Masahiro Kuroda, Kenta Ikeuchi, Yasushi Hara, Michel C. Huang. National Graduate Institute for Policy Studies (GRIPS), Japan Kazuyuki Tsuchiya, Akira Ohtagaki Mitsubishi Research Institute Masatoshi Yokohashi, Kaori Tsuyuki Applied Research Institute

1. Masahiro Kuroda, Kenta Ikeuchi, Yasushi Hara, Michel C. Huang.
National Graduate Institute for Policy Studies (GRIPS), Japan
Kazuyuki Tsuchiya, Akira Ohtagaki
Mitsubishi Research Institute
Masatoshi Yokohashi, Kaori Tsuyuki
Applied Research Institute
- Experiment of the Assessment of Societal and Economic
Impacts by Policy Simulator -
PAPAIOS Kochi University, October 22-23, 2016
Session: How to Assess the Structural Changes due to STI
Progress on the Society and Economy through the Input-
Output Analysis?

2. 1. What policymakers want to know?
- We need a redesign of “Science for science, technology
and innovation policy” -
2. What policymakers need to know?
- Why do we need the “Science” of “Science for science,
technology and innovation policy” ?
3. Providing inputs to policymakers reflections on policy
engagements
- PDCA Cycle is the most scientific method of
implementing STI policy for solving normative issues -
- How to make co-evolutionary relationship among scientists,
citizens and politicians ?
- How to Activate Science & Technology Capabilities
for Value Capture in the Society? –
4. Construction of Policy Simulator
2
Session One: Identifying the Policy Challenge

3. 3
Redesigning the planning and the implementation of the STI policy and
developing it as a science:
・Scientists need to move from Science for Science’s sake to Science for Society.
・Policymakers want to design an evidence-based STI policy scientifically in order to
realize the capability of science & technology toward the value capture.
Then policymakers want to know
a) Properties of -Science. Deepening the understanding of
the properties in the modern sciences and society
How can realize the productivity gain by science
and technology
b) Budgetary Concerns of Government.
Efficiency and Rationality
c) Expectation and Confidence in the Public for Science, Technology and
Innovation Policy.
Transparency and Making Understanding
Science Question 1. What policymakers want to know
- We need a redesign of “Science for science, technology
and innovation policy” -

4. 4
Identifying “Policy issues to be solved”
Rapid development of new trans-science:
(1) Benefit, but also unpredictable impacts, disasters, public controversy and damage to
environment.
(2) Such impacts are fairly difficult to understand because of their fragile and complex
characteristics.
(3) Therefore an effective collaboration among various sciences including natural, social
and human sciences is necessary in order to analyze their phenomenon scientifically and
identify “Policy issues to be solved”.
Importance of the “Impact Analysis” of STI policy alternatives as
“Policy Options”
Visualizing the social and economic impacts of alternative STI policies using scientific
evidence is highly important and effective in order to ensure transparency in decision-making
and provide accountability to the public.
Science Question 2. What policymakers need to know?
Why do we need the “Science” of “Science for science,
technology and innovation policy” ?

5. 5
Science Question 3-1. Providing inputs to policymakers
reflections on policy engagements.
- PDCA Cycle is the most scientific method of
implementing STI policy for solving normative issues -
1. Observing the current stage of society and technology: (A)
2. Having “a desired future” we wants to achieve and
identifying “Policy issues” to be solved: (B)
3. Based on comparing the Bau future and desired future we can
start formulating issues to solve and targets to achieve.(C)
4. There are multiple competing policy instruments we can use to
achieve the desired future: Assessment of “Policy Options” and
Policy making: (D)
5. Approval and understanding of the public is key to successful
implementation:（E)
6. Ex-post policy evaluation: (F)

6. 6
(5) Providing Materials for
Understanding among Stakeholders
A Bird’s eye View of Science for STI Policy
- The following PDCA Cycle is the most scientific method of
implementing STI policy for solving normative issues -
（１） Population & Demographic Factor
（２） Current Perspectives of Science & Technology
（３） Current Stages of Industrial Structure
（４） Trend of Economic Growth & Income Distribution
（５） States of Human Resource and Employment
（６） Balance of Government Budget
（７） Others
Based on observations
we can forecast/ create
visions of the future
(1) Observing the current stage of society and technology
Visions for the Future
Based on (A) we can create
Bau vision of the future
Assessment & Evaluation
Structure of Data
Choice of Alternative Policy
Instruments
・SIT Policy
・Social Technology
Policy
Assumption for
Exogenous Variables
・ Trends of STI
・ Demographic Factors
・ Global Conditions
(3)Setting Issue to Solve
Setting Targets to Achieve
Overviews of Policy
Instruments
Bird’s – eye View
of Social Statistics
Bird’s eye View of
Science & Technology
Structure making
Alternative Policy Options
Setting a Policy Issue
A
B
C D
E
F
Choice of Indicators
(4)Assessment & Evaluation of
Socio-Economic Impacts
(2) We also have
A desired “future we
want to achieve”
(6) Ex-post
evaluation

7. Science Question 3-2. Providing inputs to policymakers
reflections on policy engagements.
How to make co-evolutionary relationship among scientists, citizens
and politicians ?
How to solve the “trans-scientific” issues ?
Trans-scientific issues arise in the course of interaction between science
and society. They require cooperation between scientists, citizens and
politicians, in which every actor is aware of their responsibilities.
・ Scientist: Scientists have to be “Honest Brokers”, who can
give reliable advice to citizens and politicians.
・ Citizens: Citizens have to be independent well-educated people,
who can clearly understand the role of science and technology.
・ Politician: Politicians have to be independent representatives of
the citizens, but not biased representatives of the special interest
groups.

