Inclusive wealth footprint for cities in Japan: regional clusters for sustainable development

Abstract

Cities play a crucial role in regional sustainable development through trade linkages with surrounding economies. This study extends the inclusive wealth (IW) conceptual framework for footprint analysis, offering a comprehensive production–consumption perspective to measure regional sustainability. We empirically analyse the IW footprint for 1880 municipal-level economies in Japan by using their territorial IW accounting. We measure sustainability in the hierarchical value chains across cities and prefectures. Our findings suggest the unsustainability of production and consumption across cities in Japan, as the biased wealth clustering in cross-prefecture value chains led to wealth inequality. Additionally, we observe the distorted natural and human capital utilization characterized as the general depreciation of natural capital and shortage of human capital, which arise by the value chain participation. Our results underscore the importance of capital management and regulation in value chains. Sustainable development policy interventions must focus on optimizing inclusive capital asset management to maintain a non-declining level of wealth. This research unveils the intricate relationship between cities and their surroundings, providing valuable insights for policymakers aiming to enhance regional sustainability.

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Sustainability Science
https://doi.org/10.1007/s11625-023-01367-4
ORIGINAL ARTICLE
Inclusive wealth footprint forcities inJapan: regional clusters
forsustainable development
ShuningChen1· KenichiKurita1· TakakoWakiyama2· ShigemiKagawa3· ShunsukeManagi1
Received: 18 October 2022 / Accepted: 28 May 2023
© The Author(s), under exclusive licence to Springer Nature Japan KK, part of Springer Nature 2023
Abstract
Cities play a crucial role in regional sustainable development through trade linkages with surrounding economies. This study
extends the inclusive wealth (IW) conceptual framework for footprint analysis, offering a comprehensive production–con-
sumption perspective to measure regional sustainability. We empirically analyse the IW footprint for 1880 municipal-level
economies in Japan by using their territorial IW accounting. We measure sustainability in the hierarchical value chains across
cities and prefectures. Our findings suggest the unsustainability of production and consumption across cities in Japan, as
the biased wealth clustering in cross-prefecture value chains led to wealth inequality. Additionally, we observe the distorted
natural and human capital utilization characterized as the general depreciation of natural capital and shortage of human
capital, which arise by the value chain participation. Our results underscore the importance of capital management and
regulation in value chains. Sustainable development policy interventions must focus on optimizing inclusive capital asset
management to maintain a non-declining level of wealth. This research unveils the intricate relationship between cities and
their surroundings, providing valuable insights for policymakers aiming to enhance regional sustainability.
Keywords Footprint assessment· Inclusive wealth· Multiregional input–output model· Hieratical value chains· Regional
sustainability
Introduction
Cities have emerged as epicentres of human economic activ-
ity. Driven by urbanization, technological advancements,
and globalization, cities significantly impact regions beyond
their geographical boundaries through production and con-
sumption interconnections. These external spatial impacts
encompass environmental, economic, and social dimensions.
Cities play a crucial role in regional and global sustainability
by shaping spatial externalities. Analysing the externality
effects provides valuable insights into the challenges and
opportunities for sustainable development in urban areas and
their surrounding regions.
Ecological footprint studies the human demand on the
Earth’s ecosystems and natural resources to assess sustain-
ability that does not exceed the planet’s carrying capacity
(Wackernagel and Beyers 2019; Dasgupta etal. 2021). The
recent integration of supply chain and consumption-based
accounting perspectives into the ecological footprint concept
has advanced spatial externality research (Wiedmann etal.
2006; Hertwich and Peters 2009; Lenzen etal. 2012; Hoek-
stra 2015; Nansai etal. 2021; Zhang etal. 2017). However,
ecological footprint analysis measures the impact of human
activities, often expressed in terms of gross domestic prod-
uct (GDP), which may lead to the neglect of sustainable
human well-being concerns. Additionally, the ecological
footprint is difficult to assess for its complementarity and
substitutability with other capital assets due to the lack of a
consistent monetary measure.
Handled by Peter John Marcotullio, Hunter College, United
States.
* Shunsuke Managi
managi@doc.kyushu-u.ac.jp
1 Urban Institute, Kyushu University, 744 Motooka, Nishi-Ku,
Fukuoka819-0395, Japan
2 ISA, School ofPhysics A28, The University ofSydney,
Camperdown, NSW2006, Australia
3 Faculty ofEconomics, Kyushu University, 6-19-1 Hakozaki,
Higashi-Ku, Fukuoka812-8581, Japan

