000.00000.0000n.nnnn0.00000.00000.00*0s-0.001*
0.0031n.nnoT.-rO.l0.3

1 .n

n^n?>i?„?

n.n^iA

0.2
1.8

0.3_
2.2
2.9

-0.0407-?.o-0.0*5*-2.2-0.0*88—r2.2_

0.0711

5.3

TFP*6_IJ=e*_7
TFP*80.00000. 0000
0.0000Q.OQftn

0.00090 . 0.02*.
0.0006»n.Q1l-Q

0.1
0.2
0.1

-1.9

-3.0071
0 .0A99
0.0036

-0.6
0.9
0.5

-0.00900 .0.160
0.00*1

-0.7
L.6
0.*

-0.0105
Q.02Q50.0026

-0.8
L..8
0.2

-0.0098
0.01 ftp
0.0012-0.0552

-0.8
1.6
0.1

-?»7

-0.0085
Q, P.i 60-0.000*-0.7
i . *._
0.0

TFP50

0.0000-0.0039-0.5-0.0127-1.5-0.0276-3.3-0.0360-*.5-0.0361

TFP52

0.00000.00881.0

0.02032.*

0.01822o3

0.01071.*

0.007*

TFP5*

0.0000n.nooo0.0032-Q.QI41rji ..*

3.0097-3.a^9^

0.7

-o .a

0.006*-o.nii?

-n^o-n.pt^>-o.o-Q.0117-0.9-0.0319

-0.9

TFP56

0.0000-0.0026-3.5-3.00*0-0.7-0.0022-0.*-0.0005-0«U-0.0002

0.0-0.0006-0.1

0.00000.00000.00000.00000.0000__=0.0013

0.0
0.0
=0.2

3.00000.00003.000*

0.0
0.0
0.0

0.00000.00000.002*
0.0192

0.0
0.0
0.3

0.00000.00000.00*0

0.0
0.0
0.5

0.00000.00000..00.*8

0.0
0.0
0.6

0.00000.00000.0.0.*J..TF.R53
tppss_If.BS2
TFP58
TCPS9
TFP60

TFP61
TFP62
_JFP63
TF?6*

0.00000.00080.2

0 ^0000=0 • 00 n-o . J
0.00000.00*5
0.*
0..OOOO_=0.0206__=3• 20.00000.01150.5

0.00000.011b

1.5=0. 001J
3.0102
0.0O6Q
3.040*

0.0207=0 • 1
0.9
1 •J
1.5

2.3

=0.«00O2
0.0078
Q.O14O
0.073*-?.^-Q.0SS2-0.0387

-?«7

-*.8

-P.?

-0.0007-0.1-0.00120.5

0.00900.6

0.01**

O.J)
0.7
. 4.1
2.6

2m?.

0.0136

1.7

0.. OO03_O ..00.00510.5
0.0748B.g
0.09653.*0.017*

2.0

5.3

0.00*210.02*8-1.9-0»Q427

0.06912*1-0.03S9-2«1

5.3

0.0233.1.1=0 . O.OJ /_=0.« 3__=0. OJU1

0.0663'-a.Q3?i-0^0^77

5.7

0.0201

-1,9

=tt.1

0.06872.2-n.om

0 ..OOOO__=0 • 00 03

5.9

0.02*70.0000-n.noss
0.0231n.nnonTPP49

3.0677

0.1
2.8

0.0
O.J
1.*

0.0000_TJ:ESJ

6.2-J3.0011
0.03070.00000.001J
0.0189TFP**_J.FP.*5

0.0722

0.0
J>.0
0.3

-0.2
1.0

0.. 0Qft5_0 . P
0.00510.*
0• 06187.0
0.08853.0

0.01551.7-0.05B9-0.0018

-2.7

-**6

rP_. 3_1«3:0.0163

IU.Q0JU
0.0057
0.0616
0.05760.01*81.2

0 . O_
0.5
6..6
1.8

0.0
0.0
P-6_
1.7

As for prices, the GNP deflator drops by about 3 to 4% in 1990 and 1991 and gradually recovers
during 1992 to 1995. Consumer price and wholesale price follow a similar pattern, but the former
drops less sharply and recovers more slowly as compared with the GNP deflator. The latter falls

a little more deeply and recovers only slightly.
Private consumption continues to rise during the entire period due to a substantial increase inreal disposable income. The induced amount in 1995 is almost as high as public investment. Private
housing investment responds more quickly with a peak in 1992, while business investment grows
more slowly, but steadily, with a much greater impact on the economy.

