2 0 1 8
SPECIALEDITION

68
RIETI International Symposium

Information Technology
and the New Globalization:
Asia's economy today and tomorrow

BBL Seminar

World's Great Excess of Supply
Energy Markets: What to do when forecasting is useless2018 Special Edition

68

Contents

P1

EventsP2

BBL Seminar

P10

World's Great Excess of Supply

P14

Energy Markets: What to do when forecasting is useless

P18

Special Column by the President

P21

Assessing the Impact of AI and Robotics on Job Expectations Using
Japanese Survey Data

P23

"Power of Data Analysis" Essential to Evidence-based Policymaking

P26

Toward Artificial Intelligence Technologies as an Integral Part of Service
Business Operations

P29

Agglomeration Benefits versus Firm Selection

P32

The "Scientification" of Industry: New indicators of science intensity

P38

Policy Uncertainty in JapanP42

The Dynamics of Inter-firm Networks and Firm Growth

P48

I

P48

R e s e arc h
Activities
Research Digest

RIETI's Fourth
Medium-term Plan

RIETI Highlight?

RIETI International Symposium

Symposium

Columns

What isMessage from the Chairman

Information Technology and the New Globalization:
Asia's economy today and tomorrow

Overcoming Silos and Kakines

Macroeconomy and Low
Birthrate/Aging Population

International Trade and

P48

II Investment

III Regional Economies

P50

Ⅳ Innovation

P50

Ⅴ Industry Frontiers

P50

Ⅵ Productivity

P52

Ⅶ Human Capital

P52

Ⅷ Law and Economy

P52

Ⅸ Assessment

Raising Industrial and Firm

Policy History and Policy

RIETI's Japanese-language PR magazine RIETI Highlight is published quarterly, featuring RIETI's
most recent activities with the objective of disseminating our research outcomes to a wider
audience. This RIETI Highlight 2018 Special Edition is, as its extra number, edited in English andpublished annually for our international readers. We hope this special edition will be helpful not
only in spreading our activities and research findings but also in deepening international readers'
understanding on our mission as a Japanese leading policy think tank.

Message from the Chairman

This edition of RIETI Highlight introduces the main

The world economy continues to recover, thanks to steadyeconomic growth in the United States and China, stable crude

contents of our research achievements, symposiums, etc. thatoil price, sustained monetary easing policies in major countries,

occurred in the past 12 months. All of the contents relate to theand global momentum in IT product sales. The Japanesecurrent conditions and immediate issues of the Japanese andeconomy is also enjoying healthy growth due to favorable

world economy, and therefore should help you deepen yourconditions including monetary easing, recovery of the world

understanding of these matters.

economy, and low energy prices.

In FY2016, RIETI entered a new four-year Medium-term

Yet, although the economy is sound in and outside Japan,

Plan. Under the plan, we employ the mid- and long-term

this does not indicate that the Japanese economy's structural

economic and industrial policy perspectives of "cultivating

issues have been resolved. The pace of productivity increase

Japan's strength in the world economy," "making Japan intois slowing down in Japan and many other major countries.

an innovative nation," and "overcoming population decline"

Together with the deceleration of population increase, thisin continuing to engage in theoretical and empirical researchsituation is applying downward pressure on the rate ofthat contributes to the formulation of economic and industrial

economic growth. At the same time, income disparity continues

policies and providing evidence-based policy recommendations

to widen. How such disparity could be corrected, e.g., throughin the fields of international economy, regional economy, labor

education, is becoming an issue of increasing gravity.

economy, productivity, and innovation. At the same time,

In FY2017, RIETI engaged in far-reaching research

we are committed to actively sharing the outcome of suchactivities, releasing numerous research papers in many fields

research activities in a timely fashion through symposiums

including the macroeconomy, finance, innovation, humanand seminars. Your continued support would be sincerely

resources, energy, environment, and trade policy. Over the lastappreciated.

12 months, we held or co-organized a number of symposiums,
seminars, and workshops covering a wide range of subjects
including Brexit, corporate growth, spatial economic issues oflarge cities, Japan's growth strategy, and the effect of IT andnew globalization on the Asian economy.

About RIETI

Atsushi Nakajima
Chairman, RIETIThe Research Institute of Economy, Trade and Industry (RIETI) is a policy think tankestablished in 2001. Our mission is to conduct theoretical and empirical research, to maximize
synergies with those engaged in policymaking, and to make policy proposals based on evidence
derived from such research activities. For such activities, RIETI has developed an excellent
reputation both in Japan and abroad.

RIETI Highlight 2018 Special Edition1

S y mposium

RIETI International Symposium

Information Technology
and the New Globalization:
Asia's economy today and tomorrow
EventsDate:
Venue:

August 1, 2017
Iino Hall and Conference Center, Tokyo

Host:
RIETI
Co-hosts: Japan Productivity Center (JPC), Hitotsubashi Institute for Advanced Study (HIAS), Grant-in-Aid for Scientific Research (S)Grant Number 16H06322 Project "Service Sector Productivity in Japan (SSPJ): Determinants and Policies"

As major Asian economies face the issue of an aging and lowbirthrate society, for the development of policies that caneffectively improve the economic growth rate, it is necessary
not only to accurately identify the reality of productivity in anindustry or company through the development of a databaseand its analysis, but also to understand the effects of the useof information technology (IT), innovation, and globalization
on productivity. In the first half of this symposium, Professor
Dale Jorgenson of Harvard University and Richard Baldwin,president of the Centre for Economic Policy Research (CEPR),
delivered a lecture on the second phase of Abenomics and theconvergence from the perspective of IT and new globalization,
respectively, in a way that leverages the results of the Asia
KLEMS Conference. In the latter half of the panel discussion,seven participants analyzed the current status of the Asian
economy from the viewpoint of globalization and productivity
and held discussion about its future.

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RIETI Highlight 2017 Special Edition

Welcoming Remarks
Atsushi Nakajima
Chairman, RIETI

Today's RIETI symposium, "Information Technology and the
New Globalization: Asia's economy today and tomorrow" isorganized by RIETI and held jointly with the Japan Productivity
Center and the Hitotsubashi Institute for Advanced Study, in
conjunction with the Fourth Asia KLEMS Conference, which isscheduled to be held in Tokyo.

Sy mp o s iu m

01

Keynote Speech
The Second Phase of Abenomics
Dale W. Jorgenson
Samuel W. Morris University
Professor, Harvard University

We are all familiar with Japan's two lost decades. Since thebeginning of the 1990s, there has been little economic growthand no productivity growth. Japan's policy response to the lost
decades is the theme of my lecture. Prime Minister Shinzo Abeannounced a second phase of Abenomics as an attempt to deal
with long-term issues, opportunities of new globalization, andthe role of IT. Japan is a laggard in the application of IT and has
underinvested in this, the central engine for innovation in theworld economy.
The spread of global economic activities and value chains hastaken on enormous momentum in the last two decades. With
the collapse of Japan's bubble in 1991, a new international orderemerged with India and China overtaking Japan on the list of
the world's largest economies. In fact, China became the world's
largest economy in 2014.

EventsAsia KLEMS is a framework that has been establishedto follow up World KLEMS, a project designed to build aninternational database that allows for conducting international
productivity comparison. World KLEMS is participated byeconomists around the world and led by Professor Dale W.
Jorgenson of Harvard University, who is going to give a keynote
speech at this symposium. Asia KLEMS is part of the global
framework and its key participants from Japan include not only
RIETI but also Professor Kyoji Fukao, program director andfaculty fellow at RIETI and professor at the Institute of Economic
Research, Hitotsubashi University, who will take the podium attoday's symposium.
Needless to say, improvement of productivity is a principal
source of economic growth. In particular, given the rapid pace of
aging and birthrate decline in Japan and major Asian countries
such as China and South Korea, productivity improvement is now
the top priority issue to be solved for continuous and sustainablegrowth.
Under these circumstances, in order to develop policies thatare effective to stimulate economic growth, it is necessary toaccurately identify the reality of productivity in industries andcompanies through the development and analysis of databases like
KLEMS, which I referred to a moment ago, while understanding
the effects of the use of IT, innovation, and globalization on
productivity.
Under the theme of IT in Asia and new globalization, this
symposium will be run by leveraging the results of the Asia
KLEMS Conference. While placing the viewpoint of productivity
at the core, we will welcome participants from overseas,
including Richard E. Baldwin, who is a professor at the Graduate
Institute, Geneva and the president of the Centre for Economic
Policy Research (CEPR), as well as Professor Lawrence J. Lauof the Chinese University of Hong Kong. Professor Baldwin is
the world's top expert on international trade and economy andleads discussions about the changes brought about by IT and new
globalization to the world's economy or trades. Professor Lau
developed the first econometric model of China and has extensive
knowledge and wisdom about Chinese and East Asian economies.
Participants from Japan include Toshitaka Sekine, directorgeneral, Research and Statistics Department, Bank of Japan,
and Professor Kozo Kiyota, research associate at RIETI and aprofessor at the Keio Economic Observatory and Graduate Schoolof Economics, Keio University. These participants will bring awider scope of view to the panel discussion, which will focus on
Asia's economy today and tomorrow.
I strongly believe that the up-to-date reports from these world
authorities and their panel discussion will further enhance yourknowledge and wisdom.

Japan's response to the new world order: Abenomics
This change in the world order provoked a response by Japanby Prime Minister Abe called Abenomics. The first phase of
Abenomics is characterized by the three arrows of aggressive
monetary policy, flexible fiscal policy, and growth strategy. In
early 2016, the prime minister initiated a search for new economic
policy built on the perceived successes of the first phase of
Abenomics.
I was chosen to provide advice on the new phase of Abenomics.
My recommendations were to revitalize the Japanese economy bystimulating productivity growth. I identified non-manufacturingsectors protected from international competition as the primary
focus. The reformulation of Abenomics was completed with theeconomic policy called "Growth Strategy 2017," which I will referto as the second phase of Abenomics.
Issues facing the Japanese economy
First, Japan's productivity growth has stagnated in a period
when technologies have evolved more rapidly than in any period

RIETI Highlight 2018 Special Edition

3

RIETI International Symposiumof economic history. Second, Japan is confronted by a serious
demographic crisis with a fall in the labor force and a declining
population. The third challenge is that government revenues willrise in relation to the gross domestic product (GDP) to financeneeded expenditure and support an aging population.

EventsFirst phase of Abenomics
The traditional Japanese approach to growth was to subsidize
favored industries, which created large companies that stifle
competition. Abenomics aims to drill down through policies thatsustain cartels, stifle competition, and eliminate incentives toinvest in new technologies. The first reform was in agriculture
to diminish the influence of agricultural cooperatives andto participate in trade agreements. Second, efforts are being
made to increase competition in the highly regulated electricand gas utility sector, but doing so has been complicated by
the Fukushima Daiichi nuclear accident. The third would be tostimulate competition by eliminating bedrock regulations invarious industries.
The productivity gap between the United States and Japan at
the aggregate level for the entire economy was 15%. Japaneseindustries with striking productivity gaps include the sectorsof agriculture, energy, finance/insurance, other services,and wholesale/retail trade. These five sectors account for theentire productivity gap between Japan and the United States.
Deregulation of these industries is necessary to stimulatecompetition and improve innovation and investment in IT.
Japanese labor laws need revision to resolve the inefficient
allocation of a shrinking labor force. Trade agreements can also
play an important role in a growth strategy.
Abenomics 2.0: Growth Strategy 2017
When I met with the prime minister and his cabinet, my recipe
was simple: Japan has to end productivity stagnation through a
productivity revolution by promoting competition. The new faceof Abenomics was then created based on three principles. The
first is to boost productivity. The second is to drive innovationand trade. The third is to energize corporate activities.
As for boosting productivity, the first action is to reform thetraditional work style, meaning reforming of the labor market.
The second is to invest in human resources. The third is toembrace diversity in the labor force, or utilizing the elderly andwomen. However, where is the aforementioned drilling down tostimulate competition in cartelized industries in order to increase
productivity?
As for driving innovation and trade, the first objective is toprovide personalized medical care. The second is to have better
distribution services for business emulating Amazon or Alibaba.
The third is to increase productivity in infrastructure. The fourth

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RIETI Highlight 2017 Special Edition

is to promote the development of financial technology. However,specific talk about trade, services, and industries identified aslacking in productivity were all omitted.
The third principle is to energize corporate activities throughcorporate tax reductions, by strengthening investor confidence,and to drive inward foreign investment to facilitate technology
transfer.
Conclusion
In order for the Japanese economy to exploit ongoing IT
developments, there must be competition to drive investment andinnovation. This seems to be a key missing part of Abenomics
2.0. The second arrow of the first phase of Abenomics shouldbe abandoned for energetic reform and restoring fiscal balancethrough a shift of taxation away from investment toward
consumption. A growth strategy should be focused on adapting to
the changing world economy and the development of global value
chains. We need concrete demonstrations of initiatives to improve
productivity in Japan, which was precisely what generated
widespread support for the first phase of Abenomics.

02

Keynote Speech
The Great Convergence: Information
technology and the new globalization
Richard E. Baldwin
President, Centre for Economic
Policy Research (CEPR) /Professor of International
Economics, Graduate InstituteGenevaToday, I'd like to broaden the way you think about globalization.
Let's begin with a definition: globalization is what happens
when goods, ideas, people, services, and capital move from one
nation to another. The driving force behind the internationalflows of these things is arbitrage. Whether it is goods, services,
ideas, people, or capital, things tend to flow from where they
are abundant and thus cheap to where they are scarce and thus
expensive. When thinking about trade in goods, this arbitrage iscalled "comparative advantage."
In my 2016 book, The Great Convergence, I argue that the
global nature of globalization has changed in recent decades. In
1990, G7 countries accounted for about 70% of manufacturing
output; that percentage has fallen to below 50% as China, Korea,
India, Poland, Indonesia, and Thailand increased their shareSy mp o s iu m

Rethinking globalization
The traditional mental model for thinking about globalization istrade theory—in particular variants on David Ricardo's theory ofcomparative advantage. I think that did a good job of explaining
how globalization worked from its earliest start around 1820 rightup to 1990. But although comparative advantage still matters,
there is a new form of globalization going on.
To understand this, I invite you to suspend your disbelief andask yourself the question, "What if globalization were driven byknowledge flows, not trade flows?" Suppose that everything is
made from know-how and labor, trade costs and barriers havenot changed since 1990, and in that same year "pipelines" opened
that allowed firms to move know-how across borders. Assume
the pattern of pipelines to be the United States connected to
Mexico and China, Germany to China and Poland, and Japan to
China. In the 20th century, competition was done either with hightech and high wages or low tech and low wages. However, withthe pipelines, G7 country companies can take their know-how
and combine it with low-wage labor abroad. The manufacturingthat used to be competitive in G7 countries because theirtechnological edge outweighed high wages would be moved tohigh technology and low wages. This would cause a rapid shiftof knowledge (and therefore manufacturing) from G7 countries
to the factory economies connected by the pipelines. Knowledge
pipelines led to an information and communications technology(ICT) revolution.
Three costs that constrain globalization and the great
convergence
I would like to combine the idea of globalization as knowledge
with the traditional view of globalization to form a broader
perspective on globalization. There are three costs that form
three constraints on globalization: trade costs, communication
costs, and face-to-face costs. The steam revolution and Pax
Britannica lowered trade costs without much affecting the othertwo costs. Low trade costs made high-volume trade feasible andcomparative advantage made it profitable. The steam revolution
unbundled production and consumption, which is when
specialization started. As markets expanded globally, production
clustered locally to reduce communication costs, not trade costs.
Micro-clustering fostered innovation and ignited the bonfire ofinnovation and modern growth in G7 countries.
However, high communication costs meant G7 innovations
stayed in G7 nations and know-how imbalances appeared. Preglobalization knowledge between the rich and poor nations werefairly even. Afterwards, most of the knowledge was in the richcountries. That led to the "great divergence" where poor countries
stayed poor and formerly rich countries such as China and India
became poor. This was because trade costs came down, but
communication costs did not. The ICT revolution lowered the costof moving ideas and made offshoring feasible, while vast wage
differences made it profitable. "New globalization" is information
crossing borders. This is what led to the "great convergence"
where countries such as China and India have started to reclaim
their share of GDP as the G7's share of GDP drops.
Explaining the rise of anti-globalization
The first cause of anti-globalization is that the new globalization
breaks the monopoly that G7 labor had on G7 know-how.
Technology developed in G7 countries was moved offshore.
This broke the social contract between companies and workers.
Second, new globalization affects economies with a finer
resolution. As an example, in old globalization, international
competition happened at the level of completed products, such
as Japanese cars entering the U.S. market. In new globalization,international competition happens at the level of individual jobs.
This is no longer team Japan versus team United States, but rather
the United States getting mixed up with Japan. This makes it
hard to understand what is going on. These combined two factors
led to economic anxiety, fragility, and disenfranchisement in
G7 nations. The impacts of new globalization are more sudden,
more individual, more unpredictable, and more uncontrollable.
Any worker could lose their job next regardless of the skills they
possess.

Eventsof manufacturing. The change in G7's share of GDP share was
equally dramatic, with G7 countries accounting for 67% in 1993
and 46% in 2014.

Future of globalization
Although I started with the negatives of globalization, thesechanges are probably going to allow people to better leverage theirknow-how. Thinking about the future, I would like to speculate
about whether globalization will advance or retreat in the next five
years. I think the next step of globalization is going to be moredisruptive. Face-to-face costs remain high, and two-thirds of thepeople in rich countries who work in the service sector have notyet experienced globalization or automation.
However, technological advances in the next five years could
make it feel like foreigners are actually working in your officethrough advanced communications, not travel. Imagine if
instantaneous machine translation of spoken communication
becomes commonplace and eliminates language barriers.
Telepresence systems already exist today where you can feel likeeveryone is in the same room. Telepresence and instantaneoustranslation would allow for highly-paid professional jobs tomove abroad. Telerobotics would allow for the offshoring ofmanual jobs or even surgeons. A maid in the Philippines could

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RIETI International Symposium

work a robot cleaning hotel rooms in London. Telemedicine
would allow doctors to work on patients anywhere in the world.
Although these technologies are currently expensive and clunky,
exponential technological growth will make them affordable
and convenient in short order. The future is moving so fast thatscience fiction is starting to look a lot more like science and a lot
less like fiction.

02

Presentation
Global Value Chain in Asia and Its
Implication to Japan
Kozo Kiyota
Research Associate, RIETI /Professor, Keio Economic
Observatory and Graduate
School of Economics, Keio
University

Panel Discussion
Chair
Kyoji Fukao
Program Director and Faculty
Fellow, RIETI / Professor,
Institute of Economic Research,
Hitotsubashi University / Chairof the Fourth Asia KLEMS
Conference

Events01

Presentation
Information Technology and the New
Globalization
Lawrence J. Lau
Ralph and Claire Landau
Professor of Economics, The
Chinese University of Hong Kong

In the long run, whether or not there is economic growth or
stagnation is not likely to be constrained by supply but will
depend on the growth of aggregate demand. There is no signof satiation in many economies. The demand for public goods
remains very high, but they are not adequately supplied under
the current conditions. The enhanced possibility of capital-labor
substitution is favorable for the Japanese economy. Therefore,
the substitution of labor by capital is the right thing to do. The
advances of IT are so powerful that they will bring us closer tothe day when it is possible to have "from each according to his
ability and to each according to his need."

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RIETI Highlight 2017 Special Edition

If we look at the global value chain (GVC) income in Asia, we
can see that there is a consistent decrease in Japan and Taiwan.
On the other hand, a remarkable increase has been observed in
the manufacturing industry in China, India, and Indonesia. In
the Japanese manufacturing sector, the capital-labor substitution
has led to a decrease in the number of jobs. Offshoring has
only a marginal influence on domestic employment. However,concern is voiced over the productivity decline in the Japanesemanufacturing sector as a whole, which has resulted fromthe shutdown of highly productive domestic production sites.
Attention should also be paid to the fact that the introduction of
new technologies will change people's working style.

03

Presentation
Productivity and Price Dynamics: A Bank ofJapan economist's point of view
Toshitaka Sekine
Director-General, Research andStatistics Department, Bank ofJapan

Against the backdrop of a labor shortage, we do not observe
significant increases in wages and the general level of prices.
Under these circumstances, Japanese companies are trying to
improve productivity through their voluntary initiatives. This
has a positive effect on the government's ongoing labor market
reform, but at the same time will exert a temporary downward
pressure against prices through a decrease in the real wage
gaps. However, this will not last forever, and the mechanism
designed to achieve the 2% inflation target remains intact. WhenSy mp o s iu mmaking these considerations, it is very important to measure theproductivity in an accurate way.

