IDEAS home Printed from https://ideas.repec.org/p/fem/femwpa/2004.157.html
   My bibliography  Save this paper

How Consistent are Alternative Short-Term Climate Policies with Long-Term Goals?

Author

Listed:
  • Valentina Bosetti

    (Fondazione Eni Enrico Mattei)

  • Marzio Galeotti

    (Università di Milano and Fondazione Eni Enrico Mattei)

  • Alessandro Lanza

    (Fondazione Eni Enrico Mattei, Eni S.p.A., and CreNos)

Abstract

Choosing long-term goals is a key issue in the climate policy agenda. Targets should be easily measurable and feasible, but also effective in damage control. Once goals are set globally, given the uncertainty affecting long-term strategies and region-specific preferences for different policy instruments, policies will be better represented by a diversified portfolio to be revised over time, rather than “once and forever” decisions. It therefore becomes crucial to understand to what extent different strategies (or policy portfolios) are consistent with long-term targets, that is, when they imply emission paths which do not irreversibly diverge from globally set goals. The present paper aims to investigate emission paths implied by plausible policy scenarios against those derived by imposing alternative long-term targets, comparing, for example, differences in peak periods. Plausible policy scenarios are for instance Kyoto-type targets with or without participation by the U.S. and/or by developing countries. Different long-term targets considered focus on stabilisation of CO2 concentrations, radiative forcing and the increase in atmospheric temperature relative to pre-industrial levels. In order to account for the uncertainty surrounding the climate cycle, for each long-term goal multiple paths of emission - the most probable, the optimistic and the pessimistic ones - are considered in the comparison exercise. Comparative analysis is performed using a newly developed version of the FEEM-RICE model, a regional economy-climate model of optimal economic growth which is based on Nordhaus and Boyer’s RICE model crucially extended in order to account for induced technical change. In particular, both carbon and energy intensity are affected by a new endogenous variable – Technical Progress – which captures both the role of Learning by Researching and of Learning by Doing. These are in turn determined by the optimal levels of Research and Development and of Emission Abatement.

Suggested Citation

  • Valentina Bosetti & Marzio Galeotti & Alessandro Lanza, 2004. "How Consistent are Alternative Short-Term Climate Policies with Long-Term Goals?," Working Papers 2004.157, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2004.157
    as