On the demographic side, total population and labor force increase by 0.3 and 0.9% respectively

in 1995. The major cause for this increase is the rise in real wage which stimulates the birth rateof the female population and also the rise in labor participation ratio of a productive age
population. Real wage rises by 3.6% in 1995 with an annual average rate of acceleration of 0.7%.
Structural changes in sectoral output and employment need a special attention, as it is closelyInduced Technical Progress and Structural Adjustment

17

related to the future course of Japan's industrial policy. As shown in Table 9, construction sectors,
especially public work construction, shows the highest impact from this policy package. Related

sectors, such as iron and steel, cement and ceramic products, wood products, coal product andmining, and other mining (including ceramic clay, stone quarry, etc.), also indicate high responses
in terms of percent deviation from base line scenario. Other industries which respond strongly arein the high technology sectors, particularly electrical machinery, general machinery, and auto

mobiles, which also induce additional demand for steel. Service sectors including trade and financealso respond fairly actively.

In sharp contrast to the above positive impacts, it is noteworthy that primary sectors (except
mining), food manufacturing, textiles, and apparels suffer greatly from an import promotion

policy, indicating negative values in their responses. In other words, the negative impact is stronger
than a positive impact on these sectors. In terms of percent contribution in 1995, construction andrelated sectors account for 47.6%, high technology sectors for 28%, services sectors for 21.4%,
other minor sectors for 9.8% and the above negative sectors for -6.8%.
As for the changes in TFP, a similar remarkable contrast between competitive sectors and noncompetitive, or protected sectors, can be observed in Table 10. As described in the previous section,a decline of net output price caused by import promotion results in a positive impact in technicalprogress in competitive sectors, while a negative impact is observed for non-competitive or

protected sectors. The result of our simulation clearly indicates that 19 sectors selected for importliberalization follow exactly our theoretical hypothesis with only one exception, the apparelindustry. In the automobiles and aircraft sectors, for example, TFP increases by 2.2 and 2.9%
respectively in 1995. The steel industry, also with liberalized imports in our scenario, indicates anincrease in TFP by 1.8%, while the iron industry shows a deterioration of TFP by - 0.6%, bothin 1995, indicating a sharp contrast in competitive response in both sectors. More conservative

responses are noticeable in agriculture and food manufacturing, where the TFP falls significantly,
i.e. - 5.5% in general crops and - 5.0% in dairy products in 1995. Deterioration of terms of tradeclearly discourages technical progress in those sectors.

For other sectors which are not directly targeted for import promotion, TFP responses seem

tobe rather mixed, depending on the value noted in Table 2 and the results of net output price(px/pz). Strong positive responses in communication and trade sectors are caused by the fall in
net output prices, but a similar rise in manufactured gas is mostly due to the rise in net output
price. Real estate and railway transportation, which are fairly competitive, show negative

responses mostly because of the fall in net output prices. For similar reasons, TFP declines inpetroleum and coal products.

For the employment structure, a substantial change is caused by this policy package. The
increase in employment is most noticeable in construction, amounting to 192,000. The next highest
increase is 183,000 in the service sectors and 88,000 in the high technology sectors. Metal products

shows an increase of 13,000, but basic metal industries indicates rather negative figures. On theother hand, reduction of employment is noted in the primary sector, including mining, amounting
to 238,000. This clearly exceeds an employment increase in construction but can be accommodated

by the total increase, including those in the service and high technology sectors. Textile sectors also
indicate negative figures of -52,000, but food processing sectors indicate a rather positive

increase of 4,000. In summing up, it can be stated that on the average a fairly sizable increase inemployment opportunity has enabled the accomodation of the employment released from theagriculture and textiles despite increased technical progress.

