Heterogeneity in Residential Electricity Consumption: Aquantile Regression Approach

26 Pages Posted: 11 Oct 2015

See all articles by Manuel Frondel

Manuel Frondel

RWI Leibniz Institute for Economic Research ; Ruhr University Bochum (RUB)

Stephan Sommer

RWI - Leibniz-Institute for Economic Research

Colin Vance

Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI)

Date Written: October 9, 2015

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.

Keywords: Electricity Consumption, Conditional Demand Approach, Quantile Regression Methods

JEL Classification: D12, Q41

Suggested Citation

Frondel, Manuel and Sommer, Stephan and Vance, Colin, Heterogeneity in Residential Electricity Consumption: Aquantile Regression Approach (October 9, 2015). USAEE Working Paper No. 15-225. Available at SSRN: https://ssrn.com/abstract=2672078 or http://dx.doi.org/10.2139/ssrn.2672078

Manuel Frondel (Contact Author)

RWI Leibniz Institute for Economic Research ( email )

Hohenzollernstr. 1-3
45128 Essen
Germany

Ruhr University Bochum (RUB) ( email )

Universitätsstraße 150
Bochum, NRW 44780
Germany

Stephan Sommer

RWI - Leibniz-Institute for Economic Research ( email )

Hohenzollernstr. 1-3
Essen, 45128
Germany

Colin Vance

Rheinisch-Westfälisches Institut für Wirtschaftsforschung (RWI) ( email )

Hohenzollernstr. 1-3
Essen, 45128
Germany
0049-201-8149-237 (Phone)

HOME PAGE: http://www.rwi-essen.de

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