| Should We Redesign Forecasting Competitions? (2008) | |||||||||||||||
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| The M3-Competition continues to improve the design of forecasting competitions: It examines more series than any previous competition, improves error analyses. and includes commercial forecasting programs as competitors. To judge where to go from here, I step back to look at the M-Competitions as a whole. I discuss the advantages of the M-Competitions in hopes that they will be retained, describe how to gain additional benefit from future competitions, and finally, describe a low-cost approach to competitions. 1. Favorable design aspects of the M-Competitions The M-Competitions provide a model for conducting scientific research. They employ at least five key aspects: empirical testing, multiple hypotheses, large samples, independent validation, and full disclosure. While these aspects might seem obvious, studies in management science seldom include all of them. 1.1. Empirical testing Empirical testing is necessary to test forecasting methods. Despite the resistance of timeseries researchers (Fildes & Makridakis, 1995), interest in empirical studies has been growing among forecasters. Forecasting journals now publish many empirical comparisons. The M-Competitions have led the way in such comparisons. 1.2. Multiple hypotheses | |||||||||||||||
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