Regional difference and drivers in China's carbon emissions embodied in internal trade

Energy Economics 83 (2019) 217–228

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Regional difference and drivers in China's carbon emissions embodied in internal trade Zhaohua Wang a,b,c,d,e, Yiming Li a,b, Hailin Cai a,b, Yuantao Yang a,b, Bo Wang a,b,⁎ a

School of Management and Economics, Beijing Institute of Technology, 100081 Beijing, China Center for Energy & Environmental Policy Research, Beijing Institute of Technology, 100081 Beijing, China Collaborative Innovation Center of Electric Vehicles in Beijing, 100081, Beijing, China d Beijing Key Lab of Energy Economics and Environmental Management, Beijing 100081, China e Sustainable Development Research Institute for Economy and Society of Beijing, Beijing 100081, China b c

a r t i c l e

i n f o

Article history: Received 12 June 2018 Received in revised form 13 June 2019 Accepted 23 June 2019 Available online 05 July 2019 Keywords: CO2 emissions embodied Multiple-region-input-output analysis Structural decomposition analysis Accounting principles

a b s t r a c t To understand the impact of China's internal trade on China's carbon emissions, this article used the multiregional input-output model to compare embodied carbon emissions based on production principle and consumption principle in the eight major economic regions of China. Besides, the SDA method was used to reveal the drivers of changes in CO2 emissions. The study uses data from the 2007 and 2012 multi-regional inputoutput tables. The result shows that domestic demand emissions are the primary source of production-based emissions in China, but the proportion of external demand emissions is increasing rapidly. According to the structural decomposition of the embodied carbon emissions, it can be seen that the carbon emissions caused by the trade in intermediate products have always been a major component of external demand emissions. Further research indicates that the rapid growth in carbon emissions from the production and consumption side of the region is mainly attributed to the expansion of the final demand scale and changes in input structure of the production department. The most critical factor that restrains the increase in carbon emissions on both principles in all regions is the reduction of emission intensity in the production sector. The conclusion of this paper has important implications for how to coordinate inter-provincial trade and regionally balanced development under open economic conditions. © 2019 Elsevier B.V. All rights reserved.

1. Introduction In 2006, China became the world's largest emitter of carbon dioxide (Liu et al., 2015). The global financial crisis in 2008 then led to a gradual decline in China's economic growth (Hu and Cheng, 2017). Thereafter, China's economic resurgence was slow and was unable to sustain the rapid economic growth enjoyed before the economic decline; however, China has entered a new stage of economic development, and there are many significant changes that have taken place in the prevailing economic development model (Mi et al., 2017a). Correspondingly, China's regional carbon emissions showed a new trend in the post-financialcrisis era. The core of China's regional carbon emissions is the development of regional trade. Between the developed eastern regions and inland regions with abundant energy and less developed economies, there will be a carbon transfer problem in domestic commodity circulation; however, the inter-provincial transfer effect of trade on energy consumption carbon ⁎ Corresponding author at: School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China. E-mail address: [email protected] (B. Wang).

https://doi.org/10.1016/j.eneco.2019.06.023 0140-9883/© 2019 Elsevier B.V. All rights reserved.

emissions has a significant impact on the ecological environment of each province and the responsibility for carbon emissions (Wang et al., 2018a). At the 19 th session of the Conference of the Parties in Warsaw in 2013, the UNFCCC created a mechanism for Intended Nationally Determined Contributions (INDCs) to be submitted in the runup to the 21st session of the Conference of the Parties in Paris (COP21) in 2015 (Elzen et al., 2016). At the same time, China joined the INDC to complete China's independent emission reduction targets, it is essential to consider the balance between producer responsibility and consumer responsibility for emissions and the driving forces behind carbon emissions (Peters, 2008). Such practice that only finds the responsibility of producers is likely to cause “carbon leakage” and weaken the effect of emission reduction policies. Similarly, inter-regional trade in China will suffer an “inter-regional carbon leakage” problem (Zhang et al., 2016). There are two approaches to measuring GHG emissions: productionbased and consumption-based accounting (Senbel et al., 2003; Shigeto et al., 2012; Zhang et al., 2016). The internationally recognized emission reduction mode is widely used in global climate change agreements, including the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol. This is based on the principle of

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“producer responsibility” to account for the responsibility of each province in China. Under this accounting system, the country assumes responsibility for all emissions resulting from its production, regardless of whether the product is used for domestic consumption or export (Peters, 2008). Guan et al. (2008) and Zhang (2010) used structural decomposition analysis (SDA) to investigate the factors affecting the growth of China's production-based emissions. Xu et al. (2016) used the Single Regional Input-Output Model (SRIO) to investigate the effects of domestic production technology, economic structure, and scale factors on production-based carbon emission. Shan et al., 2017 calculated the production-based carbon emissions caused by China's foreign trade using the SRIO model. Conversely, under the consumption-based accounting method, all emissions occurring in the production and distribution chain are allocated to the final consumer of the product (Wiedmann, 2009). Peters and Hertwich (2008b) and Wang and Yang (2016) believe that consumption-based accounting could help alleviate the problem of “carbon leakage,” and this difference arises in the Kyoto model: consumption-based accounting can enrich the “common but differentiated responsibility” principle. In recent years, consumption-based accounting has become a research focus: any scholars have compared the two methods and demonstrated its advantages (Jakob et al., 2014; Girod et al., 2014; Steininger et al., 2016). Hasegawa et al. (2015) established a multi-region inputoutput table across 47 states of Japan and estimated the consumption-based carbon emissions. They found that productionbased emissions differ significantly from consumption-based emissions. Also, the ratio of carbon leakage to carbon footprint at the regional level averages over 50%. Steininger et al. (2014) considered that the climate policy approach on the consumption-based accounting can improve cost-effectiveness and justice and Guan et al. (2014) indicates that it can help to reduce global air pollution based on consumption-based accounting. Moreover, Larsen and Hertwich (2009) believe that the use of these principles could provide a more useful, less misleading indicator for assessing the performance of local climate behavior. Peters and Hertwich (2008a, 2008b) indicate that consumption-based accounting has many advantages over production-based accounting, such as solving carbon leakage, promoting comparative environmental advantage, increasing mitigation options, and encouraging technology diffusion. The issues of consumer carbon emissions have also begun to attract the attention of the international community, especially in developing countries. Considering the responsibility for consumptionbased emission is crucial for China (Jakob et al., 2014; Mi et al., 2017b). Regarding a production perspective alone, it will raise obstacles to regional emission rights and responsibilities assigned to the provinces as well as the relevant emission policies (Wang et al., 2018a), therefore, it is necessary to quantify the impact of domestic trade on domestic carbon emissions, analyze the differences between China's consumption-based emission liability and production-based emission liability, and reveal the basis for the inter-provincial transfer of carbon emission liability. At present few have compared accounting for production-based, and consumption-based, carbon emissions across China's regions (Lin and Sun, 2010; Pan et al., 2008; Wiebe et al., 2012), while research into factors driving carbon emissions growth in China's regions on the consumption side remains sparse (Feng et al., 2014). China is a vast country with great regional variations in economic development, resource endowments, population, industrial structure, and lifestyles. Specifically, the considerable economic gap between Western and Eastern China remains large and significant amounts of CO2 are emitted in poorer western regions to support consumption and exports in the richer eastern regions. China should be viewed as a homogenous entity in climate change research. Targeted regional policies are crucial to mitigating carbon emissions in China, however, studies on regions level of China with production-based and consumption-

