“Show Me the Energy Costs”: Short and Long-term Energy Cost Disclosure Effects on Willingness-to-pay for Residential Energy Efficiency

Imperfect information on future energy costs can lower the demand for more energy efficient technologies, with clear implications for energy supply, emissions and climate change. These hypotheses are explored using a randomised discrete choice experiment for property rental decisions. Results show that when energy consumption is expressed in physical units (as per the current EU labels) the will-ingness-to-pay for energy efficiency improvements is small and marginally significant. While bimonthly energy cost information displayed in monetary terms has no effect on the valuation of energy efficiency, annual monetary energy cost information led to a significant increase. This is the first paper to compare short and long-term point of sale energy cost information for household property decisions. There are clear implications for labelling policy for properties—framing energy consumption according to long-term monetary cost increases the demand for energy efficiency.

[1]  N. Kok,et al.  The capitalization of energy efficiency: Evidence from the housing market , 2020 .

[2]  Erica Myers.  Are Home Buyers Inattentive? Evidence from Capitalization of Energy Costs , 2019, American Economic Journal: Economic Policy.

[3]  F. Fuerst,et al.  Does voluntary disclosure create a green lemon problem? Energy-efficiency ratings and house prices , 2018, Energy Economics.

[4]  Mateus Souza.  Why are rented dwellings less energy-efficient? Evidence from a representative sample of the U.S. housing stock , 2018, Energy Policy.

[5]  Sébastien Houde.  How consumers respond to product certification and the value of energy information , 2018 .

[6]  M. Frondel,et al.  The Power of Mandatory Quality Disclosure: Evidence from the German Housing Market , 2018, Journal of the Association of Environmental and Resource Economists.

[7]  J. Melvin.  The split incentives energy efficiency problem: Evidence of underinvestment by landlords , 2018 .

[8]  Maya Papineau.  Energy Efficiency Premiums in Unlabeled Office Buildings , 2017 .

[9]  Mark A. Andor,et al.  Consumer Inattention, Heuristic Thinking and the Role of Energy Labels , 2016, The Energy Journal.

[10]  Arik Levinson,et al.  How Much Energy Do Building Energy Codes Save? Evidence from California Houses , 2016 .

[11]  E. Denny,et al.  Low energy efficiency in rental properties: Asymmetric information or low willingness-to-pay? , 2016 .

[12]  Sean Lyons,et al.  The price effect of building energy ratings in the Dublin residential market , 2016 .

[13]  O. Jensen,et al.  Market response to the public display of energy performance rating at property sales , 2016 .

[14]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

[15]  Benjamin K. Sovacool,et al.  Energy and environmental attitudes in the green state of Denmark: Implications for energy democracy, low carbon transitions, and energy literacy , 2015, Environmental Science & Policy.

[16]  John M. Rose,et al.  Applied Choice Analysis , 2015 .

[17]  F. Fuerst,et al.  Does energy efficiency matter to home-buyers? An investigation of EPC ratings and transaction prices in England , 2015 .

[18]  Pieter de Wilde,et al.  The gap between predicted and measured energy performance of buildings: A framework for investigation , 2014 .

[19]  Mark J. Koetse,et al.  A choice experiment on alternative fuel vehicle preferences of private car owners in the Netherlands , 2014 .

[20]  James M. Sallee,et al.  Rational Inattention and Energy Efficiency , 2013, The Journal of Law and Economics.

[21]  R. Newell,et al.  Nudging Energy Efficiency Behavior: The Role of Information Labels , 2013, Journal of the Association of Environmental and Resource Economists.

[22]  Anna Alberini,et al.  Energy Efficiency Investments in the Home: Swiss Homeowners and Expectations about Future Energy Prices , 2013 .

[23]  Steffen Kallbekken,et al.  Bridging the Energy Efficiency Gap: A Field Experiment on Lifetime Energy Costs and Household Appliances , 2012, Journal of Consumer Policy.

