Nudging Energy Efficiency Behavior: The Role of Information Labels

By Richard G. Newell, Juha Siikamäki. Journal of the Association of Environmental and Resource Economists, 2014

341 citations recorded by the source corpus.

Subfields: Building and Construction, Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/f9120db6912aef2b43c1f21bc5455f884c341aa2

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Citations in the corpus

Performance of markets for European renewable energy certificates (2019, background): “Newell and Siikamaki (2014) find that, in addition to factual information in energy-efficiency certificates, the presence of logos (e.g. the US Energy Star or EU letter grade logo) significantly increases the willingness-to-pay of consumers for energy intensive household appliances.”
Rational Inattention and Energy Efficiency (2014, background): “Fortunately, one recent study, Newell and Siikamäki (2013), takes up this issue using laboratory experiments.”
Climate policy through changing consumption choices: Options and obstacles for reducing greenhouse gas emissions (2014, neutral): “Besides providing labeling, the design of the label is also important as shown in experimental design (Newell and Siikama¨ki, 2013), but also as learned from practical experience (Sunstein, 2013).”
Determinants of households’ investment in energy efficiency and renewables: evidence from the OECD survey on household environmental behaviour and attitudes (2015, background): “standards, but EE labeling programs, which were implemented in conjunction with standards in the US, may also contribute to the ability of consumers to make costeffective trade-offs between the price of efficiency and energy-cost savings [22].”
Internal and external barriers to energy efficiency: which role for policy interventions? (2019, background): “Except for few contributions (Allcott and Sweeney 2016; Allcott and Greenstone 2017), the empirical findings confirm that lack of relevant information leads to underinvestment in energy efficiency (Ward et al. 2011; Newell and Siikamäki 2014; Davis and Metcalf 2016; Houde 2018).”
Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning (2020, background): “com/en-us/blog/microsoftmakes-it-easier-to-build-popular-language-representation-model-bert-at-large-scale/ Efficient routing of traffic to regions has been considered before by Nguyen et al. (2012) and Berral et al.”
Consumers and their behavior: state of the art in behavioral science supporting use phase modeling in LCA and ecodesign (2016, background): “…labels providing simple information on the economic value of saving energy represented the most important element guiding more cost-efficient purchases, while the addition of further information (e.g., on carbon dioxide emission or energy use) had little effect (Newell and Siikamäki 2013).”
From Fog to Smog: the Value of Pollution Information (2019, background): “4 Oberholzer-Gee and Mitsunari, 2006), change consumer choices (Hastings and Weinstein, 2008; Dranove and Jin, 2010; Jessoe and Rapson, 2014; Newell and Siikamäki, 2014; Mastromonaco, 2015; Wichman, 2017), and drive up average product quality (Jin and Leslie, 2003; Bai, 2018).”
Are consumers willing to pay to let cars drive for them? Analyzing response to autonomous vehicles (2017, methodology): “Expanding on the work of Newell and Siikamäki (2013), we used the individual-level experimental discount rate to determine the present value of fuel costs for each alternative.”