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Solving Infinite Horizon Growth Models with an Environmental Sector

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  • Kelly, David L
  • Kolstad, Charles D

Abstract

This paper concerns computational models in environmental economics and policy, particularly so-called integrated assessment models. For the most part, such models are simply extensions of standard neoclassical growth models, extended by including the environment and pollution generation. We review the structure of integrated assessment models, distinguishing between finite horizon and infinite horizon models, both deterministic and stochastic. We present a new solution algorithm for infinite horizon integrated assessment models, relying on a neural net approximation of the value function within an iterative version of the Bellman equation. Copyright 2001 by Kluwer Academic Publishers

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Bibliographic Info

Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 18 (2001)
Issue (Month): 2 (October)
Pages: 217-31

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Handle: RePEc:kap:compec:v:18:y:2001:i:2:p:217-31

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  1. 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.
  2. repec:fth:calaec:32-98 is not listed on IDEAS
  3. Peck, Stephen C. & Teisberg, Thomas J., 1993. "Global warming uncertainties and the value of information: an analysis using CETA," Resource and Energy Economics, Elsevier, vol. 15(1), pages 71-97, March.
  4. Kydland, Finn E & Prescott, Edward C, 1982. "Time to Build and Aggregate Fluctuations," Econometrica, Econometric Society, vol. 50(6), pages 1345-70, November.
  5. Gene M. Grossman & Alan B. Krueger, 1994. "Economic Growth and the Environment," NBER Working Papers 4634, National Bureau of Economic Research, Inc.
  6. Hansen, Gary D. & Sargent, Thomas J., 1988. "Straight time and overtime in equilibrium," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 281-308.
  7. Stephen C Peck & Thomas J. Teisberg, 1992. "CETA: A Model for Carbon Emissions Trajectory Assessment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 55-78.
  8. den Haan, Wouter J & Marcet, Albert, 1990. "Solving the Stochastic Growth Model by Parameterizing Expectations," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(1), pages 31-34, January.
  9. Manne, Alan & Mendelsohn, Robert & Richels, Richard, 1995. "MERGE : A model for evaluating regional and global effects of GHG reduction policies," Energy Policy, Elsevier, vol. 23(1), pages 17-34, January.
  10. Lawrence J. Christiano, 1987. "Is consumption insufficiently sensitive to innovations in income?," Staff Report 106, Federal Reserve Bank of Minneapolis.
  11. Alan Manne & Richard Richels, 1992. "Buying Greenhouse Insurance: The Economic Costs of CO2 Emission Limits," MIT Press Books, The MIT Press, edition 1, volume 1, number 026213280x, December.
  12. Christiano, Lawrence J., 1988. "Why does inventory investment fluctuate so much?," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 247-280.
  13. Hansen, Gary D., 1985. "Indivisible labor and the business cycle," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 309-327, November.
  14. Kolstad, Charles D., 1996. "Learning and Stock Effects in Environmental Regulation: The Case of Greenhouse Gas Emissions," Journal of Environmental Economics and Management, Elsevier, vol. 31(1), pages 1-18, July.
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Cited by:
  1. Leach, Andrew J., 2007. "The climate change learning curve," Journal of Economic Dynamics and Control, Elsevier, vol. 31(5), pages 1728-1752, May.
  2. Traeger, Christian, 2012. "A 4-stated DICE: quantitatively addressing uncertainty effects in climate change," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6jx2p7fv, Department of Agricultural & Resource Economics, UC Berkeley.
  3. Derek M. Lemoine & Christian P. Traeger, 2012. "Tipping Points and Ambiguity in the Economics of Climate Change," NBER Working Papers 18230, National Bureau of Economic Research, Inc.
  4. Hwang, In Chang & Reynes, Frederic & Tol, Richard, 2014. "The effect of learning on climate policy under fat-tailed uncertainty," MPRA Paper 53681, University Library of Munich, Germany.
  5. Traeger, Christian, 2013. "A 4-stated DICE: quantitatively addressing uncertainty effects in climate change," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt9034k05t, Department of Agricultural & Resource Economics, UC Berkeley.

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