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The effectiveness of carbon pricing : The role of diversification in a firm's investment decision?

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  • Compernolle, Tine

    (Tilburg University, School of Economics and Management)

  • Kort, Peter M.

    (Tilburg University, School of Economics and Management)

  • Thijssen, Jacco J. J.

    (Tilburg University, School of Economics and Management)

Abstract

It is often argued that compared to a carbon tax, a volatile carbon price under an emissions trading system poses a problem in the transition towards a low carbon economy. However, this paper shows that, when sufficiently positively correlated with the electricity price, carbon price uncertainty diminishes overall volatility because of a diversification effect. To get this result, we develop a dynamic real options model to analyze the impact of positively correlated price uncertainty on the timing of an investment decision. In contrast to static models, we show that even when the carbon price is initially the same under both policy instruments, the timing of the investment decision will typically be different. More importantly, we find that multiple correlated price uncertainties under an emissions trading system encourages investment more than less uncertainty under a carbon tax. Hence, to stimulate a low carbon (or discourage a carbon intensive) investment, an emissions trading system (carbon tax) is preferred. The policy reverts for higher levels of uncertainty and low correlations.
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  • Compernolle, Tine & Kort, Peter M. & Thijssen, Jacco J. J., 2022. "The effectiveness of carbon pricing : The role of diversification in a firm's investment decision?," Other publications TiSEM abf6597c-1ba5-4816-a46e-8, Tilburg University, School of Economics and Management.
  • Handle: RePEc:tiu:tiutis:abf6597c-1ba5-4816-a46e-8f59cb5dfb5c
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    References listed on IDEAS

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    Cited by:

    1. Andrea Amado & Koji Kotani & Makoto Kakinaka & Shunsuke Managi, 2023. "Carbon tax for cleaner-energy transition: A vignette experiment in Japan," Working Papers SDES-2023-6, Kochi University of Technology, School of Economics and Management, revised Oct 2023.
    2. Lin, Boqiang & Li, Minyang, 2023. "Emerging Industry Development and Information Transmission in Financial Markets: Evidence from China's Renewable Energy," Energy Economics, Elsevier, vol. 128(C).
    3. Li, Yangfan & Zhang, Xiaoyun, 2023. "Recycling scheme of carbon pricing for inclusive decarbonization and energy transition: A recursive computable general equilibrium analysis in China," Renewable Energy, Elsevier, vol. 217(C).
    4. Jia, Zhijie, 2023. "The hidden benefit: Emission trading scheme and business performance of downstream enterprises," Energy Economics, Elsevier, vol. 117(C).
    5. Guo, Xiaopeng & Zhang, Xinyue & Zhang, Xingping, 2024. "Incentive-oriented power‑carbon emissions trading-tradable green certificate integrated market mechanisms using multi-agent deep reinforcement learning," Applied Energy, Elsevier, vol. 357(C).

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    More about this item

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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