Eliciting public support for greening the electricity mix using random parameter techniques
Peter Grösche and
Carsten Schröder ()
Energy Economics, 2011, vol. 33, issue 2, 363-370
With its commitment to double the share of renewable fuels in electricity generation to at least 30% by 2020, the German government has embarked on a potentially costly policy course whose public support remains an open empirical question. Building on household survey data, in this paper we assess people's willingness-to-pay (WTP) for various fuel mixes in electricity generation, and capture preference heterogeneity among respondents using random parameter techniques. Based on our estimates, we trace out the locus that links the premia charged for specific electricity mixes with the fraction of people supporting the policy. Albeit people's WTP for a certain fuel mix in electricity generation is positively correlated to the renewable fuel share, our results imply that the current surcharge effectively exhausts the financial scope for subsidizing renewable fuels.
Keywords: Green; electricity; Willingness-to-pay; Preference; heterogeneity; Policy; evaluation (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (25) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
Working Paper: Elicting public support for greening the electricity mix using random parameter techniques (2010)
Working Paper: Eliciting Public Support for Greening the Electricity Mix Using Random Parameter Techniques (2010)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:33:y:2011:i:2:p:363-370
Access Statistics for this article
Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant
More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().