Using the social network analysis method, this paper explores the characteristics of the spatial association network structure of China's provincial transportation carbon emissions from 2005 to 2015 ...and its driving factors. The results are as follows: (1) The spatial association of China's provincial transportation carbon emissions exhibits an intuitive network structure. The degree of closeness which were 0.2253 and 0.2333 in 2005 and 2015 respectively shows an increasing trend on the whole. However, it hit the bottom in 2011, reaching a minimum of 0.2230, which is the “low closeness degree inflection point”. (2) The spatial association network presents a significant “core-edge” distribution pattern. Specifically, in the central and eastern regions of China, Henan and Jiangsu have degrees of up to 58.621 and 44.828, which are at the network center. However, some remote regions, like Jilin and Hainan, have degrees of less than 20.000, which are marginalized. (3) The geographical adjacency, the expansion of the difference in R&D investment, and the narrowing of the difference in economic development promote the formation of the interprovincial spatial association. Therefore, in the process of controlling carbon emissions from transportation, the government should focus on the provinces at the network center and pay attention to the impact of the R&D investment on the spatial association of transportation carbon emissions.
•The evolution trend of the spatial association network structure is analyzed.•The “core-edge” distribution of the spatial association network is described.•“Henan is a key governance province” in this study.•“Reducing the R&D investment difference between provinces” is proposed.
Improving carbon emission performance is widely regarded as one of the most cost-effective ways to combat clime change. This paper employs a parametric Malmquist index approach to measure total ...factor carbon productivity in 88 economies over the period of 1975–2013. Then, we explore the trend of carbon productivity with the log t regression test and identify potential convergent clubs. Furthermore, the Ordered Probit model is employed to examine the factors affecting the club convergence of carbon productivity growth. The main findings are as follows: (1) the carbon productivity on average increased by 63.5% during the sample period, mainly driven by technological progress; (2) the developed countries performed better than the developing countries. Meanwhile, the developed economies were far ahead in terms of technological progress, while the developing ones have performed slightly better in terms of carbon efficiency improvement; (3) although the whole sample did not show convergent trend, five convergence clubs formed with significant differences in carbon productivity growth; (4) the economies with higher GDP per capita and R&D investment tended to converge to the club with a higher carbon productivity, while the economies with higher energy intensity and foreign trade dependence tended to converge to the club with a lower carbon productivity. Finally, we draw some important policy implications.
•Total factor carbon productivity in 88 economies during 1975–2013 is estimated.•Total factor carbon productivity growth is mainly driven by technological progress.•Five convergence clubs in terms of total factor carbon productivity are identified.•Factors affecting convergent behaviors are examined.
•The impacts of COVID-19 on China's green bond market are investigated.•COVID-19 has significant impacts on the market and increases the cumulative abnormal return (CAR).•The extent of negative ...impacts depends on issuers’ governance capacity (emp), information asymmetry (InfoAsym) and debt-paying ability (debt-paying).•The impacts of emp, InfoAsym and debt-paying on the CAR are heterogeneous due to property rights and whether they are listed or not.
The paper applies the event study method and econometric models to investigate the impacts of COVID-19 on China's green bond market for the first time. We find that (1) the COVID-19 pandemic has significant impacts on China's green bond market and increases the cumulative abnormal return (CAR) of the green bonds greatly. After the pandemic is relieved, the CAR drops significantly; (2) the improving of bond issuers’ governance capacity, the weakening of information asymmetry and the reinforcing of debt-paying ability can effectively mitigate the negative impacts and positively promote the recovery of bond issuers after the pandemic; (3) the impacts of bond issuers’ governance capacity, information asymmetry and debt-paying ability on the CAR of green bonds are significantly heterogeneous before and after the pandemic due to their property rights and whether they are listed or not.
