A Correlative Study of Modern Logistics Industry in Developing Economy and Carbon Emission Using ARDL: A Case of Pakistan

Mu, Dong; Hanif, Salman; Alam, Khalid Mehmood; Hanif, Omer

doi:10.3390/math10040629

Cited by 9 publications

(5 citation statements)

References 57 publications

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“…Second, economic development is one of the most important factors of carbon emission increase in the research region. This finding is similar to the results of previous studies [27,46]. The results show that the relationship between economic development and carbon emissions is consistent with the Environmental Kuznets Curve.…”

Section: Discussionsupporting

confidence: 92%

Study on Influencing Factors and Spatial Effects of Carbon Emissions Based on Logarithmic Mean Divisia Index Model: A Case Study of Hunan Province

et al. 2022

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China has committed to peaking carbon dioxide emissions by 2030 and has set a goal of working towards carbon neutrality by 2060. Hunan province is a vital undertaking place for national industrial transfer. It is of great significance for promoting energy conservation and emission reduction to investigate the influencing factors and spatial effects of carbon emissions in Hunan province. Firstly, based on the energy consumption data of Hunan province from 2005 to 2017, this paper uses the method recommended by the Intergovernmental Panel on Climate Change (IPCC) to measure the carbon emissions of Hunan province and its economic zones. Secondly, the five-factor Logarithmic Mean Divisia Index (LMDI) model is constructed to analyze the influence degree of population size, economic development, industrial structure, energy intensity, and energy structure on carbon emissions. Finally, the spatial differences of the influencing factors in the four economic zones of Hunan province are analyzed. The research shows that: (1) An overall carbon emission reduction has been achieved in Hunan province since 2011. (2) Changsha–Zhuzhou–Xiangtan Economic Zone is the key area to achieve carbon emission reduction, while there is still the phenomenon of emission increase in the other three economic zones. (3) For all economic zones, economic development contributes the most to the increase in carbon emissions, while energy intensity shows the strongest inhibitory effect. Other factors have various effects on the four economic zones.

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Section: Discussionsupporting

confidence: 92%

Study on Influencing Factors and Spatial Effects of Carbon Emissions Based on Logarithmic Mean Divisia Index Model: A Case Study of Hunan Province

et al. 2022

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“…For the study of factors influencing carbon emissions, existing studies can be divided into two main aspects, namely market economy factors and governmental factors. The market economy factors include urbanization [20,21], rapid economic development [22] and other factors, resulting in an industrial structure characterized by energy-intensive and high-polluting heavy industries, which leads to a surge in carbon emissions. It has also been argued that the market-based emissions trading mechanism and sewage charges have not exerted their positive effects on the ecological environment [23], so the institutional arrangements of the government should not be ignored, and studies have shown that pollution monitoring and administrative control are the main reasons for the improvement of environmental quality in Western developed countries [24].…”

Section: Relevant Research On Carbon Emissionmentioning

confidence: 99%

Economic Growth Targets and Carbon Emissions: Evidence from China

Wang

Zhao

Fan

et al. 2022

IJERPH

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Carbon emissions have become a new threat to sustainable development in China, and local government actions can play an important role in energy conservation and emission reduction. This paper explores the theoretical mechanisms and transmission paths of economic growth targets affecting carbon emissions from the perspective of economic growth targets and conducts an empirical analysis based on 30 provincial panel data in China from 2003 to 2019. The results show that: economic growth targets are positively correlated with carbon emissions under a series of endogeneity and robustness; there are regional heterogeneity, target heterogeneity and structural heterogeneity in the impact of economic growth targets on carbon emissions; after economic growth targets are set, government actions can influence carbon emissions by affecting resource mismatch and industrial restructuring; It is further found that there is a “U” shaped relationship between economic pressure and carbon emissions. Based on the above findings, this paper further proposes that a high-quality performance assessment mechanism should be developed to bring into play the active role of local governments in achieving carbon reduction goals, and thus contribute to high-quality economic development.

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“…So, the important relationship between energy conservation and emission reduction in the logistics industry and high-quality economic development has also received extensive attention [ 7 ]. The economic development and logistics growth have accelerated the emission of carbon dioxide [ 12 , 13 ]. Under the background of energy-efficient and emission reduction, reducing carbon emissions of logistics, promoting low-carbon development of logistics, and improving the efficiency of logistics operation are the focus of China’s energy conservation and emission reduction development, and also an effective way to accelerate the transformation of economic development model [ 13 ].…”

Section: Literature Review and Hypotheses Developmentmentioning

confidence: 99%

Industrial structure, high-quality development of logistics industry and the economy

2023

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The logistics industry is closely related to the high-quality economic development. At different levels of industrial structure, the relationship between high-quality development of the logistics industry and the high-quality economic development will vary, resulting in different roles and paths in promoting economic development. However, there is still a lack of research on the relationship between high-quality development of the logistics industry and high-quality economic development at different levels of industrial structure, and further empirical research is needed. It used the benchmark regression model to analyze the impact of the high-quality development of the logistics industry on high-quality economic development, and the panel threshold model was used to analyze the impact of the logistics industry on high-quality economic development at different levels of industrial structure development. The results show that the high-quality development of the logistics industry has a positive role in promoting the high-quality economic development, and in different levels of industrial structure development, the impact of high-quality development level of logistics industry on the high-quality economic development is different. Therefore, it is necessary to further optimize the industrial structure, promote the deep integration and development of logistics and related industries, and continue to promote the high-quality development of the logistics industry. And when formulating development strategies for the logistics industry, governments and enterprises need to consider factors such as changes in industrial structure, the overall goals of national economy, people’s livelihood, and social development, in order to provide solid support for achieving high-quality economic development. This paper demonstrates the importance of high-quality development of the logistics industry in high-quality economic development, and it encourages the adoption of different strategies at different stages of industrial structure development to promote high-quality development of the logistics industry, and achieve high-quality economic development.

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A Correlative Study of Modern Logistics Industry in Developing Economy and Carbon Emission Using ARDL: A Case of Pakistan

Cited by 9 publications

References 57 publications

Study on Influencing Factors and Spatial Effects of Carbon Emissions Based on Logarithmic Mean Divisia Index Model: A Case Study of Hunan Province

Study on Influencing Factors and Spatial Effects of Carbon Emissions Based on Logarithmic Mean Divisia Index Model: A Case Study of Hunan Province

Economic Growth Targets and Carbon Emissions: Evidence from China

Industrial structure, high-quality development of logistics industry and the economy

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