Approaches for performing uncertainty analysis in large-scale energy/economic policy models

By A. Kann, John P. Weyant. 2000

159 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Environmental Engineering, Renewable Energy, Sustainability and the Environment

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Citations in the corpus

Quantifying the economic risks of climate change (2017, background): “, Nordhaus 2014, Hope 2011, Anthoff and Tol 2013), yet these return a collection of possible outcomes, each corresponding to different conditions, without identifying a single result that accounts for risk, in contrast to stochastic optimization (Kann and Weyant, 2000).”
Uncertain climate thresholds and optimal economic growth (2004, background): “Economists and climate scientists recognize the importance of uncertainty in parameters, but analyzing the combined effects of uncertainty and climate thresholds in optimal growth models has been difficult since this combination can pose nearly intractable computational problems [22,25,36].”
An integrated systematic analysis of uncertainties in UK energy transition pathways (2015, background): “…repeated calls to improve the frequency, sophistication and transparency of uncertainty analysis in computational modelling of energy, environmental and economic interactions (Morgan and Small, 1992; Kann and Weyant, 2000; Risbey et al., 2005; Pfenninger et al., 2014; Usher and Strachan, 2012).”
Future research challenges for incorporation of uncertainty in environmental and ecological decision-making (2008, background): “Kann and Weyant (2000) categorize types of uncertainty analyses that can be performed on large-scale energy/economic policy models, and develop a unifying framework (based on a stochastic dynamic optimization approach) for comparing uncertainty analyses containing different objective functions…”