Sep., 2016
Journal of Resources and Ecology
Vol. 7 No.5
J. Resour. Ecol. 2016 7(5) 342-351
DOI: 10.5814/j.issn.1674-764x.2016.05.004
www.jorae.cn
The Silk Road Economic Belt and Green Growth
in the East of Russia
GLAZYRINA Irina1,2*, ZABELINA Irina1,2
1. Department for ecological economics, Institute of Natural Resources, Ecology and Cryology of the Siberian branch of the Russian Academy of Sciences,
Chita 672014, Russia;
2. Transbaikal State University, Chita 672039, Russia
Abstract: The Silk Road Economic Belt (SREB) opens new development opportunities for Russia in general, and
its Eastern regions in particular, via larger-scale and multi-level international cooperation. The eastern regions of
Russia, rich in natural resources, have traditionally focused on resource extraction. In the context of the SREB,
the issues of environmental security in Eastern Russia come to the fore. Here, we propose tools for ‘diagnosis’ if a
chosen path of regional economic development proceeds according to the concept of a green economy. We use
different indicators based on eco-intensity. We determine ecological-economic development trends in the Eastern
border regions of Russia at the initial stage of the Silk Road Economic Belt formation to serve as a starting point
and guideline for development processes within the SREB. If cooperation is directed to implementing the best
Chinese production chains, significant improvements in the quality of economic growth in Russia will be achieved.
Key words: Silk Road Economic Belt; economic development; ecological pressure; green growth model; crossborder cooperation
1
Introduction
The Silk Road Economic Belt (SREB) strategy proposed by
China’s President Xi Jinping in 2013 aimed “to promote
greater cooperation, development and prosperity among the
countries of Asia, Europe and Africa” (Dong et al. 2015).
For Russia and its Eastern regions, it opens new opportunities for development through larger-scale and multilevel international cooperation. It is very important that environmental objectives during ‘Ecological Civilization’ development take a central place in the strategy whereby “the
core ideology is to respect nature, to follow nature, and to
protect nature, and to drive human sustainable development” (Dong et al. 2015).
Eastern regions of Russia, rich in natural resources, have
traditionally focused on resource extraction and, to some
extent, processing. Raw-material industries encompass sig-
nificant economic segments. With steady demand for natural
raw materials, including demand globally, this trend will
undoubtedly continue. Therefore, in the context of the SREB
strategy, the issues of environmental security in Eastern
Russia has emerged.
One of the first studies devoted to the green economy
was Blueprint for a Green Economy (Pearce et al. 1989).
This book investigated the problem of natural and physical
capital substitutability. The concept and principles of the
green economy were later presented in the Report of United
Nations Environment Programme (UNEP) “Towards a
green economy: Pathways to sustainable development and
poverty eradication” (The official website of the United
Nations Environment Programme 2011). A green economy,
according to UNEP’s definition, is an economic system
“that results in improved human well-being and social equity, while significantly reducing environmental risks and
Received: 2016-03-21 Accepted: 2016-07-28
Foundation: Siberian Branch of Russian Academy of Sciences (Project IX.88.1.6.)
*Corresponding author: Irina Petrovna Glazyrina. E-mail: [email protected]
Citation: Glazyrina I., Zabelina I. 2016. The Silk Road Economic Belt and Green Growth in the East of Russia. Journal of Resources and Ecology, 7(5):
342-351.
GLAZYRINA Petrovna Irina, et al.: The Silk Road Economic Belt and Green Growth in the East of Russia
ecological scarcities” (The official website of the United
Nations Environment Programme 2010). UNEP underlines
that, in any green economy, “growth in income and employment is driven by public and private investments that
reduce carbon emissions and pollution, enhance energy and
resource efficiency and prevent the loss of biodiversity and
ecosystem services” (The official website of the United Nations Environment Programme 2011 p.16). One of the key
goals of the green economy is eradicating poverty. UNEP’s
report states that transitioning to a green economy can contribute to poverty reduction.