04

Presentation
Globalization, AI and Productivity: From theviewpoint of the service economy
Masayuki Morikawa
Vice President, RIETI

labor. AI does not replace all of the employees because somebody
has to supervise people, and the supervisor's productivity does
not gone up, thus his wage should not go up. Therefore, I am notreally sure that this whole snapback will work, but if you cast thewhole thing as either capital or labor, it is a temporary deviation
to capital and will snap back. Since AI is infinitely reproducible,
whoever can control and use it the best will win everything. I
think the nature of this technology will fundamentally encourage
inequality.

In the past six years, a significant increase was seen in the volumeof Japanese service exports while its merchandise exports grew at
a very modest pace. This allowed the entire Japanese economy to
improve its productivity through the resource reallocation effect.
High productivity is often seen in manufacturers without plants,
companies with large headquarters functions, and firms making
use of IT. The fourth industrial revolution is a cornerstone of the
Abenomics' Growth Strategy 2017. However, the service industry
is more aggressive than the manufacturing industry in terms of
the use of big data, and companies engaged in the global market
have a positive view of the impact of artificial intelligence (AI).
In addition, it is likely that there is a complementary relationshipbetween AI and high-skilled labor rather than a substitutive one.

Panel Discussion
Fukao: If there is a free flow of knowledge and capital beyond
national borders, how Japan can raise the level of the affluence?
How should we reform the education systems or what kind ofknowledge accumulation is important? Also, there are issues
such as cyber security, economic systems including site-seeing
assets, and so on. In order to have a more affluent society, what
can we do? At the same time, could you please comment on thepresentations by the four panel members?
Baldwin: The importance of quality in absolutely everything isdone in Japan. This edge of the Japanese way of doing things waslimited to the manufacturing sector because only goods could crossborders; however, exporting this excellence through the service
sector will expand; that is an opportunity to take account of.
Professor Lau commented on the substitutability of capital andJorgenson: The manufacturing sector in Japan from the pointof view of productivity is very healthy, but the challenge is in
the service sectors. It is important to try to limit this drag on
productivity that is due to inappropriate government policy thathas focused attention on limiting entry into certain key sectorsthat turn out to be those that are important in international trade.
What is needed is a clear focus, an identification and targetingof the industries where this is a problem and drilling down to the
bedrock of regulations that are holding back productivity growth.
That will make it possible for Japan to play a leadership role as theway that Apple Inc. has played in smartphones for example. The
key to enhancing incomes in Japan and enabling Japan to takeadvantage of the opportunities are being created through this very
rapid globalization process that Professor Baldwin described.

Events

Fukao: Professor Jorgenson earlier said that the quality of laboris high in Japan, but it is not necessarily utilized effectively.
How can wages in Japan be raised in general? Also, what isthe concrete direction we should realize in labor reform under
Abenomics?

Lau: AI and robotics increase the substitutability between capitaland labor. The isoquant will change because it becomes flatter
between capital and labor. We focus on substitution and the real
wage rate, but we should also look at the cost of computing or
AI relative to the wage rate. The wage rate is not going to go up
because the cost of computing and AI has come way down. I amvery happy to see the rising productivity in the service sector inJapan, but Japan needs to create jobs that cannot move away. As
Paul Samuelson predicted, the factor price equalization is actually
happening.
Morikawa: Graduate students will not be easily substituted by
new technologies not because they have high expertise in theirwork, but rather they have malleable skills. In terms of policy,
investment for education is important and, among all, improving
the quality of the teachers is imperative. Paying more for newly
hired teachers will prevent them from taking up another higherwage job. Regarding the basic income, it is important to establish

RIETI Highlight 2018 Special Edition

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RIETI International Symposiuma safety net, and, also, it is necessary to think about negative
income tax systems.
Sekine: Japan can maintain the affluence only by increasing
productivity. Needless to say, the government has to work on
the growth strategy in the labor market. Also, it is important towork on deregulation and introduce more competition. Further,companies' responses to labor shortages are also important.
The tighter labor market conditions have induced them to raise
productivity. If we continue to have a high-pressure economy, thepotential growth of Japan's economy would be boosted throughthe improvement of productivity, and this could be driven bythese corporate responses.

EventsKiyota: If AI and robots are different from traditional capital,
we should be cautious in thinking about this substitution. In
order to estimate the elasticity of substitution between AI/robots
and labor inputs, however, we need their price data. As for the
impact of globalization on employment in Japan, the impact ofoutward foreign direct investment would be negligible. Somepeople say both trade and the technology change affect expansionof wage gaps, but others say the effect of technology change isstronger than trade. For now, globalization does not seem to havesignificantly negative effects on the wage gaps in Japan. However,in the United States, a study found significantly positive effects
of globalization on increasing executive compensation. It may benecessary to focus more on a small percentage of people who arebenefiting from globalization.
Fukao: Thank you. I would like to shift our attention tocompanies. What kinds of policies are needed to invigorate
Japanese companies, for example, a reduction in corporate taxes?
Jorgenson: As a consequence of the aggressive monetary
policy of the Bank of Japan, the devaluation of the yen was
finally successful and a very important macroeconomic barrier
to Japan's successful access to the world market, including thebenefits of globalization and participation in global value chains
was removed. That has increased trade in services relative tomanufacturing. Also, we need to consider labor market reform.
There is a great opportunity for increased efficiency andincreased utilization of the highly skilled Japanese labor force.
The enormous investments that have been made in human capitalin Japan have led to the very high quality of labor force that it
currently enjoys.
Morikawa: One regulation we need to focus on is theoccupational licensing system in the service industry. It is
desirable moving from licensing to certification or to having

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graded licenses, for example, allowing the hygienist to do someof the dentist's work or the nurse to do some of the doctor's work.
Deregulating the occupational licensing system is important interms of increasing productivity in the service industry.
Sekine: The exchange rate is a sensitive issue, but the Bank ofJapan acknowledges that it is one of the important transmission
channels, although the Bank does not aim at a specific level.
Monetary policy should be conducted in accordance withdomestic necessities so as to support economic activity andensure price stability of each country. Now, I want to hear fromDr. Morikawa about the utilization of big data. Unlike U.S.
corporate managers who recognize the importance of big data
especially to manage blue-collar workers, Japanese corporate
managers seem to be reluctant to utilize big data. I think this is an
issue that we need to address.
Morikawa: In the United States, many companies utilized the
IT revolution to change their businesses, but Japanese companies
tend to worry excessively about compliance infringement. It may
inhibit them from taking risks.
Kiyota: According to the data introduced at the RIETI
symposium in 2015, Japan was ranked 196th out of 199 countries
in terms of the stock of the inward foreign direct investment
relative to GDP. The regulation and language barrier do not
fully explain this; this is about the uniqueness of Japan. Against
the backdrop of labor shortage, we do not observe significant
increases in wages. Japanese outward foreign direct investment
is increasing, but Japanese companies have 32 trillion yen ofinternal reserves within foreign affiliates as of the end of 2015.
Why are they not coming back to the Japanese workers?
Fukao: I would like to go back to what was mentioned by
Dr. Morikawa first. In terms of ICT advancement and new
globalization, China is the largest beneficiary which is followedby India. For further advancement of Asia, what kinds of policies
are needed?
Baldwin: When the outsourcing started in 1985–1986, the wage
difference was 40 to 1 between Japan and China. The success ofAsia, especially in manufacturing, was this combination of hightech and low wages. Between 1985 and 2000, there were no free
trade agreements in East Asia, but after China approached the
Association of Southeast Asian Nations (ASEAN) for a free trade
agreement, the domino effect happened in Asia. Unfortunately,
the Trans-Pacific Strategic Economic Partnership Agreement(TPP) is stalled currently. Right now, it seems like it might be
Japan that is keeping it going. The Regional ComprehensiveSy mp o s iu m

Lau: East Asian industrialization started in Japan, but as theJapanese wage rate went up, labor-intensive industries moved
successively to lower-cost locations such as Hong Kong, thenTaiwan, then South Korea, then Southeast Asia, and Mainland
China when it opened to the world in 1978. All of these economies
adopted some form of export promotion policy rather than importsubstitution. This was facilitated by the favorable exchange rate forJapan. Similarly, Taiwan and China had large devaluations of theircurrencies. In addition, we need to look at Samuelson's idea offactor-price equalization more carefully. Factor price equalization
under globalization is a way of viewing this.
Jorgenson: I agree with Professor Baldwin on the importanceof free trade agreements and the proliferation. In East Asia, all of
the IT products have been grouped under a free trade agreement.
It has had the most important impact in moving IT to the lowest
cost producer, by and large, China, but that is now moving on toother parts of East Asia. This is a graphic illustration of a creative
response to a particular situation in the fact that information about
IT is difficult to contain, and therefore flows across internationalboundaries, leading to a free trade agreement in the production
and trade that facilitates international integration through value
chains.
The free trade agreement regarding a commodity is that it is
not necessary to think in terms of the TPP, something that is inagreement among countries, that we need to be more creative thanthat, and it seems that Japan has a very sophisticated approach tothis. That is going to be a very important positive force in making
use of the developments that we have been discussing here having

to do with robotics and AI.
Baldwin: AI should stand for almost intelligent not artificial
intelligence because the thing does not think. I read a story about
AlphaGo (a computer program that plays the board game Go).
The research started by giving it 30 million board positions. It
divided itself in half and played itself at computer speed for six
months, learning from its mistakes. It went very well and beat theworld's best player. However, if the board is changed from 19 to 19
to 20 to 20, it would have lost completely because it did not reallyknow how to play strategically. As for the Japanese uniqueness,
if you had a whole series of secret immigrants who came in andtook over Japanese service sector jobs, the output was going up,labor productivity did not seem to be going up, and the wages
most certainly were not going up. I wonder if the very nature of
AI as pattern recognition only is not understanding some of those,
but I will leave that as speculation.
Jorgenson: The way that the literature and global value chains
have evolved, it has emerged that there are three regional centersof global value chain development: North America, Asia, andEurope. The United States is now reexamining its policy toward
integration within North America. Asia is taking advantage ofthis lack of leadership in North America, but I also think that thesame thing is true in Europe. The great German reform that took
place before the current government came to power has motivatedand powered a lot of the development of global value chains
within Europe, which has been a great success. However, when
you look at the bottom line, it turns out that Asia has gained thecomparative advantage in the development of global value chains.

EventsEconomic Partnership (RCEP) will also be useful. Even keeping
the TPP going will continue to be a good thing. Those are thethings that we can do to continue Asia's success.

Fukao: Our session has now concluded. Thank you very much.

Note: Titles and affiliations are as of the day of the event.

RIETI Highlight 2018 Special Edition

9

BBL

Seminar

RIETI's periodic Brown Bag Lunch (BBL) seminars welcome an array of guest experts to share their research and views.
The sessions encourage lively discussions that contributes to dynamic policy-related debate.

World's Great
Excess of Supply
Date : May 12, 2017
Speaker:Atsushi Nakajima
Chairman, RIETI

Moderator:

Satoshi Nohara
Consulting Fellow, RIETI / Director, Economic and Industrial Policy
Division, Economic and Industrial Policy Bureau, METI

EventsWorld economy with intensifying trend against
globalization
My recent book, Era of Large Excess Economy, examines
the world's supply-demand balance as an underlying factor
of intensifying sentiments for anti-globalization and curbing
migration, as seen in developments since 2016 such as Brexit(Britain's decision to leave the European Union) and theinauguration of Donald Trump as the U.S. president. The sudden
drop in crude oil prices in early 2016 and the ongoing negativeinterest rate trend in Japan and Europe could also be explained
from the perspective of excess supply of energy and money.
Since the bursting of the economic bubble in 1990, Japan
has had to spend a lot of time processing the excess supply oflabor, production capacity and debt. What has been happening
to the world economy since the collapse of Lehman Brothers
is, indeed, the global version of Japan's post-bubble struggles,characterized by the structural excess of labor, goods, money,
and energy.

Changing the world economy
In the 2000s, low- and middle-income economies enjoyed someof the strongest growth in the post-war era until the collapse of
the economic bubble. This was largely attributed to the fierce
increase in exports from emerging economies, mainly in Asia, in
response to the establishment of a global framework facilitating
greater industrial production, led by China. Other factors include
the subprime lending boom in the United States, the Chinese
economy experiencing 10% growth, and the price surge of

10

RIETI Highlight 2017 Special Edition

crude oil and other resources. The emerging and developing
economies' share in world trade also rose rapidly up until about
2010.
However, such factors that supported the strong growth of
the world economy have gone and left developed nations andemerging economies to compete for a greater share in world
trade. While emerging and developing economies have managed
to restore a positive supply-demand balance, developed nations
continue to suffer excess supply and demand shortfall.
In the post-Lehman world economy, the slower growth andeconomic disparity between countries have increased discontent
among both developed nations and emerging economies,
potentially triggering friction in international trade and foreignexchange. This tendency is becoming particularly evident in the
United States, which is suffering from a massive international
trade deficit.

Arrival of the Era of Large Excess Economy
There is a structural excess in the balance of supply and demand
for labor, goods, money and energy, respectively. With regard
to goods, developing nations have always taken an export-led
approach to boost their growth. Developed nations are prone tolosing production opportunities, which undermine their tradebalance.
Similar situations are observed with regard to the excess
of labor. The increase in the income and education level inemerging economies especially in middle-income countries has
made it easier for their citizens to immigrate globally on theirown costs, resulting in a dramatic surge in immigration fromemerging economies as well as middle-income countries, rather
than primarily from low-income countries as was the case in
the past. This trend is expected to further accelerate, potentiallyDirection of a breakthrough for the world
economyNothing positive would come about from competing for a larger
share of the pie from economic growth between developed
nations and developing countries, as it would leave developed
nations with higher dissatisfaction and make developing
countries unable to fulfill their full growth potential. One
possible solution to create a win-win situation would be to
generate an economic bubble. Trump's economic policies are
expected to have a bubble-inducing effect, but that would only
have a temporary benefit. Above all else, a bubble economy
would have serious repercussions once it collapses, and therefore
cannot be a final solution.
Let us then explore the direction of a breakthrough for theworld economy by examining how Japan has dealt with threeexcesses it faced after the bursting of its economic bubble. The
first was to solve the bad debt issues. Japan forcibly realignedbanks and other corporations to reduce their excess supply
capacity. The other was to take advantage of special demand
from China and the digital industry boom to achieve the nation's
economic recovery.
Today, even though China is no longer boasting 10% growth,
the world economy needs a special structural demand thataids its positive and stable growth. As for the digital industry
boom, post-bubble Japan achieved economic recovery thanks
to powerful help from worldwide popularity of Japan's DVD
recorders and flat-panel television sets. Similar innovation could
serve as a perfect driver for another economic recovery.
Having both developed nations and emerging economies
compete in the same arena would undoubtedly result in
discontent in international trade. At the same time, we are nolonger in the age where the supply of goods is the only driver of
economic growth. In order to sustain positive long-term growthin the world economy, it is essential for developed nations tocreate major innovation for a breakthrough, and differentiatethemselves from emerging economies in areas other than the
supply of goods.
In terms of income balance, developed nations have acompetitive edge over emerging economies, gaining surplus

from service exports and primary income. President Trump of
the United States, a major power in the developed world, does
not speak ill of service income and primary income, despite his
vocal criticism of trade balance. That means Japan is also almost
free to build up surplus in these areas.
As for excess supply of money, the economy has played amain role while finances were in a supporting role. Now thatthe money supply has increased to an excessive level, finances
should be considered more than before as a solid income tool ata standard equivalent to that of the economy. Finances represent
a field of strength particularly for developed nations, contributing
to a surplus in the balance of primary income. With regard toenergy, the sense of energy's scarcity is becoming diluted due tothe 21st-century energy revolution, which is expected to reduceenergy constraints with respect to energy volume and energyproducing regions.
The Fourth Industrial Revolution also represents a main
direction of breakthrough. If technological innovation generates
brand-new demand and investment opportunities worth a large
sum of money, both developed nations and emerging economies
will gain some room for new growth. Past industrial revolutions
were all associated with the energy revolution. The same
seems to apply to the latest wave of industrial revolution withrenewable energies and non-conventional petroleum resources. It
is important to take full advantage of it.
In order to put the world economy on a positive growth
track as a whole and give greater affluence to the world, rather
than letting developed nations continue to earn profits fromemerging and developing economies, it is important to build asocial system that promotes innovation and turn it into economic
growth.
In the case of Sweden, for example, the government offers
generous social security, quality education (the world's highest
ratio of government spending on education against GDP), andan active labor market policy to strengthen the nation's humanresources, thereby boosting its innovation-creating capability
and achieving a growth rate of over 4%, on par with emerging
economies in 2016. Advancement of human resources leads tothe promotion of innovation, and is therefore a mechanism forapproaching the Fourth Industrial Revolution.
Singapore has achieved economic growth with powerful
government-led initiatives to advance its industries. Today, it
is going one step ahead of the Fourth Industrial Revolution
by advocating the Smart Nation Vision, in which Singapore
strives to become the world's first nation to connect its basic
infrastructures and day-to-day infrastructure services with theInternet of Things (IoT). The nation's per-capita income is now
more than double that of Japan.
International collaboration is another direction for further
developing the world economy. In relation to the latest French
presidential election, opinion polls show that public confidence
in France's new pro-EU President, Emmanuel Macron, is low
when it comes to immigration and other issues that cannot beeasily resolved by France alone. This indicates that, in order toresolve various social and economic issues in France, the newpresident must be able to exert influence not only domestically
but also on the EU.

RIETI Highlight 2018 Special Edition

Eventsprovoking negative sentiments against immigrants in somedeveloped nations.
As for the excess of money, the combined money supply of
the Organisation for Economic Co-operation and Development(OECD) members and BRICs (Brazil, Russia, India and China)
nations now surpasses the global gross domestic product (GDP),following the economic shock caused by the collapse of Lehman
Brothers. The situation remains unchanged today, as the world
shifts from the age of money shortages to the age of abundantmoney circulation.
The same applies to the supply of energy. The U.S.-led shale
oil revolution since 2008 has boosted shale oil production, andconsequently brought down the price of crude oil. According toan announcement by the U.S. Department of Energy, shale oil
production might increase further into 2040, diluting concerns
about scarcity of energy resources.

11International frameworks are also effective from theperspective of promoting growth with globalization. One such
example involving Japan is the Trans-Pacific Partnership (TPP).
If it manages to improve or resolve social and economic issues
within Japan, it has the potential of making our economy growand enriching our society.

The biggest comeback strategy for the Japanese
economyEvents12

What has been discussed about the balance of primary income
and the Fourth Industrial Revolution also applies to Japan. During
the lost two decades, Japan suffered a low growth rate and anegative balance in supply and demand. However, it should not
be overlooked that, even during those days, Japan managed toconsistently gain surplus in the balance of primary income.
It is important for Japan to continue achieving this surplus
in primary income. To this end, it is essential for Japanesecompanies to enter into overseas markets to gain overseas
earnings and expand investments in foreign securities. While
China has the largest reserve of foreign currencies, Japan holds
the world's largest net foreign assets in terms of external financial
assets and liabilities. If that is the case, Japan should squarely
take on achieving greater gains in that area.
Of course, if companies' profits are reserved internally, it
would not benefit the economy. It is not good enough if only thewealthy become even wealthier. It is important how the wealthcan be repatriated and redistributed within the country.
Another essential task is to further accelerate innovation.
Among OECD members, Japan has the second-largest ratio ofdomestic value-added content in exports. In other words, valueadded contents, produced domestically, represent a high weightin Japanese exports. Topping the ranking is Australia, which has ahigh ratio of domestic value-added content because of its focus onexporting domestically-mined resources. Japan is effectively theworld's No.1 among countries that focus on exporting industrial
products, and is actually performing well in world trade.
However, by category, the ratio of research and development(R&D) is low within value-added export contents. Japanese
small- and medium-sized enterprises, in particular, do not invest
in R&D compared to those in other major developed countries.
This should be expanded to build up fundamental strength.
As for excess of money, deposits at financial institutions
represent a large proportion of Japanese households' financial
assets. This may be reflective of the Japanese people's
conservative approach to household finance. Yet, in otherwords, there is room for utilizing such money for the purpose ofgenerating greater wealth and improving their standard of living.
Furthermore, regarding the Japanese companies' capital
investments, the ratio of capital investment to GDP is higher thanthat of major Western countries, but their ratio of IT investments

RIETI Highlight 2017 Special Edition

within capital investments is quite low. Since 2000, the IT
investment ratio to GDP has remained steady, but the ratio of
non-regular employment has increased. What it might mean, in
principle, is that Japanese companies have prioritized utilizing
cheap and flexible labor over making IT investments since
2000. Fortunately, today's labor shortages have created an ideal
opportunity for promoting IT investment. Japanese companies
must invest more in IT to boost productivity, so as to achieve a
breakthrough in the Fourth Industrial Revolution.
In this sense, the development of an ultra-smart society, one
of Japan's growth strategies in Abenomics, could precede thebreakthrough of the world economy. Artificial intelligence (AI)and other technologies can deliver advanced social systems.
For example, combining the technologies for self-driving cars
and solar energy systems could bring about an energy selfsufficient car that self-drives anywhere in Japan. Such a vehicle
could resolve transportation inconvenience, for example, indepopulated communities. In recent days, there have been urban
residents with no convenient accessibility to supermarkets orother stores nearby. Establishing an ultra-smart society could
offer a more convenient way of shopping, thereby resolving theirdifficulty and potentially generating new demand.
Moderator: In Japan, some argue that the increase in the ratioof aged population could hinder productivity increase using IT
due to the issue of IT literacy. In your book, you pointed outthat Sweden has achieved a higher rate of productivity increase
than Japan, and that a strong productivity increase can still beachieved in an aging society, highlighting the importance of
educational investment and active labor market policies.
Some studies suggest that about half of all occupations will
disappear in the next 10 to 20 years as a result of the Fourth
Industrial Revolution. It is an urgent task to shift our focus tovalue-added occupations that cannot be replaced by robots.
Japanese companies have made an aggressive shift to nonregular employment, which could be easily replaced by AI androbots. This approach may have had some rationale for Japanesebusinesses, but it has cast a dark shadow over the nation's future
outlook. Our key challenge for the future is to increase productivity
and economic growth by making educational and human resources
investments and further upgrading human resources.
You have rightfully pointed out that both businesses andhouseholds are risk-aversive. Against this background lies
the pitfall of preconceived ideas. Since the bursting of Japan's
economic bubble, the idea that good companies are those with nodebt and no bankruptcy outlook has spread and taken root deepin our society. However, failure to make sufficient investment
would turn such companies into losers with no competitive edge.
There also has been a deep-rooted perception in Japan thatthe population decline would contract domestic demand, making
it unwise to invest. There are three directions as a solution.