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The inclusive wealth (IW) conceptual framework measures
natural, produced, and human capital assets as the produc-
tive basis for intergenerational well-being, providing a com-
prehensive understanding of sustainability (Dasgupta 2021;
Kurniawan and Managi 2018; Dasgupta etal. 2015). In this
study, we innovatively construct a theoretical framework for
IW footprint analysis. The IW footprint measures the wealth
carry load required to maintain sustainable human well-being.
IW footprints measure natural, produced, and human capital
assets by their footprint shadow price. The wealth footprint
relative to wealth accounts provides the spatial and structural
discussion of regional sustainability.
We take Japan as a case study to explore cities’ external spa-
tial impacts on regional sustainability by IW footprint analysis.
We measure the IW footprint based on 1880 municipal-level
territorial inclusive wealth accounts of Japan. Understanding
the challenges affecting Japan’s sustainability can shed light
on the broader implications of urban development and provide
valuable lessons for other countries.
Technically, our study sets itself apart from previous foot-
print study work through two innovative aspects. First, IW
footprint analysis applies a flexible utility function adjust-
ment framework to explain the gap between accounting and
footprint prices of capital assets. Second, we use high-reso-
lution multiregional input–output (MRIO) data to elucidate
hierarchical supply chain networks. We investigate the spatial
externality of cities by their participation in different levels of
value chain networks. These detailed data can provide a more
comprehensive understanding of the role of cities in regional
sustainable development.
Our goal is to identify potential policy interventions to opti-
mize capital management to enhance the sustainability of cities
and regional economies. We emphasize that the IW footprint
approach can be applied to all economies seeking to address
and identify sustainability issues caused by production and
consumption externalities. By focusing on specific resources,
economic activities, and socioeconomic factors, the IW foot-
print enables policymakers to identify optimal development
pathways.
The remainder of this article is organized as follows: we
begin with a concise overview of previous contributions in
studies concerning urban development and cities’ roles in sus-
tainability. We briefly discuss the environmental sustainabil-
ity aspect of the ecological footprint, a consumption-oriented
approach, and explain the necessity of examining the inclusive
wealth footprint. Subsequently, we introduce the theoretical
framework of the IW footprint and the extension to the IW
footprint analysis for cities in Japan. Following this, we present
and discuss our findings. Ultimately, we derive conclusions
and policy implications based on our results.
Literature review
Urbanization andits impact onsustainability
Cities are aggregations of population and economic
activity, driving innovation, growth, and social mobility
in human society. The formation of a city depends on its
surroundings and influences other regions through trade
interconnections. Fujita etal.’s (2001) work highlights
the role of agglomeration economies in shaping the spa-
tial distribution of economic activity and its externalities.
Besides, researchers have explored the critical role of
spatial externalities in city formation, development, and
maintenance (Jacobs 2016). Cities positively affect their
surroundings, such as knowledge spillovers and economic
agglomeration, and negative effects, such as environmental
pollution and natural resource depletion. These external
influences encompass economic, social, and environmental
aspects (Glaeser 2012).
In recent years, scientists and policymakers have
become increasingly interested in the role of cities in
sustainable development. The concept of sustainability
emphasizes how humans should treat nature and ensure
intergenerational equity in development (Baumgärt-
ner and Quaas 2010; Dasgupta 2001; Brundtland etal.
1987; Costanza and Daly 1992; Arrow etal. 1995; Solow
etal. 1993). Satterthwaite (2008, 2021) underlined the
importance of sustainable and inclusive urban develop-
ment. Research by Romero-Lankao etal. (2016) explored
urban vulnerability and resilience in the context of cli-
mate change and sustainable development. Beatley (2012)
discussed the concept of “green urbanism,” referring to
integrating nature into cities’ sustainability governance.
Newman and Kenworthy (1999) investigated urban sus-
tainability regarding transportation and energy utilization,
while Seto etal. (2012) delved into the direct and indirect
impacts of urban land change on sustainability. These stud-
ies addressed the importance of cities’ sustainability by
considering the relationship between natural resources,
the environment, and cities from social, economic, and
environmental aspects.
Measure thesustainability ofcities using
theecological footprint
Rees etal. (1996), Wackernagel and Rees (1997) and Rees
(2018) introduced the ecological footprint concept, which
measures the sustainability of human activities by con-
sidering the planet’s ecosystem and natural resource-car-
rying capacity. Ecological footprint analysis has evolved
over time and has been applied at various spatial scales.