8. Development of
the “Science of
STI policy”
Evolution of
Policy Formation
Mechanism
Copyright (C)2011 JST All Rights Reserved.
Co-evolution
Communication &
Trust
Feedback of
research results
Stimulation
Co-evolutionary Development of the “Science of STI Policy”
and the “Policy Formation Mechanism”
NormativeObjective
“Research Integrity and
Scientific Responsibility”
8
Scientist Politician
Citizens

9. A. Success Story in Japan during the High Economic Growth period 1955-1965:
- The Pyramid Hierarchy with Division of Labor -
B. Unsuccessful Story in Japan after the bubble period 1990-recent:
- What’s Structural Changes on Technology, Taste and Factor Endowments?-
C. What is our Future Challenge in Japan (1990-2060)
- What’s issues to be solved , How could create new sustainable development
and How could STI and Industrial Policies create New Values in Society?-
digital economy
D. Concluding Remarks: Further Challenges
9
Science Question 3-3. Providing inputs to policymakers
reflections on policy engagements.
- How to Activate Science & Technology Capabilities
for Value Capture in the Society? -

10. 10
A. Success Story in Japan during the High Economic Growth period 1960-1975:
- What’s circumstances for the industrial policy and How to manage it? -
“No more the stage of the aftermath of World War II”
White Paper on Economies, 1951
(1) Unlimited Labor Supply from Agriculture to Manufacturing
(2) Government Industrial Policy
a) Production Priority System
b) Industry Rationalization Policy: the Exceptions to Tax Laws Acts for
Heavy Manufacturing Promotion, Export Promotion.
c) Balanced Budget Fiscal Policy (1948-1965)
d) Financial Investment Funds by public finance
e) Investment for Infra-structure
f) Borrowed Technology for Mass-Production
(3) Increasing Domestic Consumer Demand for Durable Goods
Source of Average Annual Economic Growth(%)
1945-1950 1950-1955 1955-1960 1960-1965 1965-1970 1970-1975
Real GDP 9.4% 10.9% 8.7% 9.7% 12.2% 5.1%
Labor n.a. n.a. 2.4% 0.8% 1.3% -0.3%
Capital n.a. n.a. 4.0% 5.3% 5.4% 3.7%
TFP n.a. n.a. 2.3% 2.4% 5.5% 1.7%
source :Yutaka Kosai, Age of High Economic Growth Period, 1984

11. 11
What kind of “Division of Labor “ has been realized in Japan
during the High Growth Period?
Final Demand for Consumption & Investment
Domestic and Global Market
Industry1FirmA
MainFabrication
Ａ
Ａ
PartsProducts
Productio
Ａ
Ａ
PartsMaker
PartsProducts
(
Productio
MaterialProducts
Industry1FirmB
MainFabrication
Ａ
Ａ
PartsProducts
Productio
Ａ
Ａ
PartsMaker
PartsProducts
(
Productio
MaterialProducts
Industry1FirmC
MainFabrication
Ａ
Ａ
PartsProducts
Productio
Ａ
Ａ
PartsMaker
PartsProducts
(
Productio
MaterialProducts
Industry 2 Firma
Main Fabrication
Ａ
Ａ
Parts Products
Productio
Ａ
Ａ
Parts Maker
Parts Products
(
Productio
MaterialProducts
Industry2Firmb
MainFabrication
Ａ
Ａ
PartsProducts
Productio
Ａ
Ａ
PartsMaker
PartsProducts
(
Productio
MaterialProducts
Competitive Market Industry 1 Competitive Market Industry 2
Main Bank I Main Bank II Main Bank III Main Bank IV Main Bank V
Industrial Policy: Rationalization Policy & Public Financial Institution
The Pyramid Hierarchy with Division of Labor
Investment Creates
Another Effective
Demand
Supported
by
Unlimited
Labor
Supply
Creation
& Control
Effective
Demand
Policy
Policy
Finance by
Public
Financial
Intermediary

12. B. Unsuccessful Trend in Japan after the bubble period 1990-recent:
- What’s Structural Changes on Technology, Taste and Factor Endowments?-
12
Rapid Structural Changes since 1965
1) Flex Exchange Rate in the global economy
2) Changes on Factor Endowment :Oil Prices, Wage Rates & Interest Rates
3) Aging Population & Low Birth Rate in Developed Countries
4) Revolutionary Changes of Sciences & Technology in Trans-Science Stages
5) Changes in Consumer Taste : Commodities with High Quality Service
6) Strict Government Budgetary Constraint : Social Security Cost up & Deficit
How to create the sustainable market demand ?
How can STI Policy make a sustainable development?
Source of Average Annual Economic Growth(%)
1965-1975 1975-1985 1985-1995 1995-2000 2000-2005 2005-2010 2010-2014
Nominal GDP 15.2% 7.6% 4.1% 0.3% -0.2% -0.9% 0.20%
Real GDP 7.4% 4.0% 3.1% 0.8% 1.2% 0.3% 0.6%
Population 1.30% 0.78% 0.36% 0.22% 0.13% 0.04% -0.47%
Labor Force 1.04% 1.11% 1.10% 0.29% -0.34% -0.08% -0.14%
Capital:Tangible n.a. n.a. n.a. 1.7% 0.4% 1.0% 0.4%
Capital:Intangible n.a. n.a. n.a. 4.6% 6.9% 2.3% -0.1%
Source: National Accounts Statistics for 2014 , Population Census etc.

