The study explores the association between economic complexity index (ECI), tourism (TR), gross domestic products (GDP), gross domestic products per capita (GPC), and energy prices indices (EPI) on ...CO
2
e using the top 18 economic complexity index countries data from 1990 to 2019. We employ the second-generation cointegration methods and cross-sectionally augmented autoregressive distributed lag (CS-ARDL) to analyze the short- and long-term association also Dumitrescu and Hurlin Granger causality test applied. The results of Pesaran and Yamagata slope heterogeneity and Pesaran CD test confirm the presence of cross-sectional unit relationship and slope heterogeneity across countries, while positive long- and short-term associations were found among ECI, GDP, and CO
2
e. Also, TR, GPC, and EPI decrease carbon emissions both in the long and short term . Moreover, Augmented Mean Group (AMG) techniques verified and support these findings. The outcomes of the Dumitrescu and Hurlin Granger causality test showed that any policy aim at ECI, TR, GDP, GPC, and EPI has a considerable impact on CO
2
e. Based on the rigorous empirical analysis, we suggest that economic complexity, tourism, GDP, GPC, and energy prices would help alleviate high economic complexity countries’ environmental degradation challenges.
Energy efficiency improvement and carbon emission reduction are two important ways to mitigate energy consumptions and global warming. This paper aims to examine energy efficiency and carbon dioxide ...(CO2) emissions abatement costs of city urban areas in China. To this end, an improved slacks-based measure approach is introduced, which considers the linkage between desirable and undesirable outputs. Then, measures of energy efficiency, CO2 emission abatement cost and comprehensive state index of CO2 emissions abatement cost and CO2 emissions reduction potential are defined. The proposed model is then applied to the dataset of 285 cities in China during 2008–2012. The results show that most city urban areas in China have relatively low energy efficiencies. Surprisingly, there are gradually narrowing gaps regarding mean energy efficiencies between areas during 2008–2012. Nevertheless, there are great disparities in energy efficiencies between cities within a typical area, and even a provincial region. It is found that CO2 emissions abatement cost in urban China exhibits an increasing trend during the study period. Also, significantly geographic disparities in abatement costs between areas, regions and cites are found. Specifically, energy efficiency has significantly positive correlation with the comprehensive state index in China. Some important findings and useful policy implications are achieved.
•Urban energy efficiency and CO2 emissions abatement costs are examined.•A SBM model with the link between desirable and undesirable outputs is proposed.•Measures of energy efficiency and CO2 emissions abatement cost are defined.•The study is conducted for urban areas of 285 China’s cities during 2008–2012.
This paper incorporates the multiregional input-output (MRIO) and social network analysis (SNA) methods to investigate China’s embodied carbon transfer across provinces. We estimate the amount of ...interprovincial embodied carbon transfer from 2002 to 2012, analyse the spatial correlation network structure of carbon transfer and its determinants. Our work can clarify the spatial distribution and different roles of provinces in the carbon transfer network. The empirical results show the spatio-temporal evolution of embodied carbon transfer; in 2002, embodied carbon transfer occurred from the energy-rich northern provinces to the developed eastern and central provinces, but in 2012, it transferred to developing southwestern and southern provinces. Moreover, the northwestern provinces act as “bridges” between the central and eastern provinces; eastern provinces play a “bidirectional spillover” role that transfers carbon internally and externally. The embodied carbon transfer network proposed here can help policy makers further clarify individual provinces’ carbon emissions reduction responsibilities and curb national carbon emissions.
•The spatial correlation network structure of embodied carbon transfer in China is analysed.•The carbon emissions is with obvious regional disequilibrium and the transfer is “geographic adhesiveness”.•Northwestern provinces act as “bridges” meanwhile Eastern provinces play a “bidirectional spillover” role in carbon transfer.•The environmental path dependence is most important in affecting embodied carbon transfer in 2012.
