Do green electricity tariffs increase household electricity consumption?

ABSTRACT

In this paper we investigate whether households change electricity consumption after they switch to a green electricity tariff. Using metered data of household electricity consumption from a large provider of green electricity in Germany, our quasi-experimental analysis finds that household switching to a green tariff leads to a non-monetary renewable rebound effect of around 7.7%. Further, our findings imply that this renewable rebound effect is persistent over at least four years. These findings are observationally consistent with moral licencing effects which induce households to permanently change their habitual behaviours and/or to acquire additional electricity-consuming technologies. Thus, failure to account for a renewable rebound in policy evaluation may lead to systematically underestimate the costs of achieving energy and climate targets.

KEYWORDS:

• Rebound
• solar rebound
• green tariffs
• moral licensing
• renewables

JEL CLASSIFICATION:

• H31
• Q41
• Q42

Acknowledgements

This project benefited from funding by the German Federal Ministry of Education and Research as part of the project EE-Rebound [grant number FKZ 01UT1705C]. We are grateful to Verivox and Check24 for providing information on historical and current electricity prices and on the number of green and non-green tariffs offered by electricity providers in the past. We also thank Christina Müller for her help in collecting data on electricity prices and Elisabeth Dütschke and Elisa Rottner for their valuable comments on early drafts of the manuscript. Our paper further benefitted from comments received at the 7th Annual Conference of the European Association of Environmental and Resource Economists in Rimini, Italy (28 June - 1 July 2022). Last but not least, we are indebted to the critical feedback obtained from three anonymous reviewers.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ GoAs prevent that electricity generated by renewable energy sources RES-E) which is supported by a feed in tariff FIT) is also sold via green tariffs. In the past, RES-E generated in Germany typically benefitted from FIT, leading to an increase in the share of RES-E in electricity generation from 6.6% in 2000 to 44.4% of gross electricity generation in 2020 (AGEB (Arbeitsgemeinschaft Energiebilanzen) (2019); BDEW (Bundesverband der Energie- und Wasserwirtschaft, German Association of Energy and Water Industries), (2021). In fact, most electricity sold via green tariffs in Germany originates abroad such as hydropower from Norway (Umweltbundesamt 2019).

² In 2017, more than half the providers in Germany offered at least one green electricity product with such a label (Umweltbundesamt 2019).

³ We use the acronym LGES to ensure anonymity of this large green electricity provider.

⁴ Note that the share of ‘treated’ observations is much higher since in our notation households in the green tariff group are always treated, and households in the switching group are treated once they have switched from a grey to a green tariff. The share of treated observations is 90% for the entire sample. For details on individual switching periods, we refer to Appendix Table A1.

⁵ In an alternative specification, we replace missing price data by the average of the tariffs for those green and grey suppliers where this information could be retrieved. This alternative specification leads to qualitatively and quantitatively very similar findings as those presented in section 3.

⁶ The logic of our identification strategy is similar to the one employed by (Houde et al. 2013), for example. Houde et al. (2013) estimate the effects of providing real-time feedback on household electricity consumption. Yet, they did not have access to billing data for the time preceding the experiment for the treatment group (i.e. those receiving feedback) and the control group. Their identification strategy exploits that after some time, the control group in their field experiment also received feedback.

⁷ For example, akin to the argument provided in (Harding and Rapson 2019), households may feel guilty about an expected increase in electricity consumption and therefore switch from a grey to a green tariff.

⁸ A counterexample would be a heat wave which leads households to subscribe to a green tariff and which directly leads to a higher use of air conditioning. In addition, the parallel lines assumption would have to be violated. e.g. air conditioning increases stronger for households with a green tariff than for households with a grey tariff.

Additional information

Funding

The work was supported by the German Federal Ministry for Education and Research .