13. C. Trends on Structural Change in Japan (1955-2015 )
- What’s issues to be solved , How could create new effective demand
and How could STI and Industrial Policies create New Values in Society?-
13
Issues to be solved
1. Lack of Effective Demand Knowledge-based Open Innovation
2. Substitution :Machine vs. Unskilled Labor Develop. of Human Skill
3. Declining Population and Aging Society Immigration & Bio Technology
4. Expansion of Income Differences domestically and internationally
5. Unstable Conflicts among countries with Perception Gaps
6. Crisis of the Moral Sentiments
「Knowledge-based Open Innovation」
To dismantle the pyramid hierarchy
To create a new knowledge-based Division of Labor
by Information Technology and other Trans-Sciences

14. 14
- Expected Demographic Change in Japan-

15. 15
Demographic Development of Japan (2015 vs. 2060)

16. 16
Sophistication
ofBusiness
Process
Large-scale
Computer
Optimal Business
System
SophisticationofManufacturingProcess
Industrial
Revolution
Implementation of
Manufacturing
Process
Display Data
Channel (DDC)
Programmable Logic
Controller(PLC)
Fieldbus
Transmission Control
Protocol/Internet Protocol
(TCP/IP)
Total Control of
Manufacturing by
IoT/CPS
Creating Service
Platform
Increasing Efficiency of
function
(AI/Robotics)
 How to create the efficiency and architect the structure of manufacturing industry.
 In manufacturing it would be expected to increase the productivity in the production
process and consolidate the processes by deepening the ICT technologies.
 How to reach to a high-level of the network efficiency by implementing the new
research and development investment.
Digitalizing Information
Optimizing Basic Business Process
Systematic Creation by ICT
Digitalization of Control
Local Surveillance & Control
Network Surveillance & Control
LAN
Stand-alone System
Internet
Increasing Network efficiency
Increasing the importance of the new design for digital economy
- Knowledge & Function-based Division of Labor proposed by Babbage Concept -

17. Knowledge-Function Based Division of Labor
- Horizontal Division of Labor by Sharing Information -
17
Domestic Final Demand & Export
Consumption & Investment
Commerce Delivery
Medical Care Education
Other S.
Information Platform
Consumer & Service Sectors
Network
Main Manufacturing industries
Parts Makers
Network
Material Products
Network
Information Platform
Service Sectors & Manufacturing
Information
&
Communication
Technology
Knowledge Stock as Intangible Assets
Translational Sciences
R&D Investment
Public & Private
Institutions
Big-Data
Consumer
Needs
Information
Service
Needs
Information
/ Knowledge Stock as Intangible Assets
creates the base of the Platform.
/ Information Technology provides the
background of the Platform.
/ Big-Data provides the information of
the market needs for consumers and
producers.
/ IoT: ICT & Artificial Intelligent (AI)
1Cloud
Computing
Technology
B2C
B2B

18. Main
Fabrication
Parts
Assembly
Material
Products
Material
Products
Parts
Assembly
Material
Products
Main
Fabrication
Parts
Assembly
Material
Products
Material
Products
Parts
Assembly
Material
Products
What kind of “Division of Labor “ has been realized in Japan ?
Final Demand for Consumption and Investment
20th Century Type Industry
- Pyramid hierarchy with vertical segmentation
- Keiretsu system
- Indirect communication system with customer
21st Century Type Industry
- Cross-Industrial Platform-typed business with horizontal
specialization
- Mutual communication system with customer
Industrial Policy: Rationalization Policy & Public
Financial Institution
Industrial Policy: Rationalization Policy & Public
Financial Institution
Creation & Control Effective Demand Policy
Creation & Control Effective Demand Policy
Supply Chain System for Machinery Industry

19. 19
4. Construction of Policy Simulator
1. Analytic Framework of the structural change of economy:
Data Base for General Interdependency of the Economy -
commodity industry
Final Demand
Domestic E M Output
commodity.
industry.
non-competitive
import
value
added
Output
Intermediate
Input Transaction
Absorption Matrix
(Industry x Commodity)
Use Matrix
(Commodity x
Industry)
Consumption
Investment
Government
Factor Inputs
(Labor & Capital )

20. Data Framework: Production Activity by sector
Inter-
mediate
Input
Xij
Capital
Input
Kj
Labor
Input
Lj
Output Xj
Sector Classification
・Industrial sectors except research institutes by government and
industry are divided into the following three sectors:
i) Main products: commodity or service
ii) Intra-firm ICT activity : self-produced ICT intangible prods.
iii) Intra-firm R&D activity: self-produced R&D intangible prods.
・ R&D activities by industry and government as independent
research institute are divided into 10 research fields like life, ICT,
environment, materials, energy, space, oceanography, other natural
sciences and social sciences & humanity.
Factor Inputs :
Capitalization of Intangible Assets(R&D stock & IT stock)
・ Capital inputs are measured by quantity & price of the capital
services which were imputed from capital stock and capital cost.
・ Capital stocks & capital cost are measured consistently with
IO tables as for tangible and intangible assets.
・ Intangible assets are separately estimated by software and
knowledge stock in research fields.
・ Capital formation matrices by flow and stock for
tangible and intangible assets were estimated annually.
Labor
・ Labor inputs by sector and activity are separately estimated .
Knowledge-Flow I-O Table
Sector j ( j=1,//n) Research Institute
20
MainProducts
Intra-firmICTActivity
Intra-firmR&DActivity
IndependentResearchActivity（Industry)
ResearchInstituteActivity(Government)

