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Seven components of judgmental forecasting skill: Implications for research and the improvement of forecasts
Author(s) -
Stewart Thomas R.,
Lusk Cynthia M.
Publication year - 1994
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.3980130703
Subject(s) - predictability , brier score , reliability (semiconductor) , component (thermodynamics) , forecast skill , fidelity , computer science , consensus forecast , process (computing) , probabilistic forecasting , econometrics , machine learning , artificial intelligence , probabilistic logic , statistics , economics , telecommunications , power (physics) , physics , mathematics , quantum mechanics , thermodynamics , operating system
A decomposition of the Brier skill score shows that the performance of judgmental forecasts depends on seven components: environmental predictability, fidelity of the information system, match between environment and forecaster, reliability of information acquisition, reliability of information processing, conditional bias, and unconditional bias. These components provide a framework for research on the forecasting process. Selected literature addressing each component is reviewed, and implications for improving judgmental forecasting are discussed.