Heterogeneity in residential electricity consumption: A quantile regression approach
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Date
2015
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Abstract
Reducing household electricity consumption is of central relevance to climate
policy given the share of 12.2% of the residential sector in greenhouse gas emissions.
Drawing on data originating from the German Residential Energy Survey (GRECS),
this paper estimates the contribution of individual appliances to household electricity
demand using the conditional demand approach, which relies on readily obtainable
information on appliance ownership. Moving beyond the standard focus of mean regression,
we employ a quantile regression approach to capture the heterogeneity in
the contribution of each appliance according to the conditional distribution of household
electricity consumption. This heterogeneity indicates that there are quite large
technical potentials for efficiency improvements and electricity conservation in private
households. We also find substantial differences in the end-use shares across households
originating from the opposite tails of the electricity consumption distribution,
highlighting the added value of applying quantile regression methods in estimating
consumption rates of electric appliances.
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Keywords
Electricity Consumption, Quantile Regression Methods, Conditional Demand Approach