21. 21
1 2 3 4 5 6 7 8 9 10 11 12 13
Industry Activity
1 ・・・・・j
Intra-Firm ICT
Activity 1,・・・・・, j
Intra-Firm R&D
Activity 1,・・・・・, j
Public R&D
Activity
Industry Activity
k ・・・・・m
Intra-Firm ICT
Activity k・・・・m
Intra-Firm R&D
Activity k・・・・m
Industry R&D
Activity
ICT Industry
Activity n ・・・・・, r
ICT Industry Intra-Firm
R&DActivity n ・・・・・, r
Industry Activity
s ・・・・・x
Intra-Firm ICT
Activity s・・・・x
ICT Industry Intra-Firm
R&DActivity s ・・・・・x
Private Household Consumption Government
Consumption
Private Fixed-
Capital Formation (Tangible)
Private Fixed-Capital
Formation (Intangible)
Public Fixed-Capital
Formation (Tangible)
Public Fixed-Capital
Formation (Intangible)
Export （less） Import Output
1
Industry Activity 1 ・・
・・・j
● ● ●i=1,・・j-●１
2
Intra-Firm ICT
Activity 1,・・・・・, j
u
3
Intra-Firm R&D
Activity 1,・・・・・, j
▲１ ▲２ ▲３ ▲５
●１−（ΣI=1〜５▲＋▲１）＋▲１ ▲１ ▲１
●1
4
Public R&D Activity
● ● ● ● 0 ● ●A ●A＋●B ● ●G
R&D-●２
5
Industry Activity k ・・
・・・m
● ● ●i=k,・・m-●3
6
Intra-Firm ICT
Activity k・・・・m
u
7
Intra-Firm R&D
Activity k・・・・m
▲１ ▲２ ▲３ ▲５
●３−（ΣI=1〜５▲＋▲３）＋▲３ ▲3 ▲3
●3
8
Industry R&D
Activity
●α ●β 0 ●γ 0 ●δ
●α＋β＋γ＋δ+●G
● ● ●I
R&D
9
ICT Industry
Activity n ・・・・・, r
u u ● u ● u ●i=n,・・o-●4
10
ICT Industry Intra-Firm
R&DActivity n ・・・・・, r
▲１ ▲２ ▲３ u ▲５
●４−（ΣI=1〜５▲＋▲４）＋▲４ ▲4 ▲4
●4
11
Industry Activity s ・・
・・・x
●1 ●3 0 ●4 0 ●5 ●6 ●7 ●
12
Intra-Firm ICT
Activity s・・・・x
● ● u ●i=p,・・x-●5
13
ICT Industry Intra-Firm
R&DActivity s ・・・・・x
▲１ ▲２ ▲３ ▲５
●５−（ΣI=1〜５▲＋▲５）＋▲５ ▲5 ▲5
●5
Value-added Labor Input
●
Production Labor Input LJ (J=1・・J） LJ (J=k・・m） LJ (J=o・・・r） LJ (J=s・・・x）
Intra-Firm ICT Labor Input
LITJ (J=1・・J） LITJ (J=k・・m） LITJ (J=o・・・r） LITJ (J=s・・x）
Intra-Firm R&D Labor Input
LNJ（J＝１・・J) LNJ（J＝k・・m) LNJ（J＝s・・x)
Public R&D Labor Input
LNG
Private R&D Labor Input LNPI
Value-added Tangible Capital Service
Input
Production Tangible Capital
Service Input KJ(J=1,・・・,J) KJ(J=k・・・m) KJ(J=o・・r) KJ (J=s・・x)
Intra-Firm ICT Tangible Capital
Service Input
KITEJ (J=1・・・J) KITEJ (J=k・・・m) KITEJ (J=o・・r) KIITEJ (J=s・・x)
Intra-Firm R&D Tangible Capital
Service Input
KRDEJ (j=1・・・J) KRDEJ (J=k・・m) KRDEJ (J=s・・x)
Intra-Firm ICT Intangible Capital
Service Input
KNITEJ (J=1・・J)
Intra-Firm R&D Intangibel Capital
Service Input
KNRDEJ (J=1・・J) KNRDEJ (J=k・・m)
KNRDEJ (J=s・・
x)
Public R&D Tangible Capital Service
Input
KG
Public R&D Intangible Capital
Service Input
KNG
Industry R&D Tangible Capital
Service Input
KPI
Industry R&D Intangible Capital
Service Input
KNPI
Depreciation (tangible Assets)
DEPK
J (J=1・・J) DEPKI
J (J=1・・・J) DEPKG
DEPK
J (J=K・・N) DEPKI
J (J=k・・m) DEPPKI[
DEPK
J (J=o・・r) DEPKIT
J (J=o,・・・r) DEPK
J (J=s・・x) DEPKIT
J (J=s・・x)
Depreciation (intangible Assets)
DEPKN
J (J=1・・J) DEPKNG
DEPKN
J (J=K・・N) DEPKPIN
DEPKN
J (J=S・・N)
Value-added Total
△ △ △ ● ● △
Output ●i=1,・・j-●１ ●1 ●2 ●i=k,・・m-●3 ●3 ●I
R&D ●i=n,・・o-●4 ●i=p,・・x-●5 ●5
Input-Output Table with ITC and R&D Activities