BBLSeminar

Nakajima: During the transition of the world economy from an
era of shortage to an era of excess, there is always a possibility
that even advanced industries of high value added could
experience a structural excess in their supply capacity. This
would result in the easing of the supply-demand balance, which,in turn, gives extra price-determining power to the demand side.
In addition, while the supply capacity is in excess, consumer
prices do not rise in principle. This creates the tendency ofexcessive competition, which is not good news for industries,
businesses, and workers. Accordingly, monetary and fiscal
policies alone cannot fully resolve today's disinflation, lowinterest rates, and slow-growth trends. We need a breakthrough.
Without a breakthrough, the current cycle of slow growthalternating with moderate growth will continue for theforeseeable future, maintaining the structural trend of supply
excess. Seven or eight years have passed since the Lehman
Brothers collapse. Slightly more stagnant economic conditionsin and outside Japan and global disinflation could persist for five
more years or so.
A breakthrough provides a major seed of growth for theworld economy as it strives to reach the next significant stage of
growth. For this reason, even though the bubble economy is notdesirable, we must embrace the digital industry boom and the
Fourth Industrial Revolution as a major part of it.

Q & A
Q1. Why is it that Japan has the world's second-highest
ratio of domestic value-added contents in exports?
Does it have anything to do with the "not invented here"
attitude?

Nakajima

It has a lot to do with the industrial structure of post-war
Japan. There is nothing wrong with the "not invented here"
attitude itself. Since neighboring Asian countries lagged
behind Japan in terms of the level of industrialization in
those days, Japan did not have enough room to attempt aninternational division of labor in the process of enhancing
its industrial structure. In today's economy, the ability
to add significant values within the country is a positive
property, but it may leave the possibility that Japan does not
fully utilize beneficial resources, know-how, and industrial
products available in the rest of the world. Remaining tasks
include building an international framework that caters to
the age of globalization, and embracing the entry of foreigncompanies into the domestic market as a way of boosting
the vitality of Japanese businesses.
Q2. Personally, I believe the biggest problem is theexcessive supply of money. Is there any solution?
Nakajima

There is a strong belief in Japan that finance underpins the
economy. However, we must pursue the approach of having
finance generate value added. Also, in view of the need to
distribute wealth, it is necessary to consider, for example,
abandoning separate withholding taxation and adopting acomprehensive taxation system instead.

Events

The first direction is to raise wages. Increasing the standardof income would keep domestic demand strong even if the
population declines. The second direction is in regard to foreign
trade. Japan has promoted the TPP for this reason. Even the
TPP11, minus the United States, has the effect of increasing
domestic demand. The third direction is to initiate the Fourth
Industrial Revolution to spread new lifestyles for generating
greater demand. This is the main theme of the government's
growth strategy, amended this year.
Let me ask you one last question. In your book, you said theshift of the world economy from an era of shortage to an eraof excess will give price-determining power to consumers. Are
you suggesting that there will be downward pressure on prices
worldwide, triggering deflation or disinflation? In the era ofexcess, how long do you think the trend of low inflation and low
interest rate will continue?

Q3. Would the Fourth Industrial Revolution boost
productivity even further to continue expanding theexcessive supply of goods? Or would it promotestreamlining and appropriate allocation, eliminating
inefficiencies to contract the supply of goods?
Nakajima

I don't believe the Fourth Industrial Revolution would
eliminate the bubble economy as an economic structure.
There is no stopping the excessive supply of goods ortrend toward an economic bubble. Yet, at the time of abreakthrough, there is an absolute shortage in supply anddemand. When the Industrial Revolution occurred in
Britain, the industrial world became capable of achieving
what they had not been able to before, thereby triggering
an unprecedented level of growth. In post-WWII
reconstruction, there were phases of strong growth in world
economy, led by developed nations, in the cycle of 15 to 20
years. The greater the scale of breakthrough is, the bigger
the scale of bubble-free economic growth we can expect tosee, arriving in the cycle of several scores of years.
Note: Titles and affiliations are as of the day of the event.

RIETI Highlight 2018 Special Edition

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BBL

Seminar

RIETI's periodic Brown Bag Lunch (BBL) seminars welcome an array of guest experts to share their research and views.
The sessions encourage lively discussions that contributes to dynamic policy-related debate.

Energy Markets:
What to do when
forecasting is uselessDate : May 17, 2017
Speaker:

Robert S. Pindyck
Bank of Tokyo-Mitsubishi Professor of Economics and Finance,
Sloan School of Management, Massachusetts Institute of Technology

Moderator:

Keiichiro Kobayashi
Program Director & Faculty Fellow, RIETI /Professor, Faculty of Economics, Keio University /Research Director, Canon Institute for Global Studies

EventsIntroduction
This talk is about energy in general, but mainly about oil
prices. I will discuss oil and how other energy sources areconnected to oil and its pricing. I will also talk about the past
and what might happen in the future with energy in generaland the price of oil. Then I will discuss the linkages of otherforms of energy. I want to focus on sharp price changes andwhy they occur. This comes down to supply and demand
elasticities: what happens when supply and demand shocks
occur. Why don't we know what will happen to the price of oil?
The key is what might happen and the extent of the uncertainty.
Finally, I want to talk about what we can do in a world like
this, in which no one can predict. The key is assessing theuncertainty and thinking about option value, because oil andcoal reserves can be viewed as real options.

Recent oil price volatility
Over the last five years, the price per barrel of oil went fromaround $100 to close to $30 and has rebounded to about $48
today. These fluctuations surprised many people, but in 2005
and 2006, the price of oil increased over a period of a year
or two from $70 to over $140, dropped to about $45, andrebounded to $80. Sharp changes have begun to appear normal.
All the way back to about 1985, very sharp fluctuations haveoccurred. Why do we see these very sharp fluctuations? Does
demand for oil change that quickly? Does the supply? Why is

14

RIETI Highlight 2017 Special Edition

the price so volatile? Is it possible to forecast prices?
I am the co-author of a textbook on microeconomics whichcontains an example about the world oil market. The purposeof the example is to compare short-run and long-run supply
and demand elasticities. The competitive oil supply, added
to the amount the Organization of the Petroleum ExportingCountries (OPEC) produces (less than one-third of all world
oil production today), gives the total supply. In the short-run—meaning about one year to 1.5 or two years—the demand curveis very steep, very inelastic, and the supply curve is also very
steep and very inelastic. In the textbook example, suppose
something happens in Saudi Arabia and there's a drop in its
production of three billion barrels per year. This would cause
the supply curve to shift, creating a new intersection at a very
high price. Any shift in the supply curve or the demand curvein the short-run can cause a very big change in the price.
The long run (from 5–10 years) looks totally different.
Supply and demand are much more elastic. In the long run,people drive smaller cars, put new insulation in their homes,
etc. More sources of supply will be coming online over thelong term; new facilities are developed and new sources of oil
are discovered. The same shift in the curve over the long termcauses a much smaller change in the price. The problem is thatthings change in the short run.

Recent oil production and consumption
trendsWhat has happened in the oil market over the last three or four
years? In 2016, world oil consumption was about 97 million
barrels per day. From 2013 to 2016, production increased byProblems with forecasts

The International Energy Agency produced an approximately
20-year oil price forecast in 2012 or 2013 assuming various
policy differences. For example, strong carbon dioxide
emission policies would cause a price drop. It claimed these
forecasts were useful, but it was wrong. Large oil companies
predicted three cases, but they, too, were wrong. Natural
gas price forecasts out to 2030 by an energy agency were all
wrong. Yen-U.S. dollar exchange rate forecasts are wrong.
Forecasts are produced because people are paid to produce
them. This is called "technical analysis." This is done for thestock market as well. We look at tendencies and draw lines, but
the result is essentially trying to forecast a random walk withgibberish explanations. They sell this and people buy it.
The futures market uses information from the Energy
Information Administration (EIA) of the U.S. government.
It produces a short-term outlook every month. It looks at the
futures price and makes a forecast. The forecasted price isabove the futures price because people mistakenly believe
the futures price to be equal to the expected future oil spot
price. In other words, the futures price a year from now would
be the same as the expected spot price a year from now.
This is incorrect; it's only correct if the commodity has nosystemic risk. Under the capital asset pricing model, the beta
for oil, which measures the systemic risk, is about one. Thisis because oil, like copper, is an industrial commodity, andwhen the economy is booming, demand goes up and the pricegoes up accordingly. That means that these commodities havesystematic risks, i.e., risks correlated with the overall market or
economy. Because of these systematic risks, the futures price isbiased downwards as an estimator of the expected future spot
price. A positive beta causes the expected future spot price tobe above the futures price. At the 95% confidence interval—
which means we can be 95% sure we are within a specificrange—we can find useful information because this is a rangeof possibilities. The EIA looked at options prices. Futurescontracts involve the trading of call options and put options.
From the options prices, the implicit volatility of the spot pricecan be determined using the Black-Scholes formula, and from
that, we can determine the confidence interval. This is what theEIA did. I focus on this because the confidence interval is verylarge. According to the options prices in the options market,
an enormous amount of uncertainty exists. Even going out
only one year, we are looking at a range of about $30 to $90.
That's only the 90% confidence interval. We know that fromthe options market. This is useful. What you might ask is not somuch what the price will be, but what is the confidence interval
for the price of oil next year. This can be learned from theoptions market and the options on futures. The answer is thatthe interval is very large.

Effect of uncertainty on undeveloped oil
reserve pricing

Eventsabout three million barrels per day, mostly from the UnitedStates. Oil production in the United States has increased
dramatically, mostly due to shale oil. Russian production
increased by about a half million barrels per day and Brazilian
production increased as well. Iraq increased by about one
million barrels per day. Smaller changes have taken place inother countries as well. Libyan production decreased by about
two million barrels per day because of the ongoing civil war. If
the fighting ends, Libya can produce about 2.5 million barrels
per day. It has large oil and productive capacity. However, no
one can predict what will happen in Libya, so the price of oil
can't be predicted. If Libyan oil comes on the market, the pricewill drop dramatically.
Consumption, by contrast, has increased by about one
million barrels per day. It hasn't increased more partly becauseworld gasoline consumption has not risen very much due toimproved automobile and airplane fuel efficiency. The result
is that either inventories increase greatly or the price drops.
Inventories around the world are at their highest levels ever,but it's not enough to prevent the price from dropping. The
price dropped during this period simply because production
increased greatly amid a modest increase in consumption. Thisis simple but hard to predict.
U.S. production increased by quite a bit over the past few
years. Oil prices will continue to fluctuate over the next few
years. Attempting to forecast the price of oil is fruitless. The
right question to ask is what might happen to the price of oil.
What's the extent and nature of the uncertainty? Why this is
the right question comes down to option value. In the end, wewant to know the value of our options.

How is oil produced? The first thing to do is to find oil. We
take a guess and drill and if we're lucky, we discover oil. Thatis called an undeveloped oil reserve. We can't produce the oil,but we know it's there. Next, we have to develop the reserve
to produce the oil. That's very expensive. Maybe $1 billion,
at least. Developing offshore oil reserves can cost from $3
billion-$5 billion. After the reserve is developed, oil can beproduced for the next 10 years, maybe longer. The revenue
earned every year depends on the price of oil, but the pricefluctuates. What is that undeveloped oil reserve worth? And
when should it be developed?
Does greater uncertainty raise or lower the value of the
undeveloped oil reserve? There is world A, with very little
uncertainty, in which the oil price doesn't change much, andworld B, which has a lot of volatility. In which world is that
undeveloped oil reserve more valuable? It's worth more inworld B, even though it doesn't appear so, because of theaddition of a risk premium. Uncertainty raises the value
because the reserve is exactly like a call option. The more
uncertainty the greater the option value. If the price goes
down, the option is worthless. If it goes down by a lot, it's still
worthless. If it goes up, it becomes worth something. There isa limit on the downside: it can only be worth zero, but on theupside, there is no limit, it can be worth anything. That's why
it's important to know what the level of uncertainty is. Because
companies that deal with oil need to determine the value of
their undeveloped reserves, the key is understanding the natureof the uncertainty.

RIETI Highlight 2018 Special Edition

15

Coal and natural gas
Natural gas and coal prices are linked—but only loosely—tothe price of oil. Oil is easy to transport, so there is a world
market for it. Natural gas is not as easy to transport. That's
why today, natural gas in the central United States is only $3
per 1,000 cubic feet (Mcf). In Boston, it's $12. We don't havepipelines because people don't want them in their backyards.
There's a capacity problem. In Europe, it's about $10. In Japan,
it was about $15, but it has fallen to about $7. The issue hereis transportation. Liquefied natural gas is becoming moreprevalent. That might be why the price in Japan has gone
down. Coal is easier to transport, but it's dirty and regulated.
Its use is declining because natural gas is cheaper and cleaner.
It doesn't have a strong connection to the price of oil. Nuclear
is simply not economical. To build a nuclear power plant isvery expensive. The capital costs are huge. The regulatoryenvironment is difficult and uncertain. That's true in Japan, theUnited States, and Europe. Nobody predicted that Germany
would turn around completely on nuclear. The result is that
there has been very little or no construction of nuclear plants.

Q & A
EventsQ1. Two things are important in forecasting the future. One
is trends. The other is game-changing events, like Libya.
I agree with you on uncertainty, but if you look at trends,
it's very important for forecasting the future. However, wecannot forecast the game-changing events. What do you
think about that?
Robert S. Pindyck

I agree that you can't forecast what will happen with gamechangers. There are many other places besides Libya. Brazil
potentially has enormous offshore oil reserves, but Petrobras
has a lot of problems, as does the Brazilian government. Maybeit will produce much more in the future. We don't know. Nigeria
is another case. There is theft and disruption there. However,even the trends are unpredictable. Five or six years ago, no one
predicted that the United States would produce so much shale
oil and natural gas. Nobody predicted fracking. Over three
years, production went from six to nine million barrels per day.
That's the difficulty. The trends are often not there.
Q2. In a related question, from a policy perspective, given
the great uncertainty, what should the government do? In
research and development (R&D), for example, in the fieldof energy conservation technology or alternative energy
development, it takes time to produce outcomes. Under
great uncertainty, what should the government policy be?
Pindyck

Many people would say that the government should subsidize

16

RIETI Highlight 2017 Special Edition

R&D. I disagree with that. I don't think the government has beenvery good at picking winners and losers. If there is belief that an
externality exists, which there is in the case of oil (because ofclimate, security, impact on the economy of sharp fluctuations,etc.), then a tax is imposed. The market then should be allowed
to operate and companies decide if they should develop newtechnology, invest in R&D, etc. The pharmaceutical industry isa good example. There's a lot of uncertainty over disease. Drugcompanies develop new drugs to fight disease. The uncertainty
does not mean the government should subsidize drug companies
to develop new drugs. It's the same thing.
Q3. Oil prices were controlled by OPEC for a long time,
but it now provides only one-third of the supply. Should aninternational organization be established to stabilize oil
prices?
Pindyck

There are two parts to your question. The first is the role of
OPEC: did it affect oil prices? The second is whether thegovernment should stabilize prices by stockpiling, etc. OPEC
had very little influence on oil prices. Since its inception in
1962, OPEC has many members, but they really never agree.
They have meetings and then all go and do what they want.
OPEC has not had that great an impact since it started. Given
this volatility, should the governments do anything? No, I don't
think the governments should do anything. These are world
markets. Similarly, the copper cartel has no effect on the priceof copper. First of all, there needs to be some sort of world

BBLSeminar
Q7. If we consider a rare disaster-type shock that occurs
only once every hundred years, does this estimation
change?
Pindyckthe degree of uncertainty?

Rare disasters are my favorite. This is a world in which people
produce, buy, and trade oil. Life goes on. What would happen
in the event of some huge catastrophe? Who knows?

Pindyck

Q8. Price is influenced by market expectations. How can we

Options prices are one good way of doing this, by looking
at actual market transactions. The other way is to conductsimulations—"what-if" experiments. What if Libya does this orthat, what if Brazil does this or that, etc. There are so many such
experiments that can be done. Which are the important ones?
Which are more likely? That's very hard to decide. Options are
the best choice. If there are no options to look at to get price data,then scenarios have to be considered. Using oil as an example,
by making a list of things that could happen to increase supply,a price of $20 or $140 can be imagined with all of the possible
factors for the scenarios. The key is understanding how manydifferent things can happen and how much uncertainty exists.

understand the role of market participants' expectations?

Q4. Aside from using options prices, how can we measure

Q5. You mentioned copper. Currently, an enormous
steel and aluminum oversupply exists globally. The
government is trying to control this. U.S. President Donald
Trump is introducing an investigation. What would yourPindyck

Are you asking whether expectation influences price? The
answer is no. Many people have argued—and they only argue
this when the price goes up—that, for example, heating oil
price increases occur because speculators speculate on the
futures market and push the price up. The futures market does
not push the price up. The futures market is like a bet on a
football game. I bet on one team and you bet on the other. If myteam wins, you give me money, and if your team wins, I give
you money. It has no effect on the game. Expectations don't
affect price. Chinese demand increased because they werelocking up supply at a much more rapid rate than what theyneeded. Some other countries were doing the same thing. Then,
China said it didn't need so much oil and its consumption, etc.
dropped. How could this be predicted?

Eventsstabilization fund. Stockpiling is necessary, and knowing how
much and when to release it is also necessary. It's impossible. If
there is worry about fluctuations, then hedging should be doneon the futures market. We have futures markets for this purpose.
Governments should not come in and try to stabilize prices.

recommendation be to the U.S. administration regarding theoversupply issues?

Q9. My question is about the EIA forecast. This forecast isbased on a variety of scenarios which take many variables

Pindyck

and conditions into account. I assume it has simplified theWith regard to the word "oversupply," a buyer of steel does notthink an oversupply exists; it would think there's exactly theright amount. Whether there is a feeling that an oversupply or
undersupply exists depends on whether the party is a buyer ora seller. I think there's an oversupply of economists. I am a big
believer in free trade. We have the World Trade Organization(WTO) so we can have a playing field where we can trade freely
and have rules. Dumping and other things can be a problem. If a
problem exists, it might be appropriate to go to the International
Trade Commission. That has to do with the rules for free tradeand how to enforce them to continue trading freely.

variables. Does it have specific principles for the variables?

Q6. If the options price is unavailable, is the data on past
volatility important for predicting the confidence interval?
Pindyck

Good point. Yes, definitely. That's a very common way oflooking at volatility and uncertainty. Over the last 30 years, theprice has fluctuated enormously. Looking at the past and treating
it as some type of stochastic process, volatility can be estimated.

