Historical Fit and the Next Year of Operating Demand
Abstract
A historical model can fit observed outcomes well and still fail when the operating year changes. This article uses a chronological split of daily bicycle demand to examine that discrepancy with ordinary least squares. A model estimated on 2011 records is evaluated on 2012 records, while a pooled specification estimates an adjusted year association. The resulting forecast bias motivates a synthesis of finite-budget selection, offline evidence preparation, robustness, and model adaptation. The article distinguishes uncertainty that can shrink through additional computation from discrepancies caused by a changing input environment. It offers a transparent benchmark for that distinction without claiming that the year association identifies an intervention.
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