Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/87342 
Year of Publication: 
2011
Series/Report no.: 
Tinbergen Institute Discussion Paper No. 11-141/4
Publisher: 
Tinbergen Institute, Amsterdam and Rotterdam
Abstract: 
Experts can rely on statistical model forecasts when creating their own forecasts. Usually it is not known what experts actually do. In this paper we focus on three questions, which we try to answer given the availability of expert forecasts and model forecasts. First, is the expert forecast related to the model forecast and how? Second, how is this potential relation influenced by other factors? Third, how does this relation influence forecast accuracy? We propose a new and innovative two-level Hierarchical Bayes model to answer these questions. We apply our proposed methodology to a large data set of forecasts and realizations of SKU-level sales data from a pharmaceutical company. We find that expert forecasts can depend on model forecasts in a variety of ways. Average sales levels, sales volatility, and the forecast horizon influence this dependence. We also demonstrate that theoretical implications of expert behavior on forecast accuracy are reflected in the empirical data.
Subjects: 
model forecasts
expert forecasts
forecast adjustment
Bayesian analysis
endogeneity
JEL: 
C11
C53
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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