Growth Sources of Green Economy and Energy Consumption in China: New Evidence Accounting for Heterogeneous Regimes

Liu, Guanchun; Liu, Yuanyuan

doi:10.5547/01956574.41.6.gliu

Cited by 31 publications

(4 citation statements)

References 90 publications

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“…Most existing environmental studies are based on conventional linear models. Research however shows that in reality, variables often exhibit non-linear characteristics (Anoruo, 2011; Falk, 1986; Lee et al, 2020; Liu et al, 2020; Meo et al, 2018; Neftçi, 1984). This is a major challenge in empirical literature because a linear model will produce inconsistent and unreliable estimates in the presence of non-linearities.…”

Section: Model and Datamentioning

confidence: 99%

An asymmetric examination of the environmental effect of tourism in China

Olasehinde‐Williams

Ibikunle

2021

Tourism Economics

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This article employs the non-linear autoregressive distributed lag model in analysing the environmental impact of tourism in China from 2002Q1 to 2018Q4, while controlling for non-renewable energy consumption, trade openness, urbanisation, per capita GDP and its quadratic form. The approach permits the simultaneous testing of non-linearities in the short and long run. This is achieved through negative and positive partial sum decompositions of the regressor of interest. Findings from the article indicate the following: (i) long-run co-movements exist between tourism activities and environmental performance in China, (ii) tourism activities considerably damage the environment in China, (iii) the environment responds to tourism in an asymmetric manner, such that the damage caused by increasing tourism is smaller than the positive environmental effect of decline in tourism. Thus, less tourism protects the environment faster than more tourism damages it. A supplementary non-parametric test for non-linear causality was also performed. The result further provides strong evidence of a non-linear feedback causality between tourism activities and environmental performance in China in the first moment (mean) and second moment (variance). Tourism (environmental performance) is thus a significant predictor of China’s environmental performance (tourism).

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Section: Model and Datamentioning

confidence: 99%

An asymmetric examination of the environmental effect of tourism in China

Olasehinde‐Williams

Ibikunle

2021

Tourism Economics

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“…Yuan et al (2020) assessed the influence of manufacturing agglomeration on green economic efficiency in China and found a positive U-shaped relationship. Lee et al (2020b) explored the heterogeneity and influence mechanism of China's green total factor productivity in various industries and regions by constructing a finite mixture model based on the Solow decomposition framework. Yan et al (2020) applied the data envelopment analysis technique to evaluate China's green productivity and concluded that income levels shape the effect of new energy technology innovation on the country's green productivity growth.…”

Section: Green Economymentioning

confidence: 99%

Export Diversification and the Green Economy: The Key Role of Economic Risk

Xing

Lee

2023

Technological and Economic Development of Economy

Self Cite

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As countries propose to develop their green economy strategies to achieve sustainable development goals, many researchers and practitioners have analyzed the various factors affecting this special economy and how export diversification impacts the environment. However, there is limited knowledge about the link between export diversification and the green economy. Thus, this research study explored the impact of such diversification on the green economy by considering the role of economic risk. A new dynamic panel threshold approach was applied to the global panel data of 112 countries from 1995 to 2014. The results support the U-shaped correlation between export diversification and the green economy with an increase in economic risk. Export diversification tends to weaken the green economy when economic risk is at lower levels, but it improves the economy after reaching a certain level of economic risk. We also found that the green economy has a persistent effect over time. Under all economic risk levels, the previous level of green economy development promotes current green economy development. These findings thus provide policymakers with crucial implications.

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“…When environmental factors are taken into account, China's green TFP growth is much slower than GDP [3][4][5]. Given that China is in the difficult situation of being at the end of the era of high economic growth and environmental degradation, China's economic development model urgently needs to make a green transformation and find a high-quality development path that combines economy and ecology, and this path is the path of China's greening process with the purpose of improving green total factor productivity [6,7]. Therefore, the rapid increase of green total factor productivity is a difficult problem facing China today and needs to be solved urgently.…”

Section: Introductionmentioning

confidence: 99%

How to Improve Industrial Green Total Factor Productivity under Dual Carbon Goals? Evidence from China

Chen

2023

Sustainability

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This paper focuses on the relationship between green credit and industrial green total factor productivity under the dual carbon target. In recent years, weather extremes that break historical extremes have occurred frequently around the world, and the resulting loss of life and property has deepened people’s concern about climate change. As a responsible developing country, China has set the goal of reaching peak carbon emissions and reducing carbon intensity by 60–65% by 2030. In this context, based on China’s provincial-level data from 2006 to 2019, this paper first measures the growth rate of industrial green total factor productivity using the SBM-ML model, and then analyzes the impact of green credit on industrial green total factor productivity under the double carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We then analyze the impact of green credit on industrial green total factor productivity under the dual carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We find that green credit can improve the energy consumption structure and thus increase industrial green total factor productivity. In addition, the study finds that the interaction effect of green credit and environmental regulation suppresses the positive impact of green credit on industrial green TFP. This paper provides empirical evidence and policy implications for the orderly promotion of carbon peaking and carbon neutral efforts to effectively improve industrial green total factor productivity and promote high-quality economic development.

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Growth Sources of Green Economy and Energy Consumption in China: New Evidence Accounting for Heterogeneous Regimes

Cited by 31 publications

References 90 publications

An asymmetric examination of the environmental effect of tourism in China

An asymmetric examination of the environmental effect of tourism in China

Export Diversification and the Green Economy: The Key Role of Economic Risk

How to Improve Industrial Green Total Factor Productivity under Dual Carbon Goals? Evidence from China

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