key: cord-0943348-ko05t9y5
authors: Zhu, Bangzhu; Su, Bin; Li, Yingzhu; Ng, Tsan Sheng
title: Embodied energy and intensity in China’s (normal and processing) exports and their driving forces, 2005-2015
date: 2020-08-29
journal: Energy Econ
DOI: 10.1016/j.eneco.2020.104911
sha: 00e01bc699092957542723436eab32b23dae57bf
doc_id: 943348
cord_uid: ko05t9y5

International trade has important impacts on a country’s energy consumption. This paper first uses the time-series (2005-2015) extended input-output database to study China’s embodied energy and intensity in both normal and processing exports. Structural decomposition analysis (SDA) is then applied to analyze the driving forces behind the embodiment changes. The empirical results show that China’s energy embodied in both normal and processing exports first increased in 2005-2008, dropped in 2009 due to the global financial crisis, and then rose again after 2009, and finally dropped in 2014-2015. The embodied energy in trade as a percentage of total energy consumption in China was relatively stable before and after the global financial crisis, at around 28% over the 2005-2008 period, and 22% over the 2009-2015 period. The contribution of the aggregate embodied intensity (AEI) of exports to China’s aggregate energy intensity dropped from 30% in 2005 to 21% in 2015. Among China’s trading partners, the United States, Japan and Korea together accounted for around half of China’s embodied energy and AEI in exports in 2005, but their shares dropped to only one third in 2015. Energy efficiency improvement played the key role in reducing the embodied energy and intensity in China’s exports. Similar analysis can be applied to other regions and indicators.

With global economic growth in the last few decades, the total energy consumption by all countries have increased by around half, from 6,268 Million tonnes of oil equivalent (Mtoe) in 1990 to 9,384 Mtoe in 2015 (IEA, 2017) . Meanwhile, merchandise trade expanded by around four times, from USD 3,490 billion in 1990 to USD 16,537 billion in 2015 (WTO, 2018 . In the last two decades, many studies have examined how international trade affects a country's energy consumption and related carbon emissions or -energy/emissions embodied in trade‖, and results in -energy/carbon leakage‖ between developed and developing countries.

For example, embodied emissions in trade were found to increase from 4.3 Gt CO 2 to 7.8 Gt CO 2 over the period 1990-2008 (Peters et al., 2011) . Some countries and international organizations, e.g. the United Kingdom (UK, 2019) and the Organisation for Economic Cooperation and Development (OECD, 2019) , have started monitoring these embodiment flows and resulting consumption-based accounting, and discussed their implications to future energy and climate policy designs.

As the largest energy consumer and carbon emitter in the world, China has put forward several significant efforts to reduce energy consumption and carbon emissions. See, for example, the energy and emission target settings and accomplishments during its 11 th Five

Year Plan (2006) (2007) (2008) (2009) (2010) and 12 th Five Year Plan (2011) (2012) (2013) (2014) (2015) periods (Price et al., 2011; Hu, 2016) . In November 2014, -China's Energy Development Strategy Action Plan‖ was released by the Chinese government to provide guidelines for its energy developments during the 12 th (2011) (2012) (2013) (2014) (2015) and 13 th (2016-2020) Five Year Plans (GOSC, 2014) . As the world's manufacturing factory, significant amounts of China's energy/emissions are embodied in its exports. Consequently, China's energy efficiency improvements over time, especially during the 11 th Five Year Plan (2006) (2007) (2008) (2009) (2010) period, have greatly helped to reduce the embodied energy/emissions in its exports. It is important for China to monitor the changes of these embodiment flows and analyze the driving forces that brought about the changes.

