Abstract

The increasing cost, and demand for, household energy has increased attention to the phenomena of energy burdens. Despite this increased attention, a lack of consensus remains in pinpointing the strongest predictors, and geographic differences, that exist within the energy ecosystem. This study addresses this gap by utilizing a series of dummy variable regressions across cities, suburbs, and rural areas within Erie County, New York—a county noted to have particularly high energy burdens. Specifically, three types of predictor sets were incorporated into the methodology: a set of socioeconomic variables, physical variables, and a combination of both variable sets. The results of this study suggest that cities tend to have the highest electricity burdens. Despite the aging infrastructure in Erie County, high energy burdens were driven primarily by socioeconomic factors such as housing cost burden and poverty status. Lastly, this study explores various planning and policy implications Erie County can utilize to reduce energy burdens. In turn, this study highlights the importance of focusing policy efforts on existing social service programs to provide support to the region’s neediest households.