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Increasing the reach of low-income energy programmes through behaviourally informed peer referral

Nature Energy volume 8, pages 850–858 (2023)Cite this article

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Abstract

Subsidized energy assistance programmes are a popular policy tool for promoting energy justice, but, like other social benefits programmes, are often undersubscribed. To improve uptake, some programmes have turned to social influence strategies, such as asking programme participants to refer their peers. Here, through a field experiment with California’s low-income solar programme (N = 7,676), we show that referral behaviour depends on how existing participants are approached. Adding behavioural science strategies to a referral reward increases peer referral rates, referral quality and ultimately solar adoption. Compared with only reminding existing adopters of a potential US$200 reward for referrals that result in adoption, adding an appeal to reciprocity through a non-contingent US$1 gift—and further combining this gift with a simplified referral process—leads to 2.6–5.2 times as many solar contracts. These results highlight the potential of behaviourally informed peer referral programmes to accelerate equitable access to clean energy.

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Fig. 1: Illustration of experimental conditions.
Fig. 2: Effects of mailer campaigns on response rate, number and quality of referrals made, and the number of resulting solar contracts.
Fig. 3: Response rates, by condition, among clients who had never referred before and among those who had referred at least once before the experiment.

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Data availability

Exported data from the Salesforce database are not publicly available due to ethical and privacy concerns. An anonymized, public version of the dataset with referral behaviour and resulting solar contracts, without any personally identifiable information, is available on the Open Science Framework (https://osf.io/x4sqp/). The time-stamped data needed to generate Fig. 2c are proprietary to the non-profit partner. Zip-code-level data used in Supplementary Note 3 are not publicly available to protect the privacy of participants.

Code availability

Replication code to generate results from the anonymized, publicly available data is at https://osf.io/x4sqp/.

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Acknowledgements

We thank GRID Alternatives (particularly J. Coleman, Z. Franklin, A. Kim and L. Nobel) and B. Sigrin at the National Renewable Energy Laboratory for their collaboration. We also thank K. Aves and R. Walatka for their assistance in creating figures. This work was supported by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the US Department of Energy (DOE) under contract no. DE-AC36-08GO28308 (K.S.W. and E.T.). Funding was provided by the US Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technology Office. This manuscript was also authored by an employee of Lawrence Berkeley National Laboratory under contract no. DE-AC36-08GO28308 with the US Department of Energy (A.T.-B.). The views expressed in the article do not necessarily represent the views of the DOE or the US Government. The US Government retains and the publisher, by accepting the article for publication, acknowledges that the US Government retains a non-exclusive, paid-up, irrevocable, worldwide licence to publish or reproduce the published form of this work, or allow others to do so, for US Government purposes.

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Authors and Affiliations

  1. Harris School of Public Policy, University of Chicago, Chicago, IL, USA

    Kimberly S. Wolske

  2. Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Annika Todd-Blick

  3. National Renewable Energy Laboratory, Golden, CO, USA

    Emma Tome

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Contributions

K.S.W. and A.T.-B. conceived and implemented the study, with E.T. handling randomization of postal mail recipients. A.T.-B. and E.T. cleaned the data, which A.T.-B. analysed. K.S.W. drafted the manuscript with revisions from A.T.-B. E.T. contributed to the methods section.

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Correspondence to Kimberly S. Wolske.

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Nature Energy thanks Rohan Best, Mahelet G. Fikru and Stefan Lamp for their contribution to the peer review of this work.

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Supplementary Tables 1–11 and Notes 1–3.

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Wolske, K.S., Todd-Blick, A. & Tome, E. Increasing the reach of low-income energy programmes through behaviourally informed peer referral. Nat Energy 8, 850–858 (2023). https://doi.org/10.1038/s41560-023-01298-5

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