In the literature, there are many studies on China's embodied emissions at country level -3 -few. Some studies have calculated China's energy embodied in exports using national I-O tables for selected years, such as Kahrl and Roland-Holst (2009) for years 1997 , 2002 and 2004 Xu et al. (2009 Xu et al. ( ) for year 2002 Xu et al. ( and 2007 Liu et al. (2010) for years 1992 , 1997 , 2002 and 2005 Xie (2014) for year 1992 , 1997 , 2002 Tang et al. (2016) for year 1997 , 2002 Yan and Su (2020a) for year 2010, 2012 and 2015. Other studies use multi-region I-O tables in the calculation for selected years. For example, Cui et al. (2015) use the GTAP database for year 2001 , 2004 Gao et al. (2018) , Tao et al. (2018) and Zhang et al. (2019) China's international exports have an interesting feature that half are processing exports (see Figure 1 ). In this study, processing exports are defined as the exports of the end products of assembling/processing imported intermediate inputs that are exempted from Chinese tariff and eventually sold overseas. On the other hand, normal exports are ordinary exports and are distinct from processing exports . The energy/emissions embodied in per unit of processing exports are found to be much lower than those embodied in per unit of normal exports Jiang et al., 2015a) . However, standard I-O tables do not differentiate processing exports from normal exports. Therefore, it is necessary to construct -new‖ extended I-O tables and models, which is far more complicated than carrying out national and multi-regional embodiment analysis. As revealed in the report by WTO and IDE-JETRO (2011), some form of processing trade can be found in over 130 countries.

In the literature, there are a few studies using such extended I-O framework for China's embodied emission analysis, including Dietzenbacher et al. (2012) for year 2002, ) for year 1997 and 2002 , Xia et al. (2015 for year 2002 , Su and Thomson (2016 for year 2006 -2012 , Weitzel and Ma (2014 , Jiang et al. (2015b) , and 1 See Su and Ang (2012a) and Wang et al. (2017a) for reviews of SDA studies applied to energy and emissions.

-4 - Liu et al. (2017) for year 2007, Yan et al. (2020) for year 2002 -2012 , Zhang et al. (2020 for year 2012. However, there are only two studies using the extended framework on China's embodied energy, i.e. Jiang et al. (2015a) and Jiang et al. (2017) for year 2007. Among these studies, only three studies Xia et al., 2015; Su and Thomson, 2016) further apply the SDA technique to investigate the driving forces behind the embodiment changes in normal and processing exports.

In embodiment analysis, both the total embodiments and the embodiment intensities are useful to support policy makings. Most of the previous embodiment studies focus on the total embodiment, such as total embodied energy or emissions. Recently, propose the aggregate embodied intensity (AEI) concept by defining the AEI indicator as the ratio of embodied energy/emissions to embodied value added using the I-O framework. The AEI can be defined at the aggregate, final demand and sectoral levels or by transmission layer to analyze the relationship between energy/emissions and value added (or GDP) from the demand perspective. At the national level, the AEI in aggregate is equivalent to the aggregate intensity (AI) indicator. The AEI indicator at the higher level can be represented as a weighted sum of the AEI indicators at the lower level. It would be valuable to study the different AEI values of normal exports and processing exports in China using the extended I-O framework. 2 This paper is an attempt to analyze China's embodied energy and intensity in normal and processing exports using the time-series (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012) (2013) (2014) (2015) of Chinese extended I-O tables, and further investigate the driving forces behind the embodied energy/intensity changes using the SDA frameworks. The contributions of this paper include: (1) the national AEI framework has been extended from traditional I-O model to extended I-O model with normal/processing exports; (2) it gives the time-series (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012) (2013) (2014) (2015) estimates of China's embodied energy in normal and processing exports by sector and major trading partners; (3) it investigates the driving forces to the changes of embodied energy in normal and processing exports in China using the additive SDA framework; (4) it shows the times-series (2005) (2006) (2007) (2008) (2009) (2010) (2011) (2012) (2013) (2014) (2015) estimates of China's AEI indicators for normal and processing exports by sector and major trading partners; and (5) it analyzes the driving forces to the changes of AEI values in normal and processing exports in China using the multiplicative SDA framework.

2 For example, the AEI of emissions in exports are found to be higher than the national AI of emissions in China , India (Zhu et al., 2018) and Singapore (Su and Ang, 2020) . Recently, the national AEI framework has been further extended to the multi-region AEI framework within a country Zhou et al., 2020) .

The remaining sections of the paper will be organized as follows. Section 2 demonstrates how to derive embodied energy and intensity under an extended I-O framework and obtain the driving forces using the additive/multiplicative SDA frameworks. Section 3 presents the empirical study on China's embodied energy from 2005 to 2015. The final section summarizes the main findings and draws some key conclusions of the study.