Also, in scenario making, the key is how to use them. Could
you discuss the extreme left and right of the scenarios, therange of possibilities? We could then decide what measures
to take.
Pindyck

The forecast was useless. If a line is drawn, what does it imply?
Nothing. I don't know what the EIA did and what it assumed,
but it made a projection. The projection is useless, based on
information it doesn't have. What it comes to scenarios, the key
is that there are possibilities, and the EIA can't deal with this.
It would be useful to say there are possibilities that could affectthe price. If a party is thinking about getting into the energy
industry and producing oil, and spend money, sure, it shouldlook at scenarios and possibilities. It should know that the pricecould drop to $20 or go up to $140. The same is true for an oil
consumer. It would want to know the possibilities so that it cantake actions. It might hedge its risk on the futures market to
reduce exposure.
Note: Titles and affiliations are as of the day of the event.

RIETI Highlight 2018 Special Edition

17

SPECIAL
COLUMNb yt h ePRESIDENT

Overcoming Silos andKakines
Research Activities

Makoto Yano
President and Chief Research Officer, RIETI
Professor of Economics, Institute of Economic Research, Kyoto University

The silo effect
Recently, I often notice the phrase "silo effect" and calls
to "break down silos" when talking with European andAmerican researchers and business people. Because theword "silo" may not be familiar to people in Japan and other
Asian countries, many readers may wonder what it means.
However, "breaking down silos" is extremely important for
the Japanese society, a nation beset by long-term economic
stagnation, and, at the same time, "building up silos" is what
the emerging economies in our region must avoid at all costs.

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RIETI Highlight 2017 Special Edition

While awareness of the need to cope with the silo effect has
been growing in Europe and America, I find the issue to beeven more important for us living in this region.*1
Until recently, whenever I heard the word silo, an imageof a large farmland came to my mind, with many cows eating
grass. A silo is a building used to store animal feed and grain,such as wheat and corn. Silos are frequently seen in Europe
and North America. They can be found in Hokkaido as well.
This is what I learned in my grade school days.
What do silos have to do with economic stagnation andhealthy economic growth and development? The reason
relates to the silo's shape and structure. As you can see fromthe picture, silos are cylindrical, have no windows, and areKakine (or Fence)
Kakine is a Japanese word for fence. It can be used to refer toan artificial divide that separates "this side" from "the other."Japanese society faces many issues caused by the presenceof kakine, without which different groups might moreeasily be integrated. A kakine divides the affluent from theimpoverished, regular employees from temporary employees,
economists from lawyers, government agents from others,
and humanities from sciences. These kakines prevent
greater fluidity in society and hamper economic growth anddevelopment.
Recently, new kakines have been emerged in various partsof the world and are creating serious concerns for our society.
Brexit, for example, seems about to begin the rebuildingof a troublesome kakine between the UK and Europe. U.S.
politics seem currently to be driven by the divide between
the traditional white establishment and other groups whoare emerging as the new mainstream in American society.
Kakines between different nations and between different
ethnic groups are an increasing cause for concern even in
our region. It is no exaggeration to say that the issue of how
to break down these kakines is one of the largest issues now
facing modern society.
Kakines

Silos

Research Activities

designed to isolate their contents from external factors, inorder to prevent harvests from deteriorating. Looking at
the picture, perhaps, you may have already understood why
people talk about the importance of "breaking down silos."
Silo can also be a metaphor for compartmentalization,
describing the tendency for people to become entangled solely
in their own specialist areas as the degree of specialization
advances. In a business setting, silos may refer to thegrowing isolation of individual departments, deteriorationin coordination between departments, and even competition
between different departments of the same company for thesame customers. In an academic setting, silos may result in
researchers becoming cut off from other fields, unable toexplain the significance of their own research in a broader
context.
One of the hardest tasks of a researcher is to avoid straying
into, and becoming captured within, the cylindrical isolationof a silo. This is difficult because good research comes only
from the deep understanding of a field; a good researcher
must dig into the very core of a subject, which is like stepping
into a silo to look for a hidden treasure. At the same time,
good economic research must always be closely tied to theever changing real world; an economist must not become
captive within a silo. As a professional economist, I havestruggled to find the right balance by trying to maintainsimultaneously two opposing perspectives, one from inside,and the other from outside, the research "silo."

Wikimedia Commons
Photo via Good Free Photos

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19

RIETI's initiatives

Research Activities

At RIETI, we regard the silo and kakine problems as a highpriority research theme. Our recent research covers theflexibility of employment and corporate performances, genderdifferences and career building, open innovation and creative
destruction, and many more issues.
In addition to academic research, our public service
activities also place emphasis on the issues of silos and kakine.
As a part of this initiative, in November 2016, we invited
renowned economists including Professor Richard Baldwin,
President of the Centre for Economic Policy Research (CEPR),
one of the leading economic research institutions in Europe,
Barbara Petrongolo, Professor of Economics at the Queen
Mary University of London, and Tarun Ramadorai, Professorof Financial Economics at the Imperial College London,
to hold a symposium for general audience and researchworkshops on the theme of Brexit, an issue that has its roots
in various fences found in British society, including thefences between the UK itself and Europe, between the UK's
regions and London, between migrant workers from overseas
and workers born in the UK, and between young people andmiddle-aged or older people.

Market quality theory
The frequent references to the issues of silos and kakines
made by our external advisers reflect the renewed focus on
silos and kakines as obstacles to the development of society
throughout the world. In Western countries, as the conceptof "silo effect" has become more widely understood, there is
now frequent debate in wider society on the importance of
coordination between different fields.
Currently in Japan, a formidable kakine exists that divides
natural sciences from humanities. Even within humanities,
social sciences are separated almost completely fromliterature.
In Japan, silos and kakines are underpinned by the designof systems, making the problem more intractable than inWestern countries. As was pointed out in my 2015 book with
Masahiko Nakazawa, the kakine in Japanese society between
humanities and sciences dates back to governmental orders
on secondary and tertiary education issued in the early 20th
century (Japan's Taisho Era)*2. This tradition has become an
obstacle, and Japanese universities still maintain an extremely
rigid compartmentalized structure (in the U.S., on the other

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RIETI Highlight 2017 Special Edition

hand, many universities have a School of Arts and Sciencesthat encompasses the faculties of literature, economics,
mathematics and physics, among others).
The silos and kakines dividing academic research are huge
obstacles to innovation. An economy can be divided into twobasic sectors: making goods (production) and using goods(consumption). On the one hand, if you grow rice, eventually,
someone will eat it. On the other hand, if you want to eat rice,
you need someone to grow it. Similarly, innovation is uselessunless it is responsive to people's needs. Natural scientists
are expected to develop a method to produce goods whereassocial scientists are expected to come up with the best way
to use those products. Natural and social scientists must,
therefore, always put their utmost efforts into looking beyond
their respective silos.
The kakine between natural and social sciences might
be one of the fundamental factors hampering the growthof the Japanese economy. Motivated by this observation,
I proposed market quality theory and have continued to
study the relationship between market quality and healthy
economic growth and development. The existence of kakine
between various groups and of silos within a group is oneof the largest obstacles standing in the path of building highquality markets. If market quality falls, gains from market
transactions will be distributed unfairly between market
participants. This may in turn result in an unfair wealthdistribution, transferring economic wealth into the hands ofpeople favorably treated by silos and kakines.

Open society
In order to avoid such an unhealthy scenario, it is important
to raise the quality of markets. Recently, the EU and U.S.
governments have started advocating open science, an effort
to lower the kakine existing between the science community
and the rest, and an initiative that the Japanese government
follows. I believe that in order to keep our economy on ahealthy path of growth and development, it is even more
important to build an "open society," in which ideas and goods
flow freely without impedance by such artificial structures assilos and kakines.
Footnotes:*1
See Gillian Tett, The Silo Effect: The Peril of Expertise and thePromise of Breaking Down Barriers, Simon and Schuster, 2015.
*2

See Makoto Yano and Masahiko Nakazawa, Why Science does
not Lead to Affluence? (In Japanese, Naze kagaku ga yutakasa ni
tsunagaranainoka), Keio University Press, 2015.

Assessing the Impact
of AI and Robotics on
Job Expectations Using
Japanese Survey Data
MasayukiMorikawa
Given the early stages of diffusion of many artificial intelligence (AI) and robotic technologies, it is too early tomeasure the impact of these innovations on jobs. This column uses comprehensive survey data from Japan to measure
the extent to which workers across different industries, levels of education, and occupations perceive their jobs to be
at risk. Workers with adaptable skills acquired through higher education (particularly in science and engineering) or
occupation-specific skills (particularly those in human-intensive personal services) are less worried about their jobs
being replaced by AI and robotics.
Amid the stagnant productivity and potential growth rates in majoradvanced economies, policymakers expect the Fourth Industrial
Revolution and its technologies, including AI and robotics, todrive future economic growth. In Japan, Investments for the
Future Strategy 2017, the latest growth strategy of the Shinzo Abe
Cabinet, places the Fourth Industrial Revolution as the top priority
for growth promotion policies. On the other hand, the negative
impacts of AI and robotics, especially loss of human jobs, havebeen actively discussed around the world.

Impact of AI and robots on human jobs
According to an influential study by Frey and Osborne (2017),
about 47% of total US employment faces the risk of being
computerized. Their study attracted attention not only fromresearchers, but also policymakers around the world. David (2017)
applies a similar methodology to Japan to estimate that 55% of
employment is susceptible to being replaced by computers. On
the other hand, Arntz et al. (2016), taking a task-based approach,estimate that the share of automatable jobs in the 21 OECD
countries is only 9%, which is far smaller than the figure derived
from the occupation-based approach employed by Frey andOsborne (2017). The point of their task-based study is that someof the tasks contained in high-risk occupations cannot be easily
computerized. In addition, computers and robots may create new
products and services, and these product innovations will resultin currently unimaginable new occupations (Mokyr et al. 2015).
Furthermore, new automation technologies and some types oflabor are highly complementary (Autor 2015).
In spite of widespread interest in the impact of AI and robotics
on the labor market, studies in economics are still in the initialstages and quantitative empirical studies have been limited. A
major reason for this delay is the lack of statistical data on AI
and robotics, as the technologies are in the phase of development
and early diffusion. A possible approach to overcoming the lackof statistical data is to conduct surveys on firms or individuals
to collect subjective assessment of the impacts of these newtechnologies. A recent example of this line of study is Morikawa(2017a), in which I conducted a survey of a large number ofJapanese firms to analyze the possible impact of AI and robotics on
employment. The study detects technology-skill complementarity
at the firm level. In particular, the complementarity with AI-related
technologies is more prominent for employees with postgraduate
education. However, the individual characteristics used in theanalysis are limited and aggregated at the firm level.

Research Activities

Vice President, RIETI

A new survey on individuals
Against this backdrop, I conducted an original survey on Japaneseindividuals to present new evidence on the possible impacts ofAI and robotics on employment (Morikawa 2017b). The majorinterests of this study are the type of individuals concerned about

RIETI Highlight 2018 Special Edition

21

Research Activities

losing their jobs, and what type of jobs are likely to be replacedby the development and diffusion of AI and robotics. To be more
specific, I analyzed the relationship between various individual
characteristics (e.g. age, educational attainment, and occupation)and their perception of the impact of AI and robotics on theirown employment prospects. The main hypothesis of this study isthat highly skilled individuals tend to perceive the impact of AI
and robotics positively, and vice versa. I distinguished malleable/
adaptable general skills formed through higher education andoccupation-specific skills acquired from vocational schooling or
embodied as possessing occupational licenses.
The data used in the study originate from the 'Survey of Life
and Consumption Under the Changing Economic Structure andPolicies', which I designed and was conducted by RIETI in 2016
with exactly 10,000 respondents. The specific questionnaire
regarding the impact of AI and robotics is: "What do you think
about the impact of AI and robotics on the future of your job?"
The choices to answer this question are: 1) "I might lose my job",
2) "I don't think I will lose my job", and 3) "I don't know". The
methods of analysis are simple cross-tabulations by individual
characteristics and ordered-probit estimations. The individual
characteristics include gender, age, education, industry, type of
employment, and occupation.

According to the analysis, about 30% of people believe there is arisk of their job being replaced by AI and robotics. By age classes,

younger generations (those in their 20s and 30s) tend to perceivea risk of losing their jobs (Figure 1). This is a natural result, as thedevelopment and diffusion of AI and robotics will be advancing
gradually. By education, workers with postgraduate education
are least pessimistic about the prospect of their job, followed byuniversity graduates and those who graduated from vocational
school (Figure 2).
The ordered-probit estimation to explain risk perception bya wide range of individual characteristics confirms the crosstabulation result that those who have postgraduate education
are less likely to perceive their jobs to be at risk. Although thecoefficient for university education is statistically insignificant, thecoefficient for natural science majors is positive and significant.
A natural interpretation is that those who studied natural sciencesin higher education have better analytical skills, which are lesslikely to be replaced by the new technologies. Interestingly, thecoefficient for vocational schooling is positive and significant.
These people perceive that their occupation-specific skills, which
are not necessarily numerical or analytical, cannot be easily
substituted by AI and robotics.
Further, those who possess and use occupational licenses intheir current job perceive the risk of losing their job to be lower.
One interpretation is that the holding of occupational licenses
reflects high-level, occupation-specific skills. Since consumers'
preference for services provided by human workers is strong incurrently human-intensive services such as childcare, healthcare,and education, those who are working in these occupations may
recognize the importance of human contact and perceive therisk of substitution to be small. Another possibility is that the

Figure 1:
Impact of AI and Robotics on Employment by Age

Figure 2:
Impact of AI and Robotics on Employment by Education

40%

60%

30%

50%

Who is afraid of losing their job?

40%

20%

30%

10%

20%
0%
10%
-10%

0%

-20%

-10%

-30%

-20%

-40%

-30%

-50%

-40%
20–29

30–39

I might lose my job

40–49

50–59

60 or overI don't think I will lose my job

Primary schoolor junior highschoolSenior highschoolI might lose my job

Vocational
schoolJunior (2-year)
college(4-year)college oruniversity

GraduateschoolI don't think I will lose my job

Note: Calculated from the "Survey of Life and Consumption Under the Changing Economic Structure and Policies." Sample comprises those whoare currently working (N=6,579).

22

RIETI Highlight 2017 Special Edition

labor markets of licensed occupations are protected by laws andinvestments in developing malleable high-level skills throughregulations and the restrictions on new entry leads to monopolistic

postgraduate education and personal skills specific to human-

powers for the incumbents.

intensive services are both important.

By type of employment, the coefficients for part-time
are negative and statistically significant. On the other hand, thesubjective risk of company executives and the self-employed isstatistically indistinguishable from that of regular employees.
The result of the non-regular employees' higher subjective risk
perception is consistent with the results of the study by David(2017), which assesses the risk of job destructions induced bycomputer technology in Japan from a technical viewpoint.

Concluding remarks
The results suggest that malleable/adaptable skills acquired
through higher education, particularly in science and engineering,are complementary with new technologies such as AI androbotics. At the same time, occupation-specific skills acquired byattending professional schools or holding occupational licenses,
particularly those related to human-intensive personal services, arenot easily replaced by AI and robotics. From a policy perspective,

Editors' note: This article first appeared on www.VoxEU.org on
July 6, 2017. Reproduced with permission.
References• Arntz, M, T Gregory, and U Zierahn (2016), "The Risk ofAutomation for Jobs in OECD Countries: A Comparative Analysis,"
OECD Social, Employment and Migration Working Paper, no. 189.
• Autor, D H (2015), "Why Are There Still So Many Jobs? The History
and Future of Workplace Automation," Journal of Economic
Perspectives 29(3): 3–30.
• David, B (2017), "Computer Technology and Probable Job
Destructions in Japan: An Evaluation," Journal of the Japaneseand International Economies 43: 77–87.
• Frey, C B, and M A Osborne (2017), "The Future of Employment:
How Susceptible Are Jobs to Computerisation?," Technological
Forecasting & Social Change 114: 254–280.
• Mokyr, J, C Vickers, and N L Ziebarth (2015), "The History ofTechnological Anxiety and the Future of Economic Growth: Is ThisTime Different?," Journal of Economic Perspectives 29(3): 31–50.
• Morikawa, M (2017a), "Firms' Expectations about the Impact of AI
and Robotics: Evidence from a Survey," Economic Inquiry 55(2):1054–1063.
• Morikawa, M (2017b), "Who Are Afraid of Losing Their Jobs to
Artificial Intelligence and Robots? Evidence from a Survey," RIETI
Discussion Paper, 17-E-069.

Research Activities

employees, temporary agency workers, and entrusted employees"Power of Data
Analysis" Essential
to Evidence-based
Policymaking
Koichiro
Ito
Fellow (Specially Appointed),
RIETI

Lately, people have begun to point to the importance of evidencebased policymaking. The idea is that evidence-based discussion,
supported by scientifically rigorous data analysis, should informgovernments in their decisions in formulating and changing
policies. The concept of evidence-based policy (EBP), initiatedin the United States and the United Kingdom, has spread to othercountries. In recent years, Japanese government ministries andagencies have been increasingly showing interest.
In order to accelerate the move toward evidence-based
policymaking, government policymakers, as the users of

RIETI Highlight 2018 Special Edition23

evidence, need to have the ability to understand data analysis
results accurately as well as detecting false results so as not
to be deceived. However, a recent survey has found that such
understanding is far from being widespread.
In this article, I would like to consider what is the "power of data
analysis" that is essential to evidence-based policymaking, partly
drawing on my recent book (Ito 2017).

Lack of ability to understand data analysis posing
an obstacle to evidence-based policymaking

Research Activities
24

RIETI conducted a set of surveys to find out the actual state ofevidence-based policymaking in Japan (Morikawa, 2017). One
particularly interesting finding is how policymakers and policy
researchers responded to the question asking what factors they
think are posing an obstacle to evidence-based policymaking.
Approximately two-thirds of the respondents in both groupscited "Government officials are not skilled enough to analyze
statistical data and understand relevant research findings," pointing
to the need to enhance the analytical skills of government officials
as essential infrastructure for evidence-based policymaking.

Importance of distinguishing causality
from correlation

significant energy-saving effects."
Now, let's consider why this conclusion may be false. You want
to show the effects of energy conservation subsidies on energy
consumption based on the results of data analysis. However, apartfrom the provision of subsidies, various other factors may haveaffected energy consumption in 2010 and 2012.
For instance, energy consumption for air conditioning atfactories might have decreased because of a cooler summer in2012 than in 2010. Employees of Company A might have become
more conscious of the need to conserve energy in the wake of theGreat East Japan Earthquake in 2011. Or, perhaps Company A
introduced new, energy-efficient equipment in 2011 as had beenplanned regardless of the availability of the subsidy. Thus, fromthis data analysis, we cannot conclude that the provision of thesubsidy caused Company A to improve its energy efficiency by
20%.
In other words, while the figure below shows a correlation
between the provision of energy conservation subsidies and energy
consumption, we cannot tell whether there is causality between thetwo factors. We can exclude the influence of some factors, suchas differences in weather conditions, for which data are available.
However, data on changes in employees' awareness of the needfor energy conservation and those pointing to the fact that a certain
company was to make capital investment in 2011 regardless areusually not available. Unless we exclude the influence of thesefactors, we cannot say that the provision of subsidies is effective
as a measure to promote energy conservation by citing thecorrelation.

Although various skills are required to analyze statistical data andunderstand the resulting research findings, particularly importantis the ability to determine whether a relationship identified bydata analysis is a mere correlation or causality between policy
interventions and outcomes.
Let's consider a specific example. Suppose
Figure: Greater Energy Conservations Because of Subsidies?
that your boss asked you to find evidence
Energy consumption per unit
relevant to the policy question of whetherof production
subsidies for energy conservation measures are
effective in encouraging businesses to conserve
energy. Thus, you gather relevant historical data.
100
By examining the data, you find the following.
In 2011, Company A applied for and received afive million yen subsidy for energy conservation.
Data aggregated for Company A show that its
80
energy consumption per unit of production
decreased from 100 in 2010 to 80 in 2012.
Based on this evidence, you make thefollowing report to your boss: "As shown inTiming of
the figure on the right, Company A's energy
subsidy provisionconsumption per unit of production decreased
by 20% because of the effects of the subsidy
provision. Therefore, the provision of energy
conservation subsidies is expected to have
2010
2012

RIETI Highlight 2017 Special Edition

Mistaking mere correlation for causality in policymaking
could result in a waste of taxes by deriving the conclusionthat an ineffective policy measure has been effective. Suchmisinterpretation could also work in the opposite direction witha highly effective policy measure pronounced to have beenineffective, leading to a conclusion that calls for the abolishment of
the policy measure.
When thus explained, it is relatively easy to understand that
we should not take the presence of correlation as evidence inpolicymaking. In reality, however, the results of data analysis
provided by those referred to as "specialists in data analysis" at theforefront of policymaking are mostly cases of mere correlation,and many of them are presented as "evidence" showing causality.
This makes it all the more important for policymakers as usersof such evidence to understand the difference between mere
correlation and causality.

