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

Shanshan Wang, Tianhao Zhao, Haitao Zheng and Jie Hu
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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
Jie Hu: School of Economics and Management, Beihang University, Beijing 100191, China

Sustainability, 2017, vol. 9, issue 12, 1-13

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.

Keywords: carbon emission; ALDs mixture model; EM algorithm; heterogeneity; Chinese cities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

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