22. 22
Framework of Value-added in Input-Output Table
Industry
Activity
1 ・・・・・j
Intra-Firm
ICT
Activity
1,・・・・・, j
Intra-Firm
R&D
Activity
1,・・・・・, j
Public
R&D
Activity
Industry
Activity
k ・・・・・m
Intra-Firm
ICT
Activity
k・・・・m
Intra-Firm
R&D
Activity
k・・・・m
Industry
R&D
Activity
ICT
Industry
Activity
n ・・・・・, r
ICT Industry
Intra-Firm
R&DActivity
n ・・・・・, r
Industry
Activity
s ・・・・・x
Intra-Firm
ICT
Activity
s,・・・・・, x
ICT
Industry
Intra-Firm
R&DActivity
s ・・・・・x
Intermediate
Input ( total)
Value-added
Labor Input
●
Production
Labor Input
LJ (J=1・・J） LJ (J=k ・・m） LJ (J=o・・・r ） LJ (J=s ・・・x ）
Intra-Firm ICT
Labor Input
LITJ (J=1・・J） LITJ (J=k ・・m） LITJ (J=o・・・r ） LITJ (J=s ・・x ）
Intra-Firm R&D
Labor Input
LNJ（J＝１・・J) LNJ（J＝k ・・m) LNJ（J＝s ・・x )
Public R&D
Labor Input LNG
Private R&D
Labor Input LN
PI
Value-added
Tangible
Capital Service
Input
Production
Tangible Capital
Service Input
KJ(J=1,・・・,J) KJ(J=k・・・m) KJ(J=o・・r) KJ (J=s・・x)
Intra-Firm ICT
Tangible Capital
Service Input
KITEJ
(J=1・・・J)
KITEJ
(J=k・・・m)
KITEJ
(J=o・・r)
KIITEJ
(J=s・・x)
Intra-Firm R&D
Tangible Capital
Service Input
KRDEJ
(j=1・・・J)
KRDEJ
(J=k・・m)
KRDEJ
(J=s・・x)
Intra-Firm ICT
Intangible
Capital Service
Input
KNITEJ
(J=1・・J)
Intra-Firm R&D
Intangibel
Capital Service
Input
KNRDEJ
(J=1・・J)
KNRDEJ
(J=k・・m)
KNRDEJ
(J=s・・x)
Public R&D
Tangible Capital
Service Input
KG
Public R&D
Intangible
Capital Service
Input
KNG
Industry R&D
Tangible Capital
Service Input
KPI
Industry R&D
Intangible
Capital Service
Input
KNPI
Depreciation
(tangible
Assets)
DEPK
J
(J=1・・J)
DEPKI
J
(J=1・・・J)
DEPKG
DEPK
J
(J=K・・N)
DEPKI
J
(J=k・・m)
DEPPKI[
DEPK
J
(J=o・・r)
DEPKIT
J
(J=o,・・・r)
DEPK
J
(J=s・・x)
DEPKIT
J
(J=s・・x)
Depreciation
(intangible
Assets)
DEPKN
J
(J=1・・J)
DEPKNG DEPKN
J
(J=K・・N)
DEPKPIN DEPKN
J
(J=S・・N)
Value-added
Total
Output ●i=1・・ｊ
●i=1・・ｊ ●i=1・・ｊ ●2 ●i=k,・・m
●i=k,・・m ●i=k,・・m ●I
R&D ●i=n,・・o
●i=n・・o ●i=p,・・x
●i=p・・x ●5

23. 23
Frameowrk of Final Demand In Input-Output Table
Intermediat
e Input （ｊ
＝１、・・ｘ）
Private
Consumption
Expenditure
Government
Consumption
Expenditure
Private Capital Formation
Matrix ( Tangible)
Main ICT R&D
（ｊ＝１、・・・、ｘ）
Private Capital Formation
Matrix ( Intangible)
ICT R&D
（ｊ＝１、・・・、ｘ）
Public Capital Formation
Matrix ( Tangible)
Main ICT R&D
（ｊ＝１、・・・、ｘ）
Public Capital Formation
Matrix ( Intangible)
ICT R&D
（ｊ＝１、・・・、ｘ）
Inventry
Increase and
Othres Export (Less) Import
Industry
Activity
1 ・・・・・j xiｊ
Ci
(i=1,j)
GCi
(i=1,j)
INVK(i=1,・・x,J=1,・・j）
INVKG、
INVKITG,INVKRDG
(i=1,・・ｘ, ｊ=G)）
Intra-Firm
ICT
Activity
1,・・・・・, j
xiｊ INVK(i=1,・・x,J=1,・・j） INVKNITE(i=j、i=1,・・j）
Intra-Firm
R&D
Activity
1,・・・・・, j
xiｊ ( i=1,..j
j=1,..,x)
INVK(i=1,・・x,J=1,・・j） INVKNRDE(i=j,i=1,・・j）
Public
R&D
Activity
xiｊ (
i=G,j=1,..,x)
INVKITGii(i=1,・・ｘ）
INVKITGij (i≠j) =0
Industry
Activity
k ・・・・・m
xiｊ ( i=
ｋ・・・ｍ
j=1,..,x)
Ci
(i=k,m)
GCi
(i=k,m)
INVK(i=1,・・x,J=k,・・m）
INVKG、
INVKITG,INVKRDG
(i=k,・・m, ｊ=G)）
Intra-Firm
ICT
Activity
k・・・・m
xiｊ ( i=
ｋ・・・ｍ
j=1,..,x)
INVK(i=1,・・x,J=k,・・m） INVKNITE(i=j,i=ｋ,・・ｍ）
Intra-Firm
R&D
Activity
k・・・・m
xiｊ ( i=
ｋ・・・ｍ
j=1,..,x)
INVK(i=1,・・x,J=k,・・m）
INVKNRDE(i=j, i=k,・・
m）
Industry
R&D
Activity
xiｊ ( i=PI、
j=1,..,x)
INVKPI(i=1,・・x,J=PI） INVKNPI(i=j, j=PI）
ICT
Industry
Activity
n ・・・・・, r
xiｊ ( i=
ｎ,・・.ｒ,
j=1,..,x)
Ci
(i=n,r)
GCi
(i=n,r)
INVK(i=1,・・x,J=n,・・r）
INVKG、
INVKITG,INVKRDG
(i=ｎ,・・ｒ, ｊ=G)）
ICT
Industry
Intra-Firm
R&DActivity
n ・・・・・, r
xiｊ ( i=
ｎ,・・.ｒ,
j=1,..,x)
INVKRD
(i=1,・・x,J=n,・・r）
INVKNRDE(i=j, i=n,・・
r,）
Industry
Activity
s ・・・・・x
xiｊ ( i=s,..x
j=1,..,x)
Ci
(i=s,x)
GCi
(i=s,x)
INVK(i=1,・・x,J=s,・・ｘ）
INVKG、
INVKITG,INVKRDG
(i=ｓ,・・ｘ, ｊ=G)）
Intra-Firm
ICT
Activity
s,・・・・・, x
xiｊ ( i=s,..x
j=1,..,x)
INVK(i=1,・・x,J=s,・・ｘ） INVKNITE(i=j,i=s,・・・ｘ）
ICT
Industry
Intra-Firm
R&DActivity
s ・・・・・x
xiｊ ( i=s,..x
j=1,..,x)
INVK(i=1,・・x,J=s,・・ｘ） INVKNRDE(i=j, i=s,・・ｘ）

