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Regional distribution of photovoltaic deployment in the UK and its determinants: A spatial econometric approach

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  • Balta-Ozkan, Nazmiye
  • Yildirim, Julide
  • Connor, Peter M.

Abstract

Photovoltaic (PV) panels offer significant potential for contributing to the UK's energy policy goals relating to decarbonisation of the energy system, security of supply and affordability. The substantive drop in the cost of panels since 2007, coupled with the introduction of the Feed-in Tariff (FiT) Scheme in 2010, has resulted in a rapid increase in installation of PV panels in the UK, from 26.5MWp in 2009 to over 5GW by the end of 2014. Yet there has been no comprehensive analysis of the determinants of PV deployment in the UK. This paper addresses this gap by employing spatial econometrics methods to a recently available data set at a fine geographical detail. Following a traditional regression analysis, a general to specific approach has been adopted where spatial variations in the relationships have been examined utilising the spatial Durbin model using the cross-sectional data relating to the UK NUTS level 3 data. Empirical results indicate that demand for electricity, population density, pollution levels, education level of households and housing types are among the factors that affect PV uptake in a region. Moreover Lagrange Multiplier test results indicate that the spatial Durbin model may be properly applied to describe the PV uptake relationship in the UK as there are significant regional spillover effects.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:eneeco:v:51:y:2015:i:c:p:417-429
    DOI: 10.1016/j.eneco.2015.08.003
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    More about this item

    Keywords

    Photovoltaic; PV; Spatial spillover; FIT; Spatial econometrics; Spatial energy;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • Q28 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Government Policy
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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