The theoretical basis for our study was the concept of
sustainable development, and approaches and tools of ecological economics (Daly and Farley, 2004). Gross domestic
product (GDP) does not reflect the depletion of natural resources, loss of biodiversity and ecosystem services (Farley,
2012). In order to assess results of development, we need
additional indicators reflecting the quality of economic
growth in an environmental context. One of these is ecointensity (De Haan, 2004; Glazyrina, 2012). However, simple
reduction of eco-intensity does not guarantee the reduction
of anthropogenic pressure on the environment. A necessary
condition for the transition to a green economy is to reduce
the overall negative impacts on natural systems. As noted,
“the existing literature on green growth lacks quantitative
analysis of different economic growth patterns” (Shang et al,
2015, p.311). Therefore, developing quantitative indicators
of green growth is needed. One of significant steps in this
area was Victor (2015). The paper (Shang et al, 2015) presents analysis of economic growth patterns based on carbon
intensity in China. Here, we have tried to create tools for
‘diagnosis’ if a chosen path of regional economic develop-
343
ment proceeds according to the concept of green economy
transitioning. The main provisions of this concept correspond to the declared objectives of the SREB strategy.
2
Data sources
We collected annual data for GDP, gross domestic product
in regions (GRP), monthly income (in 2000 prices), polluted
waste water, air pollutant emissions (including sulfur dioxide, nitrogen oxides, carbon oxide, solid substance and hydrocarbons) for 2000–2013, as reported in annual volumes
of the Russia Statistical Yearbook of the Federal State Statistics Service of Russia.
3
Eastern border regions of Russia
The Eastern border regions of Russia have rich natural resource potential (minerals, forests and water resources) and
some of them possess extensive agricultural lands. However,
the level of economic development in most of them is lower
than the average for Russia. In this work, we consider seven
eastern border regions of Russia: Irkutsk, Amur and Jewish
Autonomous Regions, Khabarovsk, Trans-Baikal and Primorye Territories, Republic of Buryatia1.
Figure 1 shows that GRP per capita in most of these areas
is considerably below the national average. Exceptions are
Irkutsk Region and Khabarovsk Territory, since 2009.
A similar dynamic can be observed with respect to
growth in per capita income. In most regions, they are below the national average, with the exception of Irkutsk Region and Primorye Territory, since 2013 (Fig. 2).
The historical peculiarity of the socio-economic devel
opment of Siberia and the Russian Far East is the determinative role of the state in the organization and management
of social and economic processes, with a focus on relations
Fig.1 Dynamics of per capita GRP in Eastern border regions of Russia (Russian Rouble, 2000)
1 English translation of the names of the regions are presented in accordance with the official translation of Russian Constitution:
http://www.constitution.ru/en/10003000-04.htm.
344
Journal of Resources and Ecology Vol. 7 No. 5, 2016
Fig.2 Per capita monthly income in Eastern border regions of Russia (Russian Rouble, 2000)
with neighboring Pacific countries and markets. Natural
resources and geographical position have formed the character, scale and patterns of economic life and development.
The East of Russia is a part of the country where the exploitation of natural resources is a national industry specialization. In the Russian Far East, the share of the mineral resources sector in the structure of gross value added continues to
grow: it increased from 14.9% in 2005 to 26.5% in 2013
(Lomakina 2015). Comparative studies (Rumina and Anikina 2007; Soboleva et al. 2016; Lokosov et al. 2015) found
that under an economic, social and demographic context,
these areas are less favorable than other regions in Russia.
In 2013, the Russian Government made a decision about
transitioning to a new model of Eastern Russian development. Formation of territories for priority development and
the creation of preferences in the form of a special tax regime were announced as key mechanisms, and their implementation has begun. The road map for the development of
cooperation between China, Mongolia and Russia2 notes the
importance of enhancing trilateral political dialogue, boosting collaboration in trade, investment and humanitarian
spheres, and strengthening interaction in international and
regional affairs. It also involves elaborating a program of
cooperation in the economic corridor between Mongolia, the
Russian Federation and China within the Eurasian Economic Union, the Silk Road Economic Belt and the ‘Steppe
road’. For the border regions of Eastern Russia, whose
economies have historically focused on the extraction and
use of natural resources, this ambitious target opens new
perspectives. Still, since the processes of resource exploitation are always accompanied by a negative impact on the
environment, there is a key task to harmonize the environmental and economic interests of all parties.
4
Green growth
In the scientific community, there is a consensus that
thevector of further development of Russia should be directed towards the green economy. Sustainable progress and
environmental security goals are put in context with the
purpose of enhancing well-being, poverty reduction, modernization and innovation dynamics, development of the
human personality.
