Peer effects in the diffusion of solar photovoltaic panels
Open accessAbstract
Social interaction (peer) effects are recognized as a potentially important factor in the diffusion of new products. In the case of environmentally friendly goods or technologies, both marketers and policy makers are interested in the presence of causal peer effects as social spillovers can be used to expedite adoption. We provide a methodology for the simple, straightforward identification of peer effects with sufficiently rich data, avoiding the biases that occur with traditional fixed effects estimation when using the past installed base of consumers in the reference group. We study the diffusion of solar photovoltaic panels in California and find that at the average number of owner-occupied homes in a zip code, an additional installation increases the probability of an adoption in the zip code by 0.78 percentage points. Our results provide valuable guidance to marketers designing strategies to increase referrals and reduce customer acquisition costs. They also provide insights into the diffusion process of environmentally friendly technologies.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The instrumental variable (Early Copilot Adopter Exposure) satisfies the relevance condition.
“We believe the first component satisfies the relevance condition because prior research shows that individuals learn from peers through social interactions and shared experience (Foster and Rosenzweig 1995, Conley and Udry 2010, Bollinger and Gillingham 2012, Bailey et al. 2022).”
From The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot  (2024) · cites this paper as Bollinger and Gillingham 2012
Cites
Learning about a New Technology: Pineapple in Ghana
Conley, T. G., & Udry, C. R. (2010) · American Economic Review · doi:10.1257/aer.100.1.35 · Cited by 2,180 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Learning about a New Technology: Pineapple in Ghana
Conley, T. G., & Udry, C. R. (2010) · American Economic Review · doi:10.1257/aer.100.1.35 · Cited by 2,180 · see citing works
The Nature and Origins of Misperceptions: Understanding False and Unsupported Beliefs About Politics
Flynn, D. J., Nyhan, B., & Reifler, J. (2017) · Political Psychology · doi:10.1111/pops.12394 · Cited by 1,183 · see citing works
Disparities in rooftop photovoltaics deployment in the United States by race and ethnicity
Sunter, D. A., Castellanos, S., & Kammen, D. M. (2019) · Nature Sustainability · doi:10.1038/s41893-018-0204-z · Cited by 324 · see citing works
Rai, V., & Robinson, S. A. (2015) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2015.04.014 · Cited by 335 · see citing works
Salience of carbon taxes in the gasoline market
Rivers, N., & Schaufele, B. (2015) · Journal of Environmental Economics and Management · doi:10.1016/j.jeem.2015.07.002 · Cited by 244 · see citing works
Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works
Cooperation in the Climate Commons
Carattini, S., Levin, S., & Tavoni, A. (2019) · Review of Environmental Economics and Policy · doi:10.1093/reep/rez009 · Cited by 134 · see citing works
Minority influence in climate change mitigation
Bolderdijk, J. W., & Jans, L. (2021) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2021.02.005 · Cited by 59 · see citing works
Decay radius of climate decision for solar panels in the city of Fresno, USA
Barton-Henry, K., Wenz, L., & Levermann, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-87714-w · Cited by 28 · see citing works
Song, F., Agarwal, A., & Wen, W. (2024) · SSRN Electronic Journal (preprint) · doi:10.2139/ssrn.4856935 · Cited by 30 · see citing works
- Authors
- Bollinger, B., & Gillingham, K.
- Affiliations
- New York University (US)
- Yale University (US)
- Venue
- Marketing Science
- Published
- 2012-11
- Volume
- 31
- Issue
- 6
- Pages
- 900-912
- ISSN
- 0732-2399 (ISSN-L)
- 1526-548X
- OpenAlex
- W1975346281
- Cited by
- 1,013
- References
- 1
- Citations by year
- 2026: 91 · 2025: 103 · 2024: 89 · 2023: 101 · 2022: 102 · 2021: 110 · 2020: 66 · 2019: 77 · 2018: 63 · 2017: 55 · 2016: 52 · 2015: 45 · 2014: 27 · 2013: 22 · 2012: 7
- FWCI
- 42.75
- Type
- journal article
- Language
- en
- Open access
- green
- autopapers.ssrn.com
- Locations
- Marketing Science (publishedVersion)
- SSRN Electronic Journal (submittedVersion)
- Funders
- Centre for Economic Policy Research
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Innovation Diffusion and Forecasting
- Social Sciences › Sociology and Political Science › Social Acceptance of Renewable Energy
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Market Behavior and Pricing
- Keywords
- peer effects, diffusion of innovations, photovoltaic modules, technology adoption, social spillovers, installed base, environmentally friendly technologies, customer acquisition cost, referral marketing, California
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
