On weather normalizing customer‐level billing data

This paper develops a conceptual framework for estimating both nonlinear and time‐varying weather impacts from customer‐level billing histories. The framework is flexible insofar as multiple model specifications can be derived from it for real‐world application. Next, through statistical tests the paper evaluates the performance of 10 progressively complex weather specifications applied to a sample of billing data. These tests reject many of the simple and commonly used weather specifications, demonstrating the importance of accurate weather modeling.