based emissions are limited. This paper fills these lacunae by using a Multi-Region Input-Output (MRIO) model to compare the variation of inflows and outflows in embodied carbon emissions with these two methods. The impact of external needs on regional carbon emissions and its regional flows is revealed; the impact of final demand activities in a given region on carbon emissions in other regions have been explored. Finally, SDA is further applied to investigate the driving forces behind changes in CO2 emissions embodied in China's domestic trade at a regional level. 2. Method 2.1. Multi-region input-output model The basic expressions of the multi-region input-output model are as follows: X m ¼ Am X m þ Ym

ð1Þ

In this formula, Xm is the total output vector of China which includes nxi. xi represents the output vector of area i. Am is the production coefficient matrix of China. Ym is the Chinese final demand vector which includes nyi and yi is the final needs of the regions. In the MRIO model, formula (1) can also be expressed as: 0

1 0 x1 A11 B x2 C B A11 B C¼B @⋮A @ ⋮ xn An1

10 1 x1 A12 ⋯ A1n B x2 C A22 ⋯ A1n C CB C ⋮ ⋱ ⋮ A@ ⋮ A xn An1 ⋯ Ann ! X X X y11 þ y1i ; y22 þ y2i ; ⋮; ynn þ yni

þ

i≠1

i≠2

ð2Þ

i≠n

The sub-matrix Aii on the diagonal line represents a direct selfproduction consumption coefficient matrix of the region, and submatrix Aij is the product consumption coefficient matrix of each region to other regions which represents interregional trade in intermediate products. Similarly, vector yii represents the products which are produced in region i to satisfy final demand in region i. yir(i ≠ r) represents the products produced in region i and used in other regions, which depicts the trade of final products between regions (Zhao et al., 2016a). Based on the MRIO model, we can express production-based carbon emissions as: 

Z pi ¼ f i xi ¼ f i Lm ym

ð3Þ

fi is the carbon intensity vector of region i. f1∗ = (f1, 0,⋯, 0), f1∗ only includes the emission intensity row vector of region 1 and the other elements are zero. Lm = (I − Am)−1 is the Leontief inverse matrix of the model. Zpi is the total amount of production based emissions (scalar) in region i. As mentioned earlier, we subdivide production-based emissions into domestic demand emissions and external demand emissions. Domestic demand emissions are implied carbon emissions from products produced and consumed in the region; External demand emissions implied carbon emissions produced in the region for other regions' enduse. According to the basic relationship between input and output, here, the following equations are established to calculate the changes in output in other regions xri which are led by the ultimate demand of region i: 0

1 0 A11 x1i B x2i C B A11 B C¼B @ ⋮ A @ ⋮ xni An1

A12 A22 ⋮ An1

10 1 0 1 x1i y1i ⋯ A1n C B C B ⋯ A1n CB x2i C B y2i C C þ ⋱ ⋮ A@ ⋮ A @ ⋮ A xni yni ⋯ Ann

ð4Þ

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The vector xri can also be expressed as the output of the region r serving the final demand of region i. According to formula (4), the total output of region 1 can be represented by output vector xri: x1 ¼

X

ð5Þ

x1i

i

x1i(i ≠ 1) represents external demand emissions from region 1. Domestic demand emissions are carbon emissions from output x11 and it is a carbon emission from region 1's own consumption. Regional trade can be divided into intermediate products trade and final products trade. Thus, external demand emissions can be divided into emissions from trade in intermediate products and emissions from trade in final products (Su et al., 2010; Wang and Yang, 2016). So, the productionbased emissions of region i can be written in the following form: Z Pi ¼ f i xii þ f i

X

xij ¼ f i xii þ f i Lii

j≠i

XX j≠i

Air xrj þ f i Lii

r≠i

X

yij

ð6Þ

j≠i

Differing from production based emissions, consumption based carbon emissions result from other regions and to satisfy final demand in region i. It is expressed as: m

Z Ci ¼ f Lm yi

ð7Þ

yi represents the final requirement column vector for the region i and fm is the carbon intensity line vector in China:  T m yi ¼ yT1i ; yT2i ⋯; yTni ; f ¼ ð f 1 ; f 2 ; ⋯; f m Þ Similarly, we divide the consumer-side emissions of region i into intra-regional emissions and extraterritorial emissions. Regional emissions are equivalent to domestic emissions (Girod et al., 2014; Lin et al., 2016). Extraterritorial emissions are the carbon emissions in other regions caused by region i's final demand, so, region i's consumption-based emissions can be written as: Z Ci ¼ f i xii þ

X

f j xji ¼ f i xii þ

j≠i

þ

X r≠i

X

f r Lrr ðAri xii þ yri Þ

0r≠i @ f r Lrr

X

Arj xji A

First, we decompose the region's final requirements vector, yi is divided into three parts: vector pi, vector pi and scalar vi (yi = (pi ∘ si)vi) (Wei et al., 2017). The vector pi is formed from eight consistent column vectors α. Vector α refers to the proportion of a sector's product in a region's final demand which reflects the structure of the product. The vector si is formed from eight consistent column vectors β. The element β represents the proportion of a product provided by region r to region i as a percentage of the total demand for the product in region i, and thus reflects the distribution of product sources. Scalar vi is the total final demand of region i. Symbolic representation of multiplication of two vector elements gives consumption based emissions of region i: m

Z Ci ¼ f Lm ðpi ∘si Þvi

ð8Þ

j≠i; j≠r

Extra-territorial emissions are divided into two parts: direct tradeinduced emissions and indirect trade-induced emissions. Direct tradeinduced emissions are region's carbon emissions which results from the trade of regions i and r. Emissions from indirect trade are carbon emissions from region j which results from the trade between regions i and r. The production network is complicated, so final demand in a region can not only result in emissions from direct traders, but also indirectly results in emissions from other regions that provide intermediate products to direct traders. For instance, Beijing needs the towels from Shandong, and Shandong will develop a plush trade with Inner Mongolia. Beijing does not buy plush directly from Inner Mongolia, but the plush is used to meet Beijing's demand for towels. So, the carbon emissions are also parts of Beijing's consumer-side emissions. 2.2. Structural decomposition of changes in carbon emissions SDA is a method for estimating the drivers of carbon emissions and energy consumption. First, we change the first variable, and then change the second and third variables to get the first polar form. The second form of polarity is derived in the oppositely way. We use the arithmetic mean of SDA results based on two polar coordinates (Zhao et al., 2016b).

