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.

Additional Metadata
Keywords Bayesian analysis, endogeneity, expert forecasts, forecast adjustment, model forecasts
Publisher Erasmus School of Economics
Persistent URL hdl.handle.net/1765/26660
Series Econometric Institute Research Papers
Journal Report / Econometric Institute, Erasmus University Rotterdam
Citation
Legerstee, R, Franses, Ph.H.B.F, & Paap, R. (2011). Do experts incorporate statistical model forecasts and should they? (No. EI2011-32). Report / Econometric Institute, Erasmus University Rotterdam. Erasmus School of Economics. Retrieved from http://hdl.handle.net/1765/26660