Table 11

Increased Leisure Scenario: Macroeconomic Variables

Oooc
qpi crTPn

1989

1990

n.n

G.NE

REAL SNE

p

0.0

OcrL

PC?

0. 0000

UH1I SCAt =>QTt* =

PU 1

n. nnnn

NL

0.0000LABORUNEMPLOY
3AMX

RATE

I PM?11PAT?

firiMT^ 13Pt M5

WASH

RATE

1991

XCHG

1111.6-0 •2643
0 .52730.3

3481.2-n.i—1-7O49

INVT-30VERN.MEMT
MPT

1993

0.3

4W99.4

XCHG
0.9

1994

XCHG

5612.2

1.3

1995
6338.3

XCHG
1.
1.1

4435.41• 14869.61.2

5005.61.1

5293.0-0.1880-0 .7-0.0477

0.0

0.11760.1

0.26000.2-0.3761

-0.1

-0.2

-0.4416-0.4-0.4525-0 • 4-0.3722-0.3-0.2263—i-i—1-137*—1-7-0.1587-0 .2-0.1246-0.1-0.0719-0.1-0.3406

0.0

0.0

1.16020.0

5.71880• 18.75000.1

9.97270.2

9.00390.1

0 .AA7«?

n.nn-o

7.7070•03-33780.0

3.77340.0

4.01170.3-0 .0057-0.2-0.0180-0.6-0.0224-0 .7-0.0133-0.6-0.0077-0.2

0.00530.2

T

n. nnnn-o -OO77

O-O—1-OO7H-0- 1-0-0023o • 00.00640.1

0.00790.1

0.0031O.I

0.000-0.703-1.4-1.578-2.3-1.784-3.4-2.177-3.8-2.529-3.6-3.073-3.9

702.77-4.3

812.40-5.1

931.06-6.0

W0.0000-0.0105

0.0-0.00260.0

0.05060.1

0.10030.2

0.13500.2

0.1431

0.2

TO

O.flOflfl—Q—QQ37—1-0011Q-Q

0-0009Q.Q

0-0Q210.1

0.00220.1

0.0016

CNP

0.00001990

0.0000

I?

0.3

770.7

th

0-00

1 7 q- a1

IG'
JG

0.00000.0000Q ^0 Q109.6?

0.00000.3000

1991

XCHG
0.3

E

0.00000.0

0.0000n.nnnnn.n

n.nnnn2276.42.7

0.00000.0

0.00000.0

0.00000.0

0.00000.0

0.00000.3

1 7-1

191.874-3

84.4-4

l.q

33.81

1.5

116.75

1.9

0.0

0.0

0.00000.0

0.00000.0

0.00000.0

0.00000.0

o.o

0.0000n.noooo.no.aoooo.oq.oqoo

0.3

0.0

27.1

-109.6-0.1-161.3

-0.2

-93.3

-0.1

191-31

a. 4

4SQ.44

0.5

Soo.OO

O.S

0.0000

0.0

4.3

0.0

8.7

s. no

n.i

. 1 ?

rATPcnnv

CNPOS
an*

XCHG

1991

—0.1

n.n

XCHG

irnag

0.0

yi

1992

—in. i

0- f)

S77.A

1994

XCHG

1995

0- 7

1744.90- 41944.6.

0.62605.6

XCHG

1993

XCHG

XCHG
0. 3

0.00000.00000 •00.00000. 00.00000. 00.00000. 00.00000.3

0.00000.3

0.00—11-4Ao .o—13.46

0-

7O-77

0. o

53-35

0. 1

81.20

0.2

94.08

0.2

728.4

0 •9

2224.22. 62691.43. 03011.73. 23175.43.1

3453.7

3. I

S77-737- n0

R4«5.232.2

553.64

1- 6

-0. 1

-20.39

2. 7
-0. 1

0.0

17.44

0. 0
I. 5

INVESTXEMT-3USN

IPOS

0.0

TMVCg-.aPgT.1CMT!

rung

n-nn

INVES-SOVERNMNT

IGOS

0.00

-7.95

0 •0

-29.31

-0. i

n.nn

R6.-7<;