24. Policy Options
Policy Patterns
24
Alternative
Policy
Instruments
＋
Assessments of
Impacts on
Economy &
Society
Here, we will show an experiment to make alternative policy options for designing
IoT/CPS Policies to create the market by platform.
Concepts of Policy
Options
2. “Policy Simulator” and Making “Policy Options”
Creating “Policy Simulator” to assess the impacts of policy
instruments on the economic structure as alternative policy options.
Policy
Targets
Policy
Simulator

25. 25
内生変数 (t期)
・有形固定資本ストック
・無形固定資本ストック
外生変数:
生産プロセス別技術効率指数
P-index(i)
t期j部門別国内財価格
a) 産業部門生産活動部門
b) 企業内情報処理サービス部門
c) 企業内R&D 部門
d) 民間企業内R&D 部門
e) 政府研究機関 R&D 部門
付加価値の算出
最終ブロックの算出
産出量の算出
t期
t+1期
労働ブロック
長期生産ブロック
最適資本ブロック
投資需要
部門別供給量
政府ブロック
部門別供給量の
想定初期条件
3/22/2015
Overview: Structure
of our Multi-sectoral Economic Model
for General Interdependency
Pre-determined
Endogenous
Variables
Capital Stock & Wage(t)
Exogenous
Variables
Technology
Scenario & Population
Domestic Production Prices
Operation hours by Labor
Man-hour Labor Demand
Value- added by sector
Income: household &
Firm
Final Demand
Consumption,
Investment, Export
Output by sectors
Exogenous
Variables
Government
Expenditure
Endogenous
Variables
Tax Revenue
Labor Market
Labor Supply vs. Demand
Wage Rate (t+1)
Long-run
Technology
Choice
Determination of Optimal
Capacity at the year t+1
Capital & Labor Input(t+1)
Investment
By sector
Tangible & Intangible
Optimal Capital Stock &
Labor Inputs at the next year
Demand & Supply
Equilibrium
Short-
Run
Long-
Run

26. 26
3. Characteristics: Model for Policy Simulation
Characteristics of Model
・CGE Model: Base Year 2005
・Term of Simulations: 2005 ~ 2050
・Exogenous Scenario:
① Population Trends: 2005~2050 estimated by NIPSCR.
② Technology Trends: Public R&D Investment Scenario and Productivity
growth by Information & Communication Technology
・Sector Classification: Total 93 Industrial Sectors as follows.
* Sector is divided into Main Products and Intra-Firm R&D Activity.
** Sector is divided into Main Products, Intra-form Information management
Activity and Intra-firm R&D Activity.

27. 27
Num. Industry Num. Industry Num. Industry
001 Agri. 038 Semi-comductor 074 Software
003 Mining 041 Other Elect. 076 ICT Serv.
005 Food 044 Transp.Mach. 078 Internet
008 Textile 047 Robot 080 Med. Care
011 Paper 050 Precision 081 Education
014 Chemical 053 Oil Prod. 092 Other Serv.
017 Material 056 Other Mnf. 082 Gov. R&D (Life)
020 Genreral Mach. 059 Energy 083 Gov. R&D (ICT)
023 Elect.Mach. 062 Construct. 084 Gov. R&D (Material)
026 Cable 065 Transport 085 Gov. R&D (Energy)
029 Semicon.Instr. 068 Commu. Serv. 086 Gov. R&D (Others)
032 Comm. Mach. 071 Whole S.
035 Computer 092 Other Serv.
Industry Classification
Main
ICT
R&D
Main
R&D

28. Base Case Scenario :Exogenous Assumptions
28
Assumption 1：No Expansion of Government R&D Expenditure during 2002-2050.
Assumption 2:Science knowledge stock accumulated by the government R&D
expenditure is assumed to have an impact on the productivity increases in the
private sectors as public goods.
Assumption 3: All of tax rates including personal income tax, corporate income tax,
consumption tax, indirect, tax and property tax will be fixed at the 2005 level rates.
Assumption 4: Government consumption expenditure will be assumed to be proportional
to nominal GDP endogenously.
Assumption 5: Government capital formation for tangible and intangible assets will be
fixed at the 2005 level nominally.
Assumption 6: Structure of the population will be assumed to be given by the projections
with fertility medium-variant case by National Institute of Population and Social
Security Research.
In the Base scenario, it will give us the overview of the economic and social trend until 2050
from the year 2005. There are no any positive science policies as well as economic policies by
government, although the structural changes of the population by age and gender will be
assumed exogenously.

29. Base Case Scenario :Exogenous Assumptions
29
Assumption 1：Government R&D expenditure are classified into five science fields such
as information, life, energy, material and others. Concerning information, life, energy
and material sciences, we assume that the government R&D expenditure in tangible
and intangible assets will be expanded 10% of the nominal amount of the 2005
investment during the period 2015-2019 exogenously.
Assumption 2:Science knowledge stock accumulated by the government R&D
expenditure is assumed to have an impact on the productivity increases in the
related private sectors as public goods. The science knowledge stock for each
science field will be assumed to realize 10% and 5% TFP increase in the short-run
production function and the log-run cost function independently during the period
2020-2025.
Assumption 3: All of tax rates including personal income tax, corporate income tax,
consumption tax, indirect, tax and property tax will be fixed at the 2005 level rates.
Assumption 4: Government consumption expenditure will be assumed to be proportional
to nominal GDP endogenously.
Assumption 5: Government capital formation for tangible and intangible assets except
government R&D related investment will be fixed at the 2005 level nominally.
Assumption 6: Structure of the population will be assumed to be given by the projections
with fertility medium-variant case by National Institute of Population and Social
Security Research.
Sensitivity Analysis for Changes of Government R&D Investment
- Science fields : Information, Life, Energy and Material Sciences -

