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Current Sustainable/Renewable Energy Reports
Erschienen in: Current Sustainable/Renewable Energy Reports 4/2019

05.09.2019 | Transportation (D Chen, Section Editor)

Implications of Behavioral Economics for the Costs and Benefits of Fuel Economy Standards

verfasst von: David L. Greene

Erschienen in: Current Sustainable/Renewable Energy Reports | Ausgabe 4/2019

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Abstract

Purpose of Review

This review focuses on recent developments in the application of behavioral economics to the evaluation of energy efficiency and greenhouse gas regulations. Transportation is the largest source of CO2 emissions from energy use in the US economy and a major and growing source worldwide. Regulating the efficiency of motor vehicles has been a core component of energy policy in the USA, the EU, China, Japan, Canada, and many other nations. Recent findings concerning consumers’ actual decision-making about energy efficiency indicate that the premises of the rational economic model are not appropriate for evaluating energy-efficiency standards.

Recent Findings

Progress in behavioral psychology and economics has shown that loss aversion, the principle that faced with a risky choice human beings tend to weigh potential losses about twice as heavily as gains, is strongly affected by framing. Simple, risky choices in which there is a status quo option generally provoke loss-averse responses. Recent analyses show that the choice to buy or not buy energy-efficiency technologies induces loss aversion and can result in systematic underinvestment in energy efficiency. Empirical investigation of consumers’ fuel economy decision-making contradicts the rational economic model and is consistent with loss aversion. However, recent economic evaluations of fuel economy and greenhouse gas regulations are explicitly or implicitly premised on rational economic behavior.

Summary

Insights developed by behavioral psychologists and behavioral economists about the decision-making of real consumers provide a coherent explanation that fundamentally alters the way fuel economy regulations should be evaluated. If consumers are assumed to make decisions according to the rational economic model and markets are reasonably efficient, regulations cannot produce large private fuel savings. The behavioral economic model explains not only why such savings do exist but why consumers strongly support fuel economy regulations. The private savings from fuel economy regulations can be large relative to the social benefits of fuel economy and greenhouse gas regulations.
Vorheriger Artikel Potential Impacts of Transportation and Building Electrification on the Grid: A Review of Electrification Projections and Their Effects on Grid Infrastructure, Operation, and Planning
Nächster Artikel Mobility and Energy Impacts of Shared Automated Vehicles: a Review of Recent Literature

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Fußnoten
1
The sustainability goals are stabilizing global climate change, enhancing energy security and resiliency, eliminating air pollution, and achieving universal access to modern energy services.
 
2
Figure 1 does not include the “rebound effect,” which is the tendency for vehicle travel to increase when fuel economy improves; however, the 2 trillion gallon estimate does [2].
 
3
Daniel Kahneman was awarded the Nobel Prize in Economics in 2002 for his work in behavioral economics including Cumulative Prospect Theory and loss aversion. His book cited here, Thinking Fast and Slow, won the National Academies’ Best Book Award for 2012 [31]. Richard Thaler won the 2017 Nobel Prize in Economics for his work in behavioral economics.
 
4
Weighing losses twice as much as gains is a typical or average loss-averse response. Kahneman [27] cites a range of 1.5 to 2.5, but there is even greater variation among individuals.
 
5
“Third, by implementing the modular elements of CPT, we can conclude that loss aversion is the major driver of the EE gap. Our results indicate that other elements of CPT, such as probability weighting, have a rather negligible influence. As an exception, however, we find the determination of the reference-point to be very important. Depending on how the EE investment is framed, or perceived by the decision-maker, the EE gap might vanish or be amplified.” [23]
 
6
Sallee [34] simulated annual fuel costs based on 100,000 random drawings from actual distributions of annual miles, discount rates and the gasoline price forecasts of individual consumers. The estimates varied widely in relation to label values even though uncertainty about actual on-road fuel economy was not included. “This means that even if a fuel economy label explained the lifetime fuel costs accurately for the median driver, that estimate will be too high or too low by $6200, or 50%, on average.” [34], p., 789
 
7
The measure of variability is insensitive to the discount rate assumed. The analysis is based on annual prices of regular grade gasoline from the EIA October 26, 2018 Monthly Energy Review Table 9.4, converted to 2017 dollars using the FRED GDP price deflator.
 
