Temperature and Residential Electricity Demand for Heating and Cooling in G7 Economies: A Method of Moments Panel Quantile Regression Approach

Abstract

The global energy system is highly vulnerable to climate variability and change. This results in a vast range of impacts on the energy demand sector and production and supply channels. This article aims to estimate the impacts of variables such as heating and cooling temperatures, income, population, and price on residential electricity demand in G7 countries. Methodologically, this study uses the second-generation panel unit root and cointegration approaches (which are robust in the presence of cross-sectional dependence), a panel fixed effects model with Driscoll–Kraay standard errors, and a novel method of moments quantile regression (MM-QR) to determine long-run elasticities. The results suggest that the residential electricity demand of G7 countries is statistically and positively responsive to cold days rather than hot days. This study also presents some policy-relevant issues based on the results.