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Privatizing Climate Change Policy: Is there a Public Benefit?

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  • Daniel Matisoff

Abstract

The Chicago Climate Exchange (CCX) and the Carbon Disclosure Project (CDP) are two private voluntary initiatives aimed at reducing carbon emissions and improving carbon management by firms. I sample power plants from firms participating in each of these programs, and match these to plants belonging to non-participating firms, to control for differences between participating and non-participating plants. Using a difference-in-differences model to control for unobservable differences between participants and non-participants, and to control for the trajectory of emissions prior to program participation, I find that the CCX is associated with a decrease in total carbon dioxide emissions for participating plants when non-publicly traded firms are included in the sample. Effects are produced largely by decreases in output. CCX participation is associated with increases in carbon dioxide intensity. The CDP is not associated with a decrease of carbon dioxide emissions or electricity generation, and program participation is associated with an increase in carbon dioxide intensity. I explore these results within the context of voluntary environmental programs to address carbon emissions. Copyright Springer Science+Business Media B.V. 2012

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  • Daniel Matisoff, 2012. "Privatizing Climate Change Policy: Is there a Public Benefit?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 53(3), pages 409-433, November.
    • Handle: RePEc:kap:enreec:v:53:y:2012:i:3:p:409-433
    DOI: 10.1007/s10640-012-9568-0
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    Cited by:

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    2. Will Gans & Beat Hintermann, 2013. "Market Effects of Voluntary Climate Action by Firms: Evidence from the Chicago Climate Exchange," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 55(2), pages 291-308, June.
    3. Lin, Boqiang & Jia, Zhijie, 2017. "The impact of Emission Trading Scheme (ETS) and the choice of coverage industry in ETS: A case study in China," Applied Energy, Elsevier, vol. 205(C), pages 1512-1527.
    4. Huo, Da & Zhang, Xiaotao & Hu, Chao & Tang, Aidi & Chen, Yongchuan & Chen, Fang & Chen, Zhanming & Xu, Weiyin, 2023. "Spatial externality of journalism on carbon efficiency: A quasi-natural experiment based on interplay of journalism-based professionally generated content and digital economy," Economic Analysis and Policy, Elsevier, vol. 80(C), pages 1326-1336.
    5. Daniel Matisoff, 2015. "Sources of specification errors in the assessment of voluntary environmental programs: understanding program impacts," Policy Sciences, Springer;Society of Policy Sciences, vol. 48(1), pages 109-126, March.
    6. Sanjay Patnaik, 2020. "Emissions permit allocation and strategic firm behavior: Evidence from the oil sector in the European Union emissions trading scheme," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 976-995, March.
    7. Matisoff, Daniel C., 2013. "Different rays of sunlight: Understanding information disclosure and carbon transparency," Energy Policy, Elsevier, vol. 55(C), pages 579-592.
    8. Gao, Yuning & Li, Meng & Xue, Jinjun & Liu, Yu, 2020. "Evaluation of effectiveness of China's carbon emissions trading scheme in carbon mitigation," Energy Economics, Elsevier, vol. 90(C).
    9. Lily Hsueh, 2019. "Opening up the firm: What explains participation and effort in voluntary carbon disclosure by global businesses? An analysis of internal firm factors and dynamics," Business Strategy and the Environment, Wiley Blackwell, vol. 28(7), pages 1302-1322, November.
    10. Bowen Zhou & Michiyuki Yagi & Katsuhiko Kokubu, 2015. "An empirical examination of how the corporate governance and strategy affect GHG emissions efficiency," Discussion Papers 2015-27, Kobe University, Graduate School of Business Administration.

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    More about this item

    Keywords

    Voluntary environmental programs; Climate change policy; Chicago climate exchange; Carbon disclosure project; Difference-in-differences model; Propensity score matching; Greenwash; Q50; Q54; Q58; D80; C23;
    All these keywords.

    JEL classification:

    • Q50 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - General
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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