Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/87506
Authors: 
Franses, Philip Hans
Legerstee, Rianne
Paap, Richard
Year of Publication: 
2011
Series/Report no.: 
Tinbergen Institute Discussion Paper 11-177/4
Abstract: 
We propose a new and simple methodology to estimate the loss function associated with experts' forecasts. Under the assumption of conditional normality of the data and the forecast distribution, the asymmetry parameter of the lin-lin and linex loss function can easily be estimated using a linear regression. This regression also provides an estimate for potential systematic bias in the forecasts of the expert. The residuals of the regression are the input for a test for the validity of the normality assumption. We apply our approach to a large data set of SKU-level sales forecasts made by experts and we compare the outcomes with those for statistical model-based forecasts of the same sales data. We find substantial evidence for asymmetry in the loss functions of the experts, with underprediction penalized more than overprediction.
Subjects: 
model forecasts
expert forecasts
loss functions
asymmetry
econometric models
JEL: 
C50
C53
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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