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Recently, the ecological footprint concept has incorporated
supply chain and consumption accounting perspectives to
improve methodologies and hasexpanded to include all
aspects of natural resources in cross-regional sustainability
discussions (Wiedmann etal. 2006, 2015; Hertwich and
Peters 2009; Lenzen etal. 2012; Hoekstra 2015; Nansai
etal. 2021; Zhang etal. 2017; Lenzen and Murray 2001;
Kitzes etal. 2009).
In the urban context, the ecological footprint helps
quantify the dependence of urban consumption patterns
on resources and ecosystems beyond the city’s geographic
boundaries. Calculating the consumption of goods and ser-
vices and the waste generated by the city provides a com-
prehensive assessment of the city’s environmental impact.
Wiedmann and Lenzen (2018) analysed a country’s global
ecological footprint and the role of cities in resource con-
sumption and sustainability.
However, ecological footprint studies have limitations
when analysing the impact on sustainability. The ecologi-
cal footprint links the burden of human economic activity
(GDP) on the biosphere’s carrying capacity, but GDP is
insufficient to measure sustainable development. Discus-
sions of sustainability in economics also emphasize the
need to maintain a balanced mix of productive, natural,
human, and social capital for sustainable intergenerational
human well-being (Gutés 1996; Figge and Hahn 2005).
Achieving human well-being requires balancing natural
and socioeconomic capital at different stages of human
development, necessitating considering well-being meas-
ures other than GDP.
Furthermore, while the ecological footprint measures
the use of various natural resources, it is limited in its
ability to account for the different types of capital involved
in urban development. The indicators used to measure eco-
logical footprint, such as land and biomass, are not always
uniform and may not effectively consider the efficiency of
natural capital when other types of capital are substituted.
Therefore, converting to a unified monetary unit is neces-
sary to comprehensively analyse the impact of consump-
tion, as demonstrated by our use of the inclusive wealth
footprint methodology.
In conclusion, ecological footprint analysis primarily
focuses on the environmental dimension of sustainability,
overlooking the complex interplay of economic, social,
and environmental factors in and around cities. The eco-
logical footprint emphasizes the irreplaceability of the
natural capital. However, more comprehensive approaches
to managing nature are needed. We need to incorporate
the management of natural capital into the economic sys-
tem and invest in natural capital in consideration of other
capital to achieve optimal sustainable use of resources
(Dasgupta 2021).
Proposed approach: combining inclusive wealth
index andecological footprint
The inclusive wealth (IW) index is a metric that measures
sustainability beyond GDP. The IW conceptual framework
encompasses accounting of natural, human, and produced
capital, measuring sustainability as the capacity to main-
tain well-being across multiple dimensions (Dasgupta
etal. 2015; Managi and Kumar 2018). Cross-country
IW accounting (Managi and Kumar 2018, 2012; UNU-
IHDP and UNEP 2014) has been constructed extensively
for measuring the sustainability of nations (Coulibaly
and Managi 2023; Sugiawan etal. 2023). Recently, this
approach has been applied to the study of sustainability
in multiple aspects at the regional, sub-national, and grid
levels (Managi 2016; Ikeda and Managi 2019; Agarwal
and Saha 2021; Islam and Managi 2022; Zhang etal. 2020;
Jingyu etal. 2020).
To investigate the impact of cities’ spatial externali-
ties on regional sustainability, we propose combining
territorial IW accounts with footprint analysis. The IW
footprintestablishes a linkbetween the impat of human
activities on intergenerational human welfare and the car-
rying capacity of natural, human and produced capital.
This relationship is measured consistentently in monetary
terms. This approach allows for the analysis of spatial
externalities related to cities’ production and consump-
tion. Changes in IW footprints and each capital asset
reflect complementarity and substitution between natural
and other capital. The theoretical formulation of the IW
footprint shows inclusive capital investment to facilitate
the accumulation of multiple capitals, depending on the
production and consumption behaviour. Analysing the dif-
ference between IW footprints and territorial wealth ena-
bles the exploration and optimization of regional capital
management strategies for sustainable development. The
following sections present the methodology and empirical
data for calculating the spatial wealth footprint.
Method anddata
This section outlines the methodology and data employed
in our study. We begin by offering a brief overview of the
inclusive wealth (IW) concept and its existing limitations
for assessing cities’ roles in regional sustainability. We
then introduce the extension of the spatial IW footprint
as an approach for analysing regional sustainability. Sub-
sequently, we describe the municipal-level multiregional
input–output (MRIO) based wealth footprint accounting
approach, which makes practical use of high-resolution