Some publications characterize the term ‘green growth’ as
a transition path to a ‘green economy’ (The official website of
the Organisation for Economic Co-operation and Development 2011; De Boer et al. 2014). However, there is no
doubt that this definition should be specified in quantitative
terms. Victor (2015) proposed a model for this specification.
He used the indicators of carbon emissions eco-intensity and
elaborated a tool, which can make ‘a diagnosis’ for green,
brown or black growth in respect to climate consequences.
The green economy concept involves not only reducing
carbon emissions but also decreasing environmental pressure in general. Therefore, in determining the quantitative
characteristics of green growth, we need to consider ecointensity indicators for main pollutants, as well as characteristics of natural resource efficiency. Next, we will present
a generalized model based on Victor’s idea.
The quantitative indicators of eco-intensity can be divided
into two categories. The first one includes so-called specific
indicators that reflect the amount of pollution (and other
negative impacts) per unit of produced value added, per
employee in the economy, and sometimes per capita. The second category includes the indicators of "resource intensity":
the amount of deforestation per unit of income (e.g. wages, fiscal revenues), and water use per unit of output (value added).
2 http://special.kremlin.ru/events/president/news/49899, http://www.ruchina.org/china-article/china/864.html
GLAZYRINA Petrovna Irina, et al.: The Silk Road Economic Belt and Green Growth in the East of Russia
Figure 3 shows the general concept of the model. On the
two-dimensional graph, the horizontal axis represents one of
the indicators of eco-intensity (EI) or resource intensity. It is
always the ratio of the environmental impact (EIm) or extraction of natural resources and the economic result (ER):
EI = EIm/ER.
This indicator can quantitatively characterize the specific
volume of harmful substance emissions into the atmosphere,
the volume of polluted (not recovered) waste and the volume of contaminated wastewater and can also refer to the
volume of harvested timber, mining, consumed electricity
and/or heat energy. Thus, the horizontal axis is used to determine the specific indicators of impact on natural systems
(natural capital) per unit of economic result. (De Haan 2004;
Environmental quality of growth indicators 2005, Zabelina
and Klevakina 2011). The vertical axis shows the actual
economic result (it could be gross domestic/regional product
(GDP/GRP), income from a specific type of economic activity, including fiscal parameters, wage, number of jobs,
etc.). The point I0 denotes the initial ratio between EI and ER.
Curve G is determined by the equation EI*ER = const.
Thus, the points lying on the curve G (which is obviously a
hyperbole), are characterized by the same condition of an-
345
thropogenic impact as at point I0. The points located below
the curve G determine such ratios of ER and EI at which
negative impact on the environment (or the amount of used
natural resources) is less than at the point I0. Respectively,
at the points lying above the curve G, the negative impact is
greater than at point I0. Ecological-economic zones according to the concept of green growth are presented in Table 1.
The proposed model can be used for both temporal and
spatial analysis. In the first case, taking I0 for the ecologicaleconomic state of a region (e.g. country, industry) at the starting point of time, we can determine the direction of further
development in time and diagnose the compliance or noncompliance for the vector of green growth. In the second case,
taking I0 for the ecological and economic condition of a particular region (or the average values for the country or a
group of regions) for the selected indicators of ER and EI, it is
possible (qualitatively and quantitatively) to assess its position
in relation to other territories in the context of green growth.
5
The type of growth in Eastern Russia
The approach of Victor to the definition of quantitative indicators of green growth has been used (Shang et al. 2015)
to study the dynamics of the Chinese economy in the context
Fig.3 Ecological-economic zone according to the green growth model
Table 1 Ecological-economic zone according to the concept of green growth
Zone
Green growth zone: GG
Brown growth zone: BrG
Black growth zone: BlG
Black degrowth zone: BlD
Green degrowth zone: GD
Absolute green degrowth zone: AGD
Description
The transition from the point I0 to any point in this zone means increase of the economic result with simultaneous
reduction in both the eco-intensity and the total impact on the environment.
The transition from the point I0 to any point in this zone means increase of both the economic result and the total
negative impact on the environment with simultaneous reduction in the eco-intensity.
