Is there a Golden Rule?

Armstrong, Green, and Graefe (this issue) propose the Golden Rule in forecasting: "be conservative". According to the authors, the successful application of the Golden Rule comes through a checklist of 28 guidelines. Even if the authors of this commentary embrace the main ideas around the Golden Rule, which targets to address the "average" situation, they believe that this rule should not be applied automatically. There is no universal extrapolation method that can tackle every forecasting problem; nor are there simple rules that automatically apply without reference to the data. Similarly, it is demonstrated that for a specific causal regression model the recommended conservative rule leads to unnecessary inaccuracy. In this commentary the authors demonstrate, using the power of counter examples, two cases where the Golden Rule fails. Forecasting performance is context-dependent and, as such, forecasters (researchers and practitioners) should take into account the specific features of the situation faced. (C) 2015 Elsevier Inc. All rights reserved.