Open AccessA Bayesian approach to estimating benefits of improved forecasts
Author(s) -
KitePowell Hauke L.,
Solow Andrew R.
Publication year - 1994
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.5060010405
Subject(s) - bayesian probability , computer science , econometrics , consensus forecast , economics , artificial intelligence
We describe a Bayesian approach to estimating the economic benefits from improved forecasts. The approach takes explicit account of how decision makers use forecast information, and can provide more reliable estimates of benefits than methods based on mitigated impacts. We discuss some practical considerations in applying the approach to weather and climate forecasts, and describe the results of an application to ENSO prediction.