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data from Japan. Lastly, we discuss the data sources and
their limitations.
Inclusive wealth framework andits limitations
IW is based on the stock-and-flow approach. We revisit the
time-continued concept of human welfare by denoting time
as
s
, assuming the horizon is infinite. Let the consumption
flow at time
s
be represented by
C(s)
, the economic-scale
utility flow by
U(C(s)
), and the inclusive capital assets at
initial time
t
used for production by
K(t)
. In this context,
the intergeneration welfare
V(t)
can be expressed as
Arrow etal. (2012) define sustainable development as
follows:
Definition 1. (Arrow etal. 2012) Economic development is
sustained at
t
if
d
V
∕d
t
≥0
.
The sustainability condition for the economy is defined
as intergenerational welfare that does not decrease over
time. Based on Eq.(1) and Definition1, we obtain:
In Eq.(2), let us define the term pi(t)
≡(
𝜕V(t)
𝜕k
i
(t)
)
as the
shadow price of capital asset
i
at time
t
, and consider time
is also one capital and let
r
(t)=
𝜕V
𝜕t
be the shadow price of
time at
t
. We can express IW using the shadow price as
weight:
Non-declining IW over time signifies intergenerational
sustainability. The shadow price reflects the marginal utili-
ties created by a unit of a capital asset, and its weighted
ratio in wealth indicates the extent to which other capital
assets can substitute each capital. However, it is essential
to recognize that substitution is only permissible to a cer-
tain extent. Ultimately, no capital can be entirely substi-
tuted by any other type.
Empirically, the IW account encompasses stocks of nat-
ural, human (intangible), and produced (tangible) capital
calculated by their biophysical quantities and accounting
prices (see AnnexI for accounting details). IW accounts
have been measured at various levels, including national,
sub-national, regional, municipal, and grid levels. How-
ever, two limitations in the current IW account hinder its
assessment of regional sustainability: first, the current IW
account struggles to capture the spatial externalities of
(1)
V
(t)=
∫∞
t
[
U
(
C(s)
)
e𝛿(s−t)
]
ds=V
(
K(t),t
).
(2)
d
V(t)
dt=𝜕V
𝜕t+
∑
i[(
𝜕V(t)
𝜕k
i
(t)
)(d
ki
(
t
)
dt
)]≥0.
(3)
W
(t)=r(t)t+
∑
pi(t)ki(t)
.
economies due to its reliance on territorial accounting;
second, since the significance of finite natural capital is
often ignored in economic systems, market prices cannot
accurately capture the sensitivity of the productive base to
natural capital depletion.
We aim to expand the inclusive wealth framework by
introducing footprint analysis to address these limitations
and examine the impact of cities’ spatial externalities on
regional sustainability. We also provide market evidence
of how consumption impacts natural capital depletion and
wealth structure. By doing so, we explore temporal and
spatial capital management for cities’ spatial externalities
and sustainability.
In the next section, we explain the construction of the
IW footprint for discussing regional sustainability.
Inclusive wealth footprint measures temporospatial
sustainability
According to Wackernagel and Beyers (2019), the eco-
logical footprint measures the consumption of natural
resources at a specific point in time by an individual,
population, or activity, as well as the area of biologically
productive land and water required to absorb the waste
generated. By linking consumption and demand sides,
ecological footprint research reveals that achieving sus-
tainability necessitates managing the biosphere to meet
the stability conditions of the biosphere stock (
s
) so that
it can provide the necessary resources for consumption.
However, multiple pathways could lead the biosphere
from its current state (level s) to the target state (Target
s∗
), depending on the optimal capital management scheme
(Dasgupta 2021).
We introduce the wealth footprint concept for analysing
regional sustainability to broaden the footprint discussion
and encompass optimal capital management. To do so,
we assume an autonomous region with
j=n
economies.
Denote the population size of
j
as
Nj
and per capita human
activity index as
yj
(in this case, we use GDP per capita).
The total output of
j
is denoted as
Njyj=Yj
.
Urbanization leads to substituting biosphere stock
with other forms of capital accumulation. The ecological
footprint of urban consumption surpasses its biosphere
regeneration rate, requiring cities to obtain their biosphere
needs through trade with surrounding areas. Concurrently,
the capital agglomeration effect in cities boosts techno-
logical progress and production efficiency. The home mar-
ket effect enables cities to produce goods and services to
meet the needs of surrounding areas through trade. Let
G=G(Sj)
represent the resource and pollution absorption
supply by biosphere stock
Sj
, and
U=U(kj)
represent the
capital input
kj
for goods and services production. The

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spatial consumption impact of economy
j
at a specific
point in time is given by:
Equation(5) illustrates that economy
j
’s consumption
of all resources, including natural (ecological), produced,
and human capital, is supplied locally and from the rest
of the economies.
N
j
yj
𝛾
j
is the Ehrlich–Holdren equation that
shows the consumption impact, where
𝛾j
stands for the
technology factor, which measures the environmental,
economic, and social impact per unit of affluence. For
each economy
j
, the consumption impact may not equal
its territorial capital stock supply, leading to impact ine-
quality. However, for the region, if the aggregated con-
sumption impact of all economies does not exceed the
resources that all economies can collectively supply, we
can assume the region’s spatial sustainability is upheld,
represented as:
Equation (6) indicates the condition under which
regional spatial sustainability holds at a point in time.
However, intergenerational sustainability requires arbi-
trage among all assets (natural, produced, human) at
every moment, adjusting for the well-being of present
and future generations. Therefore, we discuss temporal
sustainability.
According to formula (5), let
I
(K)=
n
j=
1
n
k=
1[Gk,j

