Regulation in the behavioral era

Minnesota Law Review

Volumn 95, Issue 3, 2011, Pages 715-781

  Vandenbergh, Michael P ^a,b   Carrico, Amanda R ^c   Bressman, Lisa Schultz ^c  

^a Department of Law ^*  (United States)

^b Environmental Law Program   (United States)

^c VANDERBILT UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79955941623     PISSN: 00265535     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (419)

1. RICHARD H. THALER & CASS R. SUNSTEIN, NUDGE 6 (2008).
2. See, e.g., DAN ARIELY, PREDICTABLY IRRATIONAL, at xx (2008);
3. Christine Jolls et al., A Behavioral Approach to Law and Economics, 50 STAN. L. REV. 1471, 1471 (1998); (Pubitemid 128421723)
4. Daniel Kahneman & Amos Tversky, Choices, Values, and Frames, 39 AM. PSYCHOLOGIST 341, 341 (1984);
5. Matthew Rabin, Psychology and Economics, 36 J. ECON. LITERATURE 11, 11 (1998).
6. For recent accounts in popular literature, see Dan Charles, Leaping the Efficiency Gap, 325 SCIENCE 804 (2009)
7. and Michael Grunwald, How Obama Is Using the Science of Change, TIME, Apr.13, 2009, at 28.
8. See, e.g., Letter from Cass R. Sunstein, Adm'r, Office of Info. & Regulatory Affairs, to the Honorable David Strickland, Adm'r, Nat'l Highway Traffic Safety Admin. (Mar. 19, 2010), available at http://www.reginfo.gov/ public/postreview/Tire-Fuel-Efficiency-Consumer-Information-Final-Rule.pdf (encouraging the Agency to complete comprehensive studies that reflect principles of behavioral economics, such as promoting easy comparison shopping).
9. See, e.g., OFFICE OF MGMT. & BUDGET, EXEC. OFFICE OF THE PRESIDENT, 2009 REPORT TO CONGRESS ON THE BENEFITS AND COSTS OF FEDERAL REGULATIONS AND UNFUNDED MANDATES ON STATE, LOCAL, AND TRIBAL ENTITIES 35 (2010), available at http://www.whitehouse.gov/sites/default/files/omb/assets/legislative-reports/ 2009-final-BC-Report-01272010.pdf ("OMB recommends consideration of behaviorally informed approaches to regulation. Such approaches, rooted in several decades of work in social science, can serve to improve rules by incorporating insights that come from relaxing assumptions usually invoked in neoclassical economic theory. With an accurate understanding of human behavior, agencies would be in a position to suggest innovative, effective, and low-cost methods of achieving regulatory goals.");
10. see also Memorandum from Cass R. Sunstein, Adm'r, Office of Info. & Regulatory Affairs, to the Heads of Executive Departments and Agencies 1 (June 18, 2010) [hereinafter 2010 OIRA Disclosure Memo], available at http://www.whitehouse.gov/sites/default/files/omb/assets/inforeg/ disclosure-principles.pdf (providing "guidance to inform the use of disclosure and simplification in the regulatory process").
11. Behavioral economics incorporates many of cognitive psychology's findings, and it has become common in the media to apply the term "behavioral economics" to the findings of several fields. See, e.g., Hunt Allcott & Sendhil Mullainathan, Behavior and Energy Policy, 327 SCIENCE 1204, 1204-05 (2010);
12. Grunwald, supra note 3, at 28. For widely read recent works in social psychology, see NOAH J. GOLDSTEIN ET AL., YES: 50 SCIENTIFICALLY PROVEN WAYS TO BE PERSUASIVE (2008);
13. DOUGLAS MCKENZIE-MOHR & WILLIAM SMITH, FOSTERING SUSTAINABLE BEHAVIOR (1999).
14. See, e.g., W. KIP VISCUSI, FATAL TRADEOFFS: PUBLIC AND PRIVATE RESPONSIBILITIES FOR RISK 153-59 (1992) (arguing that information about risk increases regulations' effectiveness);
15. John D. Graham & Jonathan Baert Wiener, Resolving Risk Tradeoffs, in RISK VERSUS RISK 226, 241-68 (John D. Graham & Jonathan Baert Wiener eds., 1995) (describing regulatory efforts that take into account human behavior);
16. Cass R. Sunstein, Cognition and Cost-Benefit Analysis, 29 J. LEGAL STUD. 1059, 1077-88 (2000) (noting that one role of cost-benefit analysis is to correct for decisionmaking by policymakers under pressure from non-rational public responses to risk).
