| Title | The dynamic relationships among growth in the logistics industry, energy consumption, and carbon emission: recent evidence from China |
|---|---|
| ID_Doc | 33777 |
| Authors | Wang, XL; Dong, F |
| Title | The dynamic relationships among growth in the logistics industry, energy consumption, and carbon emission: recent evidence from China |
| Year | 2023 |
| Published | Journal Of Petroleum Exploration And Production Technology, 13.0, 1 |
| Abstract | In the post-pandemic era, there is a need to achieve the dynamic and coordinated development of growth in the logistics industry, energy consumption, and carbon dioxide (CO2) emissions in China's four major economic regions to ensure the high-quality development of green logistics in China. Using the data indicators of growth in the logistics industry, energy consumption, CO2 emissions, and fixed asset investment in 30 Chinese provinces from 2004 to 2018, a panel vector autoregressive model was established for the four major economic development regions of central, east, west, and northeast China. The model coefficients were estimated using the systematic generalized matrix estimation method (System-GMM), which was evaluated by a Granger causality test. The model coefficients were estimated using the System-GMM method, and the dynamic relationships between growth in the logistics industry, energy consumption, and CO2 emissions was obtained through a Granger causality test, impulse response analysis, and variance decomposition. The results showed that the growth of the logistics industry in the four major economic regions had a positive impact on energy consumption and CO2 emissions, with the degree of contribution being smaller in the east and central regions, and larger in the west and northeast regions. Fixed asset investment had a negative impact on energy consumption and CO2 emissions, with the degree of contribution being largest in the northeast, larger in the east than in the central region, and smallest in the west. Finally, according to the conclusion and analysis of the results, from the aspects of government guidance and policy support, low-carbon logistics technology innovation, and infrastructure investment, we propose the need to pay attention to the role of government guidance, accelerate the pace of energy adjustments using the structure of the logistics industry, and increase the investment in renewable energy infrastructure, while focusing on strengthening the cooperation between regions and exploring new models of low-carbon logistics development between regions. This will ensure that the country achieves its goal of reaching peak carbon by 2030 and carbon neutrality by 2060. |
| https://link.springer.com/content/pdf/10.1007/s13202-022-01562-6.pdf |
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