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The global community has set intensive targets in Sustainable Development Goals (SDGs) to better people’s lives after closing the Millennium Development Goals (MDGs). It corresponds to the 2030 aspirations of the United Nations to enhance and promote the sustainable development of human society. The current paper explores the impact of fiscal hedging and R&D in energy Using a green-energy system in SDGs. To do this, we used TOPSIS and QARDL methodologies on a 21-year dataset of South and Southeast Asian economies from 2000 to 2020. The study results show that fiscal hedging contributes favourably to the environmental degradation of the underlying economy. Research and development (R&D) in renewables has contributed negatively to ecological degradation and SDGs in the economies of South & Southeast Asia. This study suggests policy guidelines for advanced and developing economies based on fiscal stability and technical innovation through R&D to meet SDG.

The global community has set intensive targets in Sustainable Development Goals (SDGs) to better people’s lives after closing the Millennium Development Goals (MDGs). It corresponds to the 2030 aspirations of the United Nations to enhance and promote the sustainable development of human society. The current paper explores the impact of fiscal hedging and R&D in energy Using a green-energy system in SDGs. To do this, we used TOPSIS and QARDL methodologies on a 21-year dataset of South and Southeast Asian economies from 2000 to 2020. The study results show that fiscal hedging contributes favourably to the environmental degradation of the underlying economy. Research and development (R&D) in renewables has contributed negatively to ecological degradation and SDGs in the economies of South & Southeast Asia. This study suggests policy guidelines for advanced and developing economies based on fiscal stability and technical innovation through R&D to meet SDG.

Abstract China's carbon emissions have been ranking first in the world. This study filled in the gaps in research, decomposed carbon intensity from the perspective of time, space and industry. A decoupling effort model based on factor decomposition models was constructed to analyze the driving factors of carbon emissions and economic decoupling, which builded a foundation for achieving sustainable economic development. Using the Logarithmic Mean Divisia Index method (LMDI), the paper measured the carbon emission intensity of 29 provinces and cities in China from 1998 to 2019, and decomposed the decoupling effect between GDP and carbon emission on the basis of factor decomposition by tapio. The results showed that: (1) Carbon intensity declined first, then rise lightly, and finally declined steadily. For the primary industry and the tertiary industry, the carbon intensity declined steadily, while the carbon intensity increased accordingly to the overall carbon intensity. In terms of spatial evolution, the regional differences between different provinces decreased correspondingly. (2) The cumulative contribution rates of these three effects, i.e., technological progress, industrial structure and regional scale were 106.3299%, −15.1486% and 8.8188%, respectively. There were obvious differences of these cumulative contribution rates of carbon intensity among different provinces. (3) From the perspective of industrial, technological progress effect is the largest contribution for carbon intensity in the secondary industry. The Industrial structure effect mainly affects the primary and tertiary industries; and no significant difference in regional scale effect. (4) The decoupling effect gradually improved, and technological progress has played an absolute leading role in promoting the decoupling effect. Based on the research results, the key policy recommendation are put forward as follows: (1) Further improve the technological level and support clean technology enterprises. (2) Promote industrial upgrading in backward industrial provinces (3) Promote regional assistance and the introduction of high-quality foreign investment.

Abstract China's carbon emissions have been ranking first in the world. This study filled in the gaps in research, decomposed carbon intensity from the perspective of time, space and industry. A decoupling effort model based on factor decomposition models was constructed to analyze the driving factors of carbon emissions and economic decoupling, which builded a foundation for achieving sustainable economic development. Using the Logarithmic Mean Divisia Index method (LMDI), the paper measured the carbon emission intensity of 29 provinces and cities in China from 1998 to 2019, and decomposed the decoupling effect between GDP and carbon emission on the basis of factor decomposition by tapio. The results showed that: (1) Carbon intensity declined first, then rise lightly, and finally declined steadily. For the primary industry and the tertiary industry, the carbon intensity declined steadily, while the carbon intensity increased accordingly to the overall carbon intensity. In terms of spatial evolution, the regional differences between different provinces decreased correspondingly. (2) The cumulative contribution rates of these three effects, i.e., technological progress, industrial structure and regional scale were 106.3299%, −15.1486% and 8.8188%, respectively. There were obvious differences of these cumulative contribution rates of carbon intensity among different provinces. (3) From the perspective of industrial, technological progress effect is the largest contribution for carbon intensity in the secondary industry. The Industrial structure effect mainly affects the primary and tertiary industries; and no significant difference in regional scale effect. (4) The decoupling effect gradually improved, and technological progress has played an absolute leading role in promoting the decoupling effect. Based on the research results, the key policy recommendation are put forward as follows: (1) Further improve the technological level and support clean technology enterprises. (2) Promote industrial upgrading in backward industrial provinces (3) Promote regional assistance and the introduction of high-quality foreign investment.