Traditional I-O tables complied by the Chinese National Department of Statistics are based on the competitive imports assumption, and do not differentiate the normal exports and processing exports. The study by firstly shows that the competitive imports assumption can in general overestimate a country's embodiment in trade and the noncompetitive imports assumptions is advocated in embodiment studies. To support the analysis required in this paper, the extended I-O table with processing trade and non-competitive imports assumption is used as shown in Table 1 Dietzenbacher et al., 2012; Weitzel and Ma, 2014; Xia et al., 2015; Jiang et al., 2015a Jiang et al., , 2015b Su and Thomson, 2016; Jiang et al., 2017; Liu et al., 2017 f representing the energy consumption per unit of industry value added for domestic use/normal exports and processing exports respectively, the total amount of energy use in production can be formulated as 

where v and pe v are the vectors of value added for total production and processing exports, 

''0ˆˆ0 

is the additive total final demand (export) effect in the period between 1 t and 2 t ( 12 tt  ). Using the LMDI-I approach Ang, 2015; Su and Ang, 2012a) , the effects in Eqs. (4-5) can be calculated as following 

is country/region k 's additive final demand (exports) regional share effect. Detailed comparisons of different decomposition techniques in the context of additive SDA can be found in Su and Ang (2012a).

The AEI indicators proposed in can help the researchers and policy makers to better understand the relative energy/emission performance at different levels from the demand perspective. Similar as Eq. (3) competitive imports assumption, the total GDP value can be calculated using the production approach as 3

dd dp dp pe dd dd dp d ne dp pe 

is the value added embodied in processing exports.

With the AEI definition given in , the AEI in normal exports ( ne AEI ) and processing exports ( pe AEI ) can be formulated as following ,, ,

3 According to United Nations (1993), there are three approaches to calculate the GDP value, i.e. production, income and expenditure approaches. Both the production and expenditure approaches are commonly used in the I-O analysis, see Su and Ang (2015) for example.

Journal Pre-proof ). With Eqs. (3) and (11) 

where w  is the share of valued added embodied in special final demand, and d AEI is the AEI in domestic final demand. The contribution of specific final demand to the AEI in aggregate can be calculated as   w AEI AEI  , which is the same as their share of embodied energy in special final demand.

Multiplicative SDA is more suitable to analyze the relative changes in energy intensity.

Using the general formula of multiplicative SDA in Su and Ang (2015) , the changes of AEI 

is the multiplicative final demand (export) regional share effect in the period between 1 t and 2 t ( 12 tt  ). Using the LMDI-I approach Ang, 2015; Su and Ang, 2012a) , the effects in Eqs. (15a) and (15b) can be calculated as following 

where , 1 2 ( , ) eint, i D t t is sector i th energy intensity change effect, and i w is the weighted share obtained from the attribution analysis.

The 2018 4 For the embodied energy/emission flows, two commonly used approaches are EEBT and MRIO approaches (Peters, 2008; Su and Ang, 2011) . However, the EEBT approach is more convenient for trade policy analysis, while the MRIO approach can capture the feedback effects but is much more complicated and includes more uncertainties in constructing the global MRIO tables. This paper uses the EEBT approach when measuring the embodied energy in China's processing and normal exports to world countries. 

The time-series extended I-O tables enables the embodied energy in normal and processing exports for the 2005-2015 period to be obtained using Eq. (3). The embodiment results for normal and processing exports, as well as the percentage of embodied energy in total exports against China's total energy consumption, are given in Figure 2 . Embodied energy in normal/processing exports by sector and by trading partner are given in Figure 3 and Figure 4 , respectively (detailed sectoral and regional names are given in Tables A1 and   A2 in Appendix A). For ease of illustration, the sectoral results in Figure 3 are aggregated into 20 sectors, and the bilateral regional results in Figure 4 are also aggregated into 20 regions. 5

The overall trend in Figure 3 shows that the embodied energy in both normal and Some interesting patterns are observed from the results at the sectoral level. For normal exports as shown in the Figure 3(a) , the major shares of embodied energy came from sectors -S13-Basic metals‖ (16%-26%), -S06-Textiles, wearing apparel, leather and related products‖ (12%-14%), -S10-Chemicals and pharmaceutical products‖ (10%-11%), and -S17-Machinery and equipment‖ (8%-11%). The share of sector -S13-Basic metals‖ dropped significantly around the global financial crisis, from 26.5% in 2008 to only 13.9% in 2009; in contrast, the share of sector -S06-Textiles, wearing apparel, leather and related products‖ and sector -S17-Machinery and equipment‖ relatively increased.