ð9Þ

According to formula (9), we obtain the change in consumption based emissions from period 0 to period t:     m m v − f Lm p ∘s v0;t ΔZ Ci ¼ f t Lm t pi;t ∘s  i;t i;t m 0 m0 0;t 0;t    m m m ¼ Δ f Lt pi;t ∘si;t vi;t þ f 0 ΔL pi;t ∘si;t vi;t þ f 0 Lm 0 Δpi ∘si;t vi;t   m m m m þf 0 L0 pi;0 ∘Δsi vi;t þ f 0 L0 pi;0 ∘si;0 Δvi  m   ¼ C Δf þ C ΔLm þ C ðΔpi Þ þ C ðΔsi Þ þ C ðΔvi Þ

ð10Þ

According to formula (10), changes in region i's consumption-based emissions can be divided into five parts: the effect of carbon emission intensity on production sectors in different regions C(Δfm), the structural effect of intermediate product input C(ΔLm), the product structure effect of regional final demand C(Δpi), the source structure effect of final demand C(Δsi), and the scale effect of final demand C(Δvi). Structural decomposition does not allow uniqueness, different ordering of factors will lead to different forms of decomposition. The results of different forms of decomposition vary. The best way to deal with this is to take the average of all decomposition methods and then analyze the results, but this is computationally onerous. The commonly used method is a average bipolar method. The forward decomposition method is used in this paper. m −1 If Lm , then: t = (I − At ) m m m m ΔLm ¼ Lm t −L0 ¼ Lt ΔA L0

1

219

ð11Þ

In this paper, we decompose the change in the Leontief inverse matrix. Taking region 1 as an example, we can break Am down into five parts: Am = Aii + Ann + A1i + Ai1 + Aij, Aii only takes the value A11 of the neutron matrix Am. It reflects the structure of the use of regional intermediate products by regional production sector 1. Ann only takes the value Aii (i ≠ 1) of the sub-matrix group Am. It reflects the structure of inputs from other regions to intermediate products in their respective regions. Ai1 takes the sub-matrix group value Ai1 (i ≠ 1) of Am. It reflects the backward industrial correlation effect of region 1. A1i is a sub-matrix group A1i (i ≠ 1) of Am which reflects the use structure of other regions for intermediate products of region i. This reflects the forward industrial correlation effect of region 1. Aij = Am − Aii − Ann − A1i − Ai1 − Aij demonstrates the industrial linkages between the production sectors in other regions. The following formula can be obtained from the above relationships: ΔAm ¼ ΔAii þ ΔAnn þ ΔA1i þ ΔAi1 þ ΔAij

ð12Þ

The following formula can be obtained according to the changes in emission intensity in China: Δf m ¼ Δf i þ Δf −i

ð13Þ

where fi represents the carbon intensity of region i and f−i is the intensity of carbon emissions in other regions of the production sector. Taking region 1 as an example: f−1 = (0,f2, ⋯fm).

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By adding formulae (11)–(13) to formula (10), we can get nine factors that affect the consumption-based emissions in different regions of China from period 0 to period t (as shown in Appendix A). The decomposition of production-based emissions is similar to the consumer- based emissions. Changes in production- based emissions in region i during period 0 to period t can be broken down into the following 30 factors (as shown in Appendix A):   Z p1;t −Z p1;0 ¼ C ðΔ f 1 Þ þ C ðΔAii Þ þ C ðΔAnn Þ þ C ðΔA1i Þ þ C ðΔAi1 Þ þ C ΔAij þC ðΔp1 Þ þ ⋯ þ C ðΔpm Þ þ C ðΔs1 Þ þ ⋯ þ C ðΔsm Þ þC ðΔv1 Þ þ ⋯ þ C ðΔvm Þ ð14Þ

3. Data Cities contribute 85% of China's total CO2 emissions. Therefore, cities are considered to be the critical areas for the implementation of adaptation and CO2 policies aimed at combating climate change. CEADs built a list of CO2 emissions from Chinese cities based on the definitions provided by the IPCC Emissions Accounting Methodology. We obtain the list of industry emissions from 30 provinces in 2007 and 2010 from the CEADs Provincial CO2 Emissions Account and Data. According to the data available and data-matching principles, China's multi-regional input-output table also comes from the CEADs database, which was announced on 23 November 2017. This table includes 42 economic sectors and five forms of final demands. This form involves 22 provinces, four municipalities, and four autonomous regions (Hong Kong, Macau, and Tibet are not included). Each “province” (here we use this word to represent all provinces, cities, and autonomous regions mentioned above) contains one primary industry, 23 secondary industries, and six tertiary industries. To analyze the comparability of the results, according to the results of MRIO in 30 provinces, we summarized these regions for eight economic zones as Northeast region, Jingjin (Beijing-Tianjin) region, Northern Coastal region, Central region, Eastern Coastal region, Southern Coastal region, Northwest region, and Southwest region. To ensure data consistency, we aggregated the input-

Fig. 1. Production-based carbon flow of eight economic zones in 2007.

