The dynamic impact of economic growth and economic complexity on CO2 emissions: An advanced panel data estimation

格兰杰因果关系 面板数据 经济 样品(材料) 因果关系(物理学) 同种类的 计量经济学 估计 宏观经济学 自然资源经济学 数学 物理 组合数学 量子力学 化学 管理 色谱法
作者
Wanhai You,Zhang Yue,Chien‐Chiang Lee
出处
期刊:Economic Analysis and Policy [Elsevier BV]
卷期号:73: 112-128 被引量:125
标识
DOI:10.1016/j.eap.2021.11.004
摘要

The goal of this study is to explore the causal relationship among economic growth, economic complexity and CO 2 emissions by using panel data of 95 countries for the period 1996–2015. A novel panel Granger approach proposed by Juodis et al. (2021) is adopted. Under this approach, we can explore the Granger causality in homogeneous or heterogeneous panels. To uncover the heterogeneous causal effects at different income levels, this study further divide the sample into three groups according to their annual income levels. Empirical results show that there are bi-directional causalities among economic growth, economic complexity and CO 2 emissions for all groups. However, the magnitudes of the effects are heterogeneous for different groups. As to low-income countries, economic complexity is positive and significant for CO 2 emissions, while CO 2 emissions are negative for economic complexity. Furthermore, there is a positive interaction between economic complexity and CO 2 emissions for middle-income countries. Regarding high-income countries, however, increasing economic complexity might effectively reduce CO 2 emissions, and CO 2 emissions can significantly increase economic complexity. Additionally, economic complexity will prominently decrease GDP in low-income countries. These findings are robust to different economic complexity indexes. Our results suggest that both developing and developed countries should set a reasonable CO 2 emissions target, and on this basis, maintain a good balance between economic complexity and CO 2 emissions.

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