For processing exports as shown in Figure 3 (b), the embodied energy was mainly from sectors -S15-Computer, electronic and optical products‖ (34%-40%), -S16-Electrical equipment‖ (14%-19%), and -S06-Textiles, wearing apparel, leather and related products‖ (6%-12%). Different from the processing exports, the share of embodied energy in these major sectors did not change that much during the global financial crisis. Overall speaking, there was a shift from light manufacturing to equipment manufacturing, especially for -S16-Electrical equipment‖ and -S17-Machinery and equipment‖.

It is also interesting to find some trends in China's embodied energy in bilateral trade.

For normal exports as shown in the Figure 4 (a), the major shares of embodied energy were with the United States (17%-25%), Japan (7%-12%) and Korea (6%-9%). Most of the regional share decreased in 2009 with a time lag, but the share of the United States where the global financial crisis originated dropped earlier from 2007. For processing exports as shown in the Figure 4(b) , the major shares of embodied energy were with the United States (19%-30%), Japan (7%-12%), Korea (5%-6%) and Germany (3%-6%). Overall speaking, there were significant shifts from the United States, Japan and Korea to the other economies in the rest of the world.

The changes in embodied energy as discussed in Section 3.2 were driven by many factors, such as the energy efficiency improvement/deterioration and export demand increase/decrease. To better understand the driving forces behind the changes in embodied energy, additive SDA was applied using Eqs. (6-10). The chaining approach was adopted to ). It was found that more than 75% of the total energy intensity effects for processing exports came from energy efficiency improvements in , vd f . Among the 36 sector classifications, the largest contributing sectors for energy efficiency improvement were sector -S13-Basic metals‖, sector -S10-Chemicals and pharmaceutical products‖, sector -S21-Electricity, gas, water supply‖ and sector -S24-Transportation and storage‖. Their energy efficiency improvements accounted for more than 70% of the total energy efficiency improvements during the 2005-2015 period. Particularly, sector -S13-Basic metals‖ alone contributed to around 38% of the total energy efficiency improvement.

However, these major contributing sectors also experienced some occasional increases in energy intensity, such as the sector -S13-Basic metals‖ in -2008 and 2012 , -S21-Electricity, gas, water supply‖ in 2007 -2008 . can be obtained using the Eq. (11). The aggregate embodied intensity (AEI) defined in Section 2 to evaluate the contribution of exports to embodied energy relative to their contributions to value added (or GDP) can be calculated using the Eq. (14). The AEI values for normal and processing exports and their contributions to national aggregate intensity (AI) in China are given in Figure 6 . The share of embodied value added in exports by major sectors and major trading partners are given in Figure 7 and Figure 8 respectively (detailed sectoral and regional names are given in Tables A1 and A2 in Appendix A). Similar to Figures 3 and 4 , the sectoral and regional classifications were grouped into 20 sectors/regions for ease of illustration.

From Figure 6 , the over trend shows that the AEI in normal exports and processing exports persistently decreased over the entire period of study. For example, the AEI in normal As explained in , the AEI in exports can be represented as the weighted sum of the sectoral AEI, where the weights are the share of sectoral embodied value added. From normal exports as shown in Figure 7 (a), the value added or GDP was mainly generated from the demands in sectors -S06-Textiles, wearing apparel, leather and related products‖ (17%-20%), -S17-Machinery and equipment‖ (8%-11%), -S13-Basic metals‖ (6%-12%), and -S10-Chemicals and pharmaceutical products‖ (6%-8%). The global financial crisis decreased the share in sector -S13-Basic metals‖ significantly from 11.9% in 2008 to 6.0% in 2009, leaving the share in sector -S06-Textiles, wearing apparel, leather and related products‖ and -S20-Other manufacturing‖ relatively increased.

For processing exports as shown in Figure 7 (b), the value added or GDP was mainly generated from the demands in sectors -S15-Computer, electronic and optical products‖ (41%-49%), -S06-Textiles, wearing apparel, leather and related products‖ (7%-15%), and -S16-Electrical equipment‖ (11%-15%). Among these major sectors, there was a shift from J o u r n a l P r e -p r o o f Journal Pre-proof -17 --S06-Textiles, wearing apparel, leather and related products‖ to sectors -S15-Computer, electronic and optical products‖ and -S16-Electrical equipment‖.

