A Bayesian technique for refining the uncertainty in global energy model forecasts

• Main Authors: Tschang, F. Ted, Dowlatabadi, Hadi
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 1995
• Subjects: Bayesian updating; Forecasting; Energy model; Uncertainty analysis; Business; Management Sciences and Quantitative Methods
• Online Access: https://ink.library.smu.edu.sg/lkcsb_research/2283; https://ink.library.smu.edu.sg/context/lkcsb_research/article/3282/viewcontent/1_s2.0_016920709402010M_main.pdf
• Institution: Singapore Management University

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 u...