Fig. 2. Production-based carbon flow of eight economic zones in 2012.

output tables and carbon emission lists into 17 departments (see Appendix B for details). 4. Results analysis 4.1. China's regional carbon emissions under two principles The embodied CO2 transfer that occurred between the eight regions in China due to production-based increased from 5479.94 Mt in 2007 to 9635.24 Mt in 2012. The share of total CO2 footprint increased by 175.8%.According to the SDA of production-based accounts, there are two sources of embodied CO2 emissions: the main source is domestic demand emission, but with the development of the economy and the rapid increase in trade flows between eight regions, the other source of external demand emissions increased from 295.69 Mt in 2007 to 3617.8 Mt in 2012. The transfers in 2007 are illustrated in Fig. 1. The colours the linking ribbons correspond to outflow regions. Here, only the representative and determinant transfers of each region are shown in Figs. 1–4. The external demand emission transfer from the Northwest Region accounted for 56.28% of the total production-based emissions in this region. Others regions with nearly three-fifths of embodied CO2 inflow mainly outsourced the increments therein to the northwest region. The increments can be interpreted as the trade volume driving the external demand supply chain. From the perspective of regional flow of external demand, Eastern coastal, Southern coastal, and Northern coastal regions made the greatest contribution to external demand emissions. The Eastern coastal region, as a region with a larger CO2 inflow, absorbed much of the CO2 from the Central region (196.78 Mt) and the Northern coastal region (153.24 Mt). The CO2 absorbed from these two regions accounted for 64.9% of the total of Eastern coastal CO2 inflow in 2007. This was followed by the Southern coastal absorption of CO2 from Southwest region (91.21 Mt). The Northern coastal region mainly absorbed CO2 from the Northeast region (77.8 Mt). All of these regions appear a phenomenon about “consumption in developed regions and pollution in developing regions”. From the perspective of China's geographical situation, the flow of external demand emissions came regions such as the more developed coastal regions. Compared with 2007, the external demand emissions from the production-based accounting of the eight regions in 2012 had increased

Z. Wang et al. / Energy Economics 83 (2019) 217–228

significantly. It grew by 4155 Mt in these five years. We can see the corresponding tendency and variation between regions in Figs. 1 and 2. The largest increment of the embodied CO2 outflow came from Central the region (689.19 Mt), which accounted for 23% of the total trade, followed by that from the Northwest region to the Central region (171.05 Mt), and the Northwest to Eastern costal region (162.65 Mt), which accounted for 22.01% and 20.88% of the total outflow, respectively. As an underdeveloped area of China, the Central and Western regions supports the economic development of the Middle East by providing high carbon-intensive and low-value-added products. A large proportion of Central and Western regional carbon emissions are induced by the consumption of goods and services consumed in developed regions of China. The share of embodied CO2 transfers that occurred between the regions due to consumption of finished goods and services in the oveall CO2 footprint in China increased from 2298.36 Mt in 2007 to 3616.85 Mt in 2012, which increased 136.5%. Fig. 3 shows that the extra demand emissions in the Eastern Coastal region, Southern Coastal region, and Jingjin region account for more than 50% of the total amount of embodied CO2 transfer in inter-regions trade in China. Jingjin region was the largest CO2 embodied emission source for other regions, accounting for 73% overall. Other bilateral transfers involved drifts from the Northern coastal region to the Northeast region and Jingjin region respectively (32%), and the Eastern Coastal region to Central, and Northwest regions respectively (25%). Regarding the sources of CO2 transfer, the Central region and the Southwest region were the main sources of CO2 outflow, and these CO2 outflows from Central regions accounted for 35% (Northern coastal region), 30% (Eastern coastal region), and 27% (Southern coastal region) of the total outflows from these regions, those from the Southwest region accounted for 25% (Southern coastal region) thereof. This shows that most of the consumption-based emission from the Jingjin region, Northern coastal and Southern coastal region came from extra-regional production. The regions that provide emissions services for the final demand in other regions are mainly the Central region and the Southwest region. In a similar way, the embodied emission transfer in 2012 exhibited the same trend compared to 2007 (a network visualization is shown in Fig. 4). The developed coastal regions are not rich in natural resources so they have to important and consume vast amounts of energy resources and goods from

Fig. 3. Consumption-based carbon flow of eight economic zones in 2007.

221

Fig. 4. Consumption-based carbon flow of eight economic zones in 2012.

large industrial regions (e.g. the Central region) to meet economic development, production, and manufacturing requirements. It is appearent that almost all of the large CO2 transfers drifted from the ennergy-rich, underdeveloped inland regions to more developed regions, as typified by embodied CO2 transfers from the Central and Northwest regions to those along the coast. Compared with results of Figs. 1–4, the differences in carbon emissions between all regions are due to the eastern coastal provinces (including Jingjin, the Central Coastal area and the Southern Coastal region) as the richest areas in China. These areas have large amounts of carbon emissions flowing from undeveloped Central and Western regions in China. More than 74% of the consumption-based carbon emissions in Jingjin stem region from other regions. About 50% of the consumption-based carbon emissions in the Eastern coastal region and the Southern coast flow from other regions. As the capital of China, more than 85% of Beijing's emissions are due to the consumption of products and services from other regions. For example, Beijing has transferred 20 Mt of carbon emissions and 21 Mt of carbon emissions from Hebei and Inner Mongolia, respectively. Accounting for 14% and 15% of all such outsourced carbon emissions. The provinces with the most massive outflow of carbon emissions are mainly in the undeveloped provinces of Western China: provinces with the largest inflow of carbon emissions lie mainly in the wealthier eastern regions. The western provinces mainly export high carbon intensive products, while importing low-carbon intensity products. Inner Mongolia is the province with the largest outflow of carbon emissions because it is one of the significant suppliers of energy products in China. In contrast, the eastern provinces import high-carbon-intensive products while producing and exporting low-carbon-intensive products. Guangdong is the province with the biggest inflow emissions. Here, we further decompose external demand emissions and domestic emissions and obtain more detailed data pertaining to embodied carbon in eight regional trade flows (Fig. 5). From Fig. 5, we can see that in the eight regions of China, the carbon emissions caused by the trade in intermediate products have been the main components of external demand emissions. From the decomposition of external demand emissions in 2007, we can see that the emissions caused by the trade in intermediate products in the Central region and the Northern Coastal region far exceeded the emissions caused by final product exports, accounted for more than 80% of the

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Fig. 5. Composition decomposition of external demand emissions and extra-regional emissions in 2007 and 2012 (unit: million tons).

