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When do households invest in solar photovoltaics? An application of prospect theory

descriptionPublicationkeyboard_double_arrow_right Article , Preprint , Journal , Conference object , Other literature type 01 Oct 2017Embargo end date: 01 Jan 2018 Germany Publisher:Elsevier BVJournal:Energy Policy, volume 109, pages 270-278 (issn: 0301-4215,

Authors: Klein, Martin; Deissenroth, Marc;

doi: 10.1016/j.enpol.2017.06.067 , 10.48550/arxiv.1808.05572

arXiv: 1808.05572 , http://arxiv.org/abs/1808.05572

When do households invest in solar photovoltaics? An application of prospect theory

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Abstract

While investments in renewable energy sources (RES) are incentivized around the world, the policy tools that do so are still poorly understood, leading to costly misadjustments in many cases. As a case study, the deployment dynamics of residential solar photovoltaics (PV) invoked by the German feed-in tariff legislation are investigated. Here we report a model showing that the question of when people invest in residential PV systems is found to be not only determined by profitability, but also by profitability's change compared to the status quo. This finding is interpreted in the light of loss aversion, a concept developed in Kahneman and Tversky's Prospect Theory. The model is able to reproduce most of the dynamics of the uptake with only a few financial and behavioral assumptions

Country

Germany

Related Organizations

German Aerospace Center
Germany

Keywords

Prospect Theory, Systemanalyse und Technikbewertung, Energy Policy, Deployment, Econometrics (econ.EM), Feed-in tariff design, Photovoltaics, Investment Dynamics, FOS: Economics and business, Deployment modelling, Investment, Prospect theory, Economics - Econometrics

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	59
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%