Boundedly rational consumers, energy and investment literacy, and the display of information on household appliances

It is an ongoing debate how to increase the adoption of energy-efficient light bulbs and household appliances in the presence of the so-called ‘energy efficiency gap’. One measure to support consumers’ decision-making towards the purchase of more efficient appliances is the display of energy-related information in the form of energy-efficiency labels on electric consumer products. Another measure is to educate consumers in order to increase their level of energy and investment literacy. Thus, two questions arise when it comes to the display of energy-related information on appliances: (1) What kind of information should be displayed to enable consumers to make rational and efficient choices? (2) What abilities and prior knowledge do consumers need to possess to be able to process this information? In this paper, using a series of (recursive) bivariate probit models and three samples of 583, 877 and 1375 households from three major Swiss urban areas, we show how displaying information on the future energy consumption of electrical appliances in monetary terms (CHF), rather than in physical units (kWh), increases the probability that an individual makes a calculation and identifies the appliance with the lowest lifetime cost. In addition, our econometric results suggest that individuals with a higher level of energy and, in particular, investment literacy are more likely to perform an optimization rather than relying on a decision-making heuristic. These individuals are also more likely to identify the most (cost-)efficient appliance.

[1]  J. Muellbauer,et al.  Economics and consumer behavior , 1980 .

[2]  R. Schubert,et al.  Energy-Using Durables: The Role of Time Discounting in Investment Decisions , 2011 .

[3]  Andrew M. Jones.  Applied Econometrics for Health Economists: A Practical Guide , 2007 .

[4]  Matthias Deutsch,et al.  The effect of life-cycle cost disclosure on consumer behavior: evidence from a field experiment with cooling appliances , 2007 .

[5]  Thanasis Stengos,et al.  On the calculation of marginal effects in the bivariate probit model , 1997 .

[6]  Morten I. Lau,et al.  Estimating Individual Discount Rates in Denmark: A Field Experiment , 2002 .

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

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

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

[10]  Lei Shi.  Econometric analyses of renewable energy promotion , 2014 .

[11]  Morris Altman.  Real-world decision making : an encyclopedia of behavioral economics , 2015 .

[12]  P. Schmidt,et al.  Limited-Dependent and Qualitative Variables in Econometrics. , 1984 .

[13]  M. García-valiñas,et al.  Efficient water-using technologies and habits: A disaggregated analysis in the water sector , 2016 .

[14]  R. Howarth,et al.  ‘Normal’ markets, market imperfections and energy efficiency , 1994 .

[15]  Joachim Wilde,et al.  Identification of multiple equation probit models with endogenous dummy regressors , 2000 .

[16]  Jan DeWaters,et al.  Energy literacy of secondary students in New York State (USA): A measure of knowledge, affect, and behavior , 2011 .

[17]  Alan H. Sanstad,et al.  DISCOUNT RATES AND ENERGY EFFICIENCY , 1995 .

[18]  Heidi Bruderer Enzler,et al.  Subjective discount rates in the general population and their predictive power for energy saving behavior , 2014 .

[19]  R. Muth.  HOUSEHOLD PRODUCTION AND CONSUMER DEMAND FUNCTIONS , 1966 .

[20]  Leibniz-Informationszentrum Wirtschaft.  What's driving energy efficient appliance label awareness and purchase propensity? , 2009 .

[21]  Bradford F. Mills,et al.  Residential Energy-Efficient Technology Adoption, Energy Conservation, Knowledge, and Attitudes: An Analysis of European Countries , 2012 .

[22]  R. Newell,et al.  EXPLAINING THE ENERGY PARADOX ‡ Deconstructing the Energy-Efficiency Gap: Conceptual Frameworks and Evidence † , 2015 .

[23]  E. Hobman,et al.  Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour , 2015 .

[24]  Martin Brown,et al.  Financial Literacy and Retirement Planning in Switzerland , 2013 .

[25]  Jerry A. Hausman,et al.  Individual Discount Rates and the Purchase and Utilization of Energy-Using Durables , 1979 .

[26]  H. Simon,et al.  Theories of Decision-Making in Economics and Behavioural Science , 1966 .

[27]  Leif Gustavsson,et al.  Factors influencing energy efficiency investments in existing Swedish residential buildings , 2010 .

[28]  H. Dowlatabadi,et al.  Models of Decision Making and Residential Energy Use , 2007, Renewable Energy.

[29]  K. Train.  Discount rates in consumers' energy-related decisions: A review of the literature , 1985 .

[30]  N. J. Burnett,et al.  Gender Economics Courses in Liberal Arts Colleges , 1997 .

[31]  O. Mitchell,et al.  Baby Boomer Retirement Security: The Roles of Planning, Financial Literacy, and Housing Wealth , 2006 .

[32]  A. Kažukauskas,et al.  Inefficiencies in Residential Use of Energy -- A Critical Overview of Literature and Energy Efficiency Policies in EU and Sweden , 2014 .

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

[34]  H. Allcott,et al.  Evaluating Behaviorally-Motivated Policy: Experimental Evidence from the Lightbulb Market , 2014 .

[35]  William L. Wilkie,et al.  Public Policy and Consumer Information: Impact of the New Energy Labels , 1979 .

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

[37]  O. Mitchell,et al.  Financial Literacy: Evidence and Implications for Financial Education , 2009 .

[38]  Marek Hlavac.  stargazer : LaTeX code for well-formatted regression and summary statistics tables (R package) , 2012 .

[39]  R. Martínez-Espiñeira,et al.  Correcting for the endogeneity of pro-environment behavioral choices in contingent valuation , 2011 .

[40]  M. Johnson,et al.  Circulating microRNAs in Sera Correlate with Soluble Biomarkers of Immune Activation but Do Not Predict Mortality in ART Treated Individuals with HIV-1 Infection: A Case Control Study , 2015, PloS one.

[41]  John D. Claxton,et al.  Barriers to Consumer Choice of Energy Efficient Products , 1982 .

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

[43]  W. Greene,et al.  Marginal Effects in the Bivariate Probit Model , 1996 .

[44]  A. Kassouf,et al.  Work-Related Injuries Involving Children and Adolescents: Application of a Recursive Bivariate Probit Model , 2006 .

[45]  William H. Greene,et al.  Gender Economics Courses in Liberal Arts Colleges: Further Results , 1998 .

[46]  Gebhard Flaig,et al.  Household production and the short- and long-run demand for electricity , 1990 .

[47]  M. Coller,et al.  Eliciting Individual Discount Rates , 1999 .

[48]  Michael Siegrist,et al.  Desired and Undesired Effects of Energy Labels—An Eye-Tracking Study , 2015, PloS one.

[49]  Anthony Murphy,et al.  Score Tests of Normality in Bivariate Probit Models , 2007 .

[50]  Leslie Lamport,et al.  Latex : A Document Preparation System , 1985 .