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Modeling the impact of a carbon tax: A trial analysis for Washington State

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  • Mori, Keibun

Abstract

In recent years, energy policy makers have proposed a carbon tax as an economy-wide policy tool to curb greenhouse gas (GHG) emissions. The quantification of its impact on GHG emissions has relied on an energy-economy model, whose complexity often makes it difficult to comprehend how it simulates the interaction of a carbon tax and energy demand. This study therefore aims at developing an alternative model called the Carbon Tax Analysis Model (C-TAM). The elasticity-based approach used in C-TAM is less sophisticated than an equilibrium-based approach used in an energy-economy model, but C-TAM is designed to maximize its predictive capabilities by using a wide range of elasticities for each sector and fuel use, accounting for likely changes in fuel mix for electricity generation, and addressing the model's sensitivity to elasticity estimates with Monte Carlo simulation. The trial analysis in this study evaluates a potential carbon tax in Washington State, suggesting a carbon tax at US$30 per metric ton of CO2 (tCO2) lowers GHG emissions by 8.4% from the business-as-usual (BAU) scenario in 2035. The study concludes that C-TAM can provide meaningful policy implications by forecasting detailed impact on revenues and energy demand for each sector and fuel use.

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  • Mori, Keibun, 2012. "Modeling the impact of a carbon tax: A trial analysis for Washington State," Energy Policy, Elsevier, vol. 48(C), pages 627-639.
    • Handle: RePEc:eee:enepol:v:48:y:2012:i:c:p:627-639
    DOI: 10.1016/j.enpol.2012.05.067
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    2. Alberto Gago & Xavier Labandeira & Xiral López Otero, 2014. "A Panorama on Energy Taxes and Green Tax Reforms," Hacienda Pública Española / Review of Public Economics, IEF, vol. 208(1), pages 145-190, March.
    3. Freyre, Alisa & Klinke, Sandra & Patel, Martin K., 2020. "Carbon tax and energy programs for buildings: Rivals or allies?," Energy Policy, Elsevier, vol. 139(C).
    4. Runst, Petrik & Thonipara, Anita, 2020. "Dosis facit effectum why the size of the carbon tax matters: Evidence from the Swedish residential sector," Energy Economics, Elsevier, vol. 91(C).
    5. Domon, Shohei & Hirota, Mayu & Kono, Tatsuhito & Managi, Shunsuke & Matsuki, Yusuke, 2022. "The long-run effects of congestion tolls, carbon tax, and land use regulations on urban CO2 emissions," Regional Science and Urban Economics, Elsevier, vol. 92(C).
    6. Wang, Nan & Mogi, Gento, 2017. "Industrial and residential electricity demand dynamics in Japan: How did price and income elasticities evolve from 1989 to 2014?," Energy Policy, Elsevier, vol. 106(C), pages 233-243.
    7. Lucia Rotaris & Alessandro Gardelli, 2018. "Carbon Tax acceptability: A comparative experimental analysis," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2018(1), pages 117-132.
    8. Dong, Huijuan & Dai, Hancheng & Geng, Yong & Fujita, Tsuyoshi & Liu, Zhe & Xie, Yang & Wu, Rui & Fujii, Minoru & Masui, Toshihiko & Tang, Liang, 2017. "Exploring impact of carbon tax on China’s CO2 reductions and provincial disparities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 596-603.
    9. Yang, Mian & Fan, Ying & Yang, Fuxia & Hu, Hui, 2014. "Regional disparities in carbon dioxide reduction from China's uniform carbon tax: A perspective on interfactor/interfuel substitution," Energy, Elsevier, vol. 74(C), pages 131-139.
    10. Knizley, Alta A. & Mago, Pedro J. & Smith, Amanda D., 2014. "Evaluation of the performance of combined cooling, heating, and power systems with dual power generation units," Energy Policy, Elsevier, vol. 66(C), pages 654-665.
    11. Nikos Sakkas & Sofia Yfanti & Costas Daskalakis & Eduard Barbu & Marharyta Domnich, 2021. "Interpretable Forecasting of Energy Demand in the Residential Sector," Energies, MDPI, vol. 14(20), pages 1-17, October.
    12. Runst, Petrik & Thonipara, Anita, 2019. "Dosis facit effectum: Why the scope of the carbon tax matters - Evidence from the Swedish residential sector," ifh Working Papers 19/2019, Volkswirtschaftliches Institut für Mittelstand und Handwerk an der Universität Göttingen (ifh).
    13. Wang, Banban & Wei, Jie & Tan, Xiujie & Su, Bin, 2021. "The sectorally heterogeneous and time-varying price elasticities of energy demand in China," Energy Economics, Elsevier, vol. 102(C).
    14. Miller, Mark & Alberini, Anna, 2016. "Sensitivity of price elasticity of demand to aggregation, unobserved heterogeneity, price trends, and price endogeneity: Evidence from U.S. Data," Energy Policy, Elsevier, vol. 97(C), pages 235-249.

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