Energy Expenditure in Egypt: Empirical Evidence Based on a Quantile Regression Approach

This paper investigates the key factors affecting household energy expenditure in Egypt. Based upon the latest 2015 Egyptian HIECS Survey, we develop a quantile regression model with an innovative variable selection approach via the adaptive lasso regularization technique to untangle the spectrum of household energy expenditure. Unsurprisingly, income, age, household size, housing size, and employment status are salient predictors for energy expenditure. Housing characteristics have a moderate impact, while socio-economic attributes have a much larger one. The most significant variations in household energy expenditures in Egypt are mainly due to variations in income, household size, and housing type. Our findings document substantial differences in household energy expenditure, originating from the asymmetric tails of the energy expenditure distribution. This outcome highlights the added value of implementing quantile regression methods. Our empirical results have various interesting policy implications regarding residential energy efficiency and carbon emissions reduction in Egypt. It proposes that targeting policies to specific households can improve the effectiveness of energy efficiency policies. These policies could combine both supply-side interventions, such as reducing energy services' cost and demand-side policies for energy-intensive consumers.

Automated summary

This paper investigates the key factors affecting household energy expenditure in Egypt using a quantile regression model. The study finds that income, household size, and housing type have significant impacts on energy expenditure, and suggests targeting policies to specific households to improve the effectiveness of energy efficiency policies.