The transition from the point I0 to any point in this zone means increase of the economic result with simultaneous
increase in both the eco-intensity and the total impact on the environment
The transition from the point I0 to any point in this zone means decrease of the economic result with simultaneous
increase in both the eco-intensity and the total impact on the environment.
The transition from the point I0 to any point in this zone means decrease of the economic result and the total impact on the environment with simultaneous increase of the eco-intensity.
The transition from the point I0 to any point in this zone means decrease of the economic result, eco-intensity and
the total impact on the environment
346
of carbon emissions. The authors' calculations showed that
in the period from 1971 to 2010, the economic growth in
China was characterized by a brown or black ‘color’; this
situation improved after 2005.
Journal of Resources and Ecology Vol. 7 No. 5, 2016
A similar calculation for the whole of Russia revealed the
brown character of growth in the context of carbon emissions in the period 2000, 2004–2013, except 2004 (Fig. 4).
Inflation processes had been taken into account. However,
Fig.4 Carbon emissions in Russia: color of growth 2000–2013 (Russian Ruble, 2000)
347
GLAZYRINA Petrovna Irina, et al.: The Silk Road Economic Belt and Green Growth in the East of Russia
the calculations for each region separately showed a high
differentiation of these indicators, even within the group of
the Eastern border regions. On Fig. 4 a–h, the horizontal
axis shows the eco-intensity, that is, in this case, the amount
of carbon emissions per 1000 Russian rubles. The vertical
axis shows the magnitude of the regional product (GRP,
GDP for Russia in total). The year 2000 is selected as a
starting point, denoted by I0. These figures reveal green
growth in Khabarovsk Territory, green-brown growth in
Zabaikalsky Territory, Primorye Territory, Irkutsk Region
and Republic of Buryatia, black growth in Amur Region and
the Jewish Autonomous Region.
A similar analysis was conducted for the emissions of
pollutants: SO2, NOx, solid substance, hydrocarbons. The
emissions of these substances are designated as ESO2, ENOx,
Ess, EHC, respectively. The results are presented in Table 2.
They show a high degree of differentiation of regions in the
East of Russia. The most favorable situation is observed in
Khabarovsk and Primorye Regions. The least prosperous are
Jewish and Amur Regions, where we see a significant number of black growth points. For Russia in general, the number of green and brown growth points is almost the same. A
point of black growth was detected only once, in 2004, for
carbon emissions.
Table 2 Eastern border regions of Russia: color of growth
Country, region / Indicator
Russian Federation
Green growth
Etotal
+ (2013)
ESO2
+
ENOx
+ (2004–2005)
+ (2006–2013)
+
Etotal
+
ESO2
+
ENOx
+ (2012)
+ (2004–2011, 2013)
EСО
+ (2004, 2009, 2011–2013)
+ (2005–2008, 2010)
Ess
+
EHC
Amur Region
+
Etotal
+ (2001–2003)
+ (2004–2013)
ESO2
+ (2004–2006, 2008–2001, 2013)
+ (2007, 2012)
ENOx
+ (2004–2008)
EСО
Ess
Republic of Buryatia
+ (2004–2011, 2013)
+ (2012)
+ (2012)
+ (2005–2006)
+ (2004, 2007–2011, 2013)
EСО
+ (2004–2007, 2009–2010)
+ (2008, 2011–2013)
Ess
+
EHC
+ (2004, 2008–2011)
+ (2005–2007, 2012–2013)
Etotal
+ (2003–2007, 2009–2011)
+ (2001–2002, 2008, 2012–2013)
ESO2
+ (2004–2008, 2010–2011)
+ (2009, 2012–2013)
ENOx
+ (2004–2007)
+ (2008–2013)
EСО
+ (2009)
+ (2004–2008, 2010–2013)
Ess
+ (2004–2007, 2009–2013)
+ (2008)
+ (2005–2009)
Etotal
+ (2004–2013)
ESO2
+ (2004, 2006–2013)
ENOx
EСО
+ (2004, 2010–2013)
+ (2001–2003)
+ (2005)
+
+ (2006–2013)
+ (2004, 2006–2013)
+ (2007–2013)
ENOx
EHC
Primorye Territory
+ (2004, 2011–2013)
+ (2005)
+ (2001–2006)
ESO2
Irkutsk Region
+ (2009–2013)
+
+ (2005–2010)
EHC
Etotal
+ (2004)
+
EHC
Trans–Baikal Territory
Black growth
+ (2001–2012)
+ (2005–2013)
EСО
Ess
Brown growth
+ (2004–2005)
348
Journal of Resources and Ecology Vol. 7 No. 5, 2016
(Continued)
Country, region / Indicator
Ess
Green growth
Brown growth
EHC
Khabarovsk Territory
+
Etotal
+ (2001–2002, 2005–2013)
ESO2
+
ENOx
+ (2005–2013)
EСО
+
Ess
+ (2006–2013)
+ (2003–2004)
+ (2004)
+ (2004–2005)
EHC
+
Etotal
ESO2
Jewish Autonomous Region
+ (2005–2013)
