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Social Effects in the Diffusion of solar Photovoltaic Technology in the UK


  • Laura-Lucia Richter


The main research question in this paper is whether the installation rate of solar pv technology is affected by social spillovers from spatially close households. The installed base, defined as the cumulative number of solar v installations within a neighbourhood by the end of a particular month, serves as a measure for the social effects of interest. Motivated by the technology-specific time lag between the decision to adopt a solar Pv panel and the completion of the installation, the third lag of the installed base serves as main regressor of interest in the panel data model employed. The results suggest small, but positive and significant social effects that can be exploited to promote adoption: at the average installation rate of 0.7 installations per 1,000 owner-occupied households, one more solar PV panel in the postcode district increases the installation rate three months later by one percent. At the average number of 6,629 owner—occupied households within a postcode district, this implies an increase in the number of new installations in the neighbourhood by 0.005. Projects involving a high number of installations could hence promote diffusion. A major limitation of the model is that social spillovers are assumed to spread within defined neighbourhoods, only. spatial econometric methods could allow for social effects across these borders.

Suggested Citation

  • Laura-Lucia Richter, 2013. "Social Effects in the Diffusion of solar Photovoltaic Technology in the UK," Cambridge Working Papers in Economics 1357, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:1357

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    Cited by:

    1. Allan, Grant J. & McIntyre, Stuart G., 2017. "Green in the heart or greens in the wallet? The spatial uptake of small-scale renewable technologies," Energy Policy, Elsevier, vol. 102(C), pages 108-115.
    2. Collins, Matthew & Curtis, John, 2017. "Advertising and investment spillovers in the diffusion of residential energy efficiency renovations," Papers WP569, Economic and Social Research Institute (ESRI).
    3. Johannes Rode & Sven Müller, 2016. "Spatio-temporal variation in peer effects - The case of rooftop photovoltaic systems in Germany," ERSA conference papers ersa16p579, European Regional Science Association.
    4. repec:gam:jeners:v:9:y:2016:i:1:p:26:d:61701 is not listed on IDEAS
    5. Christa Brelsford & Caterina De Bacco, 2018. "Are `Water Smart Landscapes' Contagious? An epidemic approach on networks to study peer effects," Papers 1801.10516,
    6. De Groote, Olivier & Pepermans, Guido & Verboven, Frank, 2016. "Heterogeneity in the adoption of photovoltaic systems in Flanders," Energy Economics, Elsevier, vol. 59(C), pages 45-57.
    7. Collins, Matthew & Curtis, John, 2017. "Identification of the information gap in residential energy efficiency: How information asymmetry can be mitigated to induce energy efficiency renovations," Papers WP558, Economic and Social Research Institute (ESRI).
    8. Paul Westacott & Chiara Candelise, 2016. "A Novel Geographical Information Systems Framework to Characterize Photovoltaic Deployment in the UK: Initial Evidence," Energies, MDPI, Open Access Journal, vol. 9(1), pages 1-20, January.
    9. Wiggins, Seth, 2016. "It’s All Local? How Sub-State Policies Affect Western US Residential Solar Adoption," 2016 Annual Meeting, July 31-August 2, 2016, Boston, Massachusetts 235667, Agricultural and Applied Economics Association.
    10. Balta-Ozkan, Nazmiye & Yildirim, Julide & Connor, Peter M., 2015. "Regional distribution of photovoltaic deployment in the UK and its determinants: A spatial econometric approach," Energy Economics, Elsevier, vol. 51(C), pages 417-429.

    More about this item


    social effects; installed base; product adoption; diffusion; solar PV technology; micro-generation;

    JEL classification:

    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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