From Eqs. (12) and (13), the AEI in exports can also be represented as the weighted sum of the AEI in bilateral trade with the trading partners, where the weights are the share of regional embodied value added. As shown in Figure 8(a) , the major contributors to value added or GDP embodied in normal exports were from bilateral trade with the United States (19%-27%), Japan (8%-14%) and Korea (5%-7%). Most of the regional share decreased after the global financial crisis, but the share of the United States dropped earlier from 24.0% in 2007 to 21.7% in 2008. Figure 8(b) shows that the major contributors to value added or GDP embodied in processing exports were from bilateral trade with the United States (20%-31%), Japan (7%-12%), Korea (5%-6%) and Germany (3%-6%). Similar as the embodied energy, there was significant shifts from the United States and Japan to other economies in the rest of the world.

The AEI changes discussed in Section 3.4 were the net impact of many driving factors, although the energy efficiency improvement is supposed to be the key factor. To isolate the impacts of individual driving forces, multiplicative SDA was applied using Eqs. (16) (17) (18) (19) . The chaining approach was adopted to minimize the temporal aggregate effect in the SDA results (Su and Ang, 2012b) . For ease of illustration in the figures, the logarithm of the multiplicative decomposition results for normal and processing exports are shown in Figure   9 (a) and Figure 9 (b), respectively.

The overall patterns behind the driving forces to AEI changes were quite similar for normal and processing exports throughout the studying period. Among the four driving factors discussed in Eqs. (16) (17) (18) (19) , the largest contributor was the energy efficiency improvement, followed by the production structure optimization. The AEI of normal exports declined substantially in 2009 mainly due to the combined energy intensity effect and final demand sectoral effect, whereas the AEI of processing exports declined smoothly over time as the production structure effect largely offset the energy intensity effect in 2009. Energy efficiency improvements among 36 sectors were found to be similar to the results of the additive SDA in Section 3.3. The largest four contributing sectors were -S13-Basic metals‖, -S10-Chemicals and pharmaceutical products‖, -S21-Electricity, gas, water supply‖ and -S24-Transportation and storage‖. Their energy efficiency improvements helped to reduce around 30% of the AEI of normal exports and processing exports during the 2005-J o u r n a l P r e -p r o o f Journal Pre-proof -18 -2015 period. Particularly, sector -S13-Basic metals‖ alone contributed to around 16% of AEI reduction. The largest energy efficiency improvements by sector -S13-Basic metals‖ happened in periods 2008-2009, 2011-2012 and 2014-2015 .

This paper is an extension of the time-series study on embodied emissions in process trade in Su and Thomson (2016) and the national AEI framework proposed in . Su and Thomson (2016) is the first study to provide the time-series estimates of embodied emissions only in China's normal/processing exports for 2006-2012. In contrast, this paper analyzes not only embodied energy but also embodied energy intensity in normal/processing exports for 2005-2015. The embodied energy and embodied emissions analyzed in these two studies are also not the same. Their differences mainly come from the fuel mix in final energy consumption by sector and emission intensity in power generation due to generation efficiency and generation mix . There is no relationship between the AEI in exports and national AEI or sectoral AEI reported in previous studies, until the national AEI framework developed in . This study (Section 2. 

This paper is an extension of the studies by Su and Thomson (2016) and . It analyzed China's embodied energy and intensity in both normal and processing Prosperous international trade has brought countries closer than before, enhancing different countries' specialization areas in the regional and global supply chains, and also contributed to reducing unbalanced resource distributions among world countries. At the same time, the -leakage‖ phenomenon through embodied energy in trade will continue, and most likely will increase. With a global thirst for energy, it is of key importance to evaluate the costs and benefits of such leakages, especially when designing national energy saving policies and studying the energy security issues for a country, especially during the US-China trade war and COVID-19 periods. One of the key findings from this paper is that China contributed around 500-800 Mtce of energy each year during the period 2005-2015 through its exports (especially the normal exports) to other countries. As developed countries are the major end uses of embodied energy from developing countries, it is essential for developed countries to help energy conservation in the developing countries through technology transfer and investment in energy efficiency technologies. Ultimately, this will also help reducing the global carbon emissions, and combating the climate change issues.

