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• W2549773986 abstract "Explicitly representing uncertainty is recognised as a fundamental requirement of any long-term forecast. We propose and illustrate an expert elicitation protocol for constructing long-term probabilistic projections. Each projection represents a possible realization of a time series with autocorrelation properties, and thus a plausible future evolution of a quantity of interest. We illustrate the approach using two quantities – GDP growth rates and coal prices – that were elicited as part of a project producing baseline forecasts of greenhouse gas emissions in South Africa to 2050. The elicited projections can be used as inputs to deterministic structural models of the energy, economic, and environmental sectors (e3 or energy-environment-economic models), to generate similar probabilistic projections for any desired outputs of the e3 model. An R package for the generation and visualization of these probabilistic projections is provided." @default.
• W2549773986 created "2016-11-30" @default.
• W2549773986 creator A5021706963 @default.
• W2549773986 creator A5040801955 @default.
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• W2549773986 date "2017-02-01" @default.
• W2549773986 modified "2023-10-17" @default.
• W2549773986 title "Expert elicitation of autocorrelated time series with application to e3 (energy-environment-economic) forecasting models" @default.
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• W2549773986 doi "https://doi.org/10.1016/j.envsoft.2016.11.007" @default.
• W2549773986 hasPublicationYear "2017" @default.
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