Abstract
This paper investigates the relation between estimation techniques and the estimates of consumers’ discount rates. In an earlier paper, the author estimated the average value of discount rates using direct elicitation, which was found to be 50.8%. In this paper, consumers’ discount rates adopted in purchasing room air conditioners are estimated using revealed-preference data. Estimates using hedonic pricing and qualitative choice models indicate discount rates of 13.6% and 10.7%, respectively. The results reveal that the rate estimated using direct elicitation is four- or five-fold the rate estimated using hedonic pricing method or qualitative choice analysis. A possible reason for this is that consumers make cognitive errors and desire unrealistically high returns from the use of energy-efficient models. This paper also examines how consumers’ attentiveness to energy efficiency affects their discount rates, finding that inattentiveness may cause the adoption of higher discount rates.
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The datasets generated during the current study are available from the corresponding author on reasonable request.
Notes
The monetary valuation of environmental goods and services is one of the research areas to which revealed-preference approach is applied. The hedonic pricing method has been utilized to estimate the implicit prices of nonmarket goods such as air pollution. Estimating the economic value of recreation resources uses travel costs as implicit prices.
Stated-preference approach used in the field of estimating the monetary value of environmental goods and services includes the contingent valuation method and conjoint analysis. Contingent valuation is a technique that draws data on preferences for environmental goods or services from people’s responses to hypothetical questions. Conjoint analysis is a method that elicits preferences for different attributes of an individual product or service using survey question.
See Kakaku.com’s website (http://kakaku.com/).
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
The additional cost of purchasing a high-efficiency model of a room air conditioner unit (i.e., ¥25,000) is calculated as the difference between the average price of high-efficiency models and that of standard-efficiency models using retail price data provided by Kakaku.com in November 2009.
Allcott and Greenstone (2012) pointed out that the unobserved attributes of energy-efficient products complicate the estimation of models for consumer choice between energy-consuming durable goods.
For a discussion of functional form choice in hedonic price functions, see Halstead et al. (1997).
This means that the data for the year in which the models were released are normalized at 2005.
The correlation coefficients between saving and income and between saving and education are 0.041 and 0.033, respectively. These suggest that consumers with higher income or higher education are not necessarily more attentive to energy efficiency.
References
Adamowicz W, Louviere J, Williams M (1994) Combining revealed and stated preference methods for valuing environmental amenities. J Environ Econ Manag 26:271–292
Allcott H (2011) Consumers’ perceptions and misperceptions of energy costs. Am Econ Rev: Pap Proc 101(3):98–104
Allcott H, Greenstone M (2012) Is there an energy efficiency gap? J Econ Perspect 26(1):3–28
Andor MA, Frondel M, Gerster A, Sommer S (2019) Cognitive reflection and the valuation of energy efficiency. Energy Econ 84:104527
Andor MA, Gerster A, Sommer S (2020) Consumer inattention, heuristic thinking and the role of energy labels. Energy J 41(1):83–112
Arthur D. Little, Inc. (1984) Measuring the impact of residential conservation programs: an econometric analysis of utility data, volume VIII. Final report for RP1587, Electric Power Research Institute
Blasch J, Filippini M, Kumar N (2019) Boundedly rational consumers, energy and investment literacy, and the display of information on household appliances. Resour Energy Econ 56:39–58
Bruderer Enzler H, Diekmann A, Meyer R (2014) Subjective discount rates in the general population and their predictive power for energy saving behavior. Energy Policy 65:524–540
Cameron TA (1992) Combining contingent valuation and travel cost data for the valuation of nonmarket goods. Land Econ 68(3):302–317
Carson RT, Flores NE, Martin KM, Wright JL (1996) Contingent valuation and revealed preference methodologies: comparing the estimates for quasi-public goods. Land Econ 72(1):80–99
Coller M, Williams MB (1999) Eliciting individual discount rates. Exp Econ 2:107–127
Davis LW, Metcalf GE (2016) Does better information lead to better choices? Evidence from energy-efficiency labels. J Assoc Environ Resour Econ 3(3):589–625
Dreyfus MK, Viscusi WK (1995) Rates of time preference and consumer valuations of automobile safety and fuel efficiency. J Law Econ 38(1):79–105
Dubin JA (1986) Will mandatory conservation promote energy efficiency in the selection of household appliance stocks? Energy J 7(1):99–118
Gately D (1980) Individual discount rates and the purchase and utilization of energy-using durables: comment. Bell J Econ 11(1):373–374
Gerarden TD, Newell RG, Stavins RN (2017) Assessing the energy-efficiency gap. J Econ Lit 55(4):1486–1525
Gillingham K, Palmer K (2014) Bridging the energy efficiency gap: policy insights from economic theory and empirical evidence. Rev Environ Econ Policy 8(1):18–38
Gillingham K, Newell RG, Palmer K (2009) Energy efficiency economics and policy. Ann Rev Resour Econ 1:597–620
Goett A (1983) Household appliance choice: revision of REEPS behavioral models. Final report for research project 1918-1, Electric Power Research Institute