total embodied emission. As can be seen from Fig. 5(b), the situation changed in 2012. The proportion of emissions caused by the trade in intermediate products in the Jingjin region and the Northwest region increased significantly, while the share from the Eastern Coastal region fell sharply. As a result, the production of intermediate products, and final product trade, in the Eastern Coastal region remained similar. Panels (c) and (d) in Fig. 5 show the decomposition of extra-regional emissions in 2007 and 2012, respectively. Similar to the decomposition of external demand emissions, direct trade is the major component of emissions outside the region. It is worth noting that, in the eight regions of China in 2007 and 2012, the Eastern Coastal region was dominated by direct trade. The emissions of direct trade in the Central region in 2012 were slightly higher than those in the Eastern Coastal region, indicating that the Central region had been actively involved in domestic trade during the past five years and developed rapidly. Next, we analyze the regional composition of external emissions and extraterritorial emissions: Fig. 6 shows the production-based emissions of China in 2007 and 2012 and the breakdown of their regional structure. As shown in Fig. 6(a), the trade in intermediate products flowing from the Northeast region to the Northern Coastal region in 2007 caused emissions of up to 65.77 Mt, accounted for 27.26% of the Northeast region's external demand emissions. This shows that trade between the Northeast and the Northern Coastal region intermediate products was large-scale. The proportion of embodied carbon in intermediate product trade between the Jingjin region and the Northern Coastal region was also high, reaching 10.84%, but the proportion of embodied carbon in the intermediate product trade between the Jingjin region and the Eastern Coastal region was the highest, reaching 17.43%. This shows that, compared with the nearby Northern Coastal region, the Jingjin region had closer trade links with the Eastern Coastal region, the most developed region in China. Similarly, the Northern Coastal region had the closest trade with the Eastern Coastal region. The emission

of intermediate products from the Northern Coastal region to the Eastern Coastal region was 132.07 Mt, accounted for 27.39% of the total embodied emissions. The emissions flow of intermediate products and final products from the Eastern Coastal region to various regions are more balanced. Among them, the greatest efflux came from the trade with intermediate products and intermediate products of the Northern Coastal region. Similar to the Eastern Coastal region, the largest flow in the Southern Coastal region from the trade between the Central region and the Northern Coastal region. It shows that the structure and direction of the trade in two regions are similar. The Central region, a major province of emissions from the production based produce 167.10 Mt in intermediate-product trade, causing emissions flow to the Eastern Coastal Region, which accounted for 29.79% of the central region's external demand. Northwest region's main trading partners are the Northeast region, the Northern Coastal region, and the Eastern Coastal region. The Southwest region is more inclined to trade with the Southern Coastal region. The trade volume of intermediate products flowing to the region is 77.42 Mt, accounting for 34.58% overall. The decomposition of the external demand structure of the production based in 2012 is shown in Fig. 6(c) and (d). Compared with the composition of external demand emissions in 2007, the direction and type of trade between regions changed in 2012. In case of the Northeast region, the emissions of intermediate products from the Northern Coastal region decreased significantly in 2012, and the proportion of embodied carbon in the intermediate products trade flowing to the Eastern Coastal region rose to rank first overall. In contrast to the Beijing and Tianjin, the region with the highest emissions resulting from trade in intermediate products in the Jingjin region had changed from the Eastern Coastal region to the Northern Coastal region. There was less variation in the Northern Coastal region. The external emissions of the Eastern Coastal region were concentrated in the Central region, and the trade in intermediate, and final products appeared to be flat. The trade in intermediate products from the Southern Coastal region to

Z. Wang et al. / Energy Economics 83 (2019) 217–228

223

Fig. 6. Decomposition of embodied carbon emissions in 2007 and 2012 (unit: million tons).

the Central region caused a slight decrease in emissions. The embodied carbon trade ratio of intermediate products flowing from the Northern region to the Northern Coastal region decreased from 21.07% to 8.42%. The embodied carbon trade in the Northwest region to the Northeast and the Eastern Coastal region also decreased, while the embodied

carbon trade to the Central region has increased to a significant extent. Therefore, the Northwest and the Central regions have become a trade partner with the Eastern Coastal region in 2012. The Southwest region added an intermediate product trade partner in the form of the Eastern Coastal region.

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From Fig. 6, we can also see that the domestic emissions caused by final demand in various regions of China in 2007 and 2012 were mainly caused by direct trade (including intermediate products and final products), while indirect trade (the trade demand indirectly caused emissions from intermediate products trade between other regions) accounted for a relatively low proportion of domestic emissions. 4.2. Structural decomposition analysis of carbon emission change under two principles Table 1 summarizes the impacts of various factors on the changes in production-based carbon emissions of each region. The results show that in the period from 2007 to 2012, the growth of production-based carbon emissions in the Northwest region was the highest, increasing to 209.41%, followed by the Southwest region，accounted for 82.50%, and other regions were stable between 50% and 60%. In this study period, the expansion of final demand in the region was the most important factor in promoting the rapid growth of production-based carbon emissions in each region. For example, the final demand led to an increase of 108.86% in the production-based carbon emissions of the Southwest region between 2007 and 2012. Similarly, it resulted in increases of 100.03%, 93.41%, and 92.99% in the production-based carbon emissions from the Northeast region, Northwest region, and Central region respectively. The effect of the scale of final demand on the four relatively well-developed regions (China's three coastal areas and the Jingjin region) weakened, but it also remained between 50% and 75%. The second factor causing a significant increase in production-based carbon emissions in all regions is the forward industrial linkage effect between the region and other regions. The change increased production-based emissions in the Jingjin region by 16.08%, which increased production-based emissions in the Northwest region by 10.44%. Changes in this factor brought positive effects to bear on production-based emissions in all regions, indicating that the trade in intermediate products had an essential influence on carbon emissions

in each region of China (the importance of forwarding industry correlation effect to the growth of carbon emission in production-based). In recent years, as China's economic growth has increased, and by undertaking manufacturing outsourcing in a developed country and developed regions, the export of intermediate products and the outflow of intermediate products from many production sectors in regions of China have grown rapidly. According to the results arising from interpretation of the multi-region input-output data used in the present research, there was a significant increase in intermediate product flows in most manufacturing sectors in regions of China in 2007 and 2012. In addition to the “electrical and optical equipment manufacturing industry,” the sectors with more significant growth in intermediate products also include two energy-intensive sectors, namely “metal and metal manufacturing” and “chemical raw materials and chemical manufacturing.” The decomposition of external demand emissions shows that the carbon emissions caused by the trade in intermediate products in China have rapidly increased in recent years and have become the main source of external demand emissions (Fig. 5(a)). The SDA results here further indicate that the trade in intermediate products is a major factor driving the increase of production-based emissions of the region. In Fig. 5(b), carbon emissions from final product trade in all regions also increased in 2012, which means that the extraregional demand for final products also has a significant impact on regional production-based carbon emissions. In SDA, the impact of final demand outside the region on regional production-side emissions is mainly reflected in the change in the source structure of the final demand. The results in Table 1 demonstrates that the source structure effect of final demand in the Northeast and Northern Coastal regions caused production-based emissions in the Jingjin region to increase by 3.77% and 3.80% from 2007 to 2012 respectively. Because the main final production exports in the Jingjin region have a significant increase in market share in the Northeast and Northern Coastal regions. The final demand in the two regions depends more on the Jingjin region, which means that they have more purchases of “CO2 emissions services”

