Abstract
Short-run household electricity demand has been estimated with conditional demand models by a variety of authors using both aggregate data and disaggregate data. Disaggregate data are most desirable for estimating these models. However, in many cases, available disaggregate data may be inappropriate. Furthermore, disaggregate data may be unavailable altogether. In these cases, readily available aggregate data may be more appropriate. This article develops and evaluates an econometric technique to generate unbiased estimates of household electricity demand using such aggregate data.