30. 4. Comparison: Base Case .vs. Science Promotion Scenario
30
(1) GDP trend of Base Case Scenario Cases and ICT Promotion Case
Most Miserable Scenario in the Japanese Future
In Base Case, Real GDP will be forecasted to be stagnating until 2050.
R&D Increased Case: Information & Communication Technologies will be developed by
10% increases of the 2005 level of the government R&D expenditure during 2015-2019
Annually and the accumulations of the knowledge stock as public goods are expected to the
productivity gain in the related industries after 2020
.
Real GDP Trend ( Base Case vs. R&D(Ict)) Increased (million yen)
Real GDP Trend ( Base Case vs. R&D(Ict+Life) Increased
-1,000,000
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
8,000,000
495,000,000
500,000,000
505,000,000
510,000,000
515,000,000
520,000,000
525,000,000
530,000,000
Increments
Base Case
ITC

31. Comparison on the Impacts among science fields
- GDP(Real & Nominal) and GDP Deflator :Annual Growth Rate -
31
R&D Increased Case: R&D investment in tangible and intangible assets by Government will
be expanded by 10% increases of the 2005 level of the government R&D expenditure
during 2015-2019 annually and the accumulations of the knowledge stock as public goods
are expected to the productivity gain in the related industries during the period 2021-2025.
.
Comparison of Annual Growth Rate of Real GDP by Policy Simulations(%)
agr:RGDP 2005-2015 2015-2025 2035-2025 2035-2045 2045-2050
Base -0.194 -0.077 0.015 0.116 0.259
Base+ITC -0.194 0.047 0.018 0.102 0.269
Base+ITC+Life -0.191 0.090 0.018 0.102 0.270
Base+ITC+Life+Energy -0.191 0.104 0.017 0.103 0.270
Base+ITC+Life+Energy+Material -0.191 0.149 0.018 0.100 0.269
Comparison of Annual Growth Rate of Nominal GDP by Policy Simulations(%)
agr:RGDP 2005-2015 2015-2025 2035-2025 2035-2045 2045-2050
Base 1.917 2.525 3.568 6.180 8.654
Base+ITC 1.917 1.902 3.041 5.357 7.367
Base+ITC+Life 1.919 1.878 3.031 5.342 7.344
Base+ITC+Life+Energy 1.919 1.870 3.027 5.336 7.336
Base+ITC+Life+Energy+Material 1.919 1.808 3.005 5.295 7.273
Comparison of Annual Growth Rate of GDP Deflator by Policy Simulations(%)
agr:RGDP 2005-2015 2015-2025 2035-2025 2035-2045 2045-2050
Base 1.917 2.525 3.568 6.180 8.654
Base+ITC 1.917 1.902 3.041 5.357 7.367
Base+ITC+Life 1.919 1.878 3.031 5.342 7.344
Base+ITC+Life+Energy 1.919 1.870 3.027 5.336 7.336
Base+ITC+Life+Energy+Material 1.919 1.808 3.005 5.295 7.273

32. Impacts on Real GDP Increases by R&D Investment
Accumulated Impacts by Scenarios
32
(２) Comparison of GDP Increases by Scenario Cases
Impacts on Real GDP by R&D Investment on Science Fields
: Information, Life, Energy and Material
-2000000
0
2000000
4000000
6000000
8000000
10000000
12000000
14000000
2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037 2039 2041 2043 2045 2047 2049
Real GDP increments due to 10% Government R&D Increments of 2005 level by Science Fields
during 2015-2019: Unit: 1 million yen
ΔGDP (ICT-Base) ΔGDP （(ICT＋Ｌｉｆｅ）-ICT) ΔGDP((ICT+Life+Energy)-(ICT+Life) ΔGDP((ICT+Life+Energy+Material)-(ICT+Life+Energy)

33. 5. Problems to be solved in the Base Case
33
1) Existence of “Disguised Unemployment”
Because of the declining growth rate of real GDP, real working
hour(or operation hour) will be down comparing with the normal
operation hour. In the labor market, working share will be forced to
accomplish the full employment. It means that the so-called “disguised
unemployment” will be appeared in some industries.
0
500
1000
1500
2000
2500
3000
3500
4000
2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037 2039 2041 2043 2045 2047 2049
Index for Number of Lack of Employee
Main Production Activity:Unit 1000 persons
R&D Investment increases in ICT,Life&Energy Sciences

34. 34
Problems to be solved in the Base Case contd.
How to create the Platform Business?
0
0.01
0.02
0.03
0.04
0.05
0.06
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93
Intermediate Input Coefficient Aij:Information
Service to Others
2010 76 2030 76 2050 76
0
0.005
0.01
0.015
0.02
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93
Intermeiate Input Coefficient Aij: Software
to Othres
2010 74 2030 74 2050 74
Increasing the productivity of ICT sectors will encourage the “out-sourcing” of
the intra information activity to the ICT specific industry. It will create new
“Platform Business”, by which new effective demand will be able to expand.

35. Relation Factor Price vs. Capital/Labor Ratio.
35
038: Semiconductor
062: Construct.
081: Education.
053: Oil Product.
078: Internet.

36. Relation Factor Price vs. Capital/Labor Ratio.
36
053: Oil Product. 053: Oil Product.
081: Education.
081: Education.062: Construct.
062: Construct.
038: Semiconductor
038: Semiconductor
078: Internet.
078: Internet.