17. We include a number of fields in the term "behavioral science." See, e.g., GARY S. BECKER & KEVIN M. MURPHY, SOCIAL ECONOMICS (2000) (economic sociology);
18. GOLDSTEIN et AL., supra note 6 (social psychology);
19. Kahneman & Tversky, supra note 2 (cognitive psychology);
20. George Loewenstein et al., Neuroeconomics, 59 ANN. REV. PSYCHOL. 647 (2008) (neuroeconomics).
21. Section 6 (a) (3) (C) (iii) of Executive Order 12, 866 directs agencies to analyze "potentially effective and reasonably feasible alternatives to the planned regulation. " Exec. Order No. 12, 866 §6 (a) (3) (C) (iii), 3 C. F. R. 638, 645 (1993)
22. reprinted in 5 U. S. C. § 601 (2006);
23. see also Jonathan Baert Wiener, Mechanism Choice, in PUBLIC CHOICE AND PUBLIC LAW (Daniel A. Farber & Anne Joseph O'Connell eds., forthcoming 2010) (manuscript at 30-31), available at http://papers.ssrn.com/sol3/papers.cfm? abstract-id=1408163 (discussing the potential influence of behavioral insights on regulatory-instrument choice);
24. OIRA Disclosure Memo, supra note 5, at 3, 9 (identifying principles to assist agencies' use of information disclosure, simplification, and default rules).
25. See discussion infra Part III. A. We use the term "electric cars" to refer to all personal light-duty vehicles that draw some or all of their energy from the electric grid, including plug-in hybrids as well as standard electric cars. The Department of Energy has included deployment of 500, 000 plug-in hybrid electric vehicles per year by 2015 in its seven "high priority performance goals." OFFICE OF MGMT. & BUDGET, EXEC. OFFICE OF THE PRESIDENT, ANALYTICAL PERSPECTIVES, BUDGET OF THE UNITED STATES GOVERNMENT, FISCAL YEAR 2011, at 79 (2010) [hereinafter ANALYTICAL PERSPECTIVES], available at http://www.whitehouse.gov/omb/budget/Analytical-Perspectives (click on "Performance & Management" hyperlink).
26. See discussion infra Part III. A; see also Thomas Webler & Seth P. Tuler, Getting the Engineering Right Is Not Always Enough: Researching the Human Dimensions of the New Energy Technologies, 38 ENERGY POL'Y 2690, 2691 (2010).
27. AHMAD FARUQUI & LISA WOOD, QUANTIFYING THE BENEFITS OF DYNAMIC PRICING IN THE MASS MARKET 30 (2008), available at http://www.eei.org/ourissues/ electricitydistribution/Documents/quantifying-benefits-final.pdf (noting that the level of off-peak to on-peak price shift needed to induce a reduction in peak load demand is often higher than utilities are willing to implement due to the fear of negative customer response).
28. Some evidence for this effect can be found in programs that have paired economic disincentives, such as taxes or fines, with public education campaigns that highlight the moral case for adoption of the target behavior. For example, a tax on plastic grocery bags in Ireland paired with an aggressive media campaign led to a ninety-four percent drop in the use of plastic bags. Elisabeth Rosenthal, With Irish Tax, Plastic Bags Go the Way of the Snakes, N. Y. TIMES, Feb. 2, 2008, at A3
29. available at 2008 WL 1990925.