Sk

+Uk,j(kk
)]
represent the
regional wealth footprint, where
K={S,k}
indicates the
inclusive capital assets that generate regional intergenera-
tional welfare. Under the steady state:
Then, the intergenerational welfare can be expressed
as the equation of
K(t)
,
I(K(t))
, and
t
, and the intergen-
erational sustainability can be met as:
where
q
(t)=
𝜕V
𝜕I
indicates the shadow price of the wealth
footprint, and
dI
dt
is the wealth footprint change rate over time.
Equation(8) shows that an economy’s wealth depends on
shared principles and cooperation with the rest of the econo-
mies, affecting
r(t)
,
pk(t)
, and
qn(t)
.
We discussed the adjustment of the wealth footprint in
wealth accounts in the context of regional sustainability.
(5)
I
j=
N
j
y
j
𝛾
j
=
n
∑
k=1
[Gk,j
(
Sk
)
+Uk,j(kk)]
.
(6)
n
∑
j=1
Ij=
n
∑
j=1
N
j
y
j
𝛾j
=
n
∑
j=1
n
∑
k=1
[Gk,j
(
Sk
)
+Uk,j(kk)]
.
(7)
Ny =Y=C=γI(K).
(8)
dV(t)
dt
=r(t)+pk(t)dK
dt
+q(t)dI
dt≥0,
Then we elaborate on the empirical measurement of the
wealth footprint in the next section.
Empirical calculation oftheinclusive wealth
footprint ofJapanese cities
This section explains the methodology for empirically cal-
culating the IW footprint of Japanese cities. If time-varying
factors such as technology, population, and production and
consumption patterns remain constant in Eq.(8), the opti-
mal spatiotemporal regional capital allocation results in a
wealth that satisfies current and future resource demands
under a steady-state condition. These resource demands are
measured by the wealth footprint, leading to the following:
For convenience, we present the shadow price
q
�
=−q
.
According to Eq.(6),
I
indicates the trade impact between
all economies. We empirically utilize the multiregional
input–output (MRIO) model to calculate wealth footprint
based on the territorial IW account (see the AnnexII and
III for the details of the estimation). Leontief’s input–output
model uses a system of linear equations to describe the flow
of goods and services between sectors. Denote
A
as the input
coefficient matrix that indicates the intermediate trade for
producing the final demand
Y(t)
. X(t) is the vector of gross
output,
X= Ax + Y=(1−A)−1Y
, and
B=(1−A)−1
is the
Leontief inverse matrix. By rearranging the Eq.(10) and
substituting Eq.(7), we get:
Here,
𝛿
=
∑
m
b=1
∑
n
j=1
∑
ipik
n
i,
b
Xn
b
is the capital input coefficient
in each economy and industrial sector. Equation(11) esti-
mates the wealth footprint for each economy embodied in
trade interconnection. The estimated footprint coefficients
q
�
γ
show the economic activity per capita impact of capital
assets measured in monetary form.
We used the wealth account from Japanese municipal-
level inclusive wealth accounting data from Managi (2016),
K. U. Urban Institute and Managi and Kuriyama (2016) for
the empirical estimation. This IW account encompassed the
municipal-level value of natural (resources provisioning
such as agriculture land, fish stock, and timber and environ-
mental regulating services), human, and produced capital
assets. The MRIO data are from the 2015 high-resolution
Japanese MRIO database of 1880 municipal departments
and 4266 divisions (Wakiyama etal. 2020).
To estimate the IW footprint, we need to estimate the
capital investment coefficient. Therefore, we construct the
(10)
∑
i
piKi=q
�
I
.
(11)
q
�I=q
�
Ny
γ
=𝛿X=𝛿BY
.

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IW satellite accounting matrix of MRIO to calculate δ.
Although δ satisfies the linear utility function, the weight
of capital input is not necessarily equal to the capital weight
of wealth due to market distortion. To obtain an optimized
input coefficient, we apply the KRAS (conflict-free rank-
ing and scaling) data reconciliation method (Lenzen etal.
2009), which adjusts the capital input using supplementary
data. Third-party data come from multiple resources, such as
satellite data on land use in Japan (E. O. R. Center 2020) and
the prefectural accounting statistics (T. Research Institute
of Economy and Industry 2021), and more (see the Annex
II and TableA2 for detailed data sources and methods).
Figure1 illustrates the data reconciliation process for the
IW-extended MRIO of Japan and the footprint estimation.
We investigate the impact of cities on wealth redistri-
bution and regional sustainability through the hierarchical
supply chain that links cities and other economies at various
levels. To evaluate the wealth footprint’s effect on regional
sustainability, we calculate the inclusive wealth (IW) trade
participation indices, the IW cluster ratio index, and the IW
and capital impact inequality index, which reveal regional
wealth changes due to trade among cities (see the attachment
for specific calculations).
The IW footprint offers two sustainability assessments for
current production and consumption patterns. The spatial
sustainability assessment evaluates economies with differ-
ent regional territorial wealth endowments. Suppose the per
capita IW footprint is evenly distributed among economies,
and the total IW footprint equals the IW endowment. In that
case, we consider the region sustainable due to the comple-
mentarity of regional production and consumption linkages.
The structural sustainability assessment evaluates whether
the capital structure in the wealth footprint is equal to the
wealth endowment. If it is, this indicates that current capital
investment meets the capital market demand, ensuring non-
declining wealth for sustainability.
Although the current wealth footprint analysis extends
the IW account to address its shortcomings, several limi-
tations remain. For instance, this study assumes regional
self-sufficiency and wealth, neglecting the impact of inter-
national trade, which does not accurately reflect real-world
conditions. This discrepancy stems from data and calcula-
tion constraints. Nevertheless, our current results illuminate
changes in Japan’s domestic capital structure resulting from
trade networks and can contribute to valuable research find-
ings and policy recommendations. In the next section, we
discuss the estimation results for further discussion.
Results anddiscussion
This section presents the results and related discussions. We
focus on three main points: (1) spatial sustainability between
Japanese cities and surrounding areas, (2) the impact of
cross-prefectural value chains on wealth redistribution, and
(3) capital structure sustainability of cities and prefectures.
Through these results, we discuss capital management
challenges for the sustainability of regional development in
Japan.
Role ofcities inwealth reallocation throughspatial
externality
We begin our discussion by presenting a series of maps of
Japan. Figure2 shows the population distribution, natural
capital ratio, per capita wealth level, and per capita wealth
Fig. 1 Schematic diagram of the process of rebalancing the IW matrix and constructing the municipal level IW-extended MRIO of Japan

