Article ID: | iaor20121622 |
Volume: | 41 |
Issue: | 1 |
Start Page Number: | 822 |
End Page Number: | 826 |
Publication Date: | Feb 2012 |
Journal: | Energy Policy |
Authors: | Gil-Alana Luis A, Payne James E, Pestana Barros Carlos |
Keywords: | statistics: inference, statistics: regression, demand |
This study examines the degrees of time persistence in U.S. total renewable energy consumption using innovative fractional integration and autoregressive models with monthly data from 1981:1 to 2010:10. The results indicate that renewable energy consumption is better explained in terms of a long memory model that incorporates persistence components and seasonality. The degree of integration is above 0.5 but significantly below 1.0, suggesting nonstationarity with mean reverting behavior. The presence of long memory behavior (persistence) in renewable energy consumption suggests that random shocks may very well move renewable energy consumption from pre‐determined target levels for a period of time.