With rapid progress in the corporate social responsibility (CSR) theories and the up-gradation of the global market information disclosure system, enterprises have increased their attention toward relevant stakeholders and social responsibility. CSR exerts a substantial impact on the sustainable development of enterprises and markets in the economic and social fields. On the one hand, the increasingly perfect supporting facilities promote the financial growth of the entire society. While on the other hand, the profit-seeking trend of capital is also on the rise. The incongruity between the rapid progress of enterprises and the lack of social responsibility limits the benign development of the market. This study discusses the antecedents of CSR from the variable combination perspective using the fuzzy-set qualitative comparative analysis. It also investigates which combination of characteristics has better CSR performance. After the configuration analysis, it is identified that four paths lead to high CSR performance. These include the market-developed type, political link type, financial performance type, and state-owned enterprise subsidy type, and the level of each type is explained in-depth. Finally, this study provides management inspiration for the government and enterprises to formulate a sound social responsibility strategy and improve CSR performance by optimizing the matching of CSR activities and business objectives.

With rapid progress in the corporate social responsibility (CSR) theories and the up-gradation of the global market information disclosure system, enterprises have increased their attention toward relevant stakeholders and social responsibility. CSR exerts a substantial impact on the sustainable development of enterprises and markets in the economic and social fields. On the one hand, the increasingly perfect supporting facilities promote the financial growth of the entire society. While on the other hand, the profit-seeking trend of capital is also on the rise. The incongruity between the rapid progress of enterprises and the lack of social responsibility limits the benign development of the market. This study discusses the antecedents of CSR from the variable combination perspective using the fuzzy-set qualitative comparative analysis. It also investigates which combination of characteristics has better CSR performance. After the configuration analysis, it is identified that four paths lead to high CSR performance. These include the market-developed type, political link type, financial performance type, and state-owned enterprise subsidy type, and the level of each type is explained in-depth. Finally, this study provides management inspiration for the government and enterprises to formulate a sound social responsibility strategy and improve CSR performance by optimizing the matching of CSR activities and business objectives.

Accurate measurement of the shadow price of carbon dioxide (CO2) is fundamental to the scientific assessment of the carbon emission reduction cost and the formulation and execution of China’s carbon emission mitigation policies. Underpinned by the directional distance function, this research uses a parametric linear programming method and a Bayes bootstrap estimation method to estimate the marginal CO2 emission reduction cost of the industrial sector in China and to quantify the related influencing factors. The results revealed that the marginal reduction cost of industrial CO2 is CNY 4565/ton. The marginal reduction cost of CO2 varies by industry, with the textile industry being the highest and the petroleum, coking and nuclear fuel processing industries the lowest. Meanwhile, an increasing number of industries are shifting to cleaner production. Furthermore, the marginal reduction cost of industrial CO2 has an “inverted U-shaped” relation with carbon intensity. Carbon emission reduction can be accomplished effectively if the carbon intensity is kept below the threshold value of 0.41 tons/CNY 10,000.

Accurate measurement of the shadow price of carbon dioxide (CO2) is fundamental to the scientific assessment of the carbon emission reduction cost and the formulation and execution of China’s carbon emission mitigation policies. Underpinned by the directional distance function, this research uses a parametric linear programming method and a Bayes bootstrap estimation method to estimate the marginal CO2 emission reduction cost of the industrial sector in China and to quantify the related influencing factors. The results revealed that the marginal reduction cost of industrial CO2 is CNY 4565/ton. The marginal reduction cost of CO2 varies by industry, with the textile industry being the highest and the petroleum, coking and nuclear fuel processing industries the lowest. Meanwhile, an increasing number of industries are shifting to cleaner production. Furthermore, the marginal reduction cost of industrial CO2 has an “inverted U-shaped” relation with carbon intensity. Carbon emission reduction can be accomplished effectively if the carbon intensity is kept below the threshold value of 0.41 tons/CNY 10,000.