Understanding the underlying determinants of energy intensity in countries with intensive energy consumption, such as China, is essential for addressing carbon emissions and global climate change. ...This study investigates the impact of spatial agglomeration on manufacturers' energy consumption behaviour using large-scale firm-level data compiled from complementary data sources in China. We create a circle around each firm instead of measuring agglomeration by aggregating economic activities in a predetermined administrative unit. In this way, we accurately capture the geographic range of concentration within a specific radius. We find that refined spatial agglomeration plays a mitigating role in shaping a firm's energy intensity. Meanwhile, agglomeration economies quickly attenuate with distance when we extend the radius. Heterogeneity analysis suggests that manufacturers' energy efficiency presents a diversified pattern across ownership and trade status. These results have important implications for researchers to understand energy efficiency heterogeneity and are beneficial for policymakers.
•The paper investigates the linkage between industrial agglomeration and energy intensity using firm-level data.•We create a circle around each firm instead of aggregating economic activities in a predetermined administrative unit.•Spatial agglomeration plays a mitigating role in shaping firm energy intensity.•The agglomeration economies quickly attenuate with distance when expanding the radius.
Technology innovation has been widely considered as a crucial way to reduce energy-related carbon dioxide (CO
2
) intensity. However, since the previous studies have largely neglected the operational ...process of innovation activities and the existence of spatial effect in carbon emissions, the impact of technology innovation on mitigation needs to be further investigated. Based on the sample of regional-level dataset in China during the period from 1998 to 2015, we first estimate the regional innovation system efficiency (RISE) with employing Data Envelopment Analysis window technique. Moreover, by adopting spatial econometric approaches, we further examine the direct effect and spatial spillover effect of RISE on CO
2
intensity in China during the study period. The results show that there exist remarkable spatial spillover effects of CO
2
intensity in China. Interestingly, RISE spatial agglomeration has higher spatial spillover effects on CO
2
intensities between two remote areas than between neighbors. More importantly, RISE can facilitate CO
2
intensity reduction at national level, whereas in across eastern-western and central-western regions, RISE in one region within a particular area can reduce its CO
2
intensity while increasing those of other regions in the other area. Finally, some policy suggestions are identified to reduce CO
2
intensity in China.
The outbreak of coronavirus (COVID-19) has forced China to lockdown many cities and restrict transportation, industrial, and social activities. This provides a great opportunity to look at the ...impacts of pandemic quarantine on air quality and premature death due to exposure to air pollution. In this study, we applied the difference-in-differences (DID) model to quantify the casual impacts of COVID-19 lockdown on air quality at 278 cities across China. A widely used exposure-response function was further utilized to estimate the short-term health impacts associated with changes in PM2.5 due to lockdown. Results show that lockdown has caused drastic reduction in air pollution level in terms of all criteria pollutants except ozone. On average, concentrations of PM2.5, PM10, NO2, SO2 and CO are estimated to drop by 14.3 μg/m3, 22.2 μg/m3, 17.7 μg/m3, 2.9 μg/m3, and 0.18 mg/m3 as the result of lockdown. Cities with more confirmed cases of COVID-19 are related to stronger responses in air quality, despite that similar lockdown measures were implemented by the local governments. The improvement of air quality caused by COVID-19 lockdown in northern cities is found to be smaller than that of southern cities. Avoided premature death associated with PM2.5 exposures over the 278 cities was estimated to be 50.8 thousand. Our results re-emphasize the effectiveness of emission controls on air quality and associated health impacts. The high cost of lockdown, still high level of air pollution during lockdown and smaller effects in northern cities implies that source-specific mitigation policies are needed for continuous and sustainable reduction of air pollution.
Display omitted
•Causal effect exists between COVID-19 lockdown and air quality changes in China.•Concentrations of all air pollutants decreased due to lockdown, except for ozone.•Changes in air quality are more salient for cities with more confirmed cases.•Reduction of PM2.5 concentration is associated with large health benefits.
Major findings: Lockdown due to COVID-19 outbreak caused substantial effects on air quality and associated short-term health impacts in China.
