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Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison

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  • Babiker, Mustafa
  • Gurgel, Angelo
  • Paltsev, Sergey
  • Reilly, John

Abstract

This paper develops a multi-regional general equilibrium model for climate policy analysis based on the latest version of the MIT Emissions Prediction and Policy Analysis (EPPA) model. We develop two versions so that we can solve the model either as a fully inter-temporal optimization problem (forward-looking, perfect foresight) or recursively. The standard EPPA model on which these models are based is solved recursively, and it is necessary to simplify some aspects of it to make inter-temporal solution possible. The forward-looking capability allows one to better address economic and policy issues such as borrowing and banking of GHG allowances, efficiency implications of environmental tax recycling, endogenous depletion of fossil resources, international capital flows, and optimal emissions abatement paths among others. To evaluate the solution approaches, we benchmark each version to the same macroeconomic path, and then compare the behavior of the two versions under a climate policy that restricts greenhouse gas emissions. We find that the energy sector and CO2 price behavior are similar in both versions (in the recursive version of the model we force the inter-temporal theoretical efficiency result that abatement through time should be allocated such that the CO2 price rises at the interest rate.) The main difference that arises is that the macroeconomic costs are substantially lower in the forward-looking version of the model, since it allows consumption shifting as an additional avenue of adjustment to the policy. On the other hand, the simplifications required for solving the model as an optimization problem, such as dropping the full vintaging of the capital stock and fewer explicit technological options, likely have effects on the results. Moreover, inter-temporal optimization with perfect foresight poorly represents the real economy where agents face high levels of uncertainty that likely lead to higher costs than if they knew the future with certainty. We conclude that while the forward-looking model has value for some problems, the recursive model produces similar behavior in the energy sector and provides greater flexibility in the details of the system that can be represented.

Suggested Citation

  • Babiker, Mustafa & Gurgel, Angelo & Paltsev, Sergey & Reilly, John, 2009. "Forward-looking versus recursive-dynamic modeling in climate policy analysis: A comparison," Economic Modelling, Elsevier, vol. 26(6), pages 1341-1354, November.
  • Handle: RePEc:eee:ecmode:v:26:y:2009:i:6:p:1341-1354
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    References listed on IDEAS

    as
    1. John Reilly, Marcus Sarofim, Sergey Paltsev and Ronald Prinn, 2006. "The Role of Non-CO2 GHGs in Climate Policy: Analysis Using the MIT IGSM," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 503-520.
    2. Henry D. Jacoby & Richard S. Eckaus & A. Denny Ellerman & Ronald G. Prinn & David M. Reiner & Zili Yang, 1997. "CO2 Emissions Limits: Economic Adjustments and the Distribution of Burdens," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 31-58.
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    4. Babiker, Mustafa & Reilly, John M. & Jacoby, Henry D., 2000. "The Kyoto Protocol and developing countries," Energy Policy, Elsevier, vol. 28(8), pages 525-536, July.
    5. McFarland, J. R. & Reilly, J. M. & Herzog, H. J., 2004. "Representing energy technologies in top-down economic models using bottom-up information," Energy Economics, Elsevier, vol. 26(4), pages 685-707, July.
    6. Rutherford, Thomas F., 1995. "Extension of GAMS for complementarity problems arising in applied economic analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 19(8), pages 1299-1324, November.
    7. Harold Hotelling, 1931. "The Economics of Exhaustible Resources," Journal of Political Economy, University of Chicago Press, vol. 39, pages 137-137.
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