This paper proposes a simple method to compute prediction intervals for expert-adjusted forecasts in case the analyst does not have the underlying model forecasts and thus has to create own approximate model forecasts, based on data available to the analyst. An illustration to airline revenues data shows that experts can substantially reduce forecast uncertainty.

Additional Metadata
Keywords Airline revenues, Approximate model forecasts, Expert-adjusted forecasts, Forecast uncertainty, Prediction intervals
JEL Time-Series Models; Dynamic Quantile Regressions (jel C22), Model Evaluation and Testing (jel C52), Forecasting and Other Model Applications (jel C53)
Persistent URL hdl.handle.net/1765/130345
Journal Advances in Decision Sciences
Citation
Franses, Ph.H.B.F. (2018). Prediction intervals for expert-adjusted forecasts. Advances in Decision Sciences (Vol. 22). Retrieved from http://hdl.handle.net/1765/130345