Uncertainty, Learning, and Optimal Technological Portfolios: A Dynamic General Equilibrium Approach to Climate Change

Seung-Rae Kim ()

No 54, Computing in Economics and Finance 2005 from Society for Computational Economics

Abstract: How is the design of efficient climate policies affected by the potentials for induced technological change and for future learning about key parameter uncertainties? We address this question using a new integrated climate-economy model incorporating endogenous technological change to explore optimal technological portfolios against global warming in the presence of uncertainty and learning. We explicitly consider the interplays between induced innovation, the stringency of environmental policies, and possible environmental risks within the general equilibrium framework of probabilistic integrated assessment. We find that the value of resolving key scientific uncertainties would be non-trivial in the face of binding climate limits, but at the same time it can significantly decrease with induced innovation and knowledge spillovers that might otherwise be absent. The results also show that scientific uncertainties in climate change could justify immediate mitigation actions and accelerated investments in new energy technologies, reflecting risk-reducing considerations.

Keywords: Uncertainty; Learning; Optimal technological portfolios; Endogenous technological change; Stochastic growth model; Probabilistic integrated assessment; Carbon-free technology; Expected value of information (search for similar items in EconPapers)
JEL-codes: D81 O33 Q28 (search for similar items in EconPapers)
Date: 2005-11-11
New Economics Papers: this item is included in nep-dge and nep-ene
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