9 .0

7*n-A7

17. 7

A6-77

7-

56.07

1.4

63.00

0.00000.00000.3

0.00000.0

0.30000.0

0.00000.0

0.00000.0

0.00000.0

n-3

n.nnnn- 0.0

Q-OOOQ

0.0

n.OQOOo.o

0.00000*00.0000

0.3

0.0

33.63

0.0

71.81

0.1

2.50

0.0

-0.19

0.0

6.00

0.0

-D+Jt

3Z5..12-

TMVg'JTngY—PQTVT

IN/T-50VERNMENT

MPT

JGDS

PY9ORTSEXPORTSSee general

EOS

0.00

-16.16

■a

■a

a

6

o

0.3

mattomai

rprK

I

S2.

0-1

n.nn

1990

o

XCHG

7Ti.7

rino

1989

CONS-NONPROFIT

XCHG

0. 0000C

EXPORTS

0.9

ftl

-3.2

n.nnnnINVES-30VSR.NMNT

1992
40*57.9

0-1

INV5STMSMT-3JSN

XCHG

VPgSTQN

n.nnon

1989
CONS-NONPROFIT.MQHP1 .

US
3FD0L

C3P

JAPAN

n.i

n. nnnoPE*S CONSg<;=rnMnMTrfootnote at the end of Table

5.

-37.735- 7.

_3.0i.JL2_

0.85

Induced Technical Progress and Structural Adjustment

19

6.2. Impacts of Increased Leisure

The second policy simulation deals with a policy to reduce working hours and to promote

expenditures related to leisure. This policy measure has been taken in the past several years withspecial reference to working hours. Local governments have also taken various policy measures,such as regional development for resort areas, strengthening welfare facilities, etc. Here we takeup a scenario which is not directly linked to such policy instruments but is related to changes in

consumers' behavior as influenced by such policies in order to evaluate the impact on the economy
as a whole. In other words, this is an alternative scenario in which consumers place more emphasis
on leisure-oriented service expenses than other conventional consumers expenditures. We

temporarily assume in this new scenario that the component of private consumption for "63.
Other service" is raised by about ¥4 trillion, 15%, and that other components are reduced by thesame amount, leaving total expenditure unchanged.
The macroeconomic result of this structural shift of private consumption in favor of leisure-oriented services is indicated in Table 11. Although there is no macroeconomic stimulus, theeconomy starts to grow in 1990. Real GNP grows about 1% in terms of deviation from the baseline forecast. This is mostly because of the active response of private business investment in thetertiary sector, especially in other services. Stimulated by this tertiary sector's investment, private

housing, private consumption, and imports start to grow with a certain time lag. The current

account surplus declines by about $1.5 to $3.0 billion, indicating a favorable direction of this
scenario. Employment also increases more than the previous scenario, although induced GNP isonly one-third of the previous case. Prices are fairly stable, particularly for the first three years,
though they tend to rise slightly thereafter.

As for sectoral break-down of output, there is a marked contrast between growing and stagnant
sectors, as shown in Table 12. Obviously, the highest positive response is shown in the other services
sector, amounting to ¥4.0 to ¥3.5 trillion, 5.4% increase (in 1995), in terms for deviation from thebase line forecast. Investment-oriented sectors also show higher percent deviations: about 2% inconstruction, 1.0 to 1.6% in machineries, and 1.5 to 2.4% in basic metal, ceramics and othermining. Pulp and paper also rises because of their dependence on services. Negative responses of-0.2 to -0.9% are noted for general crops, food processing, and textiles all of which arenegatively affected by the change in consumption components.
Sectoral changes in employment also follow the pattern of output. As compared with theprevious scenario, however, the changes are relatively more significant. Employment in the otherservices sector rises 4.1%, the highest among 64 sectors. Here the increased employment amounts

to about 600,000, about 80% of the total increased employment. The rest of the increase isaccoutned for mostly by investment-oriented sectors, such as construction and machineries.
Negative responses are indicated in agriculture, food, and textiles, but the reduced employment
is rather negligible.