Halstead JM, Bouvier RA, Hansen BE (1997) On the issue of functional form choice in hedonic price functions: further evidence. Environ Manag 21(5):759–765
Hamamoto M (2012) Consumers’ energy-saving investment decisions and discount rates. In: Arimura T, Takeda S (eds) Economic analysis of emissions trading and energy conservation: current state of Japanese firms and households. Nihonhyoronsha, Tokyo, pp 191–211 (in Japanese)
Harrison GW, Lau MI, Williams MB (2002) Estimating individual discount rates in Denmark: a field experiment. Am Econ Rev 92(5):1606–1617
Hausman JA (1979) Individual discount rates and the purchase and utilization of energy-using durables. Bell J Econ 10(1):33–54
He S, Blasch J, van Beukering P, Wang J (2022) Energy labels and heuristic decision-making: the role of cognition and energy literacy. Energy Econ 114:106279
Heinzle SL (2012) Disclosure of energy operating cost information: a silver bullet for overcoming the energy-efficiency gap? J Consum Policy 35(1):43–64
Houde S (2014) How consumers respond to environmental certification and the value of energy information. NBER Working Paper No. 20019, National Bureau of Economic Research
Houston DA (1983) Implicit discount rates and the purchase of untried, energy-saving durable goods. J Consum Res 10:236–246
Irfan M, Elavarasan RM, Ahmad M, Mohsin M, Dagar V, Hao Y (2022) Prioritizing and overcoming biomass energy barriers: application of AHP and G-TOPSIS approaches. Technol Forecast Soc Chang 177:121524
Khan I, Zakari A, Zhang J, Dagar V, Singh S (2022) A study of trilemma energy balance, clean energy transitions, and economic expansion in the midst of environmental sustainability: new insights from three trilemma leadership. Energy 248:123619
Lancaster KJ (1966) A new approach to consumer theory. J Polit Econ 74(2):132–157
Matisoff DC, Noonan DS (2022) Ecolabels, innovation, and green market transformation: learning to LEED. Cambridge University Press, Cambridge
Mau P, Eyzaguirre J, Jaccard M, Collins-Dodd C, Tiedemann K (2008) The ‘neighbor effect’: simulating dynamics in consumer preferences for new vehicle technologies. Ecol Econ 68:504–516
Meier AK, Whittier J (1983) Consumer discount rates implied by purchases of energy-efficient refrigerators. Energy 8(12):957–962
Min J, Azevedo IL, Michalek J, de Bruin WB (2014) Labeling energy cost on light bulbs lowers implicit discount rates. Ecol Econ 97:42–50
Morita M, Matsumoto S, Tasaki T (2014) Effect of an energy rebate program on implicit discount rate: a hedonic analysis of the Japanese Eco Point Program. Rev Environ Econ Policy Stud 7(2):24–36 (in Japanese)
Newell RG, Siikamäki J (2014) Nudging energy efficiency behavior: the role of information labels. J Assoc Environ Resour Econ 1(4):555–598
Newell RG, Siikamäki J (2015) Individual time preferences and energy efficiency. Am Econ Rev: Pap Proc 105(5):196–200
Revelt D, Train K (1998) Mixed logit with repeated choices: households’ choices of appliance efficiency level. Rev Econ Stat 80:647–657
Rosen S (1974) Hedonic prices and implicit markets: product differentiation in pure competition. J Polit Econ 82(1):34–55
Ruderman H, Levine MD, McMahon JE (1987) The behavior of the market for energy efficiency in residential appliances including heating and cooling equipment. Energy J 8(1):101–124
Sallee JM (2014) Rational inattention and energy efficiency. J Law Econ 57(3):781–820
Schleich J, Gassmann X, Faure C, Meissner T (2016) Making the implicit explicit: a look inside the implicit discount rate. Energy Policy 97:321–331
Schubert R, Stadelmann M (2015) Energy-using durables—why consumers refrain from economically optimal choices. Front Energy Res 3:7
Stadelmann M (2017) Mind the gap? Critically reviewing the energy efficiency gap with empirical evidence. Energy Res Soc Sci 27:117–128
Stadelmann M, Schubert R (2018) How do different designs of energy labels influence purchases of household appliances? A field study in Switzerland. Ecol Econ 144:112–123
Tang C, Irfan M, Razzaq A, Dagar V (2022) Natural resources and financial development: role of business regulations in testing the resource-curse hypothesis in ASEAN countries. Resour Policy 76:102612
Tietenberg T (2009) Reflections—energy efficiency policy: pipe dream or pipeline to the future? Rev Environ Econ Policy 3(2):304–320
Train K (1985) Discount rates in consumers’ energy-related decisions: a review of the literature. Energy 10(12):1243–1253
Whitehead JC, Phaneuf DJ, Dumas CF, Herstine J, Hill J, Buerger B (2010) Convergent validity of revealed and stated recreation behavior with quality change: a comparison of multiple and single site demands. Environ Resour Econ 45:91–112
Xie M, Irfan M, Razzaq A, Dagar V (2022) Forest and mineral volatility and economic performance: evidence from frequency domain causality approach for global data. Resour Policy 76:102685
Zhang C, Khan I, Dagar V, Saeed A, Zafar MW (2022) Environmental impact of information and communication technology: unveiling the role of education in developing countries. Technol Forecast Soc Chang 178:121570
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This research was funded by support from Soka City and the Institute of Human and Environmental Symbiosis Research, Dokkyo University.
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Hamamoto, M. Estimating consumers’ discount rates in energy-saving investment decisions: a comparison of revealed and stated approaches. SN Bus Econ 3, 120 (2023). https://doi.org/10.1007/s43546-023-00504-6
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DOI: https://doi.org/10.1007/s43546-023-00504-6