U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights

Long-Term Economic Modeling for Climate Change Assessment
Published: November 01, 2015
Posted: December 21, 2015

Large-scale applied general equilibrium models play a key role in enabling decision makers to evaluate the implications of proposed energy or climate strategies. A growing concern, however, has been whether these models produce reliable projections, which necessitates improving model accuracy and gauging performance on an ongoing basis. In a recent study, Department of Energy-funded researchers at the Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change enhanced and tested the MIT Economic Projection and Policy Analysis (EPPA) model. They introduced a new strategy for modeling the final consumption of various goods, compared results of historical simulations against actual data, and conducted sensitivity analyses of future projections to key parameters under various scenarios. The researchers found that historical simulations of energy use performed better for developed regions than developing regions; the new consumer modeling strategy improved representation of shifts in consumption patterns; and emissions results were more sensitive to gross domestic product growth than energy and nonenergy substitution elasticity or autonomous (non-price-driven) efficiency improvement. The improved model thus can provide more accurate projections for decision makers to refer to when evaluating the cost-effectiveness of different climate change mitigation strategies.

Reference: Chen, Y.-H., S. Paltsev, J. M. Reilly, J. F. Morris, and M. H. Babiker. 2015. “Long-Term Economic Modeling for Climate Change Assessment,” Economic Modelling 52(Part B), 867–83. DOI: 10.1016/j.econmod.2015.10.023. (Reference link)

Contact: Bob Vallario, SC 23.1, (301) 903-5758
Topic Areas:

  • Research Area: Multisector Dynamics (formerly Integrated Assessment)

Division: SC-23.1 Climate and Environmental Sciences Division, BER


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