As expected, sectoral price changes are generally small, except in other services, construction,coal products, and pulp and paper products where the output prices rise 1.5 to 2.5% in responseto the demand increase in 1995.

Regarding sectoral technical progress, the changes are again very small, except for other services

and communication. The former's increase is affected by the rise in net output price, while thelatter's rise is mostly due to the fall in net output price. This contrast is based on the differencein their parameters X. Cement, belonging to the former group, also shows a small increase in TFP.
In summing up, this scenario deals with a structural change in demand pattern in favor ofleisure-oriented service activities. The result, therefore, is characterized as (1) service orientationand structural shift in output and employment, (2) demand increase centering investment in the

20

Journal of Applied Input-Output Analysis, Vol.1, No.l, 1992

Table 12 Increased Leisure Scenario: Sectoral Output
1989

1990

iCHG

1991

iCHG

n.no

_XAQ

1992
.=.40.IL9_

-O.S

1993
5CHS
-51«J-5_=.Q..

1994-35..j,J

XCHG
=0o_

1995

-0.3

0.3

0.000

-6.663•1.4-4.083-0.3-2.447-0.5-0.317

-0.

0.585

O.I

1.594

.XA03-000

Q.DOOO.0.0_-.0.0000

0.00000,_0.0000

0.0

0.00000.00-25.52■ ■0.60.0000..
-1.59

.0.0

XR04

0.0
-0.2

0.0

-1.29

0,

0.50

0.0

0.73

_a*ooaoo.ooooXR02-JtaO5_

0.4

-7.47
.0000

O.OJ

0.0000__0.0

0.00000.

_0.0000

0.443

0.0

-5.650-0.2-3.372-0.

-5.551-0.2-1.816-AS7O

Q.l

7.8A501 .7

1.7000DL.

7.4170

1.0__LmJL31Q

0.0
0.0000_0.0_ ._0.0000

0,0.00000.0

0,._0.P00.0

XR06

0.000

9.344

X3P7

n.nnoftnr^n|n

XROS

0.0000_Q.000.0

0.00000.0

0.00000.0

0.0000D.OOOQ_0.0000

0.0

0.000.0.

xaio

0.00000.00000.0_
0.0

0.00000.0

0.0000

JCA11_
XR12_D • 0000
0.000

0 .00 00
11.4950.0___D.0000

0.6

29.8830.0
1.4

0.0000.
37.7200.00-SO.790.9_=3JOU50.

-0.3_XRQ9_.

XR14

0.00

-30.85_XR15_
XR16

0.00=19.73_. -0.2.
-0.3-106.6_XR17__

0.0

0.5._

__.0.000__25.343._

XR19

0.00

-49.14

-1.3

xang

0.00

-15.09

il-i-

XR20

.000

-5.392-1.5-XR2L—

n.nn-37.oqXR22

0.0-110.8-XJL23-

-0.5.
-0.6

0.867.

0.0

15.523.

_0.3_

-1.4

-25.36-0.9-3.211-0.8-0.8~-78.l ~ -0.
-3.762.... -0,-27.19-0,—0 . 4-1.758-0-33.52-1.0-47.7_2.j43 3-0.2

rB.152-O.l_-27.43-0.9-0.633-O.Z=.4.29

±0.1

-47.9

-0.6

l...4__12 5.4.6

1_.5_

0.0. .

-23.82

-0.3

-1.47

-0.

-1.327-0.3-44.7~^b.6~

46.95347.5001.

48.6561.0

53.645775.72143.611

144.801.4

132.79

1.7

1.4

67.84

0.8

30.85

0.

31.22

0.3

50.67

0.5

=0.6_
0.5
0
-0.3

.nl. 131
12.859- 0 . 2.
0.5

r 0 . 335.
11.264-0.
0.

_^0._?_20863^-26.750 ..4-0.2

64.. 816^-21.83Q.
-0.

_J.1_.

2A..9J)

O-uL-XA31_

n.nr>-i7.si

^fluJ

XR32

0.000

11.5140.6

48.006

1.06.66=_Q..2._0.5

19.063

0*6

-O.I

-6.13

0.3

109.930.5

13.546

50.82

0-7

75.18

0.

