published in: Journal of Evolutionary Economics, 2022, 32, 501-530
This paper develops a pseudo-panel approach to examine household electricity demand behavior through the household life cycle and its response to income variations to help strengthen the energy policy-making process. Our empirical methodology is based on three rich independent microdata surveys (the National Housing Surveys), which are representative of the French housing sector. The resulted sample covers the 2006-2016 period. Using within estimations, this paper finds striking evidence that the income elasticity of French residential electricity demand is 0.22, averaged over our four cohorts of generations.
In light of other works, our estimate stands in the lower range. The empirical results also show that residential electricity consumption follows an inverted U-shaped distribution as a function of the age of the household's head. Most notably, it appears that households at the mid-point of their life cycle are relatively the largest consumers of electricity. This outcome has important implications for policy-making. Any public policy aimed at reducing household energy consumption should consider this differentiation in consumption according to the position of households over the life cycle, and therefore target as priority households at the highest level of consumption.
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.