    Download full text from publisher

    File URL: https://feem-media.s3.eu-central-1.amazonaws.com/wp-content/uploads/NDL2004-157.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. David Popp, 2003. "ENTICE: Endogenous Technological Change in the DICE Model of Global Warming," NBER Working Papers 9762, National Bureau of Economic Research, Inc.
    2. Valentina Bosetti, Carlo Carraro and Marzio Galeotti, 2006. "The Dynamics of Carbon and Energy Intensity in a Model of Endogenous Technical Change," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 191-206.
    3. Marzio Galeotti & Carlo Carraro, 2004. "Does Endogenous Technical Change Make a Difference in Climate Policy Analysis? A Robustness Exercise with the FEEM-RICE Model," Working Papers 2004.152, Fondazione Eni Enrico Mattei.
    4. Carlo Carraro & Barbara Buchner, 2003. "China and the Evolution of the Present Climate Regime," Working Papers 2003.103, Fondazione Eni Enrico Mattei.
    5. William D. Nordhaus & David Popp, 1997. "What is the Value of Scientific Knowledge? An Application to Global Warming Using the PRICE Model," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 1-45.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Barry Anderson & Emanuele Borgonovo & Marzio Galeotti & Roberto Roson, 2014. "Uncertainty in Climate Change Modeling: Can Global Sensitivity Analysis Be of Help?," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 271-293, February.
    2. Bosetti, Valentina & Carraro, Carlo & Galeotti, Marzio, 2006. "Stabilisation Targets, Technical Change and the Macroeconomic Costs of Climate Change Control," Climate Change Modelling and Policy Working Papers 12050, Fondazione Eni Enrico Mattei (FEEM).
    3. Valentina Bosetti & Carlo Carraro & Marzio Galeotti, 2006. "The Dynamics of Carbon and Energy Intensity in a Model of Endogenous Technical Change," The Energy Journal, , vol. 27(1_suppl), pages 191-206, January.
    4. Cantore, Nicola, 2011. "Distributional aspects of emissions in climate change integrated assessment models," Energy Policy, Elsevier, vol. 39(5), pages 2919-2924, May.
    5. Marzio Galeotti & Carlo Carraro, 2004. "Does Endogenous Technical Change Make a Difference in Climate Policy Analysis? A Robustness Exercise with the FEEM-RICE Model," Working Papers 2004.152, Fondazione Eni Enrico Mattei.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wei, Yi-Ming & Mi, Zhi-Fu & Huang, Zhimin, 2015. "Climate policy modeling: An online SCI-E and SSCI based literature review," Omega, Elsevier, vol. 57(PA), pages 70-84.
    2. Radulescu, Doina & Stimmelmayr, Michael, 2010. "The impact of the 2008 German corporate tax reform: A dynamic CGE analysis," Economic Modelling, Elsevier, vol. 27(1), pages 454-467, January.
    3. Shiell, Leslie & Lyssenko, Nikita, 2014. "Climate policy and induced R&D: How great is the effect?," Energy Economics, Elsevier, vol. 46(C), pages 279-294.
    4. Lint Barrage, 2019. "The Nobel Memorial Prize for William D. Nordhaus," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(3), pages 884-924, July.
    5. Richard S. J. Tol & In Chang Hwang & Frédéric Reynès, 2012. "The Effect of Learning on Climate Policy under Fat-tailed Uncertainty," Working Paper Series 5312, Department of Economics, University of Sussex Business School.
    6. Kenneth Gillingham & William D. Nordhaus & David Anthoff & Geoffrey Blanford & Valentina Bosetti & Peter Christensen & Haewon McJeon & John Reilly & Paul Sztorc, 2015. "Modeling Uncertainty in Climate Change: A Multi-Model Comparison," NBER Working Papers 21637, National Bureau of Economic Research, Inc.
    7. Pizer, William A., 1999. "The optimal choice of climate change policy in the presence of uncertainty," Resource and Energy Economics, Elsevier, vol. 21(3-4), pages 255-287, August.
    8. Baker, Erin, 2005. "Uncertainty and learning in a strategic environment: global climate change," Resource and Energy Economics, Elsevier, vol. 27(1), pages 19-40, January.
    9. Matthias Schmidt & Hermann Held & Elmar Kriegler & Alexander Lorenz, 2013. "Climate Policy Under Uncertain and Heterogeneous Climate Damages," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 54(1), pages 79-99, January.
    10. Richard S.J. Tol, 2003. "The Marginal Costs Of Carbon Dioxide Emissions: An Assessment Of The Uncertainties," Working Papers FNU-19, Research unit Sustainability and Global Change, Hamburg University, revised Apr 2003.
    11. Grimaud, André & Lafforgue, Gilles & Magné, Bertrand, 2011. "Climate change mitigation options and directed technical change: A decentralized equilibrium analysis," Resource and Energy Economics, Elsevier, vol. 33(4), pages 938-962.
    12. Greiner, Alfred & Semmler, Willi, 2005. "Economic growth and global warming: A model of multiple equilibria and thresholds," Journal of Economic Behavior & Organization, Elsevier, vol. 57(4), pages 430-447, August.
    13. Brian C. O'Neill & Paul Crutzen & Arnulf Gr�bler & Minh Ha Duong & Klaus Keller & Charles Kolstad & Jonathan Koomey & Andreas Lange & Michael Obersteiner & Michael Oppenheimer & William Pepper & Warre, 2006. "Learning and climate change," Climate Policy, Taylor & Francis Journals, vol. 6(5), pages 585-589, September.
      • Brian C. O'Neill & Paul Crutzen & Arnulf Grübler & Minh Ha-Duong & Klaus Keller & Charles Kolstad & Jonathan Koomey & Andreas Lange & Michael Obersteiner & Michael Oppenheimer & William Pepper & Warre, 2006. "Learning and climate change," Post-Print halshs-00134718, HAL.
    14. André Grimaud & Gilles Lafforgue, 2008. "Climate change mitigation policies : Are R&D subsidies preferable to a carbon tax ?," Revue d'économie politique, Dalloz, vol. 118(6), pages 915-940.
    15. Roberto Roson & Francesco Bosello, 2007. "Estimating a Climate Change Damage Function through General Equilibrium Modeling," Working Papers 2007_08, Department of Economics, University of Venice "Ca' Foscari".
    16. Barbara Buchner & Carlo Carraro, 2004. "Economic and environmental effectiveness of a technology-based climate protocol," Climate Policy, Taylor & Francis Journals, vol. 4(3), pages 229-248, September.
    17. Marlos Goes & Nancy Tuana & Klaus Keller, 2011. "The economics (or lack thereof) of aerosol geoengineering," Climatic Change, Springer, vol. 109(3), pages 719-744, December.
    18. Stefano Giglio & Bryan Kelly & Johannes Stroebel, 2021. "Climate Finance," Annual Review of Financial Economics, Annual Reviews, vol. 13(1), pages 15-36, November.
    19. Mark Kagan, 2012. "Climate Change Skepticism in the Face of Catastrophe," Tinbergen Institute Discussion Papers 12-112/VIII, Tinbergen Institute, revised 29 Sep 2014.
    20. Johan Eyckmans & Cathrine Hagem, 2009. "The European Union's Potential for Strategic Emissions Trading through Minimal Permit Sale Contracts," CESifo Working Paper Series 2809, CESifo.

    More about this item

    Keywords

    Climate policy; Long-term climate targets; Climate sensitivity uncertainty; Capping radiative forcing;
    All these keywords.

    JEL classification:

    • H0 - Public Economics - - General
    • H2 - Public Economics - - Taxation, Subsidies, and Revenue
    • H3 - Public Economics - - Fiscal Policies and Behavior of Economic Agents

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:fem:femwpa:2004.157. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Alberto Prina Cerai (email available below). General contact details of provider: https://edirc.repec.org/data/feemmit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.