As the economy enters the new normal in China, more and more intellectuals are concerned about the energy consumption in the economic green transformation and development process; this article ...computes the energy consumption embodied in various final demand types by the utilization of the environmentally extended input-output (EEIO) model during 2000–2014. Then, the structural decomposition analysis is adopted for exploring energy consumption changes’ driving factors considering various final demand categories. Furthermore, the decoupling between economic growth and energy consumption embodied in various final demand categories is revealed by the application of the Tapio model in China. The results indicate as below: (1) the energy consumption embodied in various final demand categories increased significantly during the study period; (2) the gross fixed capital formation (GFCF) was most conducive to the growth of energy consumption, while the construction department emerged as the greatest energy user in GFCF; (3) coal and oil were two main energy sources consumed regardless of any final demand categories; (4) in the three drivers, the scale effect had a primary contribution to increasing energy consumption. The intensity effect made a crucial contribution to mitigating energy consumption. The structural effect had a mild contribution to the energy consumption changes; (5) the five final demand categories were roughly characterized by the weak decoupling over the period 2000–2014. GFCF determined the decoupling index between economy growth and energy consumption largely. Finally, this article put forward implied policies concerning the reduction of energy utilization in China.
The fiscal imbalance between the central and local governments under fiscal centralization may motivate local governments to pass tax burdens on firms. The causal identification of the tax system ...reform and the sustainable export innovation behavior of firms are of great significance. This study uses the income tax sharing policy of China to examine the impact of fiscal centralization on the sustainable export innovation behavior of firms. We find that this tax reform has significantly inhibited the increase of the export value-added rate of firms, and has an increasing trend with the share ratio between the Central Government and the local government. Moreover, this effect mainly comes from the crowding-out effect of imported intermediate goods on domestic intermediate goods. The tests show that the above conclusions are consistent with the general logic of local governments. When they face greater downward fiscal pressure, they will further pass the tax burden on local firms and force the firms to promote their export performance to expand the tax base. This short-sighted behavior of replacing “quality improvement” with “quantity increase” is an important factor that affects the sustainable export innovation behavior of firms and the climb in the global value chain.
Based on the pattern of difference in Chinese social trust, this study classifies the social trust into trust in family members, trust in acquaintances, and trust in strangers. Then, the ...correlational relationship between different types of social trust and subjective well-being is examined using the micro survey data in China. It is found that different types of social trust vary greatly in the correlation with subjective well-being. The main findings are as follows: (a) Trust in family members has no significant correlation with subjective well-being; (b) Only “totally trust acquaintances” has a significant positive correlation with subjective well-being; (c) Trust in strangers has a significant positive correlation with subjective well-being—the higher the trust level, the stronger the correlation with subjective well-being will be—and (d) Urban–rural and male–female differences exist in the correlational relationship between trust in strangers and subjective well-being.
China’s rural industrialization, which flourished in the 1980s, has suddenly declined since the mid-1990s. Based on the perspective of institutional change of rural collective construction land, this ...paper discusses the reasons behind the rise and fall of China’s rural industrialization. Using the empirical tests of China’s provincial panel data from 1987 to 1997, it is found that from the 1980s to the mid-1990s, the government relaxed the regulation of collective construction land and allowed its transfer, which was the institutional basis for the rapid rise of China’s rural industrialization with township and village enterprises (TVEs) as the main form. Furthermore, this paper takes the government’s policy of prohibiting the circulation of collective construction land from the mid-1990s as the breakthrough point, and uses the “Land Administration Law of China” promulgated in 1998 as a quasi-natural experiment to examine the causal relationship between restricting the circulation of collective construction land and the decline of TVEs. It is found that the restrictions on the circulation of collective construction land caused by the implementation of the law significantly hindered the development of TVEs. After the implementation of the Land Administration Law, in areas affected more by the law, the development scale of their TVEs shrunk even more. The analysis of this paper shows that deepening the reform of the system of property rights on agricultural land and ensuring farmers’ rights of land circulation are important ways to revitalize the rural areas.