Table 1. SDA results of changes in China's regional production-side carbon emissions from 2007 to 2012. Influencing factors

Northeast Jingjin

Northern Coastal

Eastern Coastal

Southern Coastal

Central

Northwest Southwest

Carbon emission intensity effect in the region Using structural effects of Self-produced intermediate products in the region Forward industrial linkage effect Backward industry linkage effect Using structural effects of self-produced intermediate products by other regions Industrial linkages between other regions Product structure effect of final demand in Northeast Product structure effect of final demand in Jingjin Product structure effect of final demand in Northern Coastal Product structure effect of final demand in Eastern Coastal Product structure effect of final demand in Southern Coastal Product structure effect of final demand in Central Product structure effect of final demand in Northwest Product structure effect of final demand in Southwest Source structure effect of final demand in Northeast Source structure effect of final demand in Jingjin Source structure effect of final demand in Northern Coastal Source structure effect of final demand in Eastern Coastal Source structure effect of final demand in Southern Coastal Source structure effect of final demand in Central Source structure effect of final demand in Northwest Source structure effect of final demand in Southwest The scale effect of final demand in Northeast The scale effect of final demand in Jingjin The scale effect of final demand in Northern Coastal The scale effect of final demand in Central The scale effect of final demand in Northwest The scale effect of final demand in Southwest Total change

−55.31% −25.39% 4.06% −0.22% −6.78%

−159.18% 25.96% 16.08% −1.93% 60.76%

−75.10% 50.61% 3.92% −1.40% −61.23%

−49.97% −10.98% 2.57% −0.09% −22.26%

−31.65% −3.59% 2.40% −0.86% −36.50%

−105.61% 12.75% 6.16% −0.16% −1.95%

25.99% 32.76% 10.44% −1.45% 4.04%

−90.67% 32.63% 3.04% −0.84% −12.71%

−2.97% 0.18% −0.33% 1.34% −0.37% 0.56% 2.18% 2.61% 1.54% −3.67% −0.43% −2.07% −2.01% 0.11% −1.69% 0.43% 0.19% 100.03% 5.22% 12.45% 10.66% 8.00% 5.27% 64.97%

−16.78% 1.37% −16.54% 0.84% −1.15% 0.61% 4.25% 2.82% 2.11% 3.77% 22.42% 3.80% −5.15% −1.46% −0.48% 1.00% −3.17% 11.00% 54.88% 8.94% 14.15% 12.33% 10.19% 69.02%

−2.50% 2.08% −0.07% 7.88% −2.18% 0.75% 3.01% 1.69% 1.49% −2.22% −1.03% 0.95% −2.84% −0.49% −1.17% −1.17% −1.02% 9.99% 7.99% 69.54% 12.82% 11.35% 6.06% 54.76%

−1.19% 1.78% −0.02% 1.05% −10.10% 1.15% 3.44% 2.62% 2.41% 2.11% 0.27% 1.58% 9.12% 0.32% 1.44% 0.78% 0.43% 5.44% 3.49% 7.21% 14.33% 9.11% 6.66% 52.45%

−0.09% 0.82% −0.03% 0.41% −0.75% 7.30% 1.60% 1.45% 2.57% 0.23% −1.09% −0.44% −2.44% 3.71% −3.95% −1.09% −2.53% 2.69% 2.40% 3.45% 16.65% 5.95% 12.25% 60.60%

−5.46% 1.61% −0.29% 1.29% −1.87% 1.27% 2.29% 1.92% 1.69% 0.31% −0.23% −0.15% −0.87% −0.43% 5.57% −0.59% −0.46% 4.24% 3.61% 9.41% 92.99% 9.92% 6.52% 62.45%

−8.25% 0.58% −0.61% 1.77% −1.67% 0.77% 2.32% −15.96% 1.35% −2.63% −2.57% −1.45% −2.29% −1.16% −1.17% 1.64% −1.00% 14.70% 7.67% 11.63% 13.56% 93.41% 8.91% 209.41%

−4.05% 0.65% −0.08% 0.60% −0.76% 3.77% 1.75% 1.81% −5.70% 0.65% −1.22% −0.50% −1.42% −1.56% −3.30% −0.17% 6.88% 2.17% 2.46% 3.84% 12.73% 5.60% 108.86% 82.50%

Note: The percentage in the table refers to the proportion of the carbon emissions increase caused by each factor during a certain period to the total initial carbon emissions.

Z. Wang et al. / Energy Economics 83 (2019) 217–228

from the Jingjin region. This caused the increase of production-based carbon emissions in the Jingjin region. While the growth in the demand scale in the Northeast and Northern Coastal regions also further increased production-based emissions in the Jingjin region, affecting 11.00% and 8.94%, respectively. In addition, for the Jingjin region, Northern Coastal region, Central region, Northwest region, and Southwest region, the using structural changes of self-produced intermediate products in the region also caused a significant increase in production-based emissions, which means that, in recent years, the intermediate products input structure in several regions has a trend towards high-carbonization. From the perspective of the international environment, these high-carbon changes in the domestic intermediate products input structure are affected by the international division of labor. In addition to the factors above, the changes in backward industrial linkages, and industrial linkages among other regions have generally increased production-based carbon emissions, but their effects have been relatively small. The most important factor in curbing the increase in productionbased carbon emissions of each region is the decline in the emission intensity of the production sector. During the entire study period, the decrease in the carbon intensity of the production sector in Beijing and Tianjin reduced production-based carbon emissions in the region by 159.18%. The contribution rate of the carbon intensity factor in the Central Region production sector is −105.61%. This means that the longterm efforts of these regions to improve energy efficiency have made positive contributions to reducing carbon emissions. However, the carbon intensity effect of the production sector in the Northwest region has a positive impact on changes in the production-based emissions, indicating that the production sector in the region needs to reduce the carbon intensity further in its production sector. Also, changes in the structure of the use of intermediate products in other regions, the structure of final demand products in other regions, and the source structure of final demand in other regions generally contribute to the reduction of production-based emissions from the region, but their impact is limited. The previous analysis of the composition of carbon emissions shows that the majority of consumption-based carbon emissions from within the regions, so it can be predicted that internal production technologies and economic factors are the main reasons affecting changes in the regional consumption-based emissions. The SDA results are shown in Table 2. During in this study period, the significant increase in carbon emissions of each region is mainly caused by the rapid expansion of final demand in the region. The increase in final demand in the region increase the consumption-based emissions in the Northwest region to 213.65%. The pulling effect of this factor varies from 97.50% to 213.65%. In addition, changes the structure of self-produced intermediate products in the region have also increase carbon emissions in most regions. Only those factors in Northeast region, Eastern Coastal region, and Southern Coastal region have negative effects. Similar to production-based carbon emissions, changes in the product structure