[24]  Sean Lyons,et al.  The Value of Domestic Building Energy Efficiency – Evidence from Ireland , 2012 .

[25]  Ray Galvin,et al.  Introducing the prebound effect: the gap between performance and actual energy consumption , 2012 .

[26]  Stefanie Heinzle,et al.  Disclosure of Energy Operating Cost Information: A Silver Bullet for Overcoming the Energy-Efficiency Gap? , 2012 .

[27]  H. Allcott,et al.  Is There an Energy Efficiency Gap? , 2012 .

[28]  F. Carlsson.  Non-Market Valuation: Stated Preference Methods , 2011 .

[29]  Meryl P. Gardner,et al.  Willingness to pay for electric vehicles and their attributes , 2011 .

[30]  Hunt Allcott,et al.  Consumers' Perceptions and Misperceptions of Energy Costs , 2011 .

[31]  Matthias Deutsch,et al.  Life Cycle Cost Disclosure, Consumer Behavior, and Business Implications , 2010 .

[32]  K. Willis,et al.  Willingness-to-pay for renewable energy: Primary and discretionary choice of British households' for micro-generation technologies , 2010, Energy Economics.

[33]  Tatsuyoshi Saijo,et al.  Does an energy efficiency label alter consumers' purchasing decisions? A latent class approach based on a stated choice experiment in Shanghai. , 2009, Journal of environmental management.

[34]  S. Banfi,et al.  Willingness to pay for energy-saving measures in residential buildings , 2007 .

[35]  Riccardo Scarpa,et al.  Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study , 2007 .

[36]  A. Bergmann,et al.  Valuing the attributes of renewable energy investments , 2006 .

[37]  Rolf Wüstenhagen,et al.  The influence of eco‐labelling on consumer behaviour – results of a discrete choice analysis for washing machines , 2006 .

[38]  Jordan J. Louviere,et al.  Quick and easy choice sets: Constructing optimal and nearly optimal stated choice experiments , 2005 .

[39]  David A. Hensher,et al.  A latent class model for discrete choice analysis: contrasts with mixed logit , 2003 .

[40]  J. List.  Does market experience eliminate market anomalies , 2003 .

[41]  D. McFadden,et al.  MIXED MNL MODELS FOR DISCRETE RESPONSE , 2000 .

[42]  R. G. Cummings,et al.  Unbiased Value Estimates for Environmental Goods: A Cheap Talk Design for the Contingent Valuation Method , 1999 .

[43]  K. Train,et al.  Mixed Logit with Repeated Choices: Households' Choices of Appliance Efficiency Level , 1998, Review of Economics and Statistics.

[44]  John T. Gourville.  Pennies-a-Day: The Effect of Temporal Reframing on Transaction Evaluation , 1998 .

[45]  A. Jaffe,et al.  The energy-efficiency gap What does it mean? , 1994 .

[46]  A. Jaffe,et al.  The energy paradox and the diffusion of conservation technology , 1994 .

[47]  K. Lancaster.  A New Approach to Consumer Theory , 1966, Journal of Political Economy.

[48]  Inês L. Azevedo,et al.  Labeling energy cost on light bulbs lowers implicit discount rates , 2014 .

[49]  John M. Quigley,et al.  Energy literacy, awareness, and conservation behavior of residential households , 2013 .

[50]  Rolf Wüstenhagen,et al.  Dynamic Adjustment of Eco-labeling Schemes and Consumer Choice – the Revision of the EU Energy Label as a Missed Opportunity? , 2012 .

[51]  J. Louviere,et al.  Conducting Discrete Choice Experiments to Inform Healthcare Decision Making , 2012, PharmacoEconomics.

[52]  Lucas W. Davis.  Evaluating the S l ow Adoption of Energy Efficient Investments : Are Renters Less Likely to Have Energy Efficient Appliances ? , 2010 .

[53]  Belen Chavez,et al.  Notes on : Prospect Theory : An Analysis of Decision Under Risk ( Kahneman and Tversky 1979 ) Modigliani Group : , 2012 .