What sorts of data analysis can identify
the causal effects of policy interventions?
The U.S. Commission on Evidence-Based Policymaking, launchedunder the Barack Obama administration, has been promoting theutilization of a data analysis approach that can provide scientificevidence of causality between policy interventions and outcomes.
The "randomized controlled trial (RCT)" method provides
the most reliable scientific testing. One case example of theuse of RCTs in Japan is the Agency for the Natural Resources
and Energy's Next-Generation Energy and Social Systems
Demonstration Project in which I was involved. Meanwhile, the"natural experiment" method, which takes advantage of a realworld setting similar to an unnatural setting prepared specificallyfor a social experiment and can be implemented even in cases
where RCTs are unfeasible, has continued to evolve.
Those readers interested in natural experiments may refer to Ito(2017) for more details. Here, I would like to draw attention to an
important international trend. That is, U.S. and UK policymakers
practicing evidence-based policymaking are increasingly
demanding that evidence providers conduct scientific analysis tosupport evidence. In extreme cases, policymakers (such as the U.S.
Department of Energy) have gone so far as to issue an order thatno analytical findings be admitted as evidence unless supported
by scientific analysis. By imposing stringent demands on those
providing analysis results, policymakers are creating trends toward
policy discussion based on highly reliable evidence.
Attempts to utilize evidence derived from scientific research

Editors' note: This article first appeared on www.rieti.go.jp/en/ on
May 9, 2017.

Research Activities

Why do we need to distinguish causality
from correlation?

in actual policymaking have been made in various countries. For
instance, the California Public Utilities Commission (CPUC) used
research findings from a researcher at the University of California,
Berkeley as well as mine in its policymaking meeting (Borenstein,2012; Ito, 2014). At the meeting, the commission pointed to theneed to simplify and clarify the electricity rate structure by citing
the analytical findings showing that a complex rate structure
would cause confusion on the part of consumers and fail to deliver
the intended policy effects, and this led to the simplificationand clarification of electricity rate structure in California(CPUC, 2015). In another similar example, the Inter-American
Development Bank (IDB) terminated its One Laptop per Child
program and moved on to try out new development assistanceprograms after scientific analysis showed that the provision of freelaptops did not have its intended effects on children in developing
countries (Cristia et al., 2012). Meanwhile, the University of
Chicago Crime Lab and the city of Chicago have been making
continuous efforts to jointly analyze the effects of various policy
interventions designed to prevent youths from developing criminal
behavior in a bid to promote cost-effective measures by having
cost-ineffective ones curtailed or eliminated (Heller et al., 2015).
Following these examples, Japan should work to produce
reliable evidence and start discussing how we can make effective
use of such evidence in actual policymaking.

References• Ito, Koichiro, 2017, Deta Bunseki no Chikara: Inga Kankei ni
Semaru Shikoho [The Power of Data Analysis: How to approachcausality] (in Japanese), Kobunsha Co., Ltd.
• Morikawa, Masayuki, 2017, "Evidence of ‘Evidence-Based
Policymaking'" (in Japanese), RIETI Policy Discussion Paper Series
17-P-008.
• Borenstein, Severin. 2012. "The redistributional impact of nonlinear
electricity pricing," American Economic Journal: Economic Policy,
vol. 4, no. 3, pp. 56–90.
• CPUC (California Public Utility Commission). 2015. Proposed
Decision filed by ALJ/McKINNEY/CPUC on 04/21/2015 Conf#
85061. Proceeding: R1206013.
• Cristia, Julian, Ana Santiago, Santiago Cueto, Pablo Ibarraran,and Eugenio Severio. 2012. "Technology and Child Development:
Evidence from the One Laptop per Child Program." IDB Working
Paper Series 304.
• Ito, K. 2014. "Do Consumers Respond to Marginal or Average
Price? Evidence from Nonlinear Electricity Pricing." American
Economic Review, 104(2): 537–563.
• Heller, Sara B., Anuj K. Shah, Jonathan Guryan, Jens Ludwig,
Sendhil Mullainathan, and Harold A. Pollack. 2015. "Thinking, Fastand Slow? Some Field Experiments to Reduce Crime and Dropout
in Chicago." NBER Working Paper, 21178.

RIETI Highlight 2018 Special Edition25

Toward Artificial
Intelligence
Technologies as an
Integral Part of Service
Business Operations
Yoko
KonishiSenior Fellow, RIETI

for the RIETI Column (Konishi 2014), I provided an overview
of a boom in big data. At the time, I strongly hoped that anotheremerging boom in statistics (and data science) would be alasting one. As it turns out, statistics (and data science) founda role for itself in today's world as a tool for machine learning,a data analysis method attracting much attention amid theongoing AI boom, and that for evidence-based policymaking(EBPM). What started as vague interest in data science is now
focused on this particular aspect as a tool indispensable for AI

Unprecedented opportunity
Research Activities

Recently, we have frequently encountered such terms as big
data, artificial intelligence (AI), and the Internet of Things(IoT) revolution in daily media reports or on social networking
sites (SNS). The importance of such emerging technologies
is widely recognized even among those with an aversion tonumbers and statistics (and data science). In my previous article

Figure: AI Booms and Related Developments
FY

AI

–

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↑Rumelhart et al. (1986) introduce a training algorithm called backpropagation.

Big data

Fifth-generation computer project (MITI*1) 57 billion yen

*1
*2

26

Ministry of International Trade and Industry
New Energy and Industrial Technology Development Organization

RIETI Highlight 2017 Special Edition

2
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The second neuroscience boom ends due to lack of sufficient data.
The development of machine learning techniques continues steadily.

Second neuroscience boom

National
projects20
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Ice age

Second AI boom

Machinelearning

1993Real World Computing (RWC) Project (MITI)
1991– R&D of RWC technology (20.2 billion yen)
1997– R&D of next generation information
processing technology (26.3 billion yen)

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Third AI boom

Beginning of deep learning
research Hinton et al. (2006)

Deep learning boom
↑A machine using a deep learning technology wins an image
recognition contest (2012)

Big data boom

No major AI-related national projects

Development of coretechnologies for next
generation robots(Next generation AI)(NEDO*2 / AIST)

Source: Konishi and Motomura (2017)the 2000s, and so did relevant large-scale national projects
from the first half of the 2000s through 2015. A key turning
point along the way came in 2006 when a group of researchers
introduced a new learning algorithm that allows a neuralnetwork to have multiple hidden layers connecting the input
and output layers. This activated research on deep learning.
Then, in 2012, a machine using a deep learning technology
won an image recognition contest, attracting attention from allover the world, hence creating a deep learning boom. In parallelwith this, Japan's third AI boom began in 2013. Notably,
these booms overlap with a big data boom that began in 2012.
Furthermore, in May 2015, the Artificial Intelligence ResearchCenter (AIRC), the largest AI research and development (R&D)
hub in Japan, was established within the National Institute ofAdvanced Industrial Science and Technology (AIST). It is
undertaking R&D on next-generation AI through March 2020,
and industry-government-academia collaboration in AI researchonce again has been set in motion.
Today, we have everything needed for AI development,
ranging from machine learning-based AI technologies, highperformance computing, and big data to relevant large-scale
projects and industrial application needs. They together offer
the greatest ever opportunity and explain the reason why theongoing boom is so extensive and having an impact on theentire society.

AI literacy and service business
operations

Research Activities

and EBPM.
Meanwhile, the AI boom that started in 2012 shows no signsof fading, as AI continues to evolve and find its way into oureveryday lives. Why is the AI boom this time around—the third
one—lasting so long?
The timeline in the Figure, taken from Konishi and
Motomura (2017), shows the development of AI, machinelearning, big data, and relevant large-scale national projects
over the years. In the first half of the second AI boom, machinelearning—in which computers learn from data without being
explicitly programmed—was not linked with AI technologies,
and thus, the construction of information systems involved anenormous amount of human work, i.e., writing programs forcomputers to perform specific tasks and processes. The latter
half of the second AI boom overlapped with the second boom
in neuroscience, a period in which numerous theoretical andapplied studies on neural networks were carried out. However,as the processing capacity of computers was rather limited andlarge-volume data—such as those referred to as big data—
were not available, neuroscience at this stage failed to achievea sufficiently high level of precision, ushering in the ice age ofneuroscience in the first half of the 1990s.
As shown in the Figure, AI technologies and neural networks
had no major boom from the 1990s through the first half of

AI technologies introduced for use in service business
operations are mostly purpose-specific—rather thanmultipurpose as seen in humanoid robots—and designed toperform and automate specific tasks previously carried out
by humans just as well as, or even better than, humans. In
my previous article (Konishi 2015), I defined AI literacy as
being conscious about whether excessive labor, money, ortime is spent carrying out tasks that machine learning andother AI technologies are highly capable of performing, i.e.,
categorization, repetition, exploration, organization, andoptimization. AI is most efficient when used to perform thekind of tasks in which repeating, increasing the number of
combinations, and/or spending more time will lead to greater
accuracy and/or value.
For instance, suppose there is a project that involves finding
and approaching potential customers in order to earn revenue.
In classifying the existing customers for this purpose, coming
up with several distinctive features or properties per customer
would be the maximum that a human worker is capable ofdoing. However, AI would make it possible to identify several

RIETI Highlight 2018 Special Edition27

Research Activities

dozen features or properties per customer by segmenting
customers based on their purchasing behavior. Meanwhile, an
AI system programmed to access information on economic
trends or information about certain rival companies would be
able to produce a strategy that reflects such information. Thisis very elementary, but information must be on the network to
be accessible to AI, or conversely, everything on the network
is accessible as information to AI. Unlike those that havebeen introduced for use in manufacturing operations, AI andinformation and communications technologies (ICT) currently
available for use in service operations are devices, rather thanmachines. Those devices—whether wearables or personal
computers—can be introduced on a piece-by-piece basis andmake a difference, thanks to the accumulation of massive data
as well as to the reduced size, refinement, and prevalence of
information technology equipment. Against this backdrop,
an increasing number of companies—both big and small—are showing willingness to collect big data and utilize AI
technologies. However, no matter how convenient they are, itremains our task to determine what technologies to employ forour business processes. It is not easy to gain insights into what
it takes under what environment to make a project successful
and sustainable.

Perspectives needed to make AI
sustainably useful
Konishi and Motomura (2017) reviewed 28 AI projects
undertaken by AIST regarding their respective purposes andoutcome. Many of them are practical, intended for applicationin real world service operations, for instance, to improve work
processes for providing medical and nursing care services,
make service recommendations to clients in the entertainment
industry, and optimize commodities logistics. Through thisreview, we found some answers to our simple question: Whatkinds of AI projects develop sustainably?
1. The purpose of the project and the uses of technology areclear, and benchmark targets can be translated into data.
2. Workers on the frontline are highly motivated and havestrong needs for AI.
3. It is possible to accumulate and integrate data at a relatively
low cost via sensors, networks, and the Internet.
4. It is possible to collect data continuously by integrating theprocess into the regular flow of work.
5. Knowledge obtained by analyzing data and/or the results ofcalculation can be used as additional data.

28

RIETI Highlight 2017 Special Edition

We can see that data play crucial roles in AI projects.
Meanwhile, researchers are working to develop various
techniques and algorithms collectively referred to as AI
technologies. Put into practical applications as soon as madeavailable, these technologies are quick to penetrate. Given the
programming techniques and computing environment as theystand today, it is quite easy to improve and utilize existing
systems in accordance with the needs of workers. In otherwords, since data are the key determinant of the performance ofmachine learning-based AI, the sustainable availability of highquality data is crucial to competitiveness. The quality of data isdependent on frontline workers' ability to collect data, whether
at a retail shop or inside a company office. Collecting as muchinformation as possible on the behavior of as many people aspossible will enhance the precision of analysis and the value ofdata.
The initial stage of decision making over whether or not
to introduce an AI system is quite important. In selecting a
specific AI system out of many available options, it is importantto have the perspective of looking at what outcome or value
added we intend to generate with this task and asking why wewant machines to take this task away from human workers. Just
look around your own room. You will see quite a few home
appliances that were purchased to improve efficiency or for
pure satisfaction but which have been left unused for long time.
The same holds true for business and AI investments. We often
seek to introduce AI as if doing so were a goal. In order not tofall into this pitfall, we must make sure we know the reason
and the purposes for introducing AI.
Editors' note: This article first appeared on www.rieti.go.jp/en/ on
June 2, 2017.
References• (1) Konishi, Y. (2014), "What is Needed to Ensure that the Boom in
Big Data Lasts?" RIETI Column.
• (2) Konishi, Y. and Yoichi Motomura (2017), "Initiatives andChallenges for Social Implementation of AI Technology: Learningfrom AIST's AI projects," RIETI PDP series 17-P-012 (in Japanese).
• (3) Konishi, Y. (2015), "What is Needed for AI Literacy?" RIETI
Special Series: Priorities for the Japanese Economy in 2016.

Agglomeration Benefits
versus Firm Selection
Keisuke
Kondo
The large literature on agglomeration economies attests to the higher average productivity of firms in larger
cities. However, this literature focuses on positive externalities, and a second potential mechanism—selection
against less productive firms—has received little empirical attention. This column explores how these two
mechanisms contribute to higher productivity in Japanese cities. Consistent with earlier work considering thecase of France, no evidence for a selection effect is found.
It is well known that firms, on average, are more productive inlarger cities. Agglomeration economies are considered to generate
benefits as positive externalities (e.g. Combes and Gobillon2015). However, recent theoretical studies have proposed anotherhypothesis of selection. As introduced by Melitz (2003) in theinternational trade literature, selection is defined as less-productive
firms being unable to survive in the market. Further introducing
the endogenous markup, Melitz and Ottaviano (2008) showed thatlarger markets bring about tougher selection, and, consequently,
aggregate productivity in larger cities is higher than that in smaller
cities, since only more-productive firms survive in larger markets.
A crucial empirical concern is to examine whether higher
productivity in larger cities derives from agglomeration economies
or firm selection. The standard regression approach cannot
distinguish productivity advantages of agglomeration economies
from firm selection. Although urban economists have understood
the productivity advantages of large cities as deriving fromagglomeration economies, there may be different implications ifstronger selection plays the key role. Thus, there is an increasingneed to develop a new empirical methodology that can distinguishagglomeration from selection.

Quantile approach to distinguishagglomeration from selection
To simultaneously test for agglomeration economies and firm
selection in spatial productivity differences, Combes et al.
(2012) developed a new quantile approach that focuses on
entire productivity distributions through three key parameters(shift, dilation, and truncation), whereas the standard statistical
approach only captures the shift and dilation through the mean
and variance of distributions. Agglomeration economies arecaptured by the right-shift of productivity distributions between
larger and smaller cities (i.e. the right-shift captures the differencein average productivity between larger and smaller cities).
Furthermore, Combes et al. (2012) considered the dilation effectof agglomeration economies, which indicates that more-productive
firms can enjoy greater benefits from agglomeration (i.e. thedilation examines whether productivity distributions in larger
cities are more dispersed than those in smaller cities). Finally,
the selection is detected as a left-truncation of the productivity
distribution (i.e. the left-truncation captures how less-productive
firms can't survive in larger cities).
An empirical issue is that when stronger selection exists in the
productivity distribution for larger cities, the omitted truncation
parameter causes overestimation of the right-shift effects,
and underestimation of the dilation effects of agglomeration
economies. Figure 1 (see next page) offers an intuitive explanation
regarding this bias. Panel (a) exhibits agglomeration economies

RIETI Highlight 2018 Special Edition

Research Activities

Fellow, RIETI

29

background mechanism in cities is entirely different. The quantile
approach suggested by Combes et al. (2012) compares the entire
productivity distributions between larger and smaller cities tosimultaneously examine whether agglomeration or selection plays
the more important role.

via a right-shift of the productivity distribution (same selection
in both cities). By contrast, Panel (b) exhibits stronger selection
in larger cities, but no agglomeration economies (i.e. no rightshift of the productivity distribution). In other words, both panels
show that average productivity is higher in larger cities, but the

Figure 1:
Comparing Entire Productivity Distributions Between Large and Small Cities

Density(a) Agglomeration Economies (Same selection)

−4.0

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Log (TFP)(b) Stronger Selection in Larger Cities (Same agglomeration economies)

Density

Research Activities

−5.0

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Log (TFP)
Note: Created by author. The solid and dashed lines denote productivity distributions for larger and smaller cities, respectively. Panel (a) shows
agglomeration economies (right-shift only) and the same selection. Panel (b) shows stronger selection in larger cities and the same level ofagglomeration economies.

Empirical findings
My study applies this new quantile approach to the Japanesemanufacturing sector from 1986 to 2013 (Kondo 2016). I
hardly find any stronger selection effects in larger cities (i.e.
no stronger left-truncation of productivity distribution in larger
than smaller cities). Conversely, as shown in Figure 2, higher

30

RIETI Highlight 2017 Special Edition

average productivity in larger cities is mostly explained in termsof the right-shift of the productivity distribution, suggesting that
agglomeration economies do better explain spatial productivity
differences in the Japanese manufacturing sector. In addition,
the dilation effect of agglomeration economies shows greater
variations across sectors. On the one hand, more-productive firms
enjoy greater benefits from agglomeration in some sectors, while,on the other hand, less-productive firms enjoy greater benefits

from agglomeration in other sectors.
Another key testable prediction of Combes et al. (2012) iswhether benefits from agglomeration economies decrease asinterregional accessibility increases. For example, informationand communications technology facilitates the exchange of ideas
between geographically distant cities, decreasing the potential

benefits of agglomeration economies. I find that benefits fromagglomeration economies in the Japanese manufacturing sector
have decreased in the recent decade. This suggests that whenregional economies are integrated more tightly as communicationand transportation costs decrease, the productivity advantages ofagglomeration also decrease.

Figure 2:
TFP Distributions Between Above- and Below-Median Employment Density for All Sectors(a) 1986–2000

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Research Activities

Density

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Density

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Log (TFP)

Note: Kondo (2016). The solid (dashed) line is the productivity distribution of cities with above-median (below-median) employment density.
Estimation results by sector are available in Kondo (2016).

Toward further empirical studies
The main findings in the Japanese manufacturing sector are
similar to those of Combes et al. (2012), which concluded thatfirm selection does not play a crucial role in determining spatial
productivity differences in the French manufacturing sector. By
contrast, focusing on the pre-war Japanese silk reeling industry,

Arimoto et al. (2014) concluded that selection played a key rolein explaining why aggregate productivity in silk industrial clusters
was higher than that in non-clusters. They also found that relatively
less-productive firms enjoyed greater benefits from agglomeration
economies, which indicates that the productivity distribution
for the silk industrial cluster was less dispersed than that in nonclusters. These findings are in contrast to Combes et al. (2012) andthose presented here.

RIETI Highlight 2018 Special Edition31

Limited evidence in this literature is not enough to conclude
that selection does not matter in spatial productivity differences.
This literature requires further empirical studies worldwide, since
there may be more counterexamples in other countries and time
periods. Considering why differences arise across countries andtime periods will deepen our understanding of agglomeration
economies and help us draw better implications for urban andregional policies.
Finally, in Kondo (2017), I developed a new Stata command,
estquant, which implements the quantile approach suggested by
Combes et al. (2012) on Stata. I hope that the estquant command
helps researchers apply this new approach and extend the empiricalevidence in this literature.

Editors' note: This article first appeared on www.VoxEU.org on
July 23, 2017. Reproduced with permission.

References

Research Activities• Arimoto, Y, K Nakajima and T Okazaki (2014), "Sources of
productivity improvement in industrial clusters: The case of the
prewar Japanese silk-reeling industry," Regional Science and
Urban Economics 46: 27–41.
• Combes, P-P and L Gobillon (2015), "The empirics ofagglomeration economies," in G Duranton, J V Henderson and W
C Strange (eds), Handbook of Regional and Urban Economics, 5,Amsterdam: Elsevier, Chapter 5: 247–348.
• Combes, P-P, G Duranton, L Gobillon, D Puga and S Roux (2012),"The productivity advantages of large cities: Distinguishing
agglomeration from firm selection," Econometrica 80(6): 2543–
2594.
• Kondo, K (2016), "Testing for Agglomeration Economies and Firm
Selection in Spatial Productivity Differences: The case of Japan,"
RIETI Discussion Paper 16-E-098.
• Kondo, K (2017), "Quantile Approach for Distinguishing
Agglomeration from Firm Selection in Stata," RIETI TechnicalPaper 17-T-001.
• Melitz, M J (2003), "The impact of trade on intra-industry
reallocations and aggregate industry productivity," Econometrica
71(6): 1695–1725.
• Melitz, M J and G I P Ottaviano (2008), "Market size, trade, andproductivity," Review of Economic Studies 75(1): 295–316.