37. 37
Contribution of Factors and TFP on Annual Growth of
Production
-3.00%
-2.00%
-1.00%
0.00%
1.00%
2.00%
3.00%
4.00%
2010 2020 2030 2040 2050
078 Internet Main Product Activity
ICT Case: Contribution of Factors and TFP on
Annual Growth of Production
Intremediate Input (domestic) Intermediate Input(Import)
Buss.Consumpt. Labor
Capital Indirect Tax
(less)Subsidies TFP
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
15.00%
2010 2020 2030 2040 2050
079 Internet R&D Activity
ICT Case: Contribution of Factors and TFP on Annual
Growth of Production
Intremediate Input (domestic) Intermediate Input(Import)
Buss.Consumpt. Labor
Capital Indirect Tax
(less)Subsidies TFP

38. 6. Assessment and Evaluation of the Promotion of IoT
 How to evade the risk of unemployment by substitution between machine and labor?
 Is it possible to create new market demands by the introduction of ITC?
 What is the role of the platform in ITC world?
 What is the difference in the forms of division of labors between traditional
production processes and information network processes.
Deepening
Information &
Communication
Technologies
Risk of
Unemployment
Declining
Wage rate
Increasing
Productivity
Alternative
Policy
Instruments
・How to
make
balance?
・How to
create
Market
demand?

39. 39
Process control
surveillance and
Decision by
human
Basic surveillance &
control by sensor
actuator by ICT
(Collection of local
data)
Basic automatic
control by local
network
Visualization of the
knowledge of the
skilled labor
Large scale
management and
analysis of data
Network Efficiency
Security Control
Network of field path
Increasing efficiency
of data analysis and
developing process
controlling technology
Machine learning &
artificial intelligence
Big data management
Artificial
intelligence
Encouraging new
platformer business
across various
processes and
industries
Step1.
Productivity Gaines due
To the Sophistication of
individual production process Step2.
Creation of the new
market demand due to the
outsourcing activities
Step3.
Expanding market demand for new goods and
services
Creating new productivity gains in industry
Step4.
Creation of new
markets in B to B &
B to C
Sophisticating functions and Scaling Data base
Downsizing &
Sophisticating
Sensor
Data Processing
and analyzing by
the production
process unit
ConsolidatingandNetworking
Needed Technology ①
Real time assessment of
the situation of the
activities in each
production process
Needed Technology ②
Construction of data base
for knowledge and
knowhow
and basic control in each
production process by
accumulated data
Needed Technology ③
Construction of Vertical Platform
across industries
Scenario for Productivity Gaines by IoT Development

40. Production Process
Impacts on Economy
40
 Productivity gains by IoT/CPS will be expected to have impacts on various
processes.
 Productivity gain in each production process is assumed to be exogenously given
numerically by “Productivity Index”, which is corresponding to the scenario of
technology development.
Marketing
P-Index(1)
Planning
P-Index(2)
Design
P-Index(3)
Logistic
P-index(4)
Production
P-index(5)
Op. & Sales
P-Index(6)
Maintenance
P-Index(7)
Inf. On Short-run
Market
・Market share
・Conjectural
Variation
Impacts on Short-run Supply Behavior：
P-Indexｔ(i) & Knowledge stock
Inf. On Production
Capacity
Inf. on Long-run
Expected Demand
・Investment/Capacity
Inf. On Long-run
Cost Function
・ Technical Progress
・ Factor Cost
Impacts on Long-run Technology
Choice: P-Indext+1(i)
Structure of Prices
Step1.
Productivity Gaines due to
the Sophistication of
individual production process
Step2.
Creation of the new market
demand due to the outsourcing
activities
Step3.
Expanding market demand for new
goods and services
Creating new productivity gains in
industry
Development Steps of
IoT/CPS
Logic Chart for Productivity Gaines by IoT Development

41. Increases of
Productivity
due to
developing
ICT
Production
Efficiency
Increases in
Manufacturing
Price Declining
due to Productivity
Gains
Private
Consumption
Expanding
Outsource
In Intra-firm
ICT Activity
・Productivity gain will be
expected to shift the supply
curve broadly.
・Consumer behavior is
expected to change by ICT.
Increases in
Manufacturing
Production
・ICT related goods and
investment goods.
Changes of
Employment
・Employment in ICT related
industry will be expected to
increase, but unskilled labor
may be substituted by
machine.
Increases in
Expected Demand in
the Future
Expanding ICT
Industries and ICT
Network
Expansion of ICT
Investment and
Employment
Increases in
Expected Demand
In Future
・ICT related manufacturing &
service sectors
Declining Price of
Investment Goods
・ICT related manufacturing &
service sectors
Increases of
Expected Rate of
Return
Direct Impacts
due to productivity
Indirect Impacts
due to productivity
Changes of Real
Wage Rate
Changes in
Working Hour
・ Expansion of ICT will have a
big impacts on labor market
due to the substitution between
labor and capital.: so-called
“Technology unemployment”. Private R&D
Investment
Legend：
Logic Chart of Impacts of Productivity Gains by ICT

42. Theory and Observed Facts
• “In contrast to most physical sciences, we study a
system that is not only exceedingly complex but is also
in a state of constant flux. ”
• “In order to know what the shape of these structural
relationships actually is at any given time, we have to
keep them under continuous surveillance.”
• “Without a constant inflow of new data the existing
stock of factual information becomes obsolete very
soon.”
-Wassily W. Leontief, “Theoretical Assumptions and
nonobserved facts”, Presidential address at the 83th
meeting of the American Economic Association, Detroit,
December, 29, 1970.
42

43. Total Solution Model Designing Targeting Policy
・An important & necessary condition is “alternative policy
options”, with consistency and accountability to redesign the
new social and economic structures.
・We need to create “a good translational relationship”
between natural and social & humanity sciences in order to
understand a system that is not only exceedingly complex
but is also in a state of constant flux.
Recent developments such as “Big-Data” are
contributing to contribute on the collection of data that
will be help us redefining neo-classical economics as
we know it.
43
Concluding Remarks:

44. Thank you!
44
kdb.kuroda@gmail.com
http://www.jst.go.jp/crds/scirex/en/
http://scirex.grips.ac.jp