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An analysis of US greenhouse gas cap-and-trade proposals using a forward-looking economic model

Published online by Cambridge University Press:  14 February 2011

ANGELO COSTA GURGEL
Affiliation:
College of Economics, Business and Accounting of Ribeirao Preto – University of Sao Paulo (FEA-RP/USP), Av. Bandeirantes 3900, Ribeirao Preto – SP, 14040-900Brazil. Email: angelocg@usp.br; gurgel@mit.edu
SERGEY PALTSEV
Affiliation:
MIT Joint Program on the Science and Policy of Global Change. Email: paltsev@mit.edu
JOHN REILLY
Affiliation:
MIT Joint Program on the Science and Policy of Global Change. Email: jreilly@mit.edu
GILBERT METCALF
Affiliation:
Department of Economics, Tufts University. Email: gilbert.metcalf@tufts.edu

Abstract

We develop a forward-looking version of the recursive dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model, and apply it to examine the economic implications of proposals in the US Congress to limit greenhouse gas (GHG) emissions. We find that shocks in the consumption path are smoothed out in the forward-looking model and that the lifetime welfare cost of GHG policy is lower than in the recursive model, since the forward-looking model can fully optimize over time. The forward-looking model allows us to explore issues for which it is uniquely well suited, including revenue-recycling and early action crediting. We find capital tax recycling to be more welfare-cost reducing than labor tax recycling because of its long-term effect on economic growth. Also, there are substantial incentives for early action credits; however, when spread over the full horizon of the policy they do not have a substantial effect on lifetime welfare costs.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2011

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References

Babiker, M. and Eckaus, R. (2002), ‘Rethinking the Kyoto emissions targets’, Climatic Change 54: 339414.CrossRefGoogle Scholar
Babiker, M., Gurgel, A., Paltsev, S., and Reilly, J. (2009), ‘Forward-looking versus recursive-dynamic modeling in climate policy analysis: a comparison’, Economic Modelling 26: 13411354.CrossRefGoogle Scholar
Babiker, M., Metcalf, G., and Reilly, J. (2003), ‘Tax distortions and global climate policy’, Journal of Economic and Environmental Management 46: 269287.CrossRefGoogle Scholar
Babiker, M., Reilly, J., and Jacoby, H. (2000), ‘The Kyoto Protocol and developing countries’, Energy Policy 28: 525536.CrossRefGoogle Scholar
Bovenberg, A.L., Goulder, L., and Gurney, D. (2005), ‘Efficiency costs of meeting industry-distributional constraints under environmental permits and taxes’, Rand Journal of Economics 36: 951971.Google Scholar
Brooke, A., Kendrick, D., Meeraus, A., and Raman, R. (1998), GAMS: A User's Guide, GAMS Development Corporation, 262pp.Google Scholar
Cretegny, L. and Rutherford, T.F. (2004), ‘Worked examples in dynamic optimization: analytic and numeric methods’ [Available at] http://www.mpsge.org/dyn-optm.pdf, accessed on March 20, 2006.Google Scholar
Dimaranan, B. and McDougall, R. (2002), Global Trade, Assistance, and Production: The GTAP 5 Data Base, West Lafayette: Center for Global Trade Analysis, Purdue University.Google Scholar
Hertel, T. (1997), Global Trade Analysis: Modeling and Applications, Cambridge, UK: Cambridge University Press.Google Scholar
Jacoby, H.D., Eckhaus, R.S., Ellerman, A.D., Prinn, R.G., Reiner, D.M., and Yang, Z. (1997), ‘CO2 emissions limits: economic adjustments and the distribution of burdens’, The Energy Journal 18: 3158.CrossRefGoogle Scholar
Mathiesen, L. (1985), ‘Computation of economic equilibrium by a sequence of linear complementarity problems’, Mathematical Programming Study 23: 144162.CrossRefGoogle Scholar
McFarland, J., Reilly, J., and Herzog, H.J. (2004), ‘Representing energy technologies in top-down economic models using bottom-up information’, Energy Economics 26: 685707.CrossRefGoogle Scholar
Paltsev, S. (2004), ‘Moving from static to dynamic general equilibrium economic models (Notes for a beginner in MPSGE)’, MIT Joint Program on the Science and Policy of Global Change Technical Note 4, Cambridge, MA.Google Scholar
Paltsev, S., Reilly, J.M., Jacoby, H.D., Eckaus, R.S., McFarland, J., Sarofim, M., Asadoorian, M., and Babiker, M. (2005), ‘The MIT Emissions Prediction and Policy Analysis (EPPA) model: Version 4’, MIT Joint Program on the Science and Policy of Global Change Report 125, Cambridge, MA.Google Scholar
Paltsev, S., Reilly, J.M., Jacoby, H.D., Gurgel, A.C., Metcalf, G.E., Sokolov, A.P., and Holak, J.F. (2008), ‘Assessment of U.S. cap-and-trade proposals’, Climate Policy 8: 395420.CrossRefGoogle Scholar
Rasmussen, T.N. and Rutherford, T.F. (2004), ‘Modeling overlapping generations in a complementarity format’, Journal of Economic Dynamics and Control 28: 13831409.CrossRefGoogle Scholar
Reilly, J., Sarofim, M., Paltsev, S., and Prinn, E. (2006), ‘The role of non-CO2 greenhouse gases in climate policy: analysis using the MIT IGSM’, Energy Journal 27, Special Issue on Multigas Mitigation and Climate Policy: 503–520.CrossRefGoogle Scholar
Rutherford, T.F. (1995), ‘Extension of GAMS for complementarity problems arising in applied economic analysis’, Journal of Economic Dynamics and Control 19: 12991324.CrossRefGoogle Scholar
Rutherford, T.F. (1998), ‘Overlapping Generations with Pure Exchange: An MPSGE Formulation’, University of Colorado, Mimeo [Available at] http://www.mpsge.org/olgmcp/default.htm, accessed on March 18, 2006.Google Scholar
Rutherford, T.F. (2005), ‘Using Finite-Dimensional Complementarity Problems to Approximate Infinite-Horizon Optimization Models’, University of Colorado, Mimeo [Available at] http://www.mpsge.org/ramseynlp/ramseynlp.htm, accessed on February 26, 2006.Google Scholar
Sue Wing, I. and Popp, D. (2006), ‘Representing endogenous technological change in economic models’, in Hanneman, M. and Farrell, A. (eds), Managing Greenhouse Gas Emissions in California, Chapter 7, The California Climate Change Center, U.C. Berkeley California.Google Scholar
United States Climate Change Science Program - U.S. CCSP (2007), ‘CCSP synthesis and assessment product 2.1, Part A: scenarios of greenhouse gas emissions and atmospheric concentrations’, in Clarke, L. et al. , U.S. Climate Change Science Program, Washington, DC: Department of Energy.Google Scholar
Webster, M.D., Forest, C., Reilly, J., Babiker, M., Kicklighter, D., Mayer, M., Prinn, R., Sarofim, M., Sokolov, A., Stone, P., and Wang, C. (2003), ‘Uncertainty analysis of climate change and policy response’, Climatic Change 61: 295320.CrossRefGoogle Scholar
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