Journals / Atmospheric Pollution Research / 2018 / Cilt: 9 - Sayı: 4

Panel estimation for the impacts of residential characteristic factors on CO2 emissions from residential sector in China

Pages
595–606
DOI
—
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AI Summary & Key Takeaways

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⚡ TL;DR(Too Long; Didn't Read)

The estimation results show that the impact of the household size on residential CO2 emissions varies from region to region and adds to the emissions in the eastern part will reduce it in the central part significantly.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Concerning the previous studies, we find the deficiency of the research on the factors driving the residential CO2 emissions accounting a lot for the Greenhouse gases.
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Key Findings & Data:To be specific, the household size, the urbanization rate and the total population dependence ratio as well as the residential financial characteristics including the residential consumption level, the wage income ratio and the Engel Coefficient are incorporated.
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Conclusion & Impact:The estimation results show that the impact of the household size on residential CO2 emissions varies from region to region and adds to the emissions in the eastern part will reduce it in the central part significantly.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

Concerning the previous studies, we find the deficiency of the research on the factors driving the residential CO2 emissions accounting a lot for the Greenhouse gases. Besides, when China is studied, researches mainly focused on a single province or a certain region and the studies on the national level failed to consider the differences among varied regions. In this paper, we applied an improved STIRPAT model focusing on the three regions as well as the national level in China. To be specific, the household size, the urbanization rate and the total population dependence ratio as well as the residential financial characteristics including the residential consumption level, the wage income ratio and the Engel Coefficient are incorporated. The estimation results show that the impact of the household size on residential CO2 emissions varies from region to region and adds to the emissions in the eastern part will reduce it in the central part significantly. While the per capita residential consumption level as well as the energy intensity has a positive effect on the dependent variable in all the regions. Furthermore, urbanization process and the reducing of the labor population measured by the rising total population dependence ratio decreases per capita CO2 emissions significantly in the eastern and the central part of China but increase it in the western region. The Engel coefficient decreases residential CO2 emissions in all the regions but only significantly in the eastern part of China. Based on the results obtained in China, some policy suggestions were given.

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Cite This Article

WANG, Y., ZHAO, T. (2018). Panel estimation for the impacts of residential characteristic factors on CO2 emissions from residential sector in China. Atmospheric Pollution Research, Cilt: 9 - Sayı: 4, 595–606. https://ajindex.com/articles/212563

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