Do experts incorporate statistical model forecasts and should they?

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 threequestions, which we try to answer given the availability of expert forecasts andmodel forecasts. First, is the expert forecast related to the model forecast andhow? 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 answerthese questions. We apply our proposed methodology to a large data set offorecasts and realizations of SKU-level sales data from a pharmaceutical company.We find that expert forecasts can depend on model forecasts in a variety ofways. Average sales levels, sales volatility, and the forecast horizon influence thisdependence. We also demonstrate that theoretical implications of expert behavioron forecast accuracy are reflected in the empirical data.