0.4

146.591.8

31.7891.

37.634

1.7

40.956..S±S

1.2

18.9471.

147.961.

_J_7_,2J5JL
151.24

I..J
1.6

43.11

0.5

148.57

1.6_18J-.34

2 .5

15_7_.D.0_

U2*XLI

0.2

233.931.5

265.281.8

240.671.

232.872-

30.99
n.nnnno.fio-noooQ.O

0.00000.0

0.00000.

0.0000

0.0

13.59

0.2

77.38

116.34

1.4

103.79

1,

91.32

1.0

_209_._9.2

1..1.

745.371.5

116.95

1.4

XR38

0.00

-XR3.9—n-nn

42 ..73

0.3

L 8-4 . 3

10.08

1.3

213.66

1.

XR40

0.00

233.230.6

638.26691.37

1.6

694.561.

_980.3119.651-5
0.4

1080.6115.18

28.8

1.5.

0.

137.760.4

0.00000.0

0.0000O.

0.00000.0

47.961

1.0

53.949

XR44
XR46_XR,4J_
XR48
»P4O

0.0
0.00

224.6
-25.200.4-0.1

846-J
113.92^QQQQ

n.nonnn.oo.oooo0.000-5.643-0.1

37.10958.598
1.1_5J.P5.1_ _P..9_

_£U00

0.5

0_._9_

107.85

0.7

24.26

0.6

70.03

1O/.-Q?

0

6..J2

.6_

5JBA..Q6

2507.01_2iP_

44^*37133.310.5

543.652.0

598.692617.452.0

662.20

2.0

n-nnn

t.qu

o.i

?7.410_Q*2

3JLuDjaSL30-6090.2

32.336

0^_

0*00

0.6
D
-0.2

332.96

1.7-6.054-0.3

96.16
S. 535^-3.436-XR53..
XR54
JCR55_

0.0-281.7-0.4

0.0-571.5

71.02-2 .528_j=.O . 1

.830

107.4

0.1

-1.4

-294.1-0.7-32.61-0.9

364.90JL8._453_-6.745-0.3=6 .3.7.9

=!U

3.957

-0.1

42.3

0.

98.8

0.1

-203.5-0.

-109.3-24.37zP_._2_-0.7-31.11-0«_=ao..32_^o,-44.13=J»1.A2-14.44

-1.3
rO.4_
-0.2

_XA5S_O-QOO~h.ljA

-O.1

1 7-

-0.2
0*0
-0.9

0.00000.0

0.00000,0.0000-423.8
X- 0_ --3.9.4JL..

-0.7-231.7-0,-216.94.02** 3

6.83521 • 6

6.

_323JL..6.

0.3

77.66

83.70

0.8

84.06

0.

96.66

7585.2

R413.B

1-1

814.6.1

1.

8696.6

XR60

0.00-47.31

XRSl
XR62

0.00000.0

0.0000-406.5

JLR63

o-o

mis M3_

XR64

0.00

32.05

Q*n

**<\*.u

Q.5

0.1

21.09

_5.4_.2_93

-0.

0.00
D.OQ
0.00

10.31

392.88372.0229.777-8.591

XR53

xa«.s

1.3

64..3.Q9

O-QO-O.0QO
0.000

XR56

67.551

0.00

0.2

0

81.47

0.00

_XR51_
XR52

XR50

0.8

.4

37.136

n.s

_L4*

L.l

-16.425.336_

241.50--XRA5--0.7_-0.V_

1.0

-0.3
O.Q
-0.4

-XR-41XR42-29.08_-!4.l6

-24.4

-0.4

1.9

-7.9526.590-36.73-0.

-0.2

343.?0119.03_r-3.354
12.231
67,. 039-28.780.000_0..13Q0
0.00

-42.2

=0._2_ ^zJJuJi3

44.102

-l.l

-39.2

1.3

_r9_._i6.-15.22. _-0. 5 _
.

0.3 .