30. See Exec. Order No. 12, 866 §6 (a) (C) (iii), 3 C. F. R. at 646 (requiring that agencies "assess both the costs and the benefits of the intended regulation").
31. NICK HANLEY & CLIVE L. SPASH, COST-BENEFIT ANALYSIS & THE ENVIRONMENT 4-6 (1993).
32. See Sunstein, supra note 7, at 1096.
33. See id. at 1077-88;
34. see also ANALYTICAL PERSPECTIVES, supra note 10, at 98 ("By drawing attention to the consequences of proposed courses of action, benefit-cost analysis can help the public to evaluate regulatory initiatives.").
35. See, e.g., SOC'Y FOR RISK ANALYSIS, COMMITTEE OF PAST PRESIDENTS' RECOMMENDATIONS TO OMB ON REGULATORY REVIEW 5 (2009), available at http://reginfo.gov/public/jsp/EO/fedRegReview/OIRA-EO-12866-revision-SRA- comments.pdf (recommending that OIRA "[e]nhance the role of social and behavioral sciences, regarding how and why people (as individuals or groups) behave and decide in response to risks, opportunities, and uncertainty");
36. OIRA Disclosure Memo, supra note 5, at 3-12 (providing guidance to agencies on use of behavioral principles in the regulatory process).
37. There is an ongoing debate as to whether the empirical observations reviewed here represent actual departures from rationality or are simply the result of other factors that are consistent with a rational, utility-maximizing agent. See BOUNDED RATIONALITY 10 (Gerd Gigerenzer & Reinhard Selten eds., 2001);
38. Richard A. Posner, Rational Choice, Behavioral Economics, and the Law, 50 STAN. L. REV. 1551, 1552 (1998). In this Article, we contrast empirical findings from social and behavioral findings with the "thick" conceptions of rationality that have dominated, implicitly if not explicitly, much of the study of law and economics. (Pubitemid 128421724)
39. See Russell B. Korobkin & Thomas S. Ulen, Law and Behavioral Science: Removing the Rationality Assumption from Law and Economics, 88 CALIF. L. REV. 1051, 1066, 1070-73 (2000). We do not intend to engage in the debate over the definition of rationality. Instead, we hope to offer a framework for incorporating a greater degree of behavioral realism (regardless of how labeled) into the process of regulatory development, review, and selection. For ease of discussion, we refer to this set of behavioral tendencies as "extra-rational behavior."
40. See, e.g., Matthew D. Adler, Bounded Rationality and Legal Scholarship, in THEORETICAL FOUNDATIONS OF LAW AND ECONOMICS 137, 137 (Mark D. White ed., 2010) (identifying the need for legal scholars to account for bounded rationality in the development of legal prescriptions);
41. Grant M. Hayden & Stephen E. Ellis, Law and Economics After Behavioral Economics, 55 U. KAN. L. REV. 629, 660-67 (2007) (proposing a behavioral framework that emphasizes the context of human action as an independent factor in the regulatory process);
42. Jolls et al., supra note 2, at 1476 (providing a framework for the use of behavioral economics research in law).
43. For a more general framework, see Jolls et al., supra note 2, at 1508-45. For the classic example of the development and application of a rigorous framework for legal analysis, see Guido Calabresi & A. Douglas Melamed, Property Rules, Liability Rules, and Inalienability: One View of the Cathedral, 85 HARV. L. REV. 1089, 1090-111 (1972).
44. See, e.g., W. Kip Viscusi, The Lulling Effect: The Impact of Child-Resistant Packaging on Aspirin and Analgesic Ingestions, 74 AM. ECON. REV. 324, 326-27 (1984) (documenting that the proportion of accidental aspirin ingestions from safety-capped bottles rose sharply after the introduction of childresistant bottle caps);
45. W. Kip Viscusi & Gerald Cavallo, Safety Behavior and Consumer Responses to Cigarette Lighter Safety Mechanisms, 17 MANAGERIAL & DECISION ECON. 441, 456 (1996) (suggesting that regulators consider consumer responses to product safety improvements and consider pairing technological approaches with hazard warnings and consumer education).
