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On the role of present bias and biased price beliefs in household energy consumption

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  • Werthschulte, Madeline
  • Löschel, Andreas

Abstract

The intermittency of energy billing may give rise to different biases or misperceptions, such that household energy demand deviates from its true optimum. This study investigates such deviations by linking variation in present-biased preferences and energy price beliefs to variation in energy consumed. Using both a survey and incentivized experiments, we gather measures of present bias as well as price beliefs, and observe participants’ true electricity consumption. Our main finding is that participants with present bias are predicted to consume on average 9 to 10 percent more electricity than participants with time-consistent discounting. Our results further suggest that neither the true marginal electricity price nor the perceived marginal electricity price can predict electricity consumption. These findings raise doubt as to the effectiveness of classic price-based policies in reducing household energy consumption.

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  • Werthschulte, Madeline & Löschel, Andreas, 2021. "On the role of present bias and biased price beliefs in household energy consumption," Journal of Environmental Economics and Management, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:jeeman:v:109:y:2021:i:c:s0095069621000723
    DOI: 10.1016/j.jeem.2021.102500
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    1. Kenneth Gillingham & Karen Palmer, 2014. "Bridging the Energy Efficiency Gap: Policy Insights from Economic Theory and Empirical Evidence," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 8(1), pages 18-38, January.
    2. Fischbacher, Urs & Schudy, Simeon & Teyssier, Sabrina, 2021. "Heterogeneous preferences and investments in energy saving measures," Resource and Energy Economics, Elsevier, vol. 63(C).
    3. Blasch, Julia & Boogen, Nina & Filippini, Massimo & Kumar, Nilkanth, 2017. "Explaining electricity demand and the role of energy and investment literacy on end-use efficiency of Swiss households," Energy Economics, Elsevier, vol. 68(S1), pages 89-102.
    4. Gilbert, Ben & Graff Zivin, Joshua, 2014. "Dynamic salience with intermittent billing: Evidence from smart electricity meters," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 176-190.
    5. Heutel, Garth, 2019. "Prospect theory and energy efficiency," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 236-254.
    6. Armin Falk & James J. Heckman, 2009. "Lab Experiments are a Major Source of Knowledge in the Social Sciences," Working Papers 200935, Geary Institute, University College Dublin.
    7. Qiu, Yueming & Colson, Gregory & Grebitus, Carola, 2014. "Risk preferences and purchase of energy-efficient technologies in the residential sector," Ecological Economics, Elsevier, vol. 107(C), pages 216-229.
    8. Lynham, John & Nitta, Kohei & Saijo, Tatsuyoshi & Tarui, Nori, 2016. "Why does real-time information reduce energy consumption?," Energy Economics, Elsevier, vol. 54(C), pages 173-181.
    9. David Bradford & Charles Courtemanche & Garth Heutel & Patrick McAlvanah & Christopher Ruhm, 2017. "Time preferences and consumer behavior," Journal of Risk and Uncertainty, Springer, vol. 55(2), pages 119-145, December.
    10. Stephan Meier & Charles Sprenger, 2010. "Present-Biased Preferences and Credit Card Borrowing," American Economic Journal: Applied Economics, American Economic Association, vol. 2(1), pages 193-210, January.
    11. Richard G. Newell & Juha Siikamäki, 2015. "Individual Time Preferences and Energy Efficiency," American Economic Review, American Economic Association, vol. 105(5), pages 196-200, May.
    12. Steffen Andersen & Glenn W. Harrison & Morten I. Lau & E. Elisabet Rutström, 2008. "Eliciting Risk and Time Preferences," Econometrica, Econometric Society, vol. 76(3), pages 583-618, May.
    13. Glenn W. Harrison & John A. List, 2004. "Field Experiments," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1009-1055, December.
    14. Mohammed Abdellaoui & Aurelien Baillon & Laetitia Placido & Peter P. Wakker, 2011. "The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation," American Economic Review, American Economic Association, vol. 101(2), pages 695-723, April.
