Carbon trading and regional carbon productivity

Liu, Baoliu; Ding, Jian; Hu, Jin; Su, Yuqi; Qin, Chuan

doi:10.1016/j.jclepro.2023.138395

Cited by 52 publications

(8 citation statements)

References 112 publications

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“…GTI is a factor that has lately attracted attention in the environmental economics literature as a factor affecting environmental quality. With the continued progress of GTI, an increasing number of politicians and researchers have noticed the significance of technological innovation for environmental quality by reducing pollutant emissions and ecological footprints (Wang et al 2021 ; Jian and Afshan 2022 ; Koseoglu et al 2022 ; Metawa et al 2022 ; Sharif et al 2022 ; Hou et al 2023 ; Javed et al 2023 ; Liu et al 2023 ). GTI, targeted at minimizing the effects of economic activity on climate change, is an effective instrument for transitioning to a low-carbon economy (Bel and Joseph 2018 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Determining the green technology innovation accelator and natural resources towards decarbonization for the EU countries: evidence from MMQR

Cutcu,

Cil,

Karis

et al. 2024

Environ Sci Pollut Res

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Gearing up for green technology innovation (GTI) and natural resources has become even more important in the transition to a zero-emission life, a green economy, and sustainable development goals. This attempt has become a situation that needs to be overpowered much sooner by the European countries, which have encountered challenges in many ways, especially regarding natural resources, energy supply, and the climate crisis. In this vein, the current study follows the novel, robust Method of Moment Quantile-Regression (MM-QR), which successfully yields heterogeneous information structure across quantiles, to examine the determinants of GTI for 15 EU countries over the period of 2003–2018. MM-QR estimation results indicate that the determinants of green technology innovation are heterogeneous across the EU countries. While green growth (GG) has an adverse impact on GTI in middle- and high-GTI countries, the effect of ecological footprint on GTI is positive for countries in the highest-GTI countries. The positive effects of financial development (FD) on GTI are revealed for all countries. Remarkably, environmental taxes have an adverse and positive influence on GTI in the lowest and highest quantile countries, respectively. Finally, renewable energy and greenfield FDI have no effect on GTI. Governments can promote GTI by providing financial resources, in the most immaculate way, to firms that engage in green technology projects, as well as by encouraging these through environmental taxes.

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Section: Literature Reviewmentioning

confidence: 99%

Determining the green technology innovation accelator and natural resources towards decarbonization for the EU countries: evidence from MMQR

Cutcu,

Cil,

Karis

et al. 2024

Environ Sci Pollut Res

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“…From the perspective of mechanistic analysis, some findings revealed that CTPs can stimulate technological progress, factor accumulation, scale allocation, and energy substitution effects, contributing not only to economic growth but also to achieving carbon reduction targets [13]. In addition, CTPs induce technological innovation effects, energy substitution, and structural upgrading effects; therefore, they enable the realization of green innovation potential [14].…”

Section: Literature Review and Research Hypothesis 21 Research Progre...mentioning

confidence: 99%

Heterogeneous Effects of China’s Carbon Market on Carbon Emissions—Evidence from a Regression Control Method

Liu,

Fu,

Wang

2023

Sustainability

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Carbon trading markets are crucial policy instruments in carbon emission reduction and carbon neutrality. Yet, China’s pilot programs encounter diverse operational modes and environmental factors that might impact their effectiveness. This study uses panel data from 30 provinces (2000–2019) in China and the regression control method to evaluate and analyze the heterogeneous effects of carbon trading pilots (CTPs) on emission reduction. Results reveal three types of CTP effects which are as follows: reducing both total carbon emissions (TCEs) and carbon intensity (CI) as noticed in Shanghai; decreasing CI while increasing TCE as seen in Beijing, Tianjin, Guangdong, and Hubei; and raising both TCE and CI as observed in Chongqing and Fujian. Significantly, market mechanisms in carbon pricing and state intervention, including of state-owned enterprises, play notable roles in these effects. Furthermore, CTP policies display both intensity reduction and energy rebound effects; the direction of carbon emission reduction relies on the balance between these effects. The findings offer empirical support to enhance carbon market effectiveness and provide valuable insights for regions in China and globally in order to tailor policies based on their specific conditions.

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“…In addition, the role of digital technology is realized by creating value through data elements, specifically through the generation, agglomeration, analysis and application of carbon trading data and industry-related data, to promote the construction of carbon trading market and industrial collaborative agglomeration. Carbon trading can promote green development by promoting technological progress, factor accumulation, energy conversion and so on (Liu et al, 2023). Industrial agglomeration can enhance industrial complementarity, promote the progress of green technology, and promote the green development of regional industries (Ding et al, 2022b).…”

Section: Digital Transformation and Green Transformation In Manufactu...mentioning

confidence: 99%

Dynamic Nonlinear Relationship between Digital Transformation, Green Transformation in Manufacturing Industry and Labor Structure: Evidence from Panel VAR Analysis

Jiang,

Han,

Wang

et al. 2023

REA

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<p class="MsoNormal" style="margin-top: 6pt; line-height: 13pt; text-align: justify;"><span lang="EN-US" style="font-family: arial, helvetica, sans-serif;">The digital transformation of manufacturing industry can promote the development of green transformation and promote the differentiation of workers’ skill structure; On the other hand, it will also hinder the green development due to the huge energy consumption generated by the application of digital technology and facilities. In addition, the green transformation of manufacturing industry will also have differentiated impacts on the employment of labour with different skills due to the innovation of green technology. The existing research has not discussed too much about the interaction among the digital transformation and green transformation in manufacturing industry and labour structure. So, this paper uses the PVAR model to examine the dynamic relationship between digital and green transformation within the industrial sector from the perspective of labour structure, specifically analyzing the impact difference across regions. The results suggest that there is a reciprocal connection between the digitization of manufacturing sector and the labour structure, particularly in the eastern region of China, but the overall interaction between the two remains weak. The interactive between the green transformation of manufacturing industry and the labour structure in the central and western areas has been delayed over periods 1-6. Digital and green manufacturing transformation reinforce each other in central and western regions. However, the digital revolution in the manufacturing industry is hindered by the green transformation in eastern region.</span></p>

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Carbon trading and regional carbon productivity

Cited by 52 publications

References 112 publications

Determining the green technology innovation accelator and natural resources towards decarbonization for the EU countries: evidence from MMQR

Determining the green technology innovation accelator and natural resources towards decarbonization for the EU countries: evidence from MMQR

Heterogeneous Effects of China’s Carbon Market on Carbon Emissions—Evidence from a Regression Control Method

Dynamic Nonlinear Relationship between Digital Transformation, Green Transformation in Manufacturing Industry and Labor Structure: Evidence from Panel VAR Analysis

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