Powering the change: a Contingent Valuation study on the determinants of demand for green vs. brown energy

Abstract

A Contingent Valuation study was performed to assess a potential trade-off between external costs (impacts on health caused by pollution) and the cost of electricity paid by households. Two technologies were selected for the valuation exercise: coal-fired thermal and solar photovoltaic. Our results show that households are interested in buying solar energy, and are willing to pay an additional premium for it, which would support maintenance of a feed-in tariff system. In addition, it is found that higher awareness of the external benefits and costs related, respectively, to solar and coal energy, is a crucial factor that shapes their demand in the household sector. According to the results of our study, we can expect that if electric utilities were required by regulators to provide detailed information on the external effects (and in particular, on health impacts) of coal and other fossil fuels used in their energy mix, there will be a sizeable positive shift in the demand of green electric energy in the household sector.

Keywords:

• solar photovoltaic
• coal
• energy
• electricity
• health impacts
• Contingent Valuation

JEL:

• D6
• C25
• Q42
• Q53

Acknowledgements

This research has benefitted from a Bank of Sardinia Foundation grant #1080/2010.0632. Vania Statzu has been supported by Region of Sardinia (L.R.7/2007 scholarships for young researchers). We are grateful to Luca Soru of the Oristano Energy Agency for technical support and advice

Notes

1. The Durban COP-17 in 2011 did not produce any new agreement, but an extension of the current Kyoto Protocol commitments in the wake of a global agreement by 2020. The Kyoto Protocol will remain in place as an interim agreement for at least five years before the new deal is negotiated (except for Canada, Japan and Russia, that did not accept the extension of the Kyoto commitments).

2. The NIMBY syndrome refers to people expressing the opinion that a specific facility should be sited somewhere else than their own territory.

3. If the second equation parameters are significantly different from those of the first equation, the application of a bivariate model may help to produce correct estimates as in the single bound model, while possibly increasing their efficiency, in case the choice of initial bids had been suboptimal.

4. Further analysis would be required if we were interested in assessing the potential market of a “coal electricity” product: the estimates should be weighted to take into account the group of individuals not interested in the market, which should be disentangled from the group of protesters. In the present work, we do not pursue this objective.