+ (2006–2013)
ENOx
+ (2001–2005)
+ (2004–2005)
+ (2004, 2008–2013)
+ (2005–2007)
+
EСО
Ess
+ (2006–2013)
+ (2004–2005)
EHC
+ (2008–2009)
+ (2004–2007, 2010–2012)
A very significant factor of negative impact which affects
both the quality of human life and natural systems, is the
discharge of contaminated wastewater. In the Eastern regions, there are several large rivers, the basins of which are
separated by the borders between Russia, China and Mongolia: the Selenga, Amur (Heilong) and Argun (Hailar) Rivers. Therefore, this issue is also important in the context of
cross–border relations.
Figure 5 presents the analysis results for the color of
growth in terms of polluted wastewater. The horizontal axis
shows the eco-intensity, that is, in this case, the amount of
contaminated wastewater (carbon emissions) per 1000 Russian rubles. The vertical axis shows the magnitude of the
regional product (GRP, GDP for Russia in total). The year
2000 is again selected as a starting point.
The system of payments for negative impact on the environment, which was legislatively introduced in Russia in
1992, contributed, to some extent, to the reduction of air
emissions and discharge of polluted water per unit of economic result. This means improving the quality of economic
growth (Glazyrina 2012). As shown in Figure 5, with respect to impacts on water bodies, we can conclude about
achieving a green growth trajectory for the country in total
and for most of its Eastern border regions.
6
Black growth
+
Conclusions: necessary but not sufficient
conditions
The ecological-economic trends of development in the
Eastern border regions of Russia are at an initial stage of
Silk Road Economic Belt formation. Possible effects of
SREB can be positive from an economic point of view, as
they can contribute to growth in GDP, employment and
public financial resources.
We expect that development under the umbrella of the
SREB in the east of Russia will be influenced, to some ex-
tent, by path-dependent factors. This means that the share of
the primary sector in the regional economy will remain high
for a long time, so there is a danger of ongoing environmental degradation. At the same time, eastern Russian regions are rich in tourist and recreational natural resources.
This could be the basis for the development of the environmentally sound service sector, on which there is an observable steady demand. However, the development of this sector is very slow due to shortages in investment resources.
The processes in the framework of the SREB could create
new opportunities for its promotion and extension, and
hence for the diversification of regional economies.
It is important to have quantitative tools to assess the different ways of development under the umbrella of the SREB.
Our results can serve as a starting point and guideline for
the development of plans, programs and strategies in SREB
cross–border collaboration as cooperation projects must not
worsen the current trend. On the contrary, they are intended
to contribute to improving the quality of economic growth.
In terms of the colors of growth, this means that only
those projects that contribute to development trajectory
formation in the area of green growth in all major indicators
of impacts on the environment can be thought of as corresponding to the SREB concept and the green economy.
Simple calculations show that if the eco-intensity of a particular project is lower than the eco-intensity of the region’s
economy, the total eco-intensity will decrease (if this project
is implemented). This implies that such projects will at least
not be a factor of black growth.
However, this does not guarantee that the development
trajectory will be in the zone of green growth, as it can be in a
brown zone. Reduction of eco-intensity is a necessary but not
sufficient condition for green growth. Every new production
facility increases the existing negative impacts on the environment; therefore, transitions into the zone of green growth
GLAZYRINA Petrovna Irina, et al.: The Silk Road Economic Belt and Green Growth in the East of Russia
(or maintenance of the trajectory in this zone) require that
operating companies reduce anthropogenic influence at the
expense of new equipment and more efficient use of energy,
for example.
