Abstract
More than 80% of the energy expenditures of private households in Germany are spent on space heating and hot water preparation. This creates opportunities for policymakers trying to influence energy consumer behavior. However, for these measures to be effective and efficient, the factors that determine energy usage need to be known. In this paper, we identify the determinants of heating and hot water expenditures for German households, using a panel dataset derived from yearly residential household surveys covering the years 1996–2014. Furthermore, we test for heterogeneity between households using different methods. For the full sample, we find an own-price demand elasticity of heating expenditures ranging from 0.573 to 0.690. A large number of technical and socio-demographic factors are significant determinants of energy use. Additionally, we discover significant heterogeneity in price elasticity between different socioeconomic groups. Our findings have implications for evaluating the effectiveness of policy measures that target influencing energy use across different groups of consumers.
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Notes
Similar panels from other countries include the PSID (US), BHPS (UK), SLID (Canada), and HILDA (Australia).
For a more thorough description of the SOEP panel, see Wagner et al. (2007).
This approach has also been employed by Dieckhöner (2012), among others.
Regional price data are taken from Bukold (2015).
Specifically, renters are asked what their average monthly cost of heating is, whereas homeowners are being asked what their cost of heating was in the preceding calendar year.
We also estimate our models using only household head data, which leads to results that are virtually identical both in terms of model fit and coefficient estimates. Full model results can be found in the online appendix.
In the category households and small businesses consuming 300 MWh/a or less. Data from BNetzA (2006).
Specifically, we use the price index for CC045 (electricity, gas, and other fuels) in the COICOP classification scheme, which is a weighted combination of the price indices for electricity, gas, liquid fuels, solid fuels, and other fuels (including district heating). Data taken from Federal Statistical Office (2016).
Additional F-tests results for the variables INCOME_CAPITA, SPACE, and OWNER can be found in the online appendix.
The landlord usually has to pay for energy-saving renovations like better insulation or a new, modern heating system, but the tenant then reaps the rewards through a lower heating bill, giving the landlord little incentive to undertake those renovations in the first place.
We thank an anonymous referee for this suggestion.
Note that since the cluster variable has four levels (one for each group), there are four interaction terms for each variable that we interact the cluster variable with. The table shows the significance level for which at least one interaction between that variable and a cluster level is significant.
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Acknowledgements
The authors would like to thank conference participants at the International Rebound Workshop in Aachen, Germany (March 6, 2015), the Spring Meeting of Young Economists in Ghent, Belgium (May 21–23, 2015), and the RGS Doctoral Conference in Bochum, Germany (February 23–25, 2016) for helpful feedback, in particular Manuel Frondel and Stephan Sommer. Furthermore, we are grateful to Tuğba Atasoy, Julius Frieling, Veronica Galassi, Christian Oberst, and Stefanie Wolff for constructive comments and criticism. We also thank an anonymous referee for helpful comments.
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The research activities and outcomes presented in this paper have been developed as part of the Virtual Institute ‘Transformation – Energy Transition NRW.’ The Virtual Institute encompasses ten renowned research institutes from North Rhine-Westphalia dealing with socioeconomic implications of the energy transition in NRW. It is supported by the NRW Ministry for Innovation, the Energy Research Cluster NRW, and the Mercator foundation. More information is available here: http://www.vi-transformation.de/en/. Financial support by the NRW Ministry for Innovation (MIWF NRW, Grant No. W 036C) is gratefully acknowledged.
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Schmitz, H., Madlener, R. Heterogeneity in price responsiveness for residential space heating in Germany. Empir Econ 59, 2255–2281 (2020). https://doi.org/10.1007/s00181-019-01760-y
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DOI: https://doi.org/10.1007/s00181-019-01760-y