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footprint level at the municipal level in Japan. These
results highlight the characteristics of Japanese cities.
Japan’s population is unevenly distributed (Fig.2a),
with 10 of the 47 prefectures accounting for more than half
of the total population. The capital, Tokyo, alone com-
prises more than 10% of the country’s population. The
population is primarily concentrated in five metropolitan
areas: the two megacities of Tokyo and Osaka and their
surrounding areas, as well as the local central cities in the
central, southern, and northern regions. The orange dotted
line area in Fig.2b indicates the locations with the low-
est natural capital ratios and the most densely populated
metropolitan areas. Figure2c illustrates that metropolitan
areas have the lowest per capita wealth endowment lev-
els. Regions with high natural capital endowments show
higher per capita wealth levels, correlating with sparser
populations.
Figure2d conveys an important message: only some cities
and surrounding areas are interconnected through production
and consumption, with evenly distributed wealth footprints
(the darkest areas in the south and northeast), suggesting
that cities and surrounding areas in these regions produce
and consume in a complementary manner. In contrast, the
uneven wealth footprint in other regions indicates that these
regions are not complementary. Our analysis of hierarchical
value chains reveals that 37.5% of local wealth is embodied
in cross-prefecture value chains. Therefore, it is essential to
explore the role of spatial externalities on wealth redistribu-
tion based on the value chains of municipal economies.
Figure3, the bubble chart, displays how the wealth of
1880 municipal economies was redistributed through their
pattern of participating in production and consumption net-
works. More than half (1077 units) of the economies in the
second quadrant (group II) served as wealth suppliers in the
Fig. 2 The per capita Inclusive Wealth and domestic Inclusive Wealth footprint of cities in 2015

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value chain (intermediate goods suppliers). However, they
also are consumers of wealth from other regions (final good
consumers), making them neither total consumers nor sup-
pliers. The remaining 570 municipal economies are in the
first quadrant (group I), indicating that they were complete
suppliers in both value chains (intermediate goods supplier)
and direct consumption (the final good supplier). Only 107
economies are complete consumers (third quadrant, group
III). They rely on other regions for both production and
consumption. In addition, 46 economies are in the fourth
quadrant (group IV). They serve as end producers whose
production demands from other regions but also supply final
goods to other regions.
The size of the bubble represents each economy’s wealth
endowment level. Economies with higher levels of wealth
endowment tend to be displayed on the upper half of the
central axis, indicating their wealth participated more in the
value chain as a supplier. Only a small ratio of the wealth
footprint is embodied in the final trade. In contrast, econo-
mies with low-wealth endowments have had more wealth
footprint embodied in final trade.
When we display the groups of economies classified in
Fig.3 on the map, as shown in Fig.4, we find that only the
megacities area of Tokyo has no complete consumers (group
III) and end producers (group IV). This result implies that
the complex cross-prefecture production and consumption
network formed by Tokyo’s mega-metropolitan area and the
production–consumption relationship between the city and
surrounding areas are obscure.
The inclusive wealth embodied incross‑prefectural
value chains
Due to the complex cross-prefecture value chains at the
municipal level, we summarize the wealth footprint embod-
ied in cross-prefecture value chains at the prefecture level
and present them as indicators. Table1 displays three IW
footprint indicators for 47 prefectures in Japan: IW footprint
forward/backward participation in cross-prefecture value
chains, IW footprints cluster ratio, and the impact inequal-
ity of IW footprints concerning the wealth endowment.
The bubble chart in Fig.5 further presents results in
Table1, which can categorize the prefecture-level econo-
mies into three groups. We have named these groups autarky
groups (I), cluster group (II), and supply groups (III). Econo-
mies in group I belong to local internal self-sufficiency and
have their central cities. Group II consists of large metro-
politan areas, such as Tokyo, Osaka, and their surrounding
economies. These regions display distinct wealth clusters,
absorbing wealth from other areas through backward partici-
pation in the value chain. The wealth footprint is larger than
their territorial wealth. Conversely, group III shows that due
to forward value chain participation, the territorial wealth of
these economies is provided for other regions, whose wealth
footprint is smaller than that of territorial wealth.
Results from Table1 and Fig.5 show that more than
40% of the wealth embodied in cross-prefecture value
chains is clustered in and around Tokyo. The remain-
ing approximately 40% are clustered around Osaka and
Fig. 3 Grouping of cities by IW footprint embodied in the trade channel

