IDEAS home Printed from https://ideas.repec.org/p/fem/femwpa/2016.10.html
   My bibliography  Save this paper

Adapting to Climate Change: an Analysis under Uncertainty

Author

Listed:
  • David García-León

    (University of Alicante)

Abstract

Climate change is a phenomenon beset with major uncertainties and researchers should include them in Integrated Assessment Models. However, including further dimensions in IAM models comes at a cost. In particular, it makes most of these models suffer from the curse of dimensionality. In this study we benefit from a state-reduced framework to overcome those problems. In an attempt to advance in the modelling of adaptation within IAM models, we apply this methodology to shed some light on how the optimal balance between mitigation and adaptation changes under different stochastic scenarios. We find that stochastic technology growth hardly affects the optimal bundle of mitigation and adaptation whereas uncertainty about the value of climate sensitivity and the possibility of tipping points hitting the system change substantially the composition of the optimal mix as both persuade the risk-averse social planner to invest more in mitigation. Overall, we identify that including uncertainty into the model tends to favour (long-lasting) mitigation with respect to (instantaneous) adaptation. Further research should address the properties of the optimal mix when a stock of adaptation can be built.

Suggested Citation

  • David García-León, 2016. "Adapting to Climate Change: an Analysis under Uncertainty," Working Papers 2016.10, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2016.10
    as

    Download full text from publisher

    File URL: http://www.feem.it/userfiles/attach/2016217113194NDL2016-010.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Francesco Bosello & Carlo Carraro & Enrica De Cian, 2010. "Climate Policy and the Optimal Balance between Mitigation, Adaptation and Unavoided Damage," Working Papers 2010.32, Fondazione Eni Enrico Mattei.
    2. Derek Lemoine & Christian Traeger, 2014. "Watch Your Step: Optimal Policy in a Tipping Climate," American Economic Journal: Economic Policy, American Economic Association, vol. 6(1), pages 137-166, February.
    3. Kelly, David L & Kolstad, Charles D, 2001. "Solving Infinite Horizon Growth Models with an Environmental Sector," Computational Economics, Springer;Society for Computational Economics, vol. 18(2), pages 217-231, October.
    4. Richard Tol, 1999. "Spatial and Temporal Efficiency in Climate Policy: Applications of FUND," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 14(1), pages 33-49, July.
    5. P. R. Kumaraswamy, 2013. "Introduction," China Report, , vol. 49(1), pages 1-3, February.
    6. Christian Traeger, 2014. "A 4-Stated DICE: Quantitatively Addressing Uncertainty Effects in Climate Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 59(1), pages 1-37, September.
    7. Kelly, David L. & Kolstad, Charles D., 1999. "Bayesian learning, growth, and pollution," Journal of Economic Dynamics and Control, Elsevier, vol. 23(4), pages 491-518, February.
    8. Zmarak Shalizi & Franck Lecocq, 2010. "To Mitigate or to Adapt: Is that the Question? Observations on an Appropriate Response to the Climate Change Challenge to Development Strategies," World Bank Research Observer, World Bank Group, vol. 25(2), pages 295-321, August.
    9. Leach, Andrew J., 2007. "The climate change learning curve," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1728-1752, May.
    10. Jensen, Svenn & Traeger, Christian P., 2014. "Optimal climate change mitigation under long-term growth uncertainty: Stochastic integrated assessment and analytic findings," European Economic Review, Elsevier, vol. 69(C), pages 104-125.
    11. Keller, Klaus & Bolker, Benjamin M. & Bradford, D.F.David F., 2004. "Uncertain climate thresholds and optimal economic growth," Journal of Environmental Economics and Management, Elsevier, vol. 48(1), pages 723-741, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Climate Change; Adaptation; Mitigation; Dynamic Programming; Uncertainty; Integrated Assessment; DICE;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

    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:2016.10. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (barbara racah). General contact details of provider: http://edirc.repec.org/data/feemmit.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.