International trade not only drives the energy use in the production, but also help creates the value added (or GDP) to the county. From demand side, the aggregate embodied intensity (AEI) of energy in trade can be used to evaluate the relative effectiveness of energy consumption and value added (or GDP) generation. The empirical results of this paper show that the AEI in normal exports and processing exports together contributed to around 22% of national aggregate energy intensity after global financial crisis. As the AEI in trade is the weighted sum of the sectoral AEI, the largest three sectors, i.e. sector -S06-Textiles, wearing J o u r n a l P r e -p r o o f -20 -apparel, leather and related products‖, -S13-Basic metals‖ and -S17-Machinery and equipment‖, accounted for around 40% of the AEI in normal exports; in contrast, the largest three sectors, i.e. -S06-Textiles, wearing apparel, leather and related products‖, -S15-Computer, electronic and optical products‖ and -S16-Electrical equipment‖, contributed to more than 60% of the AEI in processing exports. To further reduce the AEI in trade, Chinese government can focus on these essential sectors through improving the energy efficiency and/or enhancing the value chain in the upstream industries . This will become increasingly important when designing China's international trade policy with world countries, especially during the post COVID-19 period. Su and Thomson (2016) adopted the SDA technique to understand the driving forces behind the embodiment changes happened. This is an area deserving of further investigation as some forms of processing trade can be found in many countries/regions. Taking China for example, processing exports mainly happen in some eastern regions, like Guangdong, Fujian and Jiangsu provinces. To better support the regional development and policy making, it is valuable to use the extended I-O framework with processing trade in the empirical analysis.

Some possible future research includes (a) applying the similar analysis framework to other J o u r n a l P r e -p r o o f -21 -indicators, such as GHG emissions, water and air pollutant; (b) disaggregating China as a whole into different regions to capture the regional supply chain and feedback effects Ang, 2011, 2014b) and/or including China into the global supply chain Wang et al., 2017b; Yang and Su, 2019) ; and (c) investigating different embodiment performances of normal and processing exports in different regions or countries using the spatial decomposition techniques 6 Yan and Su, 2020b ).

-22 -Appendix A. Sectoral and Regional Classifications Agriculture, forestry and fishing S02

Mining and extraction of energy producing products S03

Mining and quarrying of non-energy producing products S04

Mining support service activities S05

Food products, beverages and tobacco S06

Textiles, wearing apparel, leather and related products S07

Wood and products of wood and cork S08

Paper products and printing S09

Coke and refined petroleum products S10

Chemicals and pharmaceutical products S11

Rubber and plastic products S12

Other non-metallic mineral products S13

Basic metals S14

Fabricated metal products S15

Computer, electronic and optical products S16

Electrical equipment S17

Machinery and equipment S18

Motor vehicles, trailers and semi-trailers S19

Other transport equipment S20

Other manufacturing; repair and installation of machinery and equipment S21 Electricity, gas, water supply, sewerage, waste and remediation services S22 Construction S23

Wholesale and retail trade; repair of motor vehicles S24

Transportation and storage S25 Accommodation and food services S26

Publishing, audiovisual and broadcasting activities S27

Telecommunications S28

IT and other information services S29

Financial and insurance activities S30

Real estate activities S31

Other business sector services S32

Public admin. and defence; compulsory social security S33 Education S34

Human health and social work S35

Arts, entertainment, recreation and other service activities S36

Private households with employed persons J o u r n a l P r e -p r o o f 

LMDI decomposition approach: A guide for implementation

Carbon emission intensity in electricity production: A global analysis

Accounting frameworks for tracking energy efficiency trends

Multi-country comparisons of energy performance: The index decomposition analysis approach

A spatial-temporal IDA approach to performance assessment in energy and emissions

The estimation of domestic value-added and employment induced by exports: An application to Chinese exports to the United States

Energy embodied in goods in international trade of China: Calculation and policy implications

Embodied energy, export policy adjustment and China's sustainable development: A multi-regional input-output analysis

China's embodied energy trade: based on hypothetical extraction method and structural decomposition analysis

Trade, production fragmentation, and China's carbon dioxide emissions

China Customs Statistical Yearbook

Interprovincial transfer of embodied primary energy in China: A complex network approach

General Office of the State Council in China

Promises and pitfalls in environmentally extended input-output analysis for China: A survey of the literature

The five-year plan: A new tool for energy saving and emissions reduction in China

World Energy Balances

Growth and structural change in China's energy economy

Evaluating the effects of embodied energy in international trade on ecological footprint in China

