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A Recursive Method for Solving a Climate–Economy Model: Value Function Iterations with Logarithmic Approximations

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  • In Chang Hwang

    (Korea Environment Institute)

Abstract

A recursive method for solving an integrated assessment model of climate and the economy is developed in this paper. The method approximates a value function with a logarithmic basis function and searches for solutions on a set satisfying optimality conditions. These features make the method suitable for a nonlinear model with many state variables and various constraints. The method produces exact solutions to a simple economic growth model and is useful for solving more demanding models such as the well-known DICE model (dynamic integrated model of climate and the economy).

Suggested Citation

  • In Chang Hwang, 2017. "A Recursive Method for Solving a Climate–Economy Model: Value Function Iterations with Logarithmic Approximations," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 95-110, June.
    • Handle: RePEc:kap:compec:v:50:y:2017:i:1:d:10.1007_s10614-016-9583-2
    DOI: 10.1007/s10614-016-9583-2
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    References listed on IDEAS

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    1. Hennlock, Magnus, 2009. "Robust Control in Global Warming Management: An Analytical Dynamic Integrated Assessment," RFF Working Paper Series dp-09-19, Resources for the Future.
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    5. Richard S. J. Tol & In Chang Hwang & Frédéric Reynès, 2012. "The Effect of Learning on Climate Policy under Fat-tailed Uncertainty," Working Paper Series 5312, Department of Economics, University of Sussex Business School.
    6. Kelly, David L. & Tan, Zhuo, 2015. "Learning and climate feedbacks: Optimal climate insurance and fat tails," Journal of Environmental Economics and Management, Elsevier, vol. 72(C), pages 98-122.
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    13. 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.
    14. In Chang Hwang, 2016. "Active learning and optimal climate policy," EcoMod2016 9611, EcoMod.
    15. Hwang, In Chang & Reynès, Frédéric & Tol, Richard S.J., 2017. "The effect of learning on climate policy under fat-tailed risk," Resource and Energy Economics, Elsevier, vol. 48(C), pages 1-18.
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    Cited by:

    1. In Chang Hwang & Richard S. J. Tol & Marjan W. Hofkes, 2019. "Active Learning and Optimal Climate Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1237-1264, August.
    2. In Chang Hwang, 2016. "Active learning and optimal climate policy," EcoMod2016 9611, EcoMod.

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