Financial development and carbon emissions in China since the recent world financial crisis: Evidence from a spatial-temporal analysis and a spatial Durbin model

Liu, Hongyan; Song, Yanrong

doi:10.1016/j.scitotenv.2020.136771

Cited by 125 publications

(51 citation statements)

References 47 publications

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“…The extent of the industrial structure affecting green development may be affected by spatial factors [ 50 ]. After conducting the LR test (Likelihood-ratio test) between spatial econometric models [ 52 , 53 , 54 , 55 ], the SDM model is chosen. The SDM model is used to evaluate the spillover effect of industrial structure adjustment on green development between adjacent provinces:

where y it represents the explained variable, x it is the explanatory variable, w is the spatial weight coefficient, and μ it is the random error term;

and

are estimated parameters.…”

Section: Variables and Model Specificationmentioning

confidence: 99%

Industrial Structure Adjustment and Regional Green Development from the Perspective of Mineral Resource Security

You

Xiao

Cheng

2020

IJERPH

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Mineral resource security is the premise and foundation of the regional green rise strategy. And the adjustment of industrial structure is an effective way to relieve the pressure of the current green economy transformation. Based on the Shift-share Method and the Spatial Durbin model, this paper takes 30 regions in China from 2006 to 2017 as examples to study the impact of industrial structure adjustment on China’s green development from the perspective of mineral resource security. The empirical results show that: China is still in the process of industrial transfer. The dynamic effect of industrial structure promotes green development from the perspective of mineral resource security, while its static effect inhibits green development from the perspective of mineral resource security. The spatial spillover effect of the industrial structure affecting green development from the perspective of mineral resource security is significant. The static structural effect of the tertiary industry promotes the green development of the region, and it has a significant negative impact on neighboring areas, while the secondary industry’s static structural effect has the opposite effect.

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where y it represents the explained variable, x it is the explanatory variable, w is the spatial weight coefficient, and μ it is the random error term;

and

are estimated parameters.…”

Section: Variables and Model Specificationmentioning

confidence: 99%

Industrial Structure Adjustment and Regional Green Development from the Perspective of Mineral Resource Security

You

Xiao

Cheng

2020

IJERPH

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“…Some scholars began to investigate the temporal and spatial variation of CO 2 emission [16,17]. However, most of them only analyze from temporal or spatial perspective, few traced the spatiotemporal evolution of CO 2 emission with precision [18]. The Exploratory Spatial Data Analysis (ESDA) model provides solutions to quantitively capture the dynamic changes of CO 2 emission from both temporal and spatial perspective, which has been applied into various fields, such as CO 2 emission from agriculture and water use [19,20].…”

Section: Introductionmentioning

confidence: 99%

Social and Economic Factors of Industrial Carbon Dioxide in China: From the Perspective of Spatiotemporal Transition

Li¹,

Cheng²,

Diao³

et al. 2021

Sustainability

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The reduction of CO2 emission has become one of the significant tasks to control climate change in China. This study employs Exploratory Spatial Data Analysis (ESDA) to identify the provinces in China with different types of spatiotemporal transition, and applies the Logarithmic Mean Divisia Index (LMDI) to analyze the influencing factors of industrial CO2 emissions. Spatial autocorrelation of provincial industrial CO2 emissions from 2003 to 2017 has been demonstrated. The results are as follows: (1) 30 provinces in China are categorized into 8 types of spatiotemporal transition, among which 24 provinces are characterized by stable spatial structure and 6 provinces show significant spatiotemporal transition; (2) For all types of spatiotemporal transition, economic scale effect is mostly contributed to industrial CO2 emission, while energy intensity effect is the most crucial driving force to reduce industrial carbon dioxide emission; (3) provinces of type HH-HH, HL-HL and HL-HH are most vital for CO2 emission reduction, while the potential CO2 emission increase of developing provinces in LL-LL, LH-LH and LL-LH should also be taken into account. Specific measures for CO2 emission reduction are suggested accordingly.

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“…Record shows that 2.7% per annum increase in greenhouse gas (GHG) emissions released after three years of landmark Paris Agreement (Le Quéré et al 2018). The rise in income of households and production activities stimulate economic growth with an intensive demand for heavy technologies and investment in energy intensive sectors (Shoaib et al 2020;Gill et al 2019;Liu and Song (2020); Lahiani, 2020). In other words, financial development has the tendency to raise the significant level of carbon emissions either from emerging economies or developing countries (Jiang, Yang and Ma 2019).…”

Section: Introductionmentioning

confidence: 99%

“…We used fossil energy consumption intensity calculated as aggregates of oil, coal, and natural gas consumptions in million tonnes of oil equivalent per real GDP. Recent studies have also adopted it (such as, Liu and Song, 2020;Shahzad et al, 2017;Lin and Agyeman, 2020;Guo and Hu, 2020 etc.). Globalization through free trade and capital increases production and boosts economic growth which in turn hamper the environmental quality via carbon dioxide emission due to increase in energy demand and consumption.…”

mentioning

confidence: 99%

Examining the link between carbon emission, carbon emission intensity and financial development in Nigeria. A Dynamic ARDL Simulation

Okere¹,

Ogbulu²,

Muoneke³

et al. 2021

Preprint

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The need for adequate and consistent policies to mitigate the continuous rise of carbon emission have motivated the energy economist in the past decades to actively involved and explore common economic agents that are driving the rising pattern in the environmental pollution. This study is positioned towards contributing to the on-going debates on this issue by exploring the impact of bank credit to the private sector on aggregate carbon emissions and carbon emission intensity in Nigeria over the period 1971– 2016 using dynamic ARDL simulations. Controlling for the influence of fossil energy intensity of consumption and economic globalization, the study found that bank credit to the private sector has a positive significant long-run increasing effect on aggregate CO2 emission and carbon emission intensity in the economy. Second, the estimated coefficients show that fossil energy intensity of consumption and economic globalization have a significant long-run and short-run increasing impact on aggregate CO2 emission and carbon emission intensity in the economy. In contrast, the population has a significant long-run and short-run reducing effect on aggregate CO2 emission and only the long run reducing effect on carbon emission intensity. Third, economic growth has significant short-run and increasing long-run effects on aggregate CO2 emission and a long run increasing effect on carbon emission intensity. In sum, the results show that the economy is yet to transient to renewable energy.

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Financial development and carbon emissions in China since the recent world financial crisis: Evidence from a spatial-temporal analysis and a spatial Durbin model

Cited by 125 publications

References 47 publications

Industrial Structure Adjustment and Regional Green Development from the Perspective of Mineral Resource Security

Industrial Structure Adjustment and Regional Green Development from the Perspective of Mineral Resource Security

Social and Economic Factors of Industrial Carbon Dioxide in China: From the Perspective of Spatiotemporal Transition

Examining the link between carbon emission, carbon emission intensity and financial development in Nigeria. A Dynamic ARDL Simulation

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