‗Made in China': A reevaluation of embodied CO2 emissions in Chinese exports using firm heterogeneity information

Analysis of CO 2 emissions embodied in China's bilateral trade: A non-competitive import input-output approach

China's energy saving potential from the perspective of energy efficiency advantages of foreign-invested enterprises

Firm ownership, China's export related emissions, and the responsibility

Regional disparity in energy intensity of China and the role of industrial and export structure

Input-occupancy-output models of the non-competitive type and their application -An examination of the China-US trade surplus

Environmental repercussions and the economic structure: An inputoutput approach

Energy embodied in the international trade of China: An energy input-output analysis

‗Made in China': A reevaluation of embodied CO 2 emissions in Chinese exports using firm heterogeneity information

Input-Output Analysis: Foundations and Extensions

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Carbon Dioxide Emissions Embodied in International Trade

From production-based to consumption-based national emission inventories

Growth in emission transfers via international trade from

Assessment of China's energy-saving and emission-reduction accomplishments and opportunities during the 11th Five Year Plan

Embodied carbon in trade: A survey of the empirical literature

Input-output analysis of CO 2 emissions embodied in trade: The effects of spatial aggregation

Multi-region input-output analysis of CO 2 emissions embodied in trade: The feedback effects

Structural decomposition analysis applied to energy and emissions: Some recent developments

Structural decomposition analysis applied to energy and emissions: Aggregation issues

Input-output analysis of CO 2 emissions embodied in trade: Competitive versus non-competitive imports

Attribution of changes in the generalized Fisher index with application to embodied emission studies

Input-output analysis of CO 2 emissions embodied in trade: A multi-region model for China

Multiplicative decomposition of aggregate carbon intensity change using input-output analysis

Multi-region comparisons of emission performance: The structural decomposition analysis approach

Multiplicative structural decomposition analysis of aggregate embodied energy and emission intensities

Demand contributors and driving factors of Singapore's aggregate carbon intensities

China's carbon emissions embodied in (normal and processing) exports and their driving forces

Input-output analysis of CO 2 emissions embodied in trade and the driving forces: Processing and normal exports

Input-output and structural decomposition analysis of Singapore's carbon emissions

Structural path and decomposition analysis of aggregate embodied energy and emission intensities

Input-output analysis of CO 2 emissions embodied in trade: The effects of sector aggregation

Trade-off analysis between embodied energy exports and employment creation in China

Driving forces of energy embodied in China-EU manufacturing trade from

UK's Carbon Footprint 1997-2016. Department for Environment, Food & Rural Affairs

Assessing drivers of economy-wide energy use and emissions: IDA versus SDA

A multi-region structural decomposition analysis of global CO2 emission intensity

China's aggregate embodied CO2 emission intensity from 2007 to 2012: A multi-region multiplicative structure decomposition analysis

Emissions embodied in Chinese exports taking into account of the special export structure of China

Trade patterns and global value chains in East Asia: From trade in goods to trade in task

Global primary energy use associated with production, consumption and international trade

Energy use by globalized economy: Totalconsumption-based perspective via multi-region input-output accounting

Assessing the impact of foreign content in China's exports on the carbon outsourcing hypothesis

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Energy and air emissions embodied in China-US trade: Eastbound assessment using adjusted bilateral trade data

What drive the changes in China's energy consumption and intensity during 12 th Five-Year Plan period?

Spatial differences in energy performance among four municipalities of China: From both the aggregate and final demand perspectives

China's emissions embodied in exports: How regional and trade heterogeneity matter

Impacts of international export on global and regional carbon intensity

Calculation of embodied energy in Sino-USA trade

Growth in embodied energy transfers via China's domestic trade: Evidence from multi-regional input-output analysis

Embodied carbon in China's foreign trade: An online SCI-E and SSCI based literature review

Energy, CO 2 emissions, and value added flows embodied in the J o u r n a l P r e -p r o o f Journal Pre-proof -28 -international trade of the BRICS group: A comprehensive assessment

Production globalization makes China's exports cleaner

Who shapes China's carbon intensity and how? A demand-side decomposition analysis

Input-output and structural decomposition analysis of India's carbon emissions and intensity

Figure 1. China's normal and processing exports

Our heartfelt thanks should be given to the National Natural Science Foundation of 

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