43.4801.9

0.5-*-7OR

0.00

-I,

-l.l

0.0

0.0__ _0..QO_00

ID .11

n-nnn

XR36

-43.75-39.280.0000

0.0

145-9

2.2

XR34

-(

0.3
0.0

7-ft

186.99n.nnn-10.71l..l_

0.0000

O..O_ _O.OOPO

-0.9

0.00

XR30

40.852LO__ ^15.10..
-84.3-7.47 _=.0*.9_2.

41.473

1.3-38.59-3.309_ 0.0.000

0.0_
-O.I

_162.05.

-1.6

19.561

XR28-0.5

0.0000

0.

0.3 .

0.0

..2.6 _
57Q-OB_XR29_-0.8

0.

_0.0000

-63.7

o-nn

XR26

-68.6

0.0000_..0.0000-12.20

0.000

XR24

-29.47_-15.5l ._jr0.5

0.0

0.0_

5CH3

-??■64

=1.35

P.O.

4.08

0.

16.40

0.2

£L.3JL2
11.70

0.
0.

_22..984

P..3.

37.39

0.1

-2.571

.12.1
301.2

lj.6_

1.3

P_._4_
-0.1

Q.0_

-13.3

0.3
0.3

-14.77-0.4

16_.O3

Q.1_

service sector, (3) technical progress in the tertiary sectors, and (4) a fall in current account surplus.
7. Concluding Remarks
We have discussed the role of sectoral technical progress in the framework of the multi-sector

econometric model of Leontief type from both a theoretical and an empirical point of view. Now
we briefly summarize the conclusions, which can be derived from the present research, andpropose future research.

First, the sectoral technical progress was explicitly incorporated into our multi-sectoral modelin order to evaluate its forward linkage effect within the Leontif framework which is based on the
V-RAS algorithm as developed by our group.

Second, sectoral technical progress functions were estimated and endogenized in the present
model. The sectoral technical progress was explained by neutral non-price factor, neutral priceInduced Technical Progress and Structural Adjustment

21

factor (or barometer of competitiveness), and biased factors induced by relative factor prices.
Although there are marked differences in the types of technical progress, it is generally observedthat Japan's technical progress is mostly labor and material (including energy) saving and capitalusing. In regard to the neutral factor, a sharp contrast can be observed between competitive andless competitive or protected sectors in terms of net output price effect. Japan's rapid technicalprogress since the 1970s in high technology oriented-sectors is partly attributable to the negative
response to net output price. Technical progress has been stagnant or even falling in those sectors
having positive responses to such changes.

Third, the multi-sectoral model was used for two alternative scenarios through inter-sectoralinteractions between forward and backward linkage effects with respect to demand, output,
foreign trade, employment, technical progress, prices (including factor prices), as well as macroeconomic growth alternatives.

The first policy scenario indicates that a promotion of import liberalization with appropriate

fiscal policy further strengthens the competitiveness of Japan's industries, especially in the hightechnology sectors, and it helps to substantially reduce the current account surplus. The structural
unemployment issue can be resolved as long as fiscal and structural policy is strong enough toenlarge employment opportunities.

The second scenario aims to change Japan's consumption pattern from conventional type tomore leisure-oriented type expenditures. Structural changes take place with an emphasis shiftingfrom conventional to more service-oriented output and employment. Furthermore, aggregate
demand is boosted as a result of the substantial rise in investment in the service sectors. The current
account surplus declines significantly. The total employment effect is greater than in the firstscenario.
In view of the growing demand for Japan's import promotion and domestic demand expansion,an optimum policy-mix for alternative growth would be the one combining the above two
scenarios, which satisfies both efficiency and welfare requirements.
Finally, with respect to future research, the TFP function needs to be elaborated upon withspecial reference to time lag structure and R&D expenditure, etc. For factor price, a database on
price of material (pr) should also be strengthened by distinguishing energy and non-energy factor

prices, thus enabling the analysis of energy impact on technical progress.
Output price function needs to be further strengthened with respect to the link between importdependency and domestic prices. This will ensure a greater elaboration in import liberalization
analysis.

