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The STIRPAT Analysis on Carbon Emission in Chinese Cities: An Asymmetric Laplace Distribution Mixture Model

Author

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  • Shanshan Wang

    (School of Economics and Management, Beihang University, Beijing 100191, China)

  • Tianhao Zhao

    (School of Economics and Management, Beihang University, Beijing 100191, China)

  • Haitao Zheng

    (School of Economics and Management, Beihang University, Beijing 100191, China)

  • Jie Hu

    (School of Economics and Management, Beihang University, Beijing 100191, China)

Abstract

In cities’ policy-making, it is a hot issue to grasp the determinants of carbon dioxide emission in Chinese cities. And the common method is to use the STIRPAT model, where its coefficients represent the influence intensity of each determinants of carbon emission. However, less work discusses estimation accuracy, especially in the framework of non-normal distribution and heterogeneity among cities’ emission. To improve the estimation accuracy, this paper employs a new method to estimate the STIRPAT model. The method uses a mixture of Asymmetric Laplace distributions (ALDs) to approximate the true distribution of the error term. Meantime, a designed two-layer EM algorithm is used to obtain estimators. We test the robustness via the comparison results of five different models. We find that the ALDs Mixture Model is more reliable the others. Further, a significant Kuznets curve relationship is identified in China.

Suggested Citation

  • Shanshan Wang & Tianhao Zhao & Haitao Zheng & Jie Hu, 2017. "The STIRPAT Analysis on Carbon Emission in Chinese Cities: An Asymmetric Laplace Distribution Mixture Model," Sustainability, MDPI, vol. 9(12), pages 1-13, December.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:12:p:2237-:d:121477
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    References listed on IDEAS

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    2. Xing, Licong & Khan, Yousaf Ali & Arshed, Noman & Iqbal, Mubasher, 2023. "Investigating the impact of economic growth on environment degradation in developing economies through STIRPAT model approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
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