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of the final demand in the region have also led to an increase in consumption-based- emissions. Only the two most developed regions in China (the Jingjin region and the Eastern Coastal region) are exceptions to this. In addition, based on China's rapid economic development, the inflow of intermediate products in developed areas of China in the less developed areas caused by emissions are included in the developed regions of China's consumption-based emissions account. As a result, the corresponding changes in the forward and post-to-industry linkages between developed regions of China and other regional economies have also caused an increase in consumption-basedemissions in the regions of China. Changes in the forward industry linkages between regions and other regions are important factors that increase the emissions from the consumption-based of each region. Since most of the current domestic final demand is still met by domestic production, the reduction in CO2 emission intensity in the production sectors in all regions is also the most important factor in effectively restraining the growth of China's consumption-based carbon emissions. The reduction in emission intensity in the production sector reduced the consumption-based carbon emissions of Northern Coastal region, Central region, and Southwest region by 63.18%, 76.71%, and 68.48% respectively. This is similar to the SDA result of production-based emissions. During this study, the decline in emissions intensity in the production sectors in other regions also reduced the consumption-based emissions in the region. As the decomposition results pertaining to carbon production-based emissions, changes in the structure of the source structure of final demand in the region only have a small effect on the consumption-based emissions of the region: because the region will select it where production technologies are generally lower-carbon than the region as a source of demand. Also, because the emissions caused by the purchase of intermediate products are included in the consumption-based emissions of the region, the backward industrial linkage effect between the region and other regions has also led to a general reduction in consumer-side emissions in all regions of China. In addition to the above factors, the effect of changes in the use of self-produced intermediate products by other regions and industrial linkages among other regions has little impact on consumption-based carbon emissions of the region. It is means that the growth of emissions in each region is mainly driven by the growth of the final demand scale and the backward industry linkage effect, while the production structure of other regions, their industrial linkages, and source structure effect of final demand in the region have impact thereon. 5. Conclusions and policy recommendations The domestic demand emissions are the primary source of China's regional production-based emissions, but external demand emissions have grown rapidly. The composition of the regional production-based emissions in China has changed to a significant extent. The proportion of foreign demand emissions in total emissions in the Jingjin region

Table 2 SDA results of consumption-based carbon emissions from 2007 to 2012. Influencing factors

Northeast

Jingjin

Northern coastal

Eastern coastal

Southern coastal

Central region

Northwest

Southwest

Carbon emission intensity effect in the region Carbon emission intensity effects in other regions Using structural effects of Self-produced intermediate products by the region Forward industry linkage effect Backward industry linkage effect Using structural effects of self-produced intermediate products by other regions Industrial linkages among other regions Product structure effect of final demand in the region Source structure effect of final demand in the region Final demand effect Total changes

−36.72% −24.05% −17.38% 10.34% −17.03% −0.95%

−31.14% −36.90% 14.94% 15.33% −10.71% 2.29%

−63.18% −17.93% 42.50% 1.06% −30.23% −3.75%

−21.53% −26.12% −4.31% 9.65% −5.14% −1.92%

−16.93% −27.21% −3.42% 8.36% −30.49% −1.94%

−76.71% −17.76% 10.76% 7.08% −4.18% −0.56%

17.88% −50.84% 25.52% 15.44% −24.55% 0.01%

−68.48% −23.73% 30.61% 9.24% −6.25% −3.13%

−7.22% 12.37% −4.72% 163.78% 78.42%

−13.88% −12.37% −1.20% 113.70% 40.07%

0.21% 15.85% 0.03% 131.83% 76.39%

−4.17% −14.25% −2.38% 97.50% 27.32%

−2.62% 17.87% −1.93% 114.44% 56.14%

−7.78% 11.68% 1.75% 155.12% 79.40%

−16.72% 5.03% −1.72% 213.65% 183.70%

−8.88% 7.75% 1.84% 164.78% 103.75%

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has increased from 51.74% to 59.90%, becoming the only region with a ratio of more than 50%. The proportion of external demand emissions in other regions has declined to varying degrees. The largest decline is found in the Northern Coastal areas, from 47.25% to 31.92%. From the perspective of the consumption-based emissions, the growth of consumption in the eight regions is similar to the increase in productionbased emissions, but the largest increase occurs in the central region, with an increase of 934.76 Mt. On the other hand, the fastest growth in the northwest region reaches 183.7%, followed by the southwest region in which the growth rate reaches 103.75%. The above conclusions have important implications for establishing a fair and effective distribution of provincial responsibility for emission reductions. First, the current carbon emissions can be traded from other regions to meet demand, so the productionbased, carbon emissions were significantly decreased, which undoubtedly contributed to the “carbon leakage” and a weakening of the effect of enacted emission reduction policy. Second, it is unfair to account on the premise of production based emissions only, because a large amount of production emissions and their growth in some less-developed areas are caused by consumer demand in other regions, especially in developed regions. Both producers and consumers are creators of carbon emissions, and it should be responsible for climate change. Finally, in the case of geographical separation of production and consumption activities, it is difficult for the production-based emission targets to enable consumers and production companies to understand the impact of the consumption and investment demand of their final products or intermediate products on carbon emissions in other regions, and it is difficult to guide carbonization of consumption models and production modalities. Therefore, when considering the distribution of emission reduction responsibilities, we should consider the issue of domestic emissions, emissions, and consumer responsibilities, thus promoting the fairness and effectiveness of carbon emission reductions. As far as the international level is concerned, China as a large exporter, adopts a consumer-side accounting programme or considers comprehensive responsibility-sharing among producers and consumers. It is useful for reducing China's carbon emission responsibilities. However, it also means that, in the future, China will not be able to transfer large amounts of emissions to other countries through trade as developed countries do today. Therefore, in the future, there needs to be more attention paid to the growth in emissions from the consumer side. The research results have important policy implications for China's underdeveloped regions coordinating trade and domestic energy-saving, emission reduction, and low-carbon economic development. Whether from the angle of absolute quantity or the growth rate, external demand emissions exert an signnificant influence on production-based carbon emissions from the Northwest region. Under the conditions of an open economy, the Northwest region needs to change its extensive growth, which has come at the expense of resources and environmental cost, for export growth. Then the Northwest region needs to promote sustainable and low-carbon trade development. The low-carbon economic transition and ecological betterment of society should be aimed at enhancing sustainable, low-carbon trade development, changing the extensive growth model. At the same time, it is necessary for the Western region to strength the technical cooperation with developed regions and introduce more advanced low-carbon technologies and environmental services. The empirical results of SDA show that, from 2007 to 2012, the expansion of final demand is the most important factor promoting the rapid growth of regional carbon emissions. The second major factor leading to a significant increase in production- based carbon emissions is the forward industrial linkage effect between each region. For the Jingjin region, the Northern Coastal area, the Central area, the Northwest region, and the Southwest region, regional