349
Thus, for green growth, it is essential that creation of new
industries should be inevitably accompanied by modernization
of existing industrial objects, housing and social infrastructure. If we seek to develop a green economy within the SREB
Fig.5 Polluted wastewater discharge: color of growth 2000–2013 (Russian Ruble, 2000)
350
framework, this principle should be basic in the elaboration
of programs and projects for cross-border cooperation.
In our study we have not taken into account that contaminants may accumulate in the natural environment. In
this case, environmental harm may exceed the damage from
nominal emissions. The algorithm for the calculation has
been proposed in previous studies (Glazyrina et al. 2006;
Glazyrina 2012), based on the idea from a recently published
article (Baumgartner et al. 2002). It has shown that real social damage is dependent on the lifetime of the production
project, not only on the amount of pollution emitted. The
tools, which take into account the accumulated damage in
estimating the color of economic growth, are the subject of
further research.
The proposed model is applicable not only in assessing
the quality of economic growth in the context of emissions
and discharge of polluted wastewater. There is another article (Glazyrina et al. 2015) to present the research of the
color of growth in the forest sector. This work considers two
parameters of eco–intensity:
(1) The amount of wages per one cubic meter of timber
harvested in the sector of wood processing (social indicator);
and
(2) Tax revenues of the state budget per one cubic meter
of harvested timber (fiscal indicator).
Our analysis showed that a significant proportion of regions with better indicators of eco-intensity also have good
prospects in the context of green growth. This suggests that
if fiscal and socioeconomic indicators (not the volume of
logging and export) form the basis of forest policy, incentives created in accordance with this policy will contribute
to the promotion of Russian forest management towards a
green economy.
Negative impacts on the environment can reveal itself in
the disintegration of entire ecosystems, thereby reducing the
quality of ecosystem services (Daly and Farley 2003; Farley
and Costanza 2010; Farley 2012; Zhang et al. 2015; Titova
2015). The assessment of such risks requires more complicated tools and indicators of eco-intensity. Some of these
indicators are presented in already published papers
(Glazyrinа 2012; Environmental quality of growth indicators 2005). These factors are not covered by this study and
require further research.
What can collaboration within the SREB provide in
terms of moving to a green economy? There is a reason to
believe that Russian-Chinese cooperation is a factor of
green growth and has great positive potential. Comparative
analysis (Glazyrina et al. 2014) based on the indicators of
eco-intensity and their dynamics for the provinces of China
and regions of Eastern Russia have demonstrated an ability
to create 1000 $ value added; emission of harmful substances into the atmosphere is much less in China than in
Russian border regions. The same fact is true in respect to
contaminated wastewater. This means that cooperation sho-
Journal of Resources and Ecology Vol. 7 No. 5, 2016
uld focus on the implementation of the best Chinese production chains to significantly improve the quality of economic
growth in Russia. China has established not only implementation but also its own production of environmentally
safe technological solutions. Therefore, Russian-Chinese
technological cooperation can be very useful for the modernization of the economies of border regions.
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丝绸之路经济带与俄罗斯东部经济的绿色增长
格拉济里纳·伊里纳，扎别利纳·伊里纳
1. 俄罗斯科学院西伯利亚分院自然资源研究所生态经济室，赤塔 672014，俄罗斯；
2. 贝加尔国立大学，赤塔 672039，俄罗斯
摘
要：丝绸之路经济带（SREB）为俄罗斯的发展提供了新的机遇，特别是其东部地区，可以通过更大规模、多层次的国
际合作获得新的发展机会。俄罗斯东部地区自然资源丰富，资源开采是其传统的重点产业。在 SREB 的背景下，环境安全成为俄
罗斯东部地区新的焦点问题。本文提出了一种“诊断”工具以判断一种区域经济发展模式是否根据绿色经济的理念进行。我们采
用基于生态强度的不同指标，研究了俄罗斯东部边境地区在丝绸之路经济带形成的初始阶段的生态-经济发展趋势，认为如果针
对中国的生产链实施合作，那么俄罗斯经济增长的质量将会得到明显的改善。
关键词：丝绸之路经济带；经济发展；生态压力；绿色增长模式；跨界合作