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adjacent areas. At the municipal level, we found difficulty
in clarifying the wealth footprints distributed in the com-
plex value chains, but the prefecture-level results show
wealth clusters in the megacities’ circles.
The flowchart in Fig.6 further shows the wealth flow
direction (in Fig.6, the blue flow direction points to the
west, and the orange flow direction points to the east). The
spatial externalities of megacities on wealth affect adja-
cent areas and even the non-adjacent areas with significant
distance. Moreover, the wealth footprint indicates that the
spatial externality led to considerable impact inequality
in production and consumption. While the surrounding
regions of megacities benefit from the wealth clustering,
the remote regions suffer a loss in wealth.
Our analysis reveals hierarchical value chains in Jap-
anese cities contributing to complex regional wealth
changes. As cities become more interconnected through
cross-prefecture networks, these linkages lead to a redistri-
bution of wealth, with megacities benefiting disproportion-
ately from interregional trade more readily than local cit-
ies. This effect goes beyond typical geographic distances.
The impact of production networks across regions must be
considered when designing policies addressing regional
differences and promoting overall regional sustainability.
Capital inequality atmunicipal andprefecture levels
In this section, we illustrate the capital structure changes
in the IW footprint to discuss structural sustainability. We
first use the bubble chart in Fig.7 to illustrate municipal
economies’ natural, human, and productive capital endow-
ment levels and the degree of participation of related capi-
tal in the value chain. The size of the bubbles indicates the
level of territorial IW. Figure7 demonstrates the comple-
mentarity of capital endowments of municipal units as they
participate in value chains. Economies with higher capital
endowments generally serve as providers. Economies with
abundant territorial natural capital tend to supply resources
to other regions through value chains. Although the case
for production and human capital may not be as evident as
natural capital, relevant trends are still discernible.
At the prefecture level, the situation changes. The skyline
in Fig.8 summarizes the capital endowment, footprint, and
cross-prefecture value chain participation in prefectures. The
width of the bar represents endowment, while the height rep-
resents the footprint. The blue shaded area indicates capital
supply, and the red shaded area indicates capital demand. A
red line above 100% signifies that a capital footprint impact
exceeds the endowment. The most striking result is the
Fig. 4 Grouping of the prefecture of Japan according to the properties identified by indices

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significant gap between the total natural and human capital
and their total footprint values. The natural capital footprint
value is substantially lower than its accounting value. Con-
versely, the human capital footprint is considerably higher
than the accounting value, which implies a depreciation of
natural capital and a shortage of human capital.
The gap between capital endowments and footprints also
varies by prefecture. Produced capital demonstrates charac-
teristics related to their groupings mentioned in Fig.5, such
as autarky groups (I), cluster group (II), and supply groups
(III). For natural capital, prefectures with higher natural
capital endowments exhibit lower capital footprints and less
cross-prefecture value chain participation. In contrast, the
megalopolises with the lowest natural capital endowments
have higher natural capital footprints and increased cross-
prefecture value chain supply participation. The natural capi-
tal footprint of regulating services surpasses the endowment
in Tokyo and Osaka.
Regarding human capital, supply group III displays a sup-
ply exceeding its load. Cluster group II, possessing the high-
est human capital, slightly surpasses its load but maintains
relative balance. Autarky group I exhibits a human capital
footprint higher than its load.
At the municipal level, we observe the participation
of natural capital in value chains in economies with high
natural capital endowments. However, the results of cross-
prefecture value chain participation indicate that only a few
natural capitals participate in cross-prefecture value chains.
The primary participation in cross-prefecture value chains
involves produced capital and human capital. The pattern of
value chain participation leads to two outcomes: the depre-
ciation of local natural capital in natural capital-abundant
regions and the exacerbation of natural capital depletion in
megacities due to the complementary utilization by capital
clustering. The capital structural inequality in the IW foot-
print suggests that local and national policy governance is
necessary for sustainable development.
Conclusions
In conclusion, this study develops an inclusive wealth foot-
print analysis using geographic accounts of inclusive wealth
to assess sustainability. Using Japan as a case study, we
measure municipal-level inclusive wealth (IW) footprints
based on wealth accounts and analyse the effects of cities’
spatial externalities through hierarchical value chains on
regional sustainable development.
The IW footprint evaluates sustainability from two
dimensions: spatial complementarity of wealth among econ-
omies and capital structural complementarity of wealth. By
considering hierarchical value chains, our empirical analysis
provides evidence for the impact of spatial externalities on
Table 1 Inclusive Wealth Footprint Indicator for Prefectures in Japan
City FW/BW Impact
inequality
Cluster (%) Join ratio (%)
Hokkaido 1.76 0.79 3.82 48.48
Aomori 1.35 0.87 0.98 49.67
Iwate 0 1 0.00 0.00
Miyagi 0 1 0.00 0.00
Akita 0 1 0.00 0.00
Yamagata 0 1 0.00 0.00
Fukushima 5.03 0.55 0.49 55.81
Ibaraki 1.88 0.73 1.97 58.72
Tochigi 22.49 0.39 0.12 63.68
Gunma 0.81 1.14 2.68 59.21
Saitama 0.76 1.15 7.50 47.48
Chiba 0.72 1.19 7.02 49.05
Tokyo 0.86 1.06 15.44 43.33
Kanagawa 0.71 1.2 11.66 48.54
Niigata 1.55 0.83 1.57 47.99
Toyama 0 1 0.00 0.00
Ishikawa 0 1 0.00 0.00
Fukui 0 1 0.00 0.00
Yamanashi 0.84 1.11 1.14 56.34
Nagano 1.46 0.84 1.62 50.48
Gifu 1.6 0.8 1.40 54.03
Shizuoka 1.5 0.82 2.99 54.84
Aichi 0.9 1.06 9.70 50.78
Mie 0.71 1.11 1.70 26.83
Shiga 1 1 2.07 63.64
Kyoto 0.78 1.14 3.01 48.73
Osaka 0.84 1.1 9.29 48.84
Hyogo 0.88 1.08 6.49 52.99
Nara 0.69 1.2 1.33 42.81
Wakayama 0 1 0.00 0.00
Tottori 0 1 0.00 0.00
Shimane 0 1 0.00 0.00
Okayama 0 1 0.00 0.00
Hiroshima 0 1 0.00 0.00
Yamaguchi 0 1 0.00 0.00
Tokushima 5.29 0.39 0.23 75.11
Kagawa 0 1 0.00 0.00
Ehime 1.7 0.75 1.04 59.80
Kochi 1.05 0.98 0.55 35.75
Fukuoka 0 1 0.02 0.00
Saga 0 1 0.00 0.00
Nagasaki 1.53 0.84 0.85 46.52
Kumamoto 0.62 1.13 1.16 21.76
Oita 0 1 0.00 0.00
Miyazaki 0 1 0.01 0.00
Kagoshima 1.4 0.89 0.90 39.76
Okinawa 0.51 1.29 1.24 29.92