The "Scientification" of Industry:
New indicators of science intensity

Kenta
IkeuchiKazuyukiMotohashi

RyuichiTamuraNaotoshiTsukadaFellow, RIETI

Faculty Fellow, RIETIAssociate Professor,
Wakkanai Hokusei Gakuen
University

Research Associate, RIETI

There is growing interest in measuring the scientific aspects of industrial innovation and performance tounderstand the economic impact of publicly funded research and development (R&D). This column presents
new indicators for science-industry linkages in Japan based on a novel dataset combining academic research
paper data, patent data, and economic census data. It finds that the academic sector is getting more involved inpatenting activities, and that scientific knowledge generated in the sector is being utilized not only in sciencebased industries, but also in many others.

32

RIETI Highlight 2017 Special Editioncaptured using patent-publication pairs, i.e. overlapping content
regarding the research output/invention between patents andresearch papers (Lissoni et al. 2013, Magerman et al. 2015).
Both of these indicators reflect only one aspect of sciencelinkages—non-patent literature citations show the degree of
disembodied scientific knowledge that flows into patents, while
the patent-publication pair indicates co-occurrence of scientificand invention activities within the same research. Our proposed
new indicators of science-industry linkages can capture the linkage
between science and technology embodied in human capital(academic inventors) via patenting, and the indicators are based ona novel dataset combining science (academic research paper data),
technology (patent data), and industry (economic census data) at
the author/inventor and firm levels to see how academic discipline,
technology, and economic activities are interlinked.
Figure 1 illustrates the relationship between the dataset and theindicators. While the non-patent literature citations of patents are
based on a firm's patent citations of scientific publications in theacademic sector, our new indicators for science-industry linkage
capture the interactions between the industry and the academia inpatenting activities, i.e. joint inventive activities (captured by joint
patent inventions) and firms' patent citations to academic patents.
Both industry citations to the academic inventors' patents and thejoint patent inventions between firms and such academics reflect

Figure 1: Framework of Indicators

Science (Paper)

Technology (Patent)

Research Activities

A scientific foundation has become increasingly integral to theindustrial innovation process. For example, genome science has
substantially changed the R&D process of the pharmaceuticalindustry. Miniaturization of the large-scale integrated circuit
fabrication process requires an understanding of the nanolevel physicality of its materials. Furthermore, advancements in
information technology have a significant impact on society andthe economy. In particular, 'big data' analysis contributes to thescientific understanding of business and management activities(Redding and Weinstein 2016). Since science sectors, such asuniversities and public research institutes, are heavily subsidized
by public money, there is a growing interest in measuring thescientific aspects of industrial innovation and performance tounderstand the economic impact of public R&D, despite severe
constraints on public spending in general. Against this background,in a recent paper, we propose new indicators of science-industry
linkages that reflect the interaction between science and industry
via academic patenting activities (Ikeuchi et al. 2017).
Traditionally, the degree of scientific basis, or ‘science intensity'of industry has been measured using non-patent literature citations
made by patents (Narin and Noma 1985, Schmoch 1997). This
indicator captures the extent to which patents (technology forindustrial use) are based on the scientific content of research
papers. Alternatively, the science-technology linkage can be

Industry(Firm performance)

Paper author/Academic inventor
Linkage at researcher level

HEIs and PRIs

# of papers by
academic field
Academic Patents

Joint Patents+

Citation

Firm Patents
NPL Citation

Firm# of employment byindustry

Patent Applicant/Economic Census
Linkage at firm level

RIETI Highlight 2018 Special Edition33

Research Activities

different channels of scientific knowledge flow from academia to
industry compared to those measured by conventional indicatorssuch as non-patent literature citations in patents. Furthermore,unlike past studies regarding paper-patent linkage at the researcher
level for particular technologies, such as biotechnology (Murray2002) and nanotechnology (Meyer 2006), our dataset covers alltechnological fields by constructing a large-scale database.
Our new indicators are intended to capture the mechanismof involving scientific knowledge in industrial innovation via
patenting activity of academia. Although universities and publicresearch institutes principally provide scientific publications as
their research outputs, there is a growing global trend of patentapplications from these institutes (OECD 2013). In Japan, national
universities, which used to be government organizations, became
independent agencies in 2004. This institutional reform allows
them to claim patent rights, and university patent applications
have increased significantly (Motohashi and Muramatsu 2012).
Therefore, a patent-based science linkage indicator has become
increasingly important.

Academia-industry interactions via
patenting in Japan
According to our dataset, as shown in Table 1, the proportionof academia among inventors increased in Japan from 3.2% in
the period 2000–2003 to 5.4% in the period 2008–2011. The
proportion of academic authors with patent inventions also
increased from 3.0% in 2000–2003 to 4.1% in 2008–2011.
Furthermore, the proportion of academic authors to total inventors
doubled from 1.4% to 2.8% during the 12-year period.
Figure 2 shows the aggregated trend of academic involvement
in industry innovation. It shows that both the shares of academiaindustry joint applications and patents citing academic patents
increased from 2000–2003 to 2004–2007. In subsequent periods(2008–2011), the share of joint applications increased further,while the share of patents citing academic patents decreased.
Additionally, the number of inventors per employee (reflecting
R&D intensity) decreased over time in the industry sector.

Table 1:Patent Inventors and Academic Authors Active in 2000–2011 in Japan

2000–2003

2004–2007

2008–2011

Total

[A]

Number of authors

316,031355,936

381,660

739,372[B]

Number of all inventors

673,927

623,849

562,8221,229,027[C]

Number of academic inventors

21,43731,42130,50553,446[C/B]

Proportion of academia in inventors

3.2%

5.0%

5.4%

4.3%

[D]

Number of patenting authors

9,532

15,726

15,59826,333[D/A]

Proportion of inventors in authors

3.0%

4.4%

4.1%

3.6%

[D/B]

Proportion of authors in inventors

1.4%

2.5%

2.8%

2.1%

Source: Authors' calculations based on Scopus and the IIP patent database.

Figure 2: Science-Industry Relations in Patents

3.0%% patents jointly invented
with academia

2.5%
2.0%

% patents citing academic
patents (applied in current
period)1.5%
1.0%% inventors in all employees

0.5%
0.0%

34

2000–2003

RIETI Highlight 2017 Special Edition

2004–2007

2008–2011

New indicators of science intensity offirms
We define science intensity as the amount of new scientificknowledge (the number of academic papers) utilized byinventors in firms through joint inventions with academia and/or academic patent citations per employee in industry. Figure 3
shows the science intensity in the total economy in Japan, which
increased from 2000–2003 to 2004–2007 by increasing both joint
inventions and academic patent citations. After the incorporationof Japan's national universities in 2004, academic patentapplications increased substantially. Moreover, industry-university

collaboration activities have been promoted for over ten years,
which has contributed to the increase in science intensity indicators
after 2004.
However, the total science intensity decreased from the second
to the last period. Along with the incorporation of the national
universities in 2004, the research outputs of the universities
sufficiently valuable for patent applications were intensively
patented, and, accordingly, patent citations to academic patents
temporarily increased sharply in 2004–2007. For that reason, in
the last period, research outputs suitable for patenting at university
might have been exhausted. The decline in joint research may be
influenced by the fact that firms saved R&D investment due to the

Figure 3:
Employee-Based Science Intensity in the Total Economy(Average number of linked academic publications per 100 employees)
4.0

0.8

3.0

3.0
0.5

0.3

2.5

0.2

2.1
0.5
2.0
1.5

via Patent Citation only (EACH period)

0.5

via Joint Invention & Patent Citation

0.2
2.4

1.0

via Joint Invention only

2.3

1.5
0.5
0.0

2000–2003

2004–2007

Research Activities

3.6
3.5

2008–2011

Figure 4: Employee-Based Science Intensity by Industry(Average number of linked academic publications per 100 employees)
60

2000–2003

2004–2007

2008–2011

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RIETI Highlight 2018 Special Edition35

recession after the collapse of Lehman Brothers in 2008.
Figure 4 (see previous page) shows the industry breakdownof employee-based science intensity. It shows that the chemicaland pharmaceutical industries substantially lead other industries.
However, the science intensity indicator has generally increasedin other industries, which means that ‘scientification' of industrial
innovation can be observed across industries. In general, the crossindustry distribution of science intensity becomes equal.

Utilization rate of science knowledge

Research Activities

We also defined an indicator from the viewpoint of science as autilization rate of science-knowledge of academic research byindustrial inventors, via joint invention with industrial inventors
and/or citations by industrial patents to academic patents. Figure
5 shows the aggregated trend of this indicator. A similar trend isobserved in the employee-based science intensity, which increased
from 2000–2003 to 2004–2007 and decreased in the subsequent
period. The changes in the utilization rate of science-knowledge
are caused not only by the demand side factors of scientificknowledge in industry, but also by the supply side factors ofscientific activities. The up-and-down trend of the utilization rateof science-knowledge is similar to that of employee-based science
intensity, but it should be noted that any changes in supply-side
factors such as new scientific advancements may affect the trend.
Viewing this trend from an academic perspective, the situation
is more complicated. In general, as shown in Figure 6, the industry
utilization rate increased over time, while a sharp decline from2004–2007 to 2008–2011 is found in some fields (e.g. chemistry,
physics, and astronomy). In contrast, some academic fields, suchas mathematics and social science, show a strong increasing
trend. Thus, the overall inequality in URSK in the academic field
decreases from 2000–2003 to 2008–2011.

Discussion and conclusion
In this column, we have presented new indicators to measurescientification of industry in Japan, by linking a scientific paper
database (science), patent information (technology), and economic
census data (industry). The new indicators reflect a mechanism ofscience linkage between science and industrial activities, whichcannot be measured by the existing indicators based on non-patent
literature citations.
These new indicators of science linkage in Japan show anincreasing trend over the past ten years. One reason behind thesetrends is the institutional reform of the academic sector in Japan, i.e.
incorporation of national universities in 2004 and various polices
stimulating university-industry collaborations from the late 1990s
onwards (Motohashi and Muramatsu 2012). These policy actions
induced academic sectors to work with industry, which involved
patenting activities.
Moreover, the growing importance of scientific inputs inindustrial innovation has an impact as well. In our analysis, sciencelinkage with industry is found not only in science-based industries,
such as pharmaceuticals and electronics, but also in many otherindustries. Our study has shown that scientific knowledge becomesgeneral inputs in almost all industries, and this trend can bereferred to as the 'science-based economy', for non-science basedindustries as well.

Figure 5:
Utilization Rate of Science Knowledge(Share of academic publications linked to industry in total academic publications)
16.0%
14.0%

13.4%
0.6%

12.1%

12.0%
10.0%
8.0%

0.4%

0.4%

9.5%

4.7%

3.4%

via Patent Citation only (EACH period)
3.3%

via Joint Invention & Patent Citation

6.0%
4.0%

8.1%

8.2%

2004–2007

2008–2011

5.9%
2.0%
0.0%

36

2000–2003

RIETI Highlight 2017 Special Edition

via Joint Invention only

Figure 6: Utilization Rate of Science Knowledge by the Science Field(Share of academic publications linked to industry in total academic publications)30%

2000–2003

2004–2007

2008–2011

25%
20%
15%
10%
5%

Editors' note: This article first appeared on www.VoxEU.org on
June 28, 2017. Reproduced with permission.
References• Breschi, S and F Malerba (1997), "Sectoral innovation systems:
technological regimes, Schumpeterian dynamics and spatial
boundaries," in C Edquist (ed.) Systems of Innovation,
Technologies, Institutions and Organisation, London: Cassel.
• European Patent Office (2015), The Worldwide Patent Statistical
Database (PATSTAT), Autumn edition.
• Goto, A, and K Motohashi (2007), "Construction of a Japanese
Patent Database and a first look at Japanese patenting activities,"
Research Policy 36 (9), 1431–1442.
• Ikeuchi, K, K Motohashi, R Tamura, and N Tsukada (2017),"Measuring Science Intensity of Industry using Linked Datasetof Science, Technology and Industry," RIETI Discussion Papers
Series 17-E-056.
• Li, G C, R Lai, A D'Amour, D M Doolin, Y Sun, V I Torvik, A Z
Yu, and L Fleming (2014), "Disambiguation and co-authorshipnetworks of the US patent inventor database (1975–2010),"
Research Policy, 43 (6), 941–955.
• Lissoni, F, F Montabio, and L Zirulia (2013), "Inventorship andauthorship as attribution rights: an enquiry into the economics ofscientific credit," Journal of Economic Behavior and Organization,
95, 49–69.
• Looy, B V, E Zimmermann, R Veugelers, A Verbeek, and K
Debackere (2003), "Do science-technology interactions pay off
when developing technology?," Scientometrics 57 (3), 355–367.
• Magerman, T, B V Looy, and K Debackere (2015), "Does
involvement in patenting jeopardize one's academic footprint? An
analysis of patent-paper pairs in biotechnology," Research Policy,
44 (9), 1702–1713.

• Mayer, K (2006), "Are patenting scientists the better scholars?
An exploratory comparison of inventor-authors with their noninventing peers in nano-science and technology," Research Policy,
35 (10), 1646–1662.
• Motohashi, K, and S Muramatsu (2012), "Examining theuniversity industry collaboration policy in Japan: Patent analysis,"
Technology in Society, 34 (2), 149–162.
• Murray, F (2002), "Innovations as co-evolution of scientific andtechnological networks: exploring tissue engineering," Research
Policy 32 (8–9), 1389–1403.
• Narin, F, and E Noma (1985), "Is technology becoming science?,"
Scientometrics, 7, 368–381.
• OECD (2013), Commercialising Public Research: New Trends andStrategies, Paris.
• Pavitt, K (1984), "Sectoral patterns of innovation: toward ataxonomy and a theory," Research Policy, 28 (6), 643–660.
• Redding, S, and D Weinstein (2016), "What big data tells us about
real income growth," VoxEU.org, October.
• Sagara, T, M Arikawa, and M Sakauchi (2001), "Distributed
location reference service", Transactions of Information Processing
Society of Japan, 42 (12), 2928–2940.
• Schmoch, U (1997), "Indicators and relations between science andtechnology," Scientometrics, 38 (1), 103–116.
• Tamada, S, Y Naito, F Kodama, K Gemba, and J Suzuki (2006),"Significant difference of dependence upon scientific knowledge
among different technologies," Scientometrics, 68 (2), 289–302.
• Torvik, V I, M Weeber, D R Swanson, and N R Smalheiser (2005),"A probabilistic similarity metric for Medline records: A model for
author name disambiguation," Journal of the American Society for
Information Science and Technology, 56 (2), 140–158.
• Torvik, V I, and N R Smalheiser (2009), "Author namedisambiguation in MEDLINE," ACM Transactions on Knowledge
Discovery from Data, 3 (3), Article 11.

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37

Research
DigestIn Research Digest, we interview authors of Discussion Papers (DP) to provide a simple introduction to theirunderstanding of problems addressed in their papers, along with the major points and policy implications.

Policy Uncertainty
in Japan
Arata Ito Fellow, RIETI

Research Activities

Arata Ito has been a fellow at RIETI since 2013. After receiving his
M.A. from Hitotsubashi University, he became a research associate at
the Institute of Economic Research, Hitotsubashi University in 2009.
In 2012 he joined the Graduate School of Economics, Universityof Tokyo as a project academic support specialist. His recent works
include: "Fiscal policy switching in Japan, the U.S., and the U.K.,"
Journal of The Japanese and International Economics, 25 (4),2011 (with Tsutomu Watanabe and Tomoyoshi Yabu) and "Policy
Uncertainty in Japan," NBER Working Paper No. 23411, 2017 (withElif C. Arbatli, Steven J. Davis, Naoko Miake, Ikuo Saito)

There is "a lack of clarity" and "uncertainty" over various government policies, e.g., re-postponement of the consumption tax
rate increase, negotiations for the Trans Pacific Partnership (TPP), and monetary policy. How would this affect consumption
activities and investment activities? RIETI Fellow Arata Ito prepared the News-based Economic Policy Uncertainty Index forJapan based on newspaper articles to quantify the uncertainty of policy steering, so as to analyze the relationship between
policy uncertainty and the economy. The study has found that the increase in policy uncertainty is the pre-stage of decline
in economic activities. The finding suggests that clarifying future policy steering to reduce policy uncertainty could prevent
deterioration of economic performance. Ito hopes that the index will prove to be useful for conducting economic research atboth the government and private levels, and implemented in academic studies for accumulating insight into policy uncertainty.

Research background and methodology- Tell us about your motivation behind conducting this study.

The world financial crisis from 2007 to 2008 caused the economy
to recede in many countries. The economy has since recovered,
but the pace of recovery has been quite slow. Why is it thatthe economic recovery has not gained momentum? Overseas
academics and media have presented several theories. One ofthem is with regard to policy uncertainty. For example, Stanford
University Professor John Taylor cited policy uncertainty as one of
the main inhibitors of economic recovery. He notes that— amidst
the poor outlook of the medical system reform, financial system
reform, as well as the monetary policy of the Federal Reserve
Board (FRB)—reduced policy uncertainty would encouragecompanies to utilize their surplus fund, thereby stimulating the
economy.
Researchers keenly observed whether actual data would
support this theory. A team of researchers including Universityof Chicago Professor Steven Davis and Stanford University
Professor Nick Bloom developed a new indicator called theEconomic Policy Uncertainty Index, focusing on newspaper

38

RIETI Highlight 2017 Special Edition

coverage, as I will explain later. Today, substantial knowledge
has been accumulated based on this index. Yet, Japan's level ofknowledge on policy uncertainty is quite poor compared to thatof European and North American countries. As the first step fornarrowing the gap, I thought it was necessary to ask three basic
questions, i.e., how Japan's policy uncertainty has changed withtime, which policy areas are the source of increasing uncertainty,
and how does policy uncertainty relate to economic activities.
- Tell us about actual results provided in your paper, particularly
about policy implications.
This policy discussion paper provides policy practitioners withthe results of joint research by Professor Davis, economists at
the International Monetary Fund's (IMF) Regional Office for
Asia and the Pacific, and myself. It gives three main findings,
corresponding to the three questions mentioned earlier. First of all,the policy uncertainty index rose when a new prime minister was
inaugurated or at the time of fiercely-contested national elections.
The index also rose at the Asian currency crisis from 1997 to 1998,
collapse of Lehman Brothers in 2008, U.S. debt ceiling crisis andU.S. credit rating downgrade in 2011, and, more recently, there-postponement of the consumption tax rate increase in 2016.
As you can see, Japan's policy uncertainty rises in response to not
only domestic factors but also overseas factors.
Next, the study also found that the rise in policy uncertainty
is attributable primarily to factors associated with fiscal policies.
More specifically, about 60% of all factors are related to fiscal
policies, while about 30% are associated with monetary policies.
Finally, simple quantitative analysis shows that the increaseof policy uncertainty is a precursor of decline in economic
performance.
Third, the study has indicated that the economy benefits fromhaving policy uncertainty kept low by way of stabilizing thegovernment's policy steering and clarifying policy outlook.
- Can you explain the method for measuring policy uncertainty?

There are several approaches to measuring policy uncertainty.
The first approach is to conduct a survey. The advantage ofthis approach is that it directly captures uncertainty facedby households and companies of varying characteristics. Its
disadvantage is the amount of work involved in conducting alarge-scale survey at high frequency, e.g., weekly or monthly. It
is also difficult to obtain retrospective data, making this approach
unsuitable for time series analysis.
There is also an approach of using newspaper coverage. The
research group led by Professor Bloom and Professor Davisdeveloped an indicator of policy uncertainty by focusing on thefrequency of newspaper coverage related to uncertainty. Against
the backdrop of this approach lies an assumption that households
and companies must be facing a state of high uncertainty whennewspapers carry a large number of such articles. The advantageof this approach is the retrospective availability of high coveragedata. Databases of articles, held by major newspapers, can be used
to search relevant articles published over a long period of time.
Its disadvantage is the difficulty in capturing uncertainty faced byhouseholds and companies of varying characteristics. This study
adopted the latter approach as it caters to the purpose of the study.