Based on the provincial panel data of China from 2001 to 2016, this study uses the social network analysis approach to empirically investigate the characteristics and driving factors of the spatial ...association network of China’s interprovincial renewable energy technology innovation. The findings are as following. 1) The spatial association of China’s interprovincial renewable energy technology innovation exhibits a typical network structure. Moreover, its network density, network hierarchy and network efficiency are 0.3696, 0.6667 and 0.7833 in 2001 and 0.4084, 0.4764 and 0.7044 in 2016, respectively, implying the spatial association network became more and more complex and the interprovincial association strengthened during the sample period. 2) This spatial association network presents a “core-edge” distribution pattern. The positions and roles of various provinces vary greatly in the spatial association network. Specifically, the developed coastal regions such as Shanghai, Beijing and Tianjin have a degree centrality, closeness centrality and betweenness centrality of above 75, 80 and 10, respectively, indicating that they always play a central role in the network. However, the northeastern regions and the relatively backward central and western regions such as Heilongjiang, Jilin, Xinjiang, Hainan and Hebei only have a degree centrality, closeness centrality and betweenness centrality of below 20, 55 and 0.1, respectively, indicating that they are at a relatively marginal position. 3) The geographical proximity and the expansion of the differences in economic development level and R&D inputs are conducive to the enhancement of the spatial association of China’s renewable energy technology innovation.
Effectively reducing transportation carbon emissions is greatly significant to achieve the carbon peaking and neutral goals of China. On the basis of considering regional technology heterogeneity, we ...employ the parametric meta-frontier approach to analyze the carbon emission performance and reduction potential of the transportation sector in China. Then, we further decompose the emission reduction potential's contributors into removing management inefficiencies and filling technology gaps. The estimated potential carbon emission reductions from transportation sector in China are 12.3 million tons, accounting for 8.4 % of the annual transportation carbon emissions. Specifically, the eastern regions, especially Shandong, Shanghai, and Liaoning have the greatest carbon emission reduction potential; while Qinghai, Jiangxi, and Ningxia have the smallest potential. As the major contributors to the potential emission reductions, filling technology gaps and removing management inefficiencies account for 57.5 % and 42.5 % of the total potential, respectively. Moreover, removing management inefficiencies dominate for the eastern region and filling technology gaps for the central and western regions. Finally, we provide provincial-specific emission mitigation strategies based on the identification of the reduction potential and its contributors. Our policy implications help decision-makers to facilitate the low-carbon development of transportation sector.
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•The carbon emission performance and reduction potential of the transportation sector in China are explored.•The estimated potential carbon emission reductions from transportation are 12.3 million tons.•Shandong, Shanghai, and Liaoning have the greatest potential, while Qinghai, Jiangxi, and Ningxia have the smallest.•Filling technology gaps and removing management inefficiencies are main contributors of the potential emission reductions.•Provincial-specific emission mitigation strategies for transportation sector are proposed.
Energy poverty has a remarkable impact on socioeconomic development and human health. To identify energy poverty and further explore its influencing factors, this study uses 8239 households from 25 ...provinces from the China Family Panel Studies (CFPS) as the research object. First, the household energy poverty index (EPI) from 2012 to 2016 is measured. Second, the partially linear functional-coefficient (PLFC) model, which can capture individual heterogeneity, is employed to investigate how renewable energy technology innovation (RETI) alleviates energy poverty, also examining the role of marketization in the alleviation effect. The findings are as follows: (1) RETI significantly alleviates household energy poverty; (2) the alleviation effect of RETI on household EPI is affected by the marketization level (ML). In particular, when the ML is greater than 5.94, the alleviation effect is stronger; (3) under the influence of the ML, the alleviation effect exhibits a significant spatial heterogeneity. The eastern provinces exhibit the most significant alleviation effect. Finally, according to the nonparametric relationship between RETI and the EPI, we propose corresponding policy recommendations to alleviate household energy poverty.
•The household energy poverty of 25 provinces in China is measured.•The renewable energy technology innovation alleviates household energy poverty.•The impact of marketization on this alleviation effect is explored by PLFC model.•The alleviation effect increases when marketization reaches a certain level.•Significant spatial heterogeneity of the alleviation effect exists.
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