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Open AccessArticle

The Environmental Impacts and Optimal Environmental Policies of Macroeconomic Uncertainty Shocks: A Dynamic Model Approach

The Research Institute of Economics and Management, Southwestern University of Finance and Economics, Chengdu 611130, China
Sustainability 2019, 11(18), 4993; https://doi.org/10.3390/su11184993
Received: 26 August 2019 / Revised: 3 September 2019 / Accepted: 10 September 2019 / Published: 12 September 2019
The existing literature on carbon policy analysis in a random environment focuses on the existence of the level (first-moment) shocks, whereas recent research emphasized the nonnegligible impact of uncertainty (second-moment) shocks on macroeconomy. This paper studies the impact of uncertainty (second-moment) shocks on the carbon emissions, abatement investment, and output. We construct an environmental dynamic stochastic general equilibrium (E-DSGE) model that features uncertainty shocks from the good demand and supply. By comparing the social welfare among carbon taxation, intensity, and capacity regimes, we show that the carbon taxation is the best policy regarding positive uncertainty shocks of households preference (good demand), whereas capacity and intensity targets are preferable under the uncertainty shocks of firms productivity (good supply). View Full-Text
Keywords: environmental policy; uncertainty shock; E-DSGE model environmental policy; uncertainty shock; E-DSGE model
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MDPI and ACS Style

Chan, Y.T. The Environmental Impacts and Optimal Environmental Policies of Macroeconomic Uncertainty Shocks: A Dynamic Model Approach. Sustainability 2019, 11, 4993. https://doi.org/10.3390/su11184993

AMA Style

Chan YT. The Environmental Impacts and Optimal Environmental Policies of Macroeconomic Uncertainty Shocks: A Dynamic Model Approach. Sustainability. 2019; 11(18):4993. https://doi.org/10.3390/su11184993

Chicago/Turabian Style

Chan, Ying T. 2019. "The Environmental Impacts and Optimal Environmental Policies of Macroeconomic Uncertainty Shocks: A Dynamic Model Approach" Sustainability 11, no. 18: 4993. https://doi.org/10.3390/su11184993

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