Examining industrial structure changes and corresponding carbon emission reduction effect by combining input-output analysis and social network analysis: A comparison study of China and Japan

Li, Zhaoling; Sun, Lu; Geng, Yong; Dong, Huijuan; Ren, Jingzheng; Liu, Zhe; Tian, Xu; Yabar, Helmut; Higano, Yoshiro

doi:10.1016/j.jclepro.2017.05.200

Cited by 138 publications

(64 citation statements)

References 40 publications

(35 reference statements)

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“…Okamoto [23] investigated the effect of a structural transition to the service industry in Japan using decomposition analysis, and he documented that the service industry reduced CO 2 emissions in Japan over the period 1995-2005. Li et al [64] applied an input-output model and social-network analysis in a comparative study of Japan and China. They argued that industrial adjustment and connectivity among various industries is improving in China, but its industrial transition process still needs to be improved to mitigate CO 2 emissions as Japan moves more toward the service sector.…”

Section: Structural Change Studiesmentioning

confidence: 99%

Testing Non-Linear Nexus between Service Sector and CO2 Emissions in Pakistan

et al. 2020

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Our pioneer study is aimed at investigating the role of the service sector in affecting sustainable environment in Pakistan. Using time series data over 1971–2014 and applying an autoregressive distributive lag (ARDL) model with structural break analysis, we establish a long-term equilibrium relationship of carbon dioxide (CO2) emissions with energy consumption, income level, services and trade openness. Our findings support a service-induced environmental Kuznets curve (EKC) hypothesis in Pakistan. The income level sharply raises environmental degradation at the early stage; however, after reaching a certain threshold, it improves environmental quality but at a lower rate. There exists an inverted U-shaped nexus between services and CO2 emissions, which implies that the service sector is less energy-intensive in terms of mitigating pollution in Pakistan. Moreover, the energy consumption has an inverted U-shaped effect on carbon emissions, which implies energy efficiencies and adoption of renewable energy has reduced pollution in the long run. The trade openness increases CO2 emissions in both the short term and long term. The quadratic term of income level has a negatively inelastic impact on CO2 emissions, which implies a very slow rate of improvement in environmental quality. On the other hand, the quadratic term of services shows a highly elastic impact on pollution, which induces the EKC hypothesis. Our robustness checks such as fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (OLS), and Toda and Yamamoto (TY) causality tests further confirm the existence of the service-induced EKC hypothesis in Pakistan. Moreover, there exists a unidirectional causality from energy consumption to CO2 emissions, a bidirectional causal relationship between economic growth and CO2 emissions, and a unidirectional causal linkage between services and CO2 emissions. Lastly, we discuss certain policy implications for designing appropriate environmental and energy policies to mitigate the pollution in Pakistan.

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Section: Structural Change Studiesmentioning

confidence: 99%

Testing Non-Linear Nexus between Service Sector and CO2 Emissions in Pakistan

et al. 2020

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“…Therefore, we referred to previous studies and the basic influence mechanisms of the variables when determining the constraints. Apparently, changes in urbanization are mostly caused by demographic changes [21,22], while transformations in industrial structure are often caused by policies, investments, and technology [11,15,16]. Moreover, a time lag in the impact of industrial structure on urbanization cannot be ruled out because tertiary industry appears to be expanding rapidly and disorderly, and it cannot match the urbanization plan in China.…”

Section: Identification Of Constraintsmentioning

confidence: 99%

How Do the Industrial Structure Optimization and Urbanization Development Affect Energy Consumption in Zhejiang Province of China?

et al. 2018

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Abstract:In response to global climate change, China has voluntarily assumed responsibility and has pledged to reach its peak in carbon emissions by 2030. Industrial structure and urbanization have important impacts on energy consumption. This paper empirically analyzes the dynamic influence of industrial structure and urbanization on energy consumption in the Zhejiang Province of China by constructing a structural vector auto regressive model using impulse response function and variance decomposition. The results show a positive impact of urbanization on energy consumption, which increases and then gradually decreases, and an impact of industrial structure on energy consumption. The results also indicate that it will take a certain period of time for an increase in the proportion of tertiary industry to curb the growth of energy consumption. Urbanization has a greater impact on energy consumption than does industrial structure.

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“…Djankov et al used the gravity model to empirically analyze the changes in trade flows between the nine Russian regions of the former Soviet Union and the three former Soviet republics from 1987 to 1996 [11]. Li et al compared changes in the industrial structure of China and Japan by combining input-output analysis with social network analysis [15]. Wang et al studied the spatial linkages of the urban economy for the Pearl River Delta in China from the perspective of industry, based on the urban flow intensity model [16].…”

Section: Introductionmentioning

confidence: 99%

“…Although these studies have showed insightful findings and made great contributions to the study of regional economy, they often focused on the external spatial interaction of regional economy, with few taking into account the complex internal economic linkages between different industrial sectors at the regional level. In the existing research, the input-output theory is a popular method to study the interactions between different sectors of a region [9,15,[17][18][19]. For example, Shi et al explored the inter-sectoral relations between five provinces of the Inland River Basin in China by adopting input-output analysis, but these studies did not measure the industrial interaction among provinces [18].…”

Section: Introductionmentioning

confidence: 99%

Exploration of the Industrial Spatial Linkages in Urban Agglomerations: A Case of Urban Agglomeration in the Middle Reaches of the Yangtze River, China

Han

Tang

et al. 2018

Sustainability

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The study of industrial spatial linkages of urban agglomerations is crucial to recognizing spatial structure and optimizing regional division and cooperation. The existing studies often focus on external spatial interaction at the inter-city level, but few have considered complex internal economic linkages at the inter-sector level. In this study, we established an integrated framework by combining the wave effect gradient field with the gravity model. The wave effect gradient field was used to analyze the inter-sector relation, while the gravity model was adopted to explore the spatial interactions of industry at the inter-city level. The Urban Agglomeration in the Middle Reaches of the Yangtze River (UAMRYR) was taken as a case study, which demonstrates the applicability of the proposed framework. The results indicate that there exists an imbalanced development in the network of industrial linkages in the study region. Each subgroup has presented a self-organized spatial linkage network, but the linkages between subgroups are immature. Compared with other sectors, the high-tech and internet industrial sectors contribute most to economic linkages among cities. Thus, policymakers should take actions to strengthen the inter-subgroup spatial linkages and give priority to the high-tech industries, which is necessary for the integrated and sustainable development of UAMRYR.

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Examining industrial structure changes and corresponding carbon emission reduction effect by combining input-output analysis and social network analysis: A comparison study of China and Japan

Abstract: Examining industrial structure changes and corresponding carbon emission reduction effect by combining input-output analysis and social network analysis: A comparison study of China and Japan, (2017),

Cited by 138 publications

References 40 publications

Testing Non-Linear Nexus between Service Sector and CO2 Emissions in Pakistan

Testing Non-Linear Nexus between Service Sector and CO2 Emissions in Pakistan

How Do the Industrial Structure Optimization and Urbanization Development Affect Energy Consumption in Zhejiang Province of China?

Exploration of the Industrial Spatial Linkages in Urban Agglomerations: A Case of Urban Agglomeration in the Middle Reaches of the Yangtze River, China

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