    15. Mohammed Abdellaoui & Han Bleichrodt & Olivier L’Haridon, 2008. "A tractable method to measure utility and loss aversion under prospect theory," Journal of Risk and Uncertainty, Springer, vol. 36(3), pages 245-266, June.
    16. Harding, Matthew & Hsiaw, Alice, 2014. "Goal setting and energy conservation," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 209-227.
    17. Vischer, Thomas & Dohmen, Thomas & Falk, Armin & Huffman, David & Schupp, Jürgen & Sunde, Uwe & Wagner, Gert G., 2013. "Validating an ultra-short survey measure of patience," Economics Letters, Elsevier, vol. 120(2), pages 142-145.
    18. Schleich, Joachim & Gassmann, Xavier & Meissner, Thomas & Faure, Corinne, 2019. "A large-scale test of the effects of time discounting, risk aversion, loss aversion, and present bias on household adoption of energy-efficient technologies," Energy Economics, Elsevier, vol. 80(C), pages 377-393.
    19. Andreas Löschel & Matthias Rodemeier & Madeline Werthschulte, 2020. "When Nudges Fail to Scale: Field Experimental Evidence from Goal Setting on Mobile Phones," CESifo Working Paper Series 8485, CESifo.
    20. Wichman, Casey J., 2014. "Perceived price in residential water demand: Evidence from a natural experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PA), pages 308-323.
    21. Alexander K. Koch & Julia Nafziger, 2019. "Correlates of Narrow Bracketing," Scandinavian Journal of Economics, Wiley Blackwell, vol. 121(4), pages 1441-1472, October.
    22. Armin Falk & Anke Becker & Thomas Dohmen & Benjamin Enke & David B. Huffman & Uwe Sunde, 2017. "Global Evidence on Economic Preferences," NBER Working Papers 23943, National Bureau of Economic Research, Inc.
    23. Tatyana Deryugina & Alexander MacKay & Julian Reif, 2020. "The Long-Run Dynamics of Electricity Demand: Evidence from Municipal Aggregation," American Economic Journal: Applied Economics, American Economic Association, vol. 12(1), pages 86-114, January.
    24. Wichman, Casey J., 2017. "Information provision and consumer behavior: A natural experiment in billing frequency," Journal of Public Economics, Elsevier, vol. 152(C), pages 13-33.
    25. Supreet Kaur & Michael Kremer & Sendhil Mullainathan, 2015. "Self-Control at Work," Journal of Political Economy, University of Chicago Press, vol. 123(6), pages 1227-1277.
    26. Jonathan Cohen & Keith Marzilli Ericson & David Laibson & John Myles White, 2020. "Measuring Time Preferences," Journal of Economic Literature, American Economic Association, vol. 58(2), pages 299-347, June.
    27. Taisuke Imai & Tom A Rutter & Colin F Camerer, 2021. "Meta-Analysis of Present-Bias Estimation using Convex Time Budgets," The Economic Journal, Royal Economic Society, vol. 131(636), pages 1788-1814.
    28. Katrina Jessoe & David Rapson, 2014. "Knowledge Is (Less) Power: Experimental Evidence from Residential Energy Use," American Economic Review, American Economic Association, vol. 104(4), pages 1417-1438, April.
    29. Schneider, Sebastian O. & Sutter, Matthias, 2020. "Higher Order Risk Preferences: Experimental Measures, Determinants and Related Field Behavior," VfS Annual Conference 2020 (Virtual Conference): Gender Economics 224643, Verein für Socialpolitik / German Economic Association.
    30. Nava Ashraf & Dean Karlan & Wesley Yin, 2006. "Tying Odysseus to the Mast: Evidence From a Commitment Savings Product in the Philippines," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 121(2), pages 635-672.
    31. Koichiro Ito, 2014. "Do Consumers Respond to Marginal or Average Price? Evidence from Nonlinear Electricity Pricing," American Economic Review, American Economic Association, vol. 104(2), pages 537-563, February.
    32. Michael D. Grubb & Matthew Osborne, 2015. "Cellular Service Demand: Biased Beliefs, Learning, and Bill Shock," American Economic Review, American Economic Association, vol. 105(1), pages 234-271, January.
    33. Steven Sexton, 2015. "Automatic Bill Payment and Salience Effects: Evidence from Electricity Consumption," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 229-241, May.
    34. Armin Falk & Anke Becker & Thomas Dohmen & David Huffman & Uwe Sunde, 2023. "The Preference Survey Module: A Validated Instrument for Measuring Risk, Time, and Social Preferences," Management Science, INFORMS, vol. 69(4), pages 1935-1950, April.
    35. Gijs van de Kuilen & Peter P. Wakker, 2011. "The Midweight Method to Measure Attitudes Toward Risk and Ambiguity," Management Science, INFORMS, vol. 57(3), pages 582-598, March.
