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.

本文调查了影响埃及家庭能源支出的关键因素。基于2015年最新的埃及HIECS调查，我们通过自适应套索正则化技术开发了具有创新变量选择方法的分位数回归模型，以解开家庭能源支出的频谱。毫不奇怪，收入，年龄，家庭规模，住房规模和就业状况是能源支出的重要预测指标。住房特征的影响适中，而社会经济属性的影响要大得多。埃及家庭能源支出的最大变化主要是由于收入，家庭规模和住房类型的变化。我们的调查结果表明，家庭能源支出存在重大差异，源于能源支出分布的不对称尾部。这一结果凸显了实施分位数回归方法的附加价值。我们的经验结果对埃及的住宅能源效率和碳排放减少具有各种有趣的政策含义。它建议针对特定家庭的政策可以提高能效政策的有效性。这些政策可以将诸如降低能源服务成本之类的供应方干预措施与针对能源密集型消费者的需求方政策相结合。它建议针对特定家庭的政策可以提高能效政策的有效性。这些政策可以将诸如降低能源服务成本之类的供应方干预措施与针对能源密集型消费者的需求方政策相结合。它建议针对特定家庭的政策可以提高能效政策的有效性。这些政策可以将诸如降低能源服务成本之类的供应方干预措施与针对能源密集型消费者的需求方政策相结合。