Management Sciences and Quantitative Methods Commons^™

A Bayesian Technique For Refining The Uncertainty In Global Energy Model Forecasts, F. Ted Tschang, Hadi Dowlatabadi

Research Collection Lee Kong Chian School Of Business

Global energy models have a large degree of uncertainty associated with them. This consists of uncertainty in the model structure as well as uncertainty in the exogenous input parameters. This paper combines Monte Carlo methods with Bayesian updating techniques to provide a method for refining the uncertainty in the Edmonds-Reilly global energy model. The Bayesian updating technique uses likelihood-based windows constructed from actual observations of the output variables to filter out the model simulations that do not conform with the observed output. The windows are based on outputs of energy consumption and carbon emissions. Two alternative model structures are examined: …