Nate Herder, B.A., Armstrong Atlantic State University, 11935 Abercorn Street, Savannah, GA 31419
With the current concerns about efficient consumption and allocation of resources, this study will allow one to estimate factors that determine per capita residential electricity consumption. As temperatures continue to rise (assuming “global warming” is a real phenomenon), as they have been since 1973, the demand for electricity will increase, along with electricity consumption. With the advances in technology, new products have become available that attempt to increase energy efficiencies not only by the energy provider but by the consumers through Government regulations on building codes and newly manufactured household appliances. In the future there is a potential for energy providers to have the ability to measure how electricity is being consumed by the consunsumer resulting in an increase the efficiency of distributed electricity. By examining various factors of both economic and non-economic variables, one can better understand the determinants of residential electricity consumption. This study has been developed in an attempt to measure residential electricity consumption per capita from 2001 to 2005. Data from 48 states have been used with the District of Columbia being measured with Maryland. While Hawaii and Alaska been excluded as outliers to the study. This study attempts to measure residential electricity consumption per capita using a panel data least squares estimation. The results are presented in a log and semi-log format to test for consistency and the overall strength of the model. Residential electricity consumption per capita increases with an increase in per capita disposable income, cooling degree days, or the real price of natural gas, whereas it decreases with an increase in the real price of electricity, the product of heating degree days and natural gas consumption, or a stronger state government involvement in energy efficiency programs. Reports from the Energy Information Administration (EIA) have been used to establish the format and support the results of this study. Previous models have been developed which apply various methods to understand the determinants of residential electricity consumption.