structural changes in the self-produced intermediate products have also led to a significant increase in production- based emissions during the study period. It means that there has been a trend towards “high carbonization” in recent years. On the contrary, the decline in the carbon intensity of the production sector is the most important factor inhibiting the increase in the production based emissions. During the study period, the most important reason for the increase in the consumer side carbon emissions in each of the regions in China was the expansion of final demand, followed by the changes to the input structure of regional production departments. Effectively restraining the production-based and the consumption-based emission reduction in the economic regions is the most important factor when seeking to reduce carbon emissions. It can be seen from the conclusion that reducing carbon emission intensity in production departments is an effective means with which to reduce carbon emissions and consumption based carbon emissions. China remains in a stage of rapid development with significant industrialization and urbanization underway. In this phase, energy demand is growing rapidly, and energy structures will be difficult to change in the short-term. Therefore, further reducing the emission intensity of the production sector is still a feasible plan, the implementation of which, will result in meeting carbon emission reduction targets. Although China's carbon intensity has declined significantly in recent years, compared to more-developed countries and even some other developing countries, China's carbon intensity remains high, and the potential to reduce the intensity of carbon emissions remains high. Recent studies have shown that the decline in carbon emission intensity in China in recent years is due to a decline in energy intensity. As a result, China needs to accelerate the adoption of energysaving technologies to further to reduce carbon emission intensity and carbon emissions in China's production and consumption based in the long-term. For the medium-term, China should aim to optimize her energy structure by reducing the proportion of coal consumption and increasing the proportion of oil, gas, and renewable energy consumption. These are undoubtedly necessary measures for carbon reduction. Acknowledgement This study is supported by the National Science Fund for Distinguished Young Scholars (Reference No. 71625003), Yangtze River Distinguished Professor of MOE, National Key Research and Development Program of China (Reference No. 2016YFA0602504), National Natural Science Foundation of China (Reference No. 91746208, 71573016, 71403021, 71521002, 71774014, 71804010), Humanities and Social science Fund of Ministry of Education of China (Reference No. 17YJC630145), National Social Science fund of China (Reference No. 17ZDA065), International Graduate Exchange Program of Beijing Institute of Technology. Appendix A. See Table A1

Table A1 Decomposition of factors affecting the change of carbon emissions in region 1. Symbol Change in production -based carbon emissions ΔZp1

C(Δf1) C(ΔAii) C(ΔAnn)

C(ΔA1i)

Implication Carbon emission intensity effect of production sector in Region 1 The effect of Region 1 on the use of self-produced intermediate products Using the structural effects of self-produced intermediate products in Region 1 by other regions Forward industry linkage effect between

Z. Wang et al. / Energy Economics 83 (2019) 217–228

Appendix A. Supplementary data

Table A1 (continued) Symbol

Change in consumption -based carbon emissions ΔZC1

Implication

Region 1 and other regions C(ΔAi1) Backward industry linkage effect between Region 1 and other regions C(ΔAij) Industrial linkages among other regions C(Δp1) Product structure effect of final demand in Region 1 C Product structure effects of final (Δp2−m) requirements in other regions C(Δs1) Source structure effect of final demand in Region 1 C Source structure effect of final demand in (Δs2−m) other regions C(Δv1) The scale effect of final demand in Region 1 C Scale effect of final demand in other regions (Δv2−m) C(Δf1) Carbon emission intensity effect of production sector in Region 1 C(Δf−1) Carbon emission intensity effects of production sectors in other regions C(ΔAii) Using structural effects of Self-produced intermediate products by Region 1 C(ΔAnn) Using structural effects of self-produced intermediate products by other regions C(ΔA1i) Forward industry linkage effect between Region 1 and other regions C(ΔAi1) Backward industry linkage effect between Region 1 and other regions C(ΔAij) Industrial linkages between other regions C(Δp1) Product structure effect of final demand in Region 1 C(Δs1) The source structure of final demand in Region 1 C(Δv1) The scale effect of final demand in Region 1

Appendix B. See Tables B2 and B3

Table B2 The abbreviated name of each sector. Abbreviation

Sector

FF MM FP TG WP PP PI NM SP MI TE EE OM PS CI TS OT

Agriculture, forestry, animal husbandry and fishery industry Minerals mining and dressing Food and tobacco industry Textile and garments industry Wood processing and furniture manufacturing Paper printing and educational and sports goods industry Petrochemical industry Non-metallic mineral products industry Smelting and pressing of metals Machinery industry Transportation equipment manufacturing industry Electrical and electronic equipment manufacturing industry Other manufacturing industry Power and steam hot water, gas and tap water production and supply Construction industry Transportation and storage services Others

Table B3 The provinces included in the eight economic zones. Code Name of zones

Regions included

1 2 3

Heilongjiang, Jilin, Liaoning Beijing, Tianjin Hebei, Shandong

4 5 6 7 8

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Northeast region Jingjin region Northern coastal region Eastern coastal region Southern coastal region Central region Northwest region Southwest region

Jiangsu, Shanghai, Zhejiang Fujian, Guangdong, Hainan Shanxi, Henan, Anhui, Hubei, Hunan, Jiangxi Neimenggu, Shanxi, Ningxia, Gansu, Qinghai, Xinjiang Sichuan, Chongqing, Guangxi, Yunnan, Guizhou, Xizang

Supplementary data to this article can be found online at https://doi.org/10.1016/j.eneco.2019.06.023.

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