Interaction between economic and socio-demographic variables should be analyzed in moredetail in view of the growing importance of the aging population issues. The relationship between
technical progress and the aging issue needs to be made more specific and more elaborated in themodel framework. This would probably be one of the most challenging areas in model building
if cross disciplinary research collaboration is to be successfully achieved.
Appendix

We assume a production function with n factors (Fi) and time (/)• Factors are divided into F5

and P- for short-term and long-term operation, respectively. /?, denotes factor price divided byoutput price and a* share parameter on each factor F,. Z denotes total factor input, X output,
and r factor productivity (TFP).

X=f(FhF2, ...F«, t)(1)(/j = 7, ... ri)

22

Journal of Applied Input-Output Analysis, Vol.1, No.l, 1992

F,=Fi+Ff(2)

X=f(Fs,....Fsn, ... Fj... FLn, t)(3)

Z = ZS + ZL

(4)

zs= 2/>/*"?

(5)
(6)
(7)

wf=p,Ff/ZL(8)2<of=l(10)

Unit factor demand, which is dependent on factor prices and time, is derived from an ordinary
profit maximization procedure with constraints on total cost and production function.

¥si/X=gs(p1)p2t ...pn, t)(11)

Ff/X=gL(phP2, ...Pn, t)(12)Aggregation of these equations into an average unit factor cost, an inverse of r (TFP), for eachgroup provides the following relations in logarithmic form.

**

i

,

zL

„

)

(14)

2 «/ = In -ir

(15)

ZL

In -1tf- = ^L (2 "fej lnp/, E «^/" 0(16)

01 = XJw,-0/(17)

02 = Sw^'f

(18)

z

zs

zL

ln^ = wln^^ + a-a) In At-z5(o> = 4^)(20)

Induced Technical Progress and Structural Adjustment

23

Note that in (14) weighted average term, %<aUsu In pj, is dropped, since they are all zero. As

described in the text in Section 4 (equation (8)), 4 are based on symmetry condition of 6^ = 6*
elasticity of substitution.
References[1]

Adams, F.G. and S. Shishido (1988), Structure of Trade and Industry in the US-Japan Economy, NIRA

[2]

Adams, F.G. and S. Shishido (1990), Structure of Trade and Industry in the US-Japan Economy, Phase

Output NRS-85-1, February.

II — Integration with Project LINK and Simulation Applications, NIRA Research Output Vol. 3, No.
1.

[3]

Binswanger, H.P. and V.R. Ruttan (1978), Induced Innovation, Baltimore and London, The Johns
Hopkins University Press.

[4]

Freeman, C, J. Clark, and L. Soete (1982), Unemployment and Technical Innovation, London,
Frances Printer.

[5]

Jorgenson, D.W. and B.N. Fraumeni (1981), "Relative Prices and Technical Change", in Modeling and

Measuring Natural Resource Substitution, ed. E. Berndt and B. Field, Cambridge, Mass., MIT Press.
[6][7]

Schumpeter, J.A. (1943), Capitalism, Socialism and Democracy New York, Harper & Row.
Shishido, S., et al. (1986), Studies on Long-Term International Impacts of Japan's High-Technology
Industries,(NRS-84-13), Foundation of Advancement of International Science, pp. 1-242, (inJapanese).

[8]

Shishido, S. and O. Nakamura (1992), "Commercial Policy and Restructuring the International
Economy", Journal of Asian Economics, Vol. 3, No. 1, pp.97-109.

[9]

Shishido, S., K. Harada and Y. Matsumura (1991), "Technical Progress in an Input-Output Frameworkwith Special Reference to Japan's High Technology Industries", W. Peterson, ed., Advances in InputOutput Analysis: Technology, Development and Planning, Proceedings of Eighth International

Conference on Input-Output Techniques, London: Oxford University Press.
[10]

Shishido, S. (1990), "Innovation and Input-Output Analysis", Innovation & I-O Technique, Vol. 1, No.
2 (April), (in Japanese).

[11]

Wago, H. (1983), "Energy Price, Substitution Elasticities and Technical Change — EconometricAnalysis by Translog Cost Function", Journal of Japan Statistical Association, Vol. 13, No. 1, pp.
73-88, (in Japanese).