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Fig. 5 Grouping prefectures of
Japan by the IW footprint clus-
ter and impact inequality
Fig. 6 The flow map of cross-prefecture IW footprint flow

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local sustainability in the context of urban expansion and
complexity.
Our main findings indicate that the formation of megac-
ity agglomerations is associated with cross-prefectural value
chains. However, cities and other regions participating in
cross-prefectural value chains do not complement each other,
leading to wealth clustering in megacities. Such clusters
promote production and consumption in and around met-
ropolitan areas, resulting in regional inequalities influenced
by wealth footprints.
Cross-prefectural value chains also impact capital struc-
tures. Natural capital primarily participates in local value
chains, while produced capital and human capital mainly
engage in cross-prefectural value chains. This leads to an
unbalanced wealth and capital structure, capital deprecia-
tion in areas with abundant natural capital, and excessive
consumption in metropolises.
Based on these conclusions, the current production and
consumption patterns in Japan weaken the spatial com-
plementarity and capital structure complementarity of the
economy, thereby affecting regional sustainable develop-
ment. Our research emphasizes the need for appropriate
capital management approaches that address regional
and capital complementarity concerns for sustainable
development.
Japan faces challenges related to immense cities, shrink-
ing towns, and depopulation, and our analysis provides
valuable insights into these issues. Policymakers and stake-
holders can use the IW footprint in the value chain to guide
policy regulation. For example, local governments should
prevent excessive wealth loss due to participation in cross-
prefectural value chains, increase the utilization and invest-
ment of natural capital, and avoid natural capital deprecia-
tion. At the regional level, adjusting the integration of local
supply chains and balancing capital complementarity among
different regions are crucial for sustainable development.
Central wealth footprint clusters and the home market should
consider appropriate agglomeration levels to avoid exces-
sive depletion of natural capital and compensate for regions
affected by unequal footprints. We propose inclusive wealth
Fig. 7 The capital footprint VCs participation and capital endowment of cities in Japan

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Fig. 8 The skyline graph of the capital endowment, footprint and participation in value chains of each prefecture

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investment to modify production and consumption patterns
for sustainable regional development.
Although this study focuses on urban sustainability in
Japan, we provide a spatiotemporal sustainability analysis
within a consistent and inclusive wealth footprint framework
applicable to any region or country. The limitations of this
study warrant further investigation. For instance, due to data
limitations, we did not consider the impact of international
trade. Future analysis should incorporate international trade
in the wealth footprint. Additionally, the impact on the bio-
sphere should include degradation due to climate change,
pollution, and other values beyond the two ecological value
services considered in this study.
Supplementary Information The online version contains supplemen-
tary material available at https:// doi. org/ 10. 1007/ s11625- 023- 01367-4.
Author contributions Conceptualization: SM, SC. Methodology: SC,
TW. Investigation: SC, KK. Visualization: SC. Funding acquisition:
SM. Project administration: SM. Supervision: SM. Writing—original
draft: SC. Writing—review and editing: SC, KK, SK.
Funding This research was supported by the Environment Research
and Technology Development Fund (JPMEERF20201001) of the Envi-
ronmental Restoration and Conservation Agency of Japan and JSPS
KAKENHI Grant number JP20H00648.
Availability of data and material The data is available upon reason-
able request.
Declarations
Conflict of interest The authors declare that they have no competing
interests.
Consent for publication Not applicable.
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