46. See Lisa Schultz Bressman & Michael P. Vandenbergh, Inside the Administrative State: A Critical Look at the Practice of Presidential Control, 105 MICH. L. REV. 47, 94-95 (2006) (noting that the selective presidential control of agency regulation, as exercised in part through OIRA, can undermine the legitimacy of such regulation). A related danger is that ad hoc review will enable agencies to overvalue one consideration at the expense of others. Many have argued that OIRA overemphasizes consideration of costs at the expense of benefits, which can tilt regulation in an antiregulatory direction.
47. See, e.g., Nicholas Bagley & Richard L. Revesz, Centralized Oversight of the Regulatory State, 106 COLUM. L. REV. 1260, 1262-63 (2006) (arguing that uneven application of cost-benefit analysis by OIRA can lead to a deregulatory bias).
48. See Elena Kagan, Presidential Administration, 114 HARV. L. REV. 2245, 2331-39 (2001) (noting the importance of transparency in the OMB and of greater White House control of agency regulation).
49. See Mathew D. McCubbins et al., Administrative Procedures as Instruments of Political Control, 3 J. L. ECON. & ORG. 243, 254-58 (1987) (arguing that congressional monitoring of agency regulation depends in part on constituent access to information about such regulation).
50. See Lisa Schultz Bressman, Procedures as Politics in Administrative Law, 107 COLUM. L. REV. 1749, 1805-07 (2007) (arguing that congressional oversight, particularly when coupled with White House regulatory review, can improve the accountability of agency regulation).
51. In developing our framework, we build on earlier work that examined the implications of behavioral economics for cost-benefit analysis. See Adler, supra note 20, at 155-62;
52. Jolls et al., supra note 2, at 1481-85;
53. Sunstein, supra note 7, at 1060-61;
54. Cass R. Sunstein, Willingness to Pay vs. Welfare, 1 HARV. L. & POL'Y REV. 303, 315-16 (2007).
55. For instance, the desires for fairness, altruistic tendencies, and morality have been extensively researched within economics. See, e.g., Kjell Arne Brekke et al., An Economic Model of Moral Motivation, 87 J. PUB. ECON. 1967, 1968 (2003) (examining the role of moral self-image in influencing prosocial behavior);
56. Catherine C. Eckel & Philip J. Grossman, Altruism in Anonymous Dictator Games, 16 GAMES & ECON. BEHAV. 181, 188 (1996) (examining altruism as a motivating factor in behavior);
57. Matthew Rabin, Incorporating Fairness into Game Theory and Economics, 83 AM. ECON. REV. 1281, 1282 (1993) (presenting a framework to study implications of fairness in economic situations).
58. See, e.g., Daniel Kahneman, A Perspective on Judgment and Choice: Mapping Bounded Rationality, 58 AM. PSYCHOLOGIST 697, 697-720 (using the term "bounded rationality" as the notion that human decisionmaking is bounded by cognitive and informational constraints).
59. See, e.g., MATTHEW D. ADLER & ERIC A. POSNER, NEW FOUNDATIONS OF COST-BENEFIT ANALYSIS 68-73 (2006);
60. Adler, supra note 20, at 160 (noting that cost-benefit analysis is "the traditional technique for implementing wealth-maximization and Kaldor-Hicks efficiency").
61. Cf. Calabresi & Melamed, supra note 21, at 1119-20 (identifying a matrix including property rules and liability rules with entitlements assigned to polluters or victims, and noting that the framework leads to the insight that a liability-rule-protected entitlement might be assigned to a polluter as well as a victim). The importance of analyzing non-rational responses to social outcome maximization emerges from our framework in a similar way. See discussion infra Part II. A.2.b.
