IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

The Social Cost of Stochastic and Irreversible Climate Change

  • Yongyang Cai
  • Kenneth L. Judd
  • Thomas S. Lontzek

There is great uncertainty about the impact of anthropogenic carbon on future economic wellbeing. We use DSICE, a DSGE extension of the DICE2007 model of William Nordhaus, which incorporates beliefs about the uncertain economic impact of possible climate tipping events and uses empirically plausible parameterizations of Epstein-Zin preferences to represent attitudes towards risk. We find that the uncertainty associated with anthropogenic climate change imply carbon taxes much higher than implied by deterministic models. This analysis indicates that the absence of uncertainty in DICE2007 and similar models may result in substantial understatement of the potential benefits of policies to reduce GHG emissions.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.nber.org/papers/w18704.pdf
Download Restriction: Access to the full text is generally limited to series subscribers, however if the top level domain of the client browser is in a developing country or transition economy free access is provided. More information about subscriptions and free access is available at http://www.nber.org/wwphelp.html. Free access is also available to older working papers.

As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 18704.

as
in new window

Length:
Date of creation: Jan 2013
Date of revision:
Handle: RePEc:nbr:nberwo:18704
Note: EEE
Contact details of provider: Postal: National Bureau of Economic Research, 1050 Massachusetts Avenue Cambridge, MA 02138, U.S.A.
Phone: 617-868-3900
Web page: http://www.nber.org
Email:


More information through EDIRC

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Mort Webster & Nidhi Santen & Panos Parpas, 2012. "An approximate dynamic programming framework for modeling global climate policy under decision-dependent uncertainty," Computational Management Science, Springer, vol. 9(3), pages 339-362, August.
  2. Weitzman, Martin L., 2009. "On Modeling and Interpreting the Economics of Catastrophic Climate Change," Scholarly Articles 3693423, Harvard University Department of Economics.
  3. Lemoine, Derek M. & Traeger, Christian P., 2011. "Tipping points and ambiguity in the economics of climate change," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt9nd591ww, Department of Agricultural & Resource Economics, UC Berkeley.
  4. Yongyang Cai & Kenneth L. Judd & Thomas S. Lontzek, 2012. "Continuous-Time Methods for Integrated Assessment Models," NBER Working Papers 18365, National Bureau of Economic Research, Inc.
  5. Christian Traeger, 2014. "Why uncertainty matters: discounting under intertemporal risk aversion and ambiguity," Economic Theory, Springer, vol. 56(3), pages 627-664, August.
  6. Nordhaus, William D & Yang, Zili, 1996. "A Regional Dynamic General-Equilibrium Model of Alternative Climate-Change Strategies," American Economic Review, American Economic Association, vol. 86(4), pages 741-65, September.
  7. Geoffrey Heal & Bengt Kriström, 2002. "Uncertainty and Climate Change," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 22(1), pages 3-39, June.
  8. Cochrane, John H. & Campbell, John, 1999. "By Force of Habit: A Consumption-Based Explanation of Aggregate Stock Market Behavior," Scholarly Articles 3119444, Harvard University Department of Economics.
  9. Kreps, David M & Porteus, Evan L, 1978. "Temporal Resolution of Uncertainty and Dynamic Choice Theory," Econometrica, Econometric Society, vol. 46(1), pages 185-200, January.
  10. Crost, Benjamin & Traeger, Christian P., 2011. "Risk and aversion in the integrated assessment of climate change," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt1562s275, Department of Agricultural & Resource Economics, UC Berkeley.
  11. Yongyang Cai & Kenneth L. Judd, 2012. "Dynamic Programming with Hermite Approximation," NBER Working Papers 18540, National Bureau of Economic Research, Inc.
  12. Epstein, Larry G & Zin, Stanley E, 1989. "Substitution, Risk Aversion, and the Temporal Behavior of Consumption and Asset Returns: A Theoretical Framework," Econometrica, Econometric Society, vol. 57(4), pages 937-69, July.
  13. 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.
  14. Thomas S. Lontzek & Daiju Narita, 2011. "Risk‐Averse Mitigation Decisions in an Unpredictable Climate System," Scandinavian Journal of Economics, Wiley Blackwell, vol. 113(4), pages 937-958, December.
  15. Anthony Fisher & Urvashi Narain, 2003. "Global Warming, Endogenous Risk, and Irreversibility," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 25(4), pages 395-416, August.
  16. Annette Vissing-J�rgensen & Orazio P. Attanasio, 2003. "Stock-Market Participation, Intertemporal Substitution, and Risk-Aversion," American Economic Review, American Economic Association, vol. 93(2), pages 383-391, May.
  17. 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.
  18. 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.
  19. Yongyang Cai & Kenneth L. Judd, 2010. "Stable and Efficient Computational Methods for Dynamic Programming," Journal of the European Economic Association, MIT Press, vol. 8(2-3), pages 626-634, 04-05.
  20. Ravi Bansal & Amir Yaron, 2004. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," Journal of Finance, American Finance Association, vol. 59(4), pages 1481-1509, 08.
  21. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, June.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:18704. 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: ()

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 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.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.