8
Hamilton [36] demonstrated that world oil prices are indistinguishable from a random walk, and nearly all the variability in US gasoline prices over time can be explained by changes in world oil prices [37].
 
9
This result is consistent with Dharshing and Hille [45] who found that numeracy and energy literacy were not statistically significantly related to the energy efficiency choices of Swiss households but impulsivity and risk aversion were.
 
10
The Ford Model T was introduced in 1908.
 
11
The fifth committee’s work is still in progress and no findings have been issued.
 
12
Assumes a 6% annual discount rate and a 13-year vehicle lifetime.
 
13
The four studies are not independent. Helfand and Wolverton [52] make extensive use of Greene [49], and Greene et al. [51] is based on estimates presented in EPA [50].
 
14
A vehicle’s mass determines the physical work that must be done to accelerate it and to overcome the friction of rolling resistance. Mass is also correlated with size and frontal area, a key determinant of aerodynamic resistance. Finally, apart from a vehicle’s mass, for vehicles with stoichiometric engines, engine size determines how much fuel is consumed per engine revolution.
 
15
The mathematical representation of loss aversion used is taken from Bernartzi and Thaler [65] and was intended to describe consumers’ behavior in the case of simple win or lose bets. Uncertainties about future fuel savings are far more complex. How best to describe consumers’ decision-making in the face of more complex uncertainties would seem to be an important subject for future research.
 
16
EUT can include risk aversion. However, risk aversion is different from loss aversion and cannot explain the magnitude of undervaluing implied by loss aversion [66].
 
17
A common definition of willingness to pay is the maximum amount of money a consumer will give up to obtain a good or avoid a bad [67].
 
18
A large part of this may be due to different vehicles having different drivers making different kinds of trips.
 
19
The assumption of independence is a convenient simplification. There is some evidence that the on-road shortfall responds to the price of gasoline [24].
 
20
The NRC’s high cost function was chosen because it better illustrates situations in which loss-averse consumers would decline fuel economy improvements.
 
21
A car buyer’s willingness to pay (WTP) for increased fuel economy is calculated based on estimated on-road as opposed to test cycle fuel economy, annual miles driven and the rate at which miles decrease over time, expected vehicle life, expected price of gasoline, and the discount rate for future fuel savings.
 
22
Taking external costs of fuel consumption into account, the socially optimal mpg would be higher than the privately optimal mpg. On the other hand, the private optimum would include fuel taxes in the price of fuel while the social optimum would not.
 
23
The automotive market is very competitive even if it is not perfectly competitive. Even assuming oligopolistic supply and Bertrand competition, the shadow price of a binding fuel economy or greenhouse gas emission constraint will induce the adoption of fuel economy improving technologies across all vehicles, except for vehicles that have already adopted all technologies justified by the shadow price.
 
24
Surveys indicate that US consumers consistently and overwhelmingly approved of fuel economy standards. Typically, 70 to 80% of respondents favored fuel economy standards and raising the standards (5, Table 9.2; 4).
 
25
Feebates that tax-inefficient vehicles and subsidize efficient vehicles at a fixed rate per gallon per mile are an example of such taxes [79, 80].
 
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Metadaten
Titel
Implications of Behavioral Economics for the Costs and Benefits of Fuel Economy Standards
verfasst von
David L. Greene
Publikationsdatum
05.09.2019
Verlag
Springer International Publishing
Erschienen in
Current Sustainable/Renewable Energy Reports / Ausgabe 4/2019
Elektronische ISSN: 2196-3010
DOI
https://doi.org/10.1007/s40518-019-00134-3

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