The relative influence of advice from human experts and statistical methods on forecast adjustments

Abstract

Decision makers and forecasters often receive advice from different sources including human experts and statistical methods. This research examines, in the context of stock price forecasting, how the apparent source of the advice affects the attention that is paid to it when the mode of delivery of the advice is identical for both sources. In Study 1, two groups of participants were given the same advised point and interval forecasts. One group was told that these were the advice of a human expert and the other that they were generated by a statistical forecasting method. The participants were then asked to adjust forecasts they had previously made in light of this advice. While in both cases the advice led to improved point forecast accuracy and better calibration of the prediction intervals, the advice which apparently emanated from a statistical method was discounted much more severely. In Study 2, participants were provided with advice from two sources. When the participants were told that both sources were either human experts or both were statistical methods, the apparent statistical-based advice had the same influence on the adjusted estimates as the advice that appeared to come from a human expert. However when the apparent sources of advice were different, much greater attention was paid to the advice that apparently came from a human expert. Theories of advice utilization are used to identify why the advice of a human expert is likely to be preferred to advice from a statistical method.

Expertise, credibility of system forecasts and integration methods in judgmental demand forecasting

“…In the expert systems literature, the same advice has been found to be discounted less when is believed to come from a human expert rather than an expert system (Lerch, Prietula, & Kulik, 1997;Waern & Ramberg, 1996). Similar results have been found in the judgmental forecasting literature (Önkal et al, 2008;Önkal, Goodwin, Thomson, Gönül, & Pollock, 2009).…”

Why Do People Give Less Weight to Advice the Further it is from Their Initial Opinion?

“…The distance effect is characterized by a negative relationship between the weight placed on the received advice and the difference between the advice and the decisionmaker's initial opinion. The feature is documented by experiments in Yaniv (2004), Yaniv and Milyavsky (2007), and Onkal, Goodwin, Thomson, Gönül and Pollock (2009)…”

Trusting forecasts

“…Similarly, Lim and O'Connor (1995) found a tendency among forecasters to persist with damaging adjustments in subsequent forecasts, despite the feedback that they were reducing accuracy. Decision makers seem to discount advice from statistical forecasts (Önkal, Goodwin, Thomson, Gönül, & Pollock, 2009). Decision makers seem to discount advice from statistical forecasts (Önkal, Goodwin, Thomson, Gönül, & Pollock, 2009).…”