Optimal climate policy: Uncertainty versus Monte Carlo
AbstractThe integrated assessment literature frequently replicates uncertainty by averaging Monte Carlo runs of deterministic models. This Monte Carlo analysis is, in essence, an averaged sensitivity analyses. The approach resolves all uncertainty before the first time period, drawing parameters from a distribution before initiating a given model run. This paper analyzes how closely a Monte Carlo based derivation of optimal policies is to the truly optimal policy, in which the decision maker acknowledges the full set of possible future trajectories in every period. Our analysis uses a stochastic dynamic programming version of the widespread integrated assessment model DICE, and focuses on damage uncertainty. We show that the optimizing Monte Carlo approach is not only off in magnitude, but can even lead to a wrong sign of the uncertainty effect. Moreover, it can lead to contradictory policy advice, suggesting a more stringent climate policy in terms of the abatement rate and a less stringent one in terms of the expenditure on abatement.
Download InfoIf 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.
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.
Bibliographic InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 120 (2013)
Issue (Month): 3 ()
Contact details of provider:
Web page: http://www.elsevier.com/locate/ecolet
Climate change; Uncertainty; Integrated assessment; Monte Carlo; Risk aversion; DICE;
Find related papers by JEL classification:
- Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters
- Q00 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - General
- D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
- D90 - Microeconomics - - Intertemporal Choice - - - General
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
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.:
- Campbell, John, 1996.
"Understanding Risk and Return,"
3153293, Harvard University Department of Economics.
- John Y. Campbell, 1995. "Understanding Risk and Return," Harvard Institute of Economic Research Working Papers 1711, Harvard - Institute of Economic Research.
- John Y. Campbell, 1993. "Understanding Risk and Return," NBER Working Papers 4554, National Bureau of Economic Research, Inc.
- Manne, Alan S. & Richels, Richard G. & Wigley, Tom M. L., 2004. "Moving Beyond Concentrations: The Challenge of Limiting Temperature Change," Working paper 531, Regulation2point0.
- 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.
- Simon Dietz, 2009. "High impact, low probability? An empirical analysis of risk in the economics of climate change," Grantham Research Institute on Climate Change and the Environment Working Papers 9, Grantham Research Institute on Climate Change and the Environment.
- Andrew J. Leach, 2004.
"The Climate Change Learning Curve,"
Cahiers de recherche
04-03, HEC Montréal, Institut d'économie appliquée.
- 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.
- Ravi Bansal & Amir Yaron, 2000. "Risks for the Long Run: A Potential Resolution of Asset Pricing Puzzles," NBER Working Papers 8059, National Bureau of Economic Research, Inc.
- Traeger, Christian P., 2012.
"Why uncertainty matters - discounting under intertemporal risk aversion and ambiguity,"
Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series
qt2w614303, Department of Agricultural & Resource Economics, UC Berkeley.
- Traeger, Christian P, 2008. "Why uncertainty matters - discounting under intertemporal risk aversion and ambiguity," CUDARE Working Paper Series 1092R2, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy, revised Jan 2012.
- Christian Traeger, 2012. "Why Uncertainty Matters - Discounting under Intertemporal Risk Aversion and Ambiguity," CESifo Working Paper Series 3727, CESifo Group Munich.
- 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.
- Kopp, Robert E. & Golub, Alexander & Keohane, Nathaniel O. & Onda, Chikara, 2012. "The influence of the specification of climate change damages on the social cost of carbon," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 6(13), pages 1-40.
- Martin L. Weitzman, 2010. "What Is The "Damages Function" For Global Warming — And What Difference Might It Make?," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 1(01), pages 57-69.
- Millner, Antony, 2013. "On welfare frameworks and catastrophic climate risks," Journal of Environmental Economics and Management, Elsevier, vol. 65(2), pages 310-325.
- 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.
- Weil, Philippe, 1990. "Nonexpected Utility in Macroeconomics," The Quarterly Journal of Economics, MIT Press, vol. 105(1), pages 29-42, February.
- Pycroft, Jonathan & Vergano, Lucia & Hope, Chris & Paci, Daniele & Ciscar, Juan Carlos, 2011.
"A tale of tails: Uncertainty and the social cost of carbon dioxide,"
Economics - The Open-Access, Open-Assessment E-Journal,
Kiel Institute for the World Economy, vol. 5(22), pages 1-29.
- Pycroft, Jonathan & Vergano, Lucia & Hope, Chris & Paci, Daniele & Ciscar, Juan Carlos, 2011. "A tale of tails: Uncertainty and the social cost of carbon dioxide," Economics Discussion Papers 2011-36, Kiel Institute for the World Economy.
- Emi Nakamura & Jón Steinsson & Robert Barro & José Ursúa, 2013.
"Crises and Recoveries in an Empirical Model of Consumption Disasters,"
American Economic Journal: Macroeconomics,
American Economic Association, vol. 5(3), pages 35-74, July.
- Emi Nakamura & Jón Steinsson & Robert Barro & José Ursúa, 2010. "Crises and Recoveries in an Empirical Model of Consumption Disasters," NBER Working Papers 15920, National Bureau of Economic Research, Inc.
- Jose Ursua & Jon Steinsson & Emi Nakamura & Robert Barro, 2008. "Crises and Recoveries in an Empirical Model of Consumption Disasters," 2008 Meeting Papers 1089, Society for Economic Dynamics.
- 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.
- Ravi Bansal & Dana Kiku & Amir Yaron, 2010. "Long Run Risks, the Macroeconomy, and Asset Prices," American Economic Review, American Economic Association, vol. 100(2), pages 542-46, May.
- Ackerman, Frank & Stanton, Elizabeth A. & Bueno, Ramón, 2010. "Fat tails, exponents, extreme uncertainty: Simulating catastrophe in DICE," Ecological Economics, Elsevier, vol. 69(8), pages 1657-1665, June.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
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.