Through analysis of the carbon emissions transfer network formed by the exchange of intermediate products among industries, we can promote the realization of national carbon emissions reduction ...goals. Therefore, it is of great significance to build a prediction model of the carbon emissions transfer network for more accurate predictions. According to the characteristics of the random oscillation sequence (ROS) of interindustry carbon emissions transfer, a hybrid prediction model denoted as the ROGM-AFSA-GVM is proposed based on the grey model (GM) for ROS and the general vector machine (GVM) optimized by the artificial fish swarm algorithm (AFSA). The proposed model uses the ROGM model to predict the general ROS trend and relies on the AFSA-GVM model to predict the nonlinear law of ROS. The predicted values of the two parts are combined to obtain predicted interindustry carbon emissions transfer values. The proposed model is used to simulate the interindustry carbon emissions transfer network of China. The simulation results show that the ROGM-AFSA-GVM model can effectively resolve the prediction problem of ROS. Comparing the predicted networks with the actually measured networks, it is verified that the proposed model is suitable for simulating the interindustry carbon emissions transfer network and has a good prediction performance.
This paper investigates the impacts of educational factors on economic growth across 31 provinces during 1996 and 2010 in China. A spatial panel estimation model is applied to study the impacts of ...education on economic growth taking into account the spatial spillover effects in Feder model and the cumulative effect. The results reveal that (1) educational factors are significantly spatially autocorrelated. Educational factors have spatial spillover effects. Regional differences of education impacts still exist. (2) Average schooling year has a more positive effect on economic output than capital investment and labor force. Basic education might play a more important role in economic growth. (3) Education sector also benefits non-education sectors on economic growth if "spatial effects of economic shocks" are considered. Some policies that may enhance education development and their impacts on economic growth are proposed.
The current era of industrial development and innovation is revolutionized using the internet, robotics, and artificial intelligence. Nevertheless, the appraisal of global economic progress shows ...increasing trends, there are environmental degradation issues associated with this improvement. The role of renewable energy, urbanization and foreign direct investment received a lot of attention in the literature on environmental issues, however, the simultaneity with information communication technology is missing. Therefore, the present study used data from 10 emerging countries during 1996–2015 and applied the novel Method of Moments Quantile Regression to analyze the nexus among the variables. Further, we applied the second-generation unit root test, and Driscoll Kraay standard errors to reach robust results. The findings revealed an inverted U-shape relationship between economic growth and environmental degradation; thus, the validity of the Environmental Kuznets Curve is revealed. Moreover, foreign direct investment is significant and positive at 0.05th-0.50th quantiles, however, it becomes insignificant at higher quantile levels. Urbanization enhances while renewable energy mitigates carbon dioxide emissions at all quantile levels. Information communication technology proxied by internet usage reduces environmental degradation significantly at 0.25th-0.95th quantile levels. Results of the study suggest insights for the policymakers to mitigate carbon dioxide emissions through encouraging renewable energy and internet use.
Carbon dioxide (CO₂) emissions are largely driven by fossil fuels. To reduce CO₂ emissions in China, it is important to determine influential factors of energy efficiency. This paper introduces a ...slacks-based measure window analysis approach to evaluate regional dynamic energy efficiency during 2001–2010, and then explores energy efficiency determinants by considering spatial effects, which is conducted based on spatial econometric models. The empirical results show that there exist evident spatial correlations between regional energy efficiencies in China. We find that, there exist evident disparities in cumulative effects of energy efficiency among the eastern, central and western areas. Interestingly, significant energy efficiency spatial spillovers can be clearly found between regions within the western area and across the eastern and western areas. It is found that, energy structure, energy price, railway transportation development and R&D stock are significant at national level. However, energy structure and railway transportation development are insignificant in the central and western areas, while energy price and R&D stock are insignificant in the eastern and central areas, respectively. Industrial structure and urbanization level are found to be insignificant at national level, but industrial structure is significant in the eastern and western areas, and urbanization level is significant in the central and western areas. Surprisingly, industrial structure and urbanization level are found to have positive impacts on energy efficiency in the western area. In addition to regional disparities and local conditions, policies making should take efficiency spatial spillovers into consideration. Several interesting policy implications are achieved.
PDF