Methodology of the News-based Economic Policy
Uncertainty Index for Japan- Can you provide details of the methodology for compiling the Newsbased Economic Policy Uncertainty Index for Japan?
Of all of the articles published in the Nikkei, Yomiuri, Asahi, andMainichi newspapers, I searched for those that contain at least one
term relating to the three categories listed below for each month.
The article search covered the period from January 1987 to today.
Economy: "keizai (economy)," "keiki (economic condition)"
Uncertainty: "futomei (unclear)," "fukakujitsu (uncertain),""fukakutei (unconfirmed)," "fuan (concern)"
Policy: "zeisei (taxation system)," "saishutsu (expenditures)"and other policy-related terms
Japanese terms corresponding to "economy" and "uncertainty"

Policy Uncertainty in Japan Arata Ito, Fellow, RIETI
www.rieti.go.jp/en/publications/summary/17060012.html

have been chosen through careful comparison of Japanese
articles and their English translations provided by the respective
newspaper publishers. Let's take the case of "uncertainty" forexample. First, I randomly selected a specific number of articles
from the searched articles containing the words "uncertainty"
or "uncertain." Then, the selected articles were comparedagainst their Japanese equivalent articles to identify Japaneseterms corresponding to "uncertainty" or "uncertain." This foundthat "futomei," "fuan," "bimyo," "fukakujitsu," "fuantei," and"fukakutei" were used as corresponding terms at a relatively highfrequency.
Then, I randomly selected a specific number of articles fromarticles containing both "keizai" or "futomei." The selected
articles were compared against their English equivalent articles
to identify English terms corresponding to "futomei." The same
comparison was made for the other five Japanese terms mentioned
above as well. Of the six terms, those that corresponded to"uncertainty" or "uncertain" at a high frequency were "futomei,""fuan," "fukakujitsu" and "fukakutei." This study therefore
adopted these four terms as Japanese equivalents of "uncertainty."
The same process was applied to the term "economy," and thestudy consequently adopted "keizai" and "keiki" as its Japaneseequivalents.
As for the "Policy" category, I used many of the terms that
Professor Davis et al. listed as candidate terms when they
compiled the U.S. version of the index. The aforementioned
method was used to determine corresponding Japanese terms. In
the end, I adopted a total of 32 terms including "zeisei (taxation
system)," "seifu saimu (government debt)," "kisei (regulations),""hoan (legislative bill)," and "Nihon Ginko (Bank of Japan)."Data of newspaper coverage, collected this way, were appliedwith seasonal adjustment and other treatments, before calculating
an index with the average for January 1987–December 2015
set at 100. Indices were also prepared for individual policies, inaddition to the index for all policies. More specifically, indiceswere compiled for fiscal policy, monetary policy, foreignexchange policy, and trade policy. Of all of the articles collectedin compiling the index for all policies, those containing each of
the individual policies were selected to calculate the respective
indices. Index data are compiled monthly, starting from January
1987.

Research Activities

PDP No. 17-P-019

Index characteristics- Tell us more about the characteristics of the pre-2000 index.

The figure on next page shows the transition of the News-based
Economic Policy Uncertainty Index for Japan. The higher theindex is, the greater is the level of uncertainty. Until the mid 1990s,
the index hovered around just below 100 in general. However,there were times when the index showed a sharp spike, e.g., in
October 1987. This was when Japan's political landscape became

RIETI Highlight 2018 Special Edition39

- Can you explain details about post-2000 periods when the indexrose?

As you can see in the figure, the index has spiked frequently
since 2000, e.g., in 2001. Then, the resignation of Prime Minister
Yoshiro Mori triggered infighting within the ruling party, driving
up political uncertainties. With no further room to lower thepolicy rate, there were discussions about the Bank of Japan (BoJ)
introducing new monetary easing measures. Fast forward to
2008, the index reached the highest level over the last 30 years.
Discussions were made on what policy approach the government
should take, especially in terms of fiscal policy, to address
economic recession triggered by the world financial crisis. In
the current decade, the index spiked at major events such as theEuropean sovereign crisis, the U.S. increase of federal debt ceiling,
the BoJ's decision to adopt a negative interest rate policy, and there-postponement of consumption tax increase. Most recently, theindex rose sharply at the time of the U.S. presidential election in
November 2016.

Yoshiyuki Arata Fellow, RIETIInterviewer

Research Activities

destabilized over the choice of successor to Prime Minister
Yasuhiro Nakasone. Meanwhile, overseas, U.S. President Ronald
Reagan was in fierce confrontation with the U.S. Congress over
the reduction of fiscal deficits.
One of the periods when the index reached a very high level
over the last 30 years was the late 1990s. At the time, the Cabinet
led by Prime Minister Ryutaro Hashimoto adopted austere fiscal
management to rebuild fiscal health. However, the 1997 Asiancurrency crisis caused the economy to rapidly deteriorate. In
response, Japan's political opposition and even some forces within
the ruling party began calling for shelving the fiscal reconstruction
initiative and shifting into a more aggressive fiscal policy. The
standoff between those promoting fiscal reconstruction and thoseseeking an aggressive fiscal approach heightened uncertainty overfiscal policy.
The index rose again in 1998. In July, the Liberal Democratic
Party (LDP) lost its majority in the Upper House election,
allowing the opposition camp to claim majority in the chamber.
The sense of concerns rose over the possible difficulty in policy
implementation under this so-called "Twisted Diet." The LDP
then forged a coalition with the Liberal Party, etc. to regain Upper
House majority, resolving the "twisted" state of the Diet. This
caused the index to drop sharply.

- The Shinzo Abe administration's decision to re-postpone theconsumption tax rate increase has significantly heightened
uncertainty. How does the consumption tax rate increase relate touncertainty?

First, it is a good idea to examine how the fiscal policy's
uncertainty index reacted when it was decided to postpone theincrease in consumption tax rate. At the time of first postponement,i.e., in November 2014, the index rose by about 20 points. At thetime of the second postponement, i.e., in May 2016, the index
rose by about 80 points. This indicates that the postponementof consumption tax rate increase does not necessarily heighten
uncertainty. Why was it that the second postponement raised
uncertainty to that extent? I believe it was attributable to the prime
minister's failure to present convincing and specific preparation forclearing the fiscal consolidation goals to which he had committed.
In a news conference announcing the re-postponement, the prime

News-based Economic Policy Uncertainty Index for Japan
250

3

10

4

13

16

Index, 1987–2015=100

12
200

6
5
150

11
7

8

14

15

9

17
18

2
1
100

50

1985

40

1990

RIETI Highlight 2017 Special Edition

1995

2000

2005

2010

2015

2020

Research Digest

Uncertainty of monetary and trade policies- Tell us about the uncertainty of monetary and trade policies, andhow the recent TPP development and U.S. presidential election
relates to uncertainty.

Let me talk about the monetary policy's uncertainty index first, andthen about trade policy's uncertainty index. The monetary policy
uncertainty index has three characteristics. First, the index rises
just before and after any changes to the framework of monetary
policy, e.g., in early 2001. At the time, with little room left forlowering the policy rate, there were debates on the introductionof new monetary easing measures. In March, the BoJ adopted thequantitative easing policy, in which the outstanding balance of
current accounts held by Japanese banks at the BoJ was used as
the main target for monetary operations in the financial market.
The index also spiked at the start of 2016, when the BoJ adopted
the negative interest rate policy. The index's second characteristic
is its sharp increase when the Japanese yen's exchange rate reaches
around 80 to the U.S. dollar. It rose in 1995 amidst debate on theofficial discount rate cut, and in 2010–2011 during the debate on
expanding the qualitative easing policy. The third characteristic of
the index was seen in early 2008, when it rose due to fear that theposition of BoJ governor could become vacant. This was because
the Twisted Diet made it difficult for the ruling party to pass BoJ
governor nominations the government had submitted.
As for the trade policy's uncertainty index, it showedsignificant increases twice in the past. The first surge came in the
period from the late 1980s to the early 1990s. This includes 1988,① October 1987: Black Monday; Prime Minister Yasuhiro Nakasone picking Noboru
Takeshita as the next LDP President; Conflict between U.S. President Ronald Reagan
and U.S. Congress over the reduction of U.S. fiscal deficits; Coordinated dollar-buying
market intervention by the central banks of Japan, United States, and Europe② March 1995: The Tokyo Metropolitan Assembly rejecting a proposed supplementarybudget containing expenditures for bailing out collapsed credit unions suffering from
non-performing loans; Coordinated dollar-buying market intervention by the central
banks of Japan, United States, and Europe; Debate on lowering the official discount rate
③ November–December 1997: Asian currency crisis; A series of collapses of banks andsecurities brokerages; Debate on a shift away from the fiscal reconstruction policy④ July–August 1998: The defeat of the ruling LDP in the Upper House election creating theTwisted Diet; Russian crisis⑤ June 2000: The ruling coalition's loss of Lower House seats in general elections,causing concerns about the government's policy executing ability⑥ February–March 2001: Fierce confrontation within the ruling party concerning theresignation of Prime Minister Yoshiro Mori; Debate on the introduction of quantitativeeasing policy as the policy rate approaching zero; Introduction of the said policy⑦ July 2001: Upper House election; Debate over Prime Minister Junichiro Koizumi's
structural reforms

when the U.S. Congress deliberated on the bill for the Omnibus
Foreign Trade and Competitiveness Act, and 1993, when final
trade negotiations for an agreement were held in the General
Agreement on Tariffs and Trade (GATT)'s Uruguay Round.
The other increase came in the period from 2011 to present. The
index's fluctuations are closely associated with developments
surrounding the TPP Agreement. For example, the index spiked
in November 2011, when the ruling Democratic Party of Japanwas suffering from severe infighting over whether Japan should
participate in TPP negotiations. The index also rose from 2014 into
2015, when the level of concerns built up over the final agreement
on TPP negotiations and its parliamentary ratification procedure.
The index reached its highest level over the last 30 years inNovember 2016 at the time of the U.S. presidential election, and in
January 2017 at the inauguration of the new U.S. President Donald
Trump. This was because of the significant uncertainty created by
the U.S. decision to leave the TPP Agreement.

Further development and future tasks- How do you plan to further expand this study, which includes thispaper as well as your previous papers?

The index I prepared this time has several issues, including theselection of terms in the "Policy" category. It is necessary to more
carefully examine terms that appear frequently in articles that refer
to policy uncertainty, as the U.S. index does. This paper could notaccomplish it.
This study compiled a new index based on newspaper coveragein order to answer three basic questions about Japan's policy
uncertainty. I hope this index will have proved to be useful for
conducting economic research at both the government and private
levels, and be utilized in academic studies for accumulatingknowledge about policy uncertainty.

Research Activities

minister indicated that the increase in tax revenues, resulting from
economic growth, would be partially used to meet the rising fiscal
demand. However, he fell short of clearly stating how he planned
to secure the tax rate increase in 2019, and generate fiscal surplus
until then.

⑧ October 2002: Fierce confrontation in the government and ruling party over the measure
to accelerate the handling of non-performing loans and the pump-priming measure
involving significant fiscal outlay; Debate on additional monetary easing; Expansion ofquantitative easing⑨ March 2008: A series of Upper House rejections on BoJ governor nominations⑩ September–October 2008: Collapse of Lehman Brothers; BoJ cutting of the policy rate;
Debate on economy-stimulus measures⑪ February 2009: U.S. Congress deliberations on the stimulus package containing the"Buy American" provisions⑫ May–June 2010: Greek debt crisis; Resignation of Prime Minister Yukio Hatoyama⑬ August 2011: U.S. government credit rating downgrade; Concerns over European debt
crisis; Resignation of Prime Minister Naoto Kan; Enhancement of monetary easing
amidst sharp appreciation of the yen; Yen-selling market intervention by the BoJ⑭ June 2012: Concerns over debt crisis in Greece and Spain; Tri-party agreement on theamendment of integrated reform bill concerning social security and taxes⑮ January–February 2016: Introduction of the negative interest rate policy⑯ May–June 2016: Re-postponement of consumption tax increase, UK referendum on its
departure from the EU⑰ November 2016: U.S. presidential election⑱ January 2017: Inauguration of Donald Trump as the new U.S. president

RIETI Highlight 2018 Special Edition

41

Research
DigestIn Research Digest, we interview authors of Discussion Papers (DP) to provide a simple introduction to theirunderstanding of problems addressed in their papers, along with the major points and policy implications.

The Dynamics ofInter-firm Networks
and Firm Growth
Yukiko Saito Senior Fellow, RIETI

Research Activities

Yukiko Umeno Saito has been a senior fellow at RIETI since 2014, and was a fellow from 2012–2014.
Prior to that, she was a researcher at the Fujitsu Research Institute, Japan from 2002 to 2012. She
received a Ph.D. in Physics from the University of Tokyo in 2002. She was a research fellow of
the Japan Society for the Promotion of Science from 1999 to 2002. Her research field is industrialorganization and spatial economics. She is interested in how firms construct inter-firm relationships andhow it affects a firm's performance.
Her works include: "Production Networks, Geography and Firm Performance," (with A.B. Bernard
and A. Moxnes), Journal of Political Economy, forthcoming (NBER Working Paper, No.21082(2015.4)); "Geographical Spread of Interfirm Transaction Networks and the Great East Japan
Earthquake," in The Economics of Interfirm Networks, Springer Publishing, 2015.

RIETI Senior Fellow Yukiko Saito has analyzed how inter-firm relationships (networks) evolve according to a firm lifecycle,
and how such networks affect firm growth. The analysis has presented a new perspective based on inter-firm networks,
as opposed to recent empirical studies' finding that firm age has a strong association with the size of subsequent growth.
Saito's analysis has found that a younger firm tends to build, revise and discontinue transaction relationships more frequently
than older firms do, that such inter-firm relationship stabilizes as their transaction relationships continue for an extended
period of time, and that a firm age affects the association between networks and growth, with younger firms achieving growthmore readily by building new transaction relationships. The findings suggest that the approach of policy support for inter-firm
networks varies depending on firms' lifecycle stages.

Research motivation- What motivated you to take on this research?

At RIETI, I am currently researching the dynamics of interorganizational networks, examining how inter-firm relationships
affect firm performance. As part of this research, I have conducted
this analysis, incorporating firm age as a new factor.
I began considering firm lifecycle in the research I was
involved in about 10 years ago. At the time, I was studying thehistorical effect of firm growth (effect of the past history of firm
growth on the firm's subsequent growth), firm metabolism, andthe effect of firm networks on firms exit. Then, Queen Mary
University of London Assistant Professor Tatsuro Senga took
an interest in these studies. About 10 years ago, the correlation
between networks and firm growth history was predicted but
not studied in depth. Compared to then, data concerning firm
networks have been accumulated, allowing the examinationof firm lifecycles in an approach incorporating the perspective

42

RIETI Highlight 2017 Special Editionof firm age. I decided to undertake this collaboration study to
re-examine the association between networks and firm growth,
adding the factor of firm age. Research collaboration is currently
ongoing. My research partners, the abovementioned Dr. Senga
and University of California, Los Angeles Lecturer Daisuke Fujii,
are both theoretical research specialists. Combining theoreticalresearch allows for even greater understanding. They are also
specially appointed RIETI fellows, and I exchange ideas withthem frequently.
Another motivation is the fact that I have gained access toTokyo Shoko Research's (TSR) 10-year panel data because of myinvolvement in a project by the Small and Medium Enterprise
Agency. TSR is a credit research company that collects detailed
data from a very large number of firms. RIETI only holds
intermittent TSR data for 2006, 2011, 2012, and 2014, making it
unsuitable for panel analysis. However, TSR provided transaction
data from 2007 to 2016 for the project of the Small and Medium
Enterprise Agency, giving me an opportunity to take on thisresearch. These data form the basis of the dataset, compiled in thisresearch.
- Why did you focus on inter-firm networks and network dynamics?

Our RIETI research project has confirmed that inter-firmtransaction networks drive firm growth from the perspective of
causality. At the same time, as the government policy highlights
the use of the "power of connections," it is considered important toprovide policy support that encourages firm growth, using interfirm networks. Presenting a more detailed mechanism is importantin order to explore evidence-based policies. Firms grow throughefforts to connect with better transaction partners and build
better relationships with existing transaction partners. I believe
examining the perspectives of network dynamics and firm growth
will help promote greater understanding.
Inter-firm networks are an important factor not only to examine
the microeconomic mechanism of firm growth, but also to
consider macroeconomic implications. More recently, Acemoglu
et al. found that macroeconomic fluctuations are caused throughinter-firm networks. We also analyzed ripple effects following
the Great East Japan Earthquake to verify them empirically.
Right now, my research is based on understanding that inter-firm
networks play an important role not only for macroeconomic
fluctuations but also for macroeconomic growth. Existing research
on Japan's "lost two decades," when the national economy
stagnated, highlights the absence of correct firm metabolism,in which low-productivity firms should exit the market. Suchstudies did not consider the effect of mutual interactions between
firms, and instead examined individual firms as completely
separate operations. However, as confirmed in research on shockpropagation, macroeconomic fluctuations do not represent the sumof microeconomic fluctuations. Furthermore, with confirmationthat inter-firm networks promote firm growth, I have come to theconclusion that macroeconomic growth should be examined fromthe networks perspective, rather than by merely adding up thegrowth of standalone firms.
This study first examined how inter-firm networks evolve
along with firm lifecycle to identify network dynamics, and how
networks would affect growth in relation to factors including firmage.

Network evolutions along with firm lifecycle and its
relationship with firm growth- What kind of research have you conducted about how an inter-firm
network evolves?

With regard to the dynamics of inter-firm networks, I have focusedon network stability. The perspective of how firms choose theirpartners in developing such networks is important, but is also
very difficult as it makes it necessary to examine the mechanism

The Dynamics of Inter-firm Networks and Firm Growth
Daisuke Fujii (Fellow, RIETI) / Yukiko Saito (Senior Fellow, RIETI) / Tatsuro Senga (Fellow, RIETI)

www.rieti.go.jp/jp/publications/dp/17e110.pdf

of inter-firm matching. This is why I decided first to examine
the relationship between firm age and network stability. Morespecifically, I studied how a network becomes stable as a firm
becomes older. To verify this, I used data to see how a firm forms,
updates, and discontinues connections (link) with suppliers andcustomers.
The analysis found that younger firms change such links
frequently compared to older firms. More precisely, compared toolder firms, younger firms tend to establish more ties with a newtransaction partners, and discontinue transactions more frequently.
Transaction stability that firms attain as they age could indicatethat such ties accumulated between firms turn into somethingsimilar to assets for firms involved. At the same time, ceasing tobuild connections with new partners means the firms could be
missing out on growth opportunities. From these perspectives, it isnecessary to examine how inter-firm networks are built and theireffect on firm growth.
As for transaction continuity, it is possible to carry out
detailed analysis on how it changes according to the nature of
suppliers and customers. More specifically, the ratio of transaction
relationships (link) continuing into next year (survival rate) was
put to regression analysis based on the characteristics of suppliersand customers. The analysis found that, as shown in Table 1,
the probability of transaction relationship continuation has apositive correlation with age of suppliers as well as customers.
Interestingly, the sales of suppliers and customers have a
different correlation with transaction continuity. The greater
the sales size of suppliers is, the higher the probability is fortransaction continuation. On the other hand, the greater the sales
size of customers is, the lower the probability is for transaction
continuation. Customers with a larger size of sales are suspected
to be rebuilding transaction relationships with new partners, rather
than maintaining transactions with existing partners. Indications
are that, as a firm grows in its size, it gains a greater benefit in

Research Activities

DP No. 17-E-110

Table 1:
Stability of Inter-firm Linkages

Continuation of business partnerships
Age of clients+

Not significant

Age of suppliers++

Net sales of clients––

Net sales of suppliers++

Distance to transaction partners––

Continuation for 2 years+

Continuation for 4 years+

Continuation for 6 years+

Number of samples

3,211,750

3,211,750

1% significance level

RIETI Highlight 2018 Special Edition43

important for younger firms, and that they require policy support
in this area. Note that this analysis examined only correlation, andhas not discussed in-depth causality. Further analysis is required
to compile more solid and specific policy suggestions. In addition
to causality, the analysis must adopt additional perspectives,e.g., whether effect of relationship development differs between
suppliers and customers, and what kind of transaction partners
firms should seek to connect with.
Interviewer

Kenta Ikeuchi Fellow, RIETI- What are the new perspectives adopted in this study?

finding better suppliers, and could therefore start spending more insearching for better suppliers.
Table 1 also shows that the more that transaction relationships
continue, the more they stabilize.
- Next, can you explain about your analysis on the relationshipbetween inter-firm networks and firm growth?

Research Activities

In order to examine the relationship between inter-firm networks
and firm growth through firm lifecycle, firm samples were divided
into five groups based on firm age, i.e. 0–4 years old, 5–9 years
old, 10–19 years old, 20–39 years old, and 40+ years old. I studied
how the relationship between inter-firm networks and firm growthvaries between these groups, and identified differences in thisrelationship according to firm age (Table 2). The groups of higher
firm age showed a smaller relationship between firm age andgrowth. The groups of lower firm age showed greater age-based
differences. Such natural results were controlled before observing
the relationship between inter-firm networks and firm growth.
As a result, age-based differences were greater for changes intransaction partners (network dynamics) than for the numberof transaction partners (network size). My observation was thatfor younger firms, those that aggressively build new transaction
partners have a greater rate of sales growth, and that a stabletransaction relationship becomes more important for older firms.
These findings suggest that seeking new transaction partners is

We presented new perspectives to existing studies on firm
growth. With regard to decisive factors for firm growth, Gibrat
examined how firm growth depends on a firm's size. There are
numerous papers that examined the relationship between firm
growth and firm size. Despites those, Haltiwanger et al. referred
to firm age in their analysis. Haltiwanger et al. highlighted theimportance of firm age, and pointed to the need to direct attention
to the effect of firm age, rather than firm size, on firm growth.
The study added that a government policy, aimed at creating
employment, should provide assistance to younger firms insteadof small- and medium-sized enterprises (SMEs). However, theirstudy fell short of explaining the mechanism on why firm age
is so important for firm growth. Our study is unique in that it
incorporates the perspective of network dynamics in examining
the relationship between firm growth and firm age, in order to
uncover the underlying mechanism. Another uniqueness is foundin the presentation of a firm age perspective in examining network
dynamics.

