Willingness to Pay for Energy Conservation and Free-Ridership on Subsidization: Evidence from Germany

Abstract

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Free-Riding in Tax Credits for Home Insulation in France: An Econometric Assessment Using Panel Data

“…As regards estimated annual proportions of free-riders among CIDD beneficiaries, our results are of the same order of magnitude as those in Grösche and Vance's estimates (Grösche & Vance 2009) in Germany.…”

“…Recent literature studying subsidies implemented to trigger domestic energy efficiency investment has focused on the assessment of free-riding. Using a discrete choice model on German cross-section data, Grösche and Vance (2009) designated potential free-riders as those whose estimated marginal willingness to pay for a particular retrofit option is higher than the observed investment cost without subsidy, and found a proportion of free-riding approaching 50%. Using the same database, Grösche, Schmidt, and Vance (2013) applied a more flexible discrete choice model to generate predicted choice probabilities for each retrofitting option.…”

Energy efficiency subsidies with price-quality discrimination

“…For comprehensive reviews, see Sorrell (2004), Gillingham et al (2009) and Allcott and Greenstone (2012). 5 The existing literature on energy efficiency subsidies is mostly empirical and concerned with estimating the effectiveness of, and inframarginal participation in, subsidy programmes (Boomhower and Davis, 2014;Grösche and Vance, 2009;Hassett and Metcalf, 1995;Houde and Aldy, 2014;Nauleau, 2014). 6 Energy efficiency subsidies can be used to address either market failure in isolation.…”

People or places? Factors associated with the presence of domestic energy efficiency measures in England.

“…They find that tax incentives do increase take-up significantly. Grösche and Vance (2009) use German household survey data to estimate discrete choice models of whether or not households installed some combination of efficiency measures (roof and wall insulation, new window glazing or replacement of heating equipment) in the years prior to the survey. Explanatory variables in their model are household-specific estimates of the direct cost of installing different combinations of measures and the energy savings from doing so.…”