Applying models for ordinal logistic regression to the analysis of household electricity consumption classes in Rio de Janeiro, BrazilMauricio Fuks and Esther Salazar Energy Economics, 2008, vol. 30, issue 4, pages 1672-1692 Abstract: This study applies the proportional odds and partial proportional odds models for ordinal logistic regression to analyze household electricity consumption classes. Micro-data from households situated in the state of Rio de Janeiro during 2004 was used to measure the performance of the models in correctly classifying household electricity consumption classes via sociodemographic, electricity usage and dwelling characteristics. The strategy of using binary logistic regressions to test the main hypothesis of the proportional odds model, suggested by Bender and Grouven, was successful in identifying which of the independent variables could be estimated via the proportional odds assumption. Results indicate that the partial proportional odds models is slightly superior to the more restrictive approach. The study includes probabilistic examples to describe how changes in the independent variables affect the probability of a household belonging to specific classes of electricity consumption. Projections using the final model indicated that the approach may be useful for estimating aggregate household electricity consumption. Downloads: (external link) Related works: Access Statistics for this article Energy Economics is edited by R. S. J. Tol and J. P. Weyant More articles in Energy Economics from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
Econpapers is hosted by the
Swedish Business School at Örebro University.