Policy implications- What policy implications have you obtained?

The Small and Medium Enterprise Agency project aims to identify
long-term changes that will have occurred to SMEs by 2030. This

Table 2:
Inter-firm Transaction Relationships and Firm GrowthFirm age

Rate of net sales growth
All ages

0–4

5–9

10–19

20–39

40–

Firm age

–

–

–

–

–

–

Number of employees+

Not significant

+

+

+

+

Number of transaction partners+

Not significant

+

+

+

+

Ratio of transaction continuation+

Not significant

Not significant

+

+

+

Ratio of new transaction partnerships

+

+

+

+

+

+

682,391

19,35846,468115,032

288,006

213,527

Number of samples
1% significance level
Coefficient ratio relative to all-age figure

44

RIETI Highlight 2017 Special Edition

2–

1.5–2

1–1.5

–1

study examined changes that have occurred to them over the last
10 years, and found rapid progression of aging among firms. As
shown in the figure, the firm population pyramid, showing the
distribution of firms according to their age, has a peak similar to
the Baby Boomer peak in the normal population pyramid, shifting
toward the high age category in the next 10 years. This study
has confirmed that the relationship between inter-firm networks
and firm growth varies according to firm age. That means that,when firm aging progresses, policy intervention must be adjusted
accordingly. It is naturally important to implement policies thatencourage firm metabolism to halt firm aging, but it is even more
important to accept the current trend of firm aging and adopt
policies that encourage firm growth in the given context.
When research advances in the future to identify what kindof partnership building will lead to firm growth, we might beable to say that firms should adopt a different type of partnershipbuilding according to their age. Then, the Small and Medium
Enterprise Agency, for example, could launch a website as part ofits policy to offer business matching, referring suitable potential
transaction partners to firms. Yet, there has not been much research
progress in this area due to the difficulty in verifying connections
between individual firms from a business matching perspective.
It is difficult to examine their compatibility as transaction partners
for both sides of business matching. This is a research task for the
future.
Figure: Firm Age Distribution
Number of firms

40,00035,00030,00025,00020,00015,00010,000
5,000
0

0

10

20

30 40
2007

50

60
2016

70

80

90

100

Firm age

Future initiatives- Finally, can you tell us about your future research?

This research was a fact-finding study on how inter-firm networks
develop through the firm lifecycle, and how such networks relate
to firm growth. However, no consideration was given to firms'
market entry and exit in their firm lifecycle. In the future, I would
like to encompass firms entering and exiting business in mystudy. Yet, there is still room for further deepening research on therelationship between firm age and firm growth. In addition to theperspective of what kind of business partnerships firms should beconnected to, as explained earlier, we must examine, in greater
detail, the perspective of building new business partnerships anddeepening closer ties with existing business partners. In fact, thereis data from Belgium that is actually for calculating value-added
taxes, but encompasses transaction volumes of all firms broken
down by business partners. This allows us to identify how firms
deepen their ties with existing business partners. I wish there wassuch data for Japan, but that is unfortunately not the case. While
it may be difficult to identify the depth of individual transactions,data such as sales value, number of customers, purchasevalue, and number of suppliers can be used to estimate theaverage depth of such transactions. I would like to examine theadvantages and disadvantages of finding new business partners
and continuing (deepening) transactions with existing business
partners.
Furthermore, the results of this fact-finding study will be used
to draw up a logical framework to deepen the understanding overindividual facts. With the relationship between firm growth, interfirm networks and firm age are beginning to be clarified, I am
currently working with my joint researchers, Dr. Senga and Dr.
Fujii, who specialize in theoretical research, to build a theoreticalmodel on this matter. In considering networks, I wish to build amodel that allows us to examine network stability, as studied inthis research, as well as desirable business partners to network
with, development of new transaction partnerships and deepeningof relations with existing business partners.
The structure for building the theoretical model is alreadyprepared. Dr. Senga studies firm dynamic model theory andsimulation analysis. Incorporating the network variables,
observed in this study, enables the simulation of firm growth.
This not only enables gauging macroeconomic effects, but also
facilitates policy simulation. Having already worked with Dr.
Senga in the K supercomputer project, I have high expectations
for the collaboration, which will enable various policy
assessments.
Dr. Fujii studies theories that explicitly incorporate networks
within the framework of economic models. Many network
analyses in the economics field only deal with local networks(around individual firms). However, our project on seismic
disaster propagation and Dr. Fujii's research can encompass
far-reaching networks as a whole rather than local networks.
For example, when examining a firm's growth factors, we canconsider the impact of the indirect business partners, such as
business partners of the firm's business partners. I would like to
use facts obtained in our research in a way that is acceptable interms of economic theories, so as to build a theoretical modelthat examines entire networks. By combining empirical researchand theoretical research, I hope to achieve research of high added
value both in terms of academic value and policy applications.

RIETI Highlight 2018 Special Edition

Research Activities

Research Digest

45

Fiscal 2016 to Fiscal 2019
In the Fourth Medium-term Plan, RIETI has been promoting research activities under three new medium- to long-term
perspectives on economic and industrial policies with consideration for related government policies such as the Japan
Revitalization Strategy and the Medium- to Long-Term and Structural Points and the Future Direction of Economic andIndustrial Policies (April 2015, Industrial Structure Council).
Research themes under the Fourth Medium-term Plan invariably set these perspectives as basic principles, and wehave put in place nine programs covering policy research areas consisting of similar individual research topics. Leading
experts in respective fields serve as program directors and supervise multiple projects conducted by fellows under the
program. If necessary, these programs will be changed or added to respond to needs for new research depending on the
progress and the changes in economic situations.

Research Activities

I

Macroeconomy and
Low Birthrate/Aging Population

II

International Trade andInvestment

Ⅸ

III

Policy History and
Policy Assessment

Regional Economies

Lineup of
Research
Programs

Ⅷ

Ⅳ

Law and Economy

Ⅶ

Human Capital

Innovation

Ⅵ

Raising Industrial andFirm Productivity

46

RIETI Highlight 2017 Special Edition

Ⅴ

Industry Frontiers

Three Medium- to Long-term Perspectives on
Economic and Industrial Policies

Making Japan into an innovative nation

Overcoming population decline

Research Activities

Cultivating Japan's strength in the world economy

Research Process
To further improve the quality of research, RIETI ensures that discussions are organized for each research project through brainstorming
workshops and discussion paper (DP)/policy discussion paper (PDP) seminars, in which Japanese and foreign experts and policymakers
participate to deepen the research.

Brainstorming

Discussion Paper andSymposiums,

Workshops

Policy Discussion

Workshops, Seminars,

Launching of a new research project

Paper Seminars

Publication of DPs andDeepening the analysis of individual papers

PDPs, Book Publication
Dissemination of research findings

RIETI Highlight 2018 Special Edition

47

Introduction of the Nine Research Programs
Pr o g r a mI

Macroeconomy and Low Birthrate/Aging Population
Program Director: Keiichiro Kobayashi
Faculty Fellow, RIETI
Professor, Faculty of Economics, Keio University
Research Director, Canon Institute for Global Studies

Maintaining long-term growth has been a challenge for economies around the world, and Japan is facinga rapidly aging population ahead of that of other nations. We will conduct research that contributes topolicies to maintain Japan's economic vitality as well as to the development of the global economy.
Specifically, we will consider system infrastructure, such as the role of Asian currency baskets, andanalyze trends in international finance and the global economy, and long-term deflation mechanisms,
etc. Furthermore, we will conduct multifaceted and integrated research on the analysis of comprehensive
panel data on the elderly, direction of the comprehensive reform of the social security and taxation
systems, policy proposals for economic recovery, fiscal consolidation, etc.

Research Activities

Pr o g r a m

IIInternational Trade and Investment
Program Director: Eiichi Tomiura
Faculty Fellow, RIETI
Professor, Faculty of Economics, Hitotsubashi University

When considering Japan's economic policies in the midst of globalization, an understanding of international
trade and foreign direct investment is even more important now than in the past. This program, focusing
on the globalization of firm activities (i.e., exports and overseas production), will study the international
trading networks of firms from theoretical and empirical perspectives, while also studying trade policies
and international trade and investment rules from empirical and legal perspectives.

Pr o g r a m III Regional Economies
Program Director: Nobuaki Hamaguchi
Faculty Fellow, RIETI
Professor, Research Institute for Economics and Business Administration (RIEB), Kobe University

This program will study the effect of international trade, movement of capital and labor, and changes intechnology on urban and rural areas and industries, while viewing the regions of Japan in the context ofthe global economy and using this to develop proposals, etc. on such important policy issues as the aging
population and regional revitalization. Specifically, we will consider policies to promote the features ofexport industries in regional areas and regional economic circulation, strengthen functions of regional
financial institutions, create social institutions that utilize cutting-edge information technology andtransport infrastructure, and utilize and strengthen international production networks (value chains), as
well as create statistical indicators that conform with the structure of economic spaces, form policymaking
frameworks, etc.

48

RIETI Highlight 2017 Special Edition

Fiscal 2016 to Fiscal 2019

Active Projects
Fiscal and Social Security Policy under a Low Birth Rateand Aging Demographics
Project Leader: Sagiri Kitao (Faculty Fellow)

Economic Analysis of the Development of the Nursing
Care Industry in China and Japan
Project Leader: Ting Yin (Fellow)

Monetary and Fiscal Policy in the Low Growth Era
Project Leader: Ippei Fujiwara (Faculty Fellow)

Exploring Inhibition of Medical Expenditure Expansion
and Health-oriented Business Management Based on
Evidence-based Medicine
Project Leader: Kazumitsu Nawata (Faculty Fellow)

Exchange Rates and International Currency
Project Leader: Eiji Ogawa (Faculty Fellow)

Active Projects
Studies on Firm Management and Internationalization
under the Growing Fluidity of the Japanese Economy
Project Leader: Hongyong Zhang (Fellow)

A Study of the Effects of Trade Policy: A microdata
analysis of Japan from the 1990s to 2010s
Project Leader: Shujiro Urata (Faculty Fellow)

Empirical Analysis of Corporate Global Activities in the
Digital Economy
Project Leader: Eiichi Tomiura (Faculty Fellow)

Analyses of Offshoring
Project Leader: Jota Ishikawa (Faculty Fellow)

Research on Global Inter-firm Networks and Related
Policies
Project Leader: Yasuyuki Todo (Faculty Fellow)

Research Activities

Microeconomics, Macroeconomics, and Political
Philosophy toward Economic Growth
Project Leader: Keiichiro Kobayashi (Faculty Fellow)

Comprehensive Research on the Current International
Trade/Investment System (pt. IV)
Project Leader: Tsuyoshi Kawase (Faculty Fellow)

Active Projects
Dynamics of Inter-organizational Network andGeography
Project Leader: Yukiko Saito (Senior Fellow)

Spatial Economic Analysis on Intracity Economic
Activities and Interregional Economic Activities
Project Leader: Takatoshi Tabuchi (Faculty Fellow)

An Empirical Framework for Studying Spatial Patterns
and Causal Relationships of Economic Agglomeration
Project Leader: Tomoya Mori (Faculty Fellow)

Innovation Enhancing Regional Economic Structure andEvolution of Cities
Project Leader: Ryohei Nakamura (Faculty Fellow)

Economic Analysis of Property and Reform Proposal
Project Leader: Motohiro Sato (Faculty Fellow)

Stable Development of Regional Economies under a
Declining Population
Project Leader: Nobuaki Hamaguchi (Faculty Fellow)

An Empirical Study on Compact City: Evaluating placebased policies in Japan
Project Leader: Keisuke Kondo (Fellow)

The Role of Regional Financial Institutions as the Coreof the Local Economy and Regional Cooperation
Project Leader: Nobuyoshi Yamori (Faculty Fellow)
RIETI Highlight 2018 Special Edition49

Pr o g r a m Ⅳ Innovation
Program Director: Sadao Nagaoka
Faculty Fellow, RIETI
Professor, Tokyo Keizai University

The creation of new knowledge and its exploitation to resolve problems which we face is the main
source of innovation. This program will develop original data to understand the innovation processes,
and will conduct research from an international perspective, so as to contribute to evidence-based policy
formation. Specifically, the program will analyze the innovation capabilities of industries, the economic
impact of artificial intelligence, intellectual property systems, open innovation, knowledge transfer and themobility of human resources across organizations, university-industry cooperation, technical standards,
and business and industrial organizations that promote innovation.

Pr o g r a m Ⅴ Industry Frontiers
Research Activities

Program Director: Hiroshi Ohashi
Faculty Fellow, RIETI
Professor, Faculty of Economics, The University of Tokyo

Through innovation in the key technological areas of sophistication of data processing and evolutionof telecommunication networks, signs of changes in the industrial structure have begun to be seen in
Japan as well as in other leading nations. Via the Internet of Things (IoT) using sensor technology, large
quantities of unstructured data have now become accessible, and artificial intelligence (AI) technology
is being gradually put into practical use. In Japan, new industrial frontiers are opening. As such, thisprogram will venture on research as to how policies should be instituted to overcome the challenges
facing the Japanese economy, taking cross-industry policies into perspective, in addition to conventional
policies intended for individual industries.

Pr o g r a m Ⅵ Raising Industrial and Firm Productivity
Program Director: Kyoji Fukao
Faculty Fellow, RIETI
Professor, Institute of Economic Research, Hitotsubashi University

The aim of this program is to measure industry- and firm-level productivity and its determinants for Japanand other East Asian countries and to conduct research on policies aimed at raising productivity. At theindustry level, in addition to updating and expanding the Japan Industrial Productivity (JIP) and China
Industrial Productivity (CIP) databases in collaboration with Hitotsubashi University, we will construct anindustrial productivity database by prefecture for Japan and examine the total factor productivity (TFP)
disparity between regions and the factors behind it, etc. At the firm or establishment level, employing
micro-data from government statistics and corporate financial data in Japan and abroad, we will
research the following: determinants of productivity gaps among firms; the impact of globalization andchanges in demand affect corporate performance; policies for raising productivity in the service sector;
productivity gaps between firms in Japan, China, and Korea; and international comparison of productivity
dynamics. We will also measure investment in intangible assets such as research and development,
software, in-house training, and organizational structure, all of which are important sources of innovationand productivity growth at both industry and firm levels, and examine the economic effects of suchinvestments.

50

RIETI Highlight 2017 Special Edition

Fiscal 2016 to Fiscal 2019

Active Projects
Productivity Revolution through IoT
Project Leader: Koichi Iwamoto (Senior Fellow)

Frontiers of Innovation Policy: Evidence from micro data
Project Leader: Sadao Nagaoka (Faculty Fellow)

Empirical Study on the Management and Utilization of
Data Generated from Industry
Project Leader: Toshiya Watanabe (Faculty Fellow)

Creation and Development of High-tech Startups
Project Leader: Yuji Honjo (Faculty Fellow)

Empirical Analysis of Innovation Ecosystems in
Advancement of the Internet of Things (IoT)
Project Leader: Kazuyuki Motohashi (Faculty Fellow)

Large-scale Simulation and Analysis of Economic
Network for Macro Prudential Policy
Project Leader: Hideaki Aoyama (Faculty Fellow)

Development of New Indicators for Service Sector
Analysis and EBPM
Project Leader: Yoko Konishi (Senior Fellow)

Economic and Financial Analysis of Commodity Markets
Project Leader: Kazuhiko Ohashi (Faculty Fellow)

Globalization, Innovation, and Competition Policy
Project Leader: Noboru Kawahama (Faculty Fellow)

Heterogeneity across Agents and Economic Growth
Project Leader: Hiroshi Yoshikawa (Faculty Fellow)

Policy Analyses on Industrial Organization
Project Leader: Hiroshi Ohashi (Faculty Fellow)

Study Group on Corporate Finance and Firm Dynamics
Project Leader: Iichiro Uesugi (Faculty Fellow)

Productivity Gaps and Industrial CompetitivenessProject Leader: Koji Nomura (Faculty Fellow)

Research Activities

Active Projects

Active Projects
East Asian Industrial Productivity
Project Leader: Kyoji Fukao (Faculty Fellow)
Microeconometric Analysis of Firm and Industry Growth
Project Leader: Kaoru Hosono (Faculty Fellow)
Analysis of the Regional-Level Industrial Productivity
and Regional Production Networks
Project Leader: Joji Tokui (Faculty Fellow)

Research on the Improvement in Resource Allocation
and Productivity among the Healthcare and Education
Service Industries
Project Leader: Tomohiko Inui (Faculty Fellow)
Research on Productivity-improving Capital Investment
Project Leader: Tsutomu Miyagawa (Faculty Fellow)

RIETI Highlight 2018 Special Edition51

Pr o g r a m Ⅶ Human Capital
Program Director: Kotaro Tsuru
Faculty Fellow, RIETI
Professor, Graduate School of Business & Commerce, Keio University

For Japan, a nation with scarce resources, to maintain and strengthen economic vitality and innovationand increase its growth potential by using its advantages amid a declining population resulting from arapidly aging society and intensifying global competition among other factors, a significant key is how
to utilize its human resources. We will conduct multifaceted, comprehensive research on ideal labormarket systems to increase worker incentive and capability; reconstruction of employment institutions
and systems from a full life-cycle perspective from early childhood education through higher education;
human resources development in employment years; and utilization of elderly as human resources as well
as from the perspective of promoting diversity including increased women's participation.

Research Activities

Pr o g r a m Ⅷ Law and Economy
Acting Program Director: Makoto Yano
President and Chief Research Officer, RIETI
Professor, Institute of Economic Research, Kyoto University

Technological innovation is expected to accelerate in many fields such as financial services, information/communications, and life sciences. In such an environment, what can a nation do to build an economy
that leads the world in innovation? Many cases have been observed that important innovation is born ina market in which free entry and free enterprise are guaranteed. In order to foster such a market, various
rules and institutional arrangements need to be built into the economy. From this viewpoint, in the present
program, the design of new types of economic and industrial policies is investigated.

Pr o g r a m Ⅸ Policy History and Policy Assessment
Program Director: Haruhito Takeda
Faculty Fellow, RIETI
Professor Emeritus, The University of Tokyo

This program aims to review and assess policy shifts, chiefly during the period 1980–2000, as we lookat the roles played by Japan's economy and society as well as its trade and economic industrial policies
at the end of the 20th century. While the final two decades of the 20th century were a time of significant
changes in Japan's economy and society, they also represent an important point of comparison when
considering the development of policy after the creation of the Ministry of Economy, Trade and Industry
from a historical perspective. We will attempt to clarify how changes in trade and industrial policy at theturn of the century were affected, based on the recognition of policy issues over the preceding quartercentury, choice of policy responses, and evaluation on their results.

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RIETI Highlight 2017 Special Edition

Fiscal 2016 to Fiscal 2019

Active Projects
Reform of Labor Market Institutions
Project Leader: Kotaro Tsuru (Faculty Fellow)
Change in the Utilization of and Investment in Human
Resources
Project Leader: Yoshio Higuchi (Faculty Fellow)

Employment System Reform to Use Human Resources
More Efficiently
Project Leader: Hideo Owan (Faculty Fellow)
Fundamental Research for Economic Growth andProductivity Improvement in Japan
Project Leader: Kazuo Nishimura (Faculty Fellow)

Research Activities

Research on Working Style Reform and HealthManagement
Project Leader: Isamu Yamamoto (Faculty Fellow)

Active Projects
Intellectual Property and Standardization—Strategy and
PolicyProject Leader: Masabumi Suzuki (Faculty Fellow)
Frontiers in Corporate Governance Analysis
Project Leader: Hideaki Miyajima (Faculty Fellow)

Active Projects
Historical Evaluation of Industrial Policy (H28FY)
Project Leader: Tetsuji Okazaki (Faculty Fellow)
Historical Study on Industrial Policy
Project Leader: Haruhito Takeda (Faculty Fellow)
Promoting Evidence-based Policy in Japan
Project Leader: Kazuo Yamaguchi (Visiting Fellow)

RIETI Highlight 2018 Special Edition

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Research Institute of Economy,Trade & Industry,IAA
https://www.rieti.go.jp/en/@en.RIETI@RIETIenglish