    36. Sebastian O. Schneider & Matthias Sutter, 2020. "Higher Order Risk Preferences: New Experimental Measures, Determinants and Field Behavior," CESifo Working Paper Series 8544, CESifo.
    37. Armin Falk & Anke Becker & Thomas Dohmen & Benjamin Enke & David Huffman & Uwe Sunde, 2018. "Global Evidence on Economic Preferences," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(4), pages 1645-1692.
    38. Takeuchi, Kan, 2011. "Non-parametric test of time consistency: Present bias and future bias," Games and Economic Behavior, Elsevier, vol. 71(2), pages 456-478, March.
    39. Kelsey Jack & Grant Smith, 2020. "Charging Ahead: Prepaid Metering, Electricity Use, and Utility Revenue," American Economic Journal: Applied Economics, American Economic Association, vol. 12(2), pages 134-168, April.
    40. Brent, Daniel A. & Ward, Michael B., 2019. "Price perceptions in water demand," Journal of Environmental Economics and Management, Elsevier, vol. 98(C).
    41. Allcott, Hunt, 2011. "Rethinking real-time electricity pricing," Resource and Energy Economics, Elsevier, vol. 33(4), pages 820-842.
    42. Andreoni, James & Kuhn, Michael A. & Sprenger, Charles, 2015. "Measuring time preferences: A comparison of experimental methods," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 451-464.
    43. Alexander L. Brown & Hwagyun Kim, 2014. "Do Individuals Have Preferences Used in Macro-Finance Models? An Experimental Investigation," Management Science, INFORMS, vol. 60(4), pages 939-958, April.
    44. Shapiro, Jesse M., 2005. "Is there a daily discount rate? Evidence from the food stamp nutrition cycle," Journal of Public Economics, Elsevier, vol. 89(2-3), pages 303-325, February.
    45. Brounen, Dirk & Kok, Nils & Quigley, John M., 2013. "Energy literacy, awareness, and conservation behavior of residential households," Energy Economics, Elsevier, vol. 38(C), pages 42-50.
    46. Ted O'Donoghue & Matthew Rabin, 2015. "Present Bias: Lessons Learned and to Be Learned," American Economic Review, American Economic Association, vol. 105(5), pages 273-279, May.
    47. Kuchler, Theresa & Pagel, Michaela, 2021. "Sticking to your plan: The role of present bias for credit card paydown," Journal of Financial Economics, Elsevier, vol. 139(2), pages 359-388.
    48. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd & Ulm, Eric R., 2017. "Scoring rules for subjective probability distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 134(C), pages 430-448.
    49. Maribeth Coller & Melonie Williams, 1999. "Eliciting Individual Discount Rates," Experimental Economics, Springer;Economic Science Association, vol. 2(2), pages 107-127, December.
    50. Sebastien Houde, Annika Todd, Anant Sudarshan, June A. Flora , and K. Carrie Armel, 2013. "Real-time Feedback and Electricity Consumption: A Field Experiment Assessing the Potential for Savings and Persistence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    51. David Laibson, 1997. "Golden Eggs and Hyperbolic Discounting," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(2), pages 443-478.
    52. Peter C. Reiss & Matthew W. White, 2005. "Household Electricity Demand, Revisited," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 853-883.
    53. Serdar Sayman & Ayse Öncüler, 2009. "An Investigation of Time Inconsistency," Management Science, INFORMS, vol. 55(3), pages 470-482, March.
    54. Steven D. Levitt & John A. List, 2007. "What Do Laboratory Experiments Measuring Social Preferences Reveal About the Real World?," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 153-174, Spring.
    55. Harrison, Glenn W., 1986. "An experimental test for risk aversion," Economics Letters, Elsevier, vol. 21(1), pages 7-11.
    56. Matthew Harding & Alice Hsiaw, 2014. "Goal Setting and Energy Conservation," Working Papers 1403, College of the Holy Cross, Department of Economics, revised Aug 2014.
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    More about this item

    Keywords

    Energy consumption; Present bias; Price beliefs; Artefactual field experiment;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D15 - Microeconomics - - Household Behavior - - - Intertemporal Household Choice; Life Cycle Models and Saving
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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