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A Meta-Analysis of the Economic Impacts of Climate Change Policy in the United States

Adam Rose and Noah Dormady

Year: 2011
Volume: Volume 32
Number: Number 2
DOI: 10.5547/ISSN0195-6574-EJ-Vol32-No2-6
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Abstract:
This paper provides a meta-analysis of a broad set of recent studies of the economic impacts of climate change mitigation policies. It evaluates the influences of the impacts of causal factors, key economic assumptions and macroeconomic linkages on the outcome of these studies. A quantile regression analysis is also performed on the meta sample, to evaluate the robustness of those key factors throughout the full range of macro findings. Results of these analyses suggest that study results are strongly driven by data inputs, economic assumptions and modeling approaches. However, they are sometimes affected in counterintuitive ways.



Investigating the Determinants of the Growth of the New Energy Industry: Using Quantile Regression Approach

Bin Xu and Boqiang Lin

Year: 2023
Volume: Volume 44
Number: Number 2
DOI: 10.5547/01956574.44.2.bixu
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Abstract:
Expanding the supplies of new energy can not only reduce CO2 emissions, but also alleviate energy shortage. This paper applies the quantile regression to investigate the new energy industry in China. The results show that economic growth exerts the greatest effect on the new energy industry in the lower 10th quantile province. This is because these provinces have the developed economies, demand for a higher ecological environment and new energy resources. Foreign energy dependence has a minimal impact on the new energy industry in the 25th–50th quantile province, due to their minimal oil importation. The contribution of technological progress to the upper 90th quantile province is the lowest, because their R&D capabilities are the weakest. The impact of energy consumption structure decreases in steps from the lower 10th quantile provinces to the upper 90th quantile provinces. The agricultural sector promotes the new energy industry in most provinces.





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