62. See THALER & SUNSTEIN, supra note 1, at 68-69.
63. Individual and household behavioral changes could reduce U. S. carbon emissions by seven percent in ten years. See Thomas Dietz, Gerald T. Gardner, Jonathan Gilligan, Paul C. Stern & Michael P. Vandenbergh, Household Actions Can Provide a Behavioral Wedge to Rapidly Reduce U. S. Carbon Emissions, 106 PROC. NAT'L ACAD. SCI. 18, 452, at 18, 452 (2009).
64. In the Carter Administration, economic analysis of regulations was conducted to determine only the cost effectiveness of regulatory actions. See Robert W. Hahn & Cass R. Sunstein, A New Executive Order for Improving Federal Regulation? Deeper and Wider Cost-Benefit Analysis, 150 U. PA. L. REV. 1489, 1505-06 (2002). Benefits analysis was added in the Reagan Administration. Id.
65. see also W. Kip Viscusi, Risk Equity, 29 J. LEGAL STUD. 843, 854 (2000).
66. For a discussion of regulatory instrument choice, see Jonathan Baert Wiener, Global Environmental Regulation: Instrument Choice in Legal Context, 108 YALE L. J. 677, 679-80, 704-35 (1999).
67. The recent OIRA memorandum on the use of behavioral approaches notes the importance of consulting with behavioral scientists and of conducting rigorous empirical studies. See 2010 OIRA Disclosure Memo, supra note 5, at 5.
68. Id.
69. See 5 U. S. C. § 706 (2) (2007);
70. Motor Vehicle Mfrs. Ass'n v. State Farm Mut. Auto. Ins. Co., 463 U. S. 29, 42-43 (1983) (interpreting the "arbitrary and capricious standard" of the Administrative Procedure Act to require that agencies demonstrate that they have considered all relevant factors and all important aspects of a problem).
71. See SEC v. Chenery Corp., 318 U. S. 80, 95 (1943) (requiring the Agency to reveal the actual basis on which it relied and declining to uphold the agency's decision on any other basis).
72. Likewise, we do not and cannot address whether behavioral or traditional economic analysis should prevail in cases of conflict. Our framework does not purport to provide a fully integrated model; indeed, pursuit of such a model is akin to pursuit of the Holy Grail. These sorts of issues are not exclusive to behavioral analysis. In some sense, they are present in the classic conflict between agency expertise and political accountability in administrative law. See Jody Freeman & Adrian Vermeule, Massachusetts v. EPA: From Politics to Expertise, 2007 SUP. CT. REV. 51 (2008)
73. (using the Supreme Court's decision in Massachusetts v. EPA, 549 U. S. 497 (2007), to discuss the tension between administrative expertise and political accountability). When technocratic judgment and political responsiveness point in different directions, agencies are forced to make a choice (and sometimes courts may have a say as well).
74. See, e.g., ADLER & POSNER, supra note 30, at 68-100.
75. See, e.g., Daniel A. Farber, Rethinking the Role of Cost-Benefit Analysis, 76 U. CHI. L. REV. 1355, 1379-96 (2009) (arguing that the European regulatory model is a superior alternative to cost-benefit analysis for regulating toxic chemicals).
76. Cf. Kahneman, supra note 29, at 705-06 (discussing how assumptions about and models of human behavior frame decisions that aim to maximize utility).
77. Cf. Gregory Scott Crespi, The Fatal Flaw of Cost-Benefit Analysis: The Problem of Person-Altering Consequences, 38 ENVTL. L. REP. 10, 703, at 10, 703 n. 1 (2008) ("Prospective cost-benefit analyses of rulemaking initiatives and subsequent OIRA review (and, upon occasion, also judicial review) now appear to be entrenched as a significant feature of the federal regulatory process." (citation omitted)).
78. See Paul C. Stern, Toward a Coherent Theory of Environmentally Significant Behavior, 56 J. SOC. ISSUES 407, 419-20 (2000);
79. Michael P. Vandenbergh, Order Without Social Norms: How Personal Norms Can Protect the Environment, 99 NW. U. L. REV. 1101, 1103-06 (2005);
80. Charlie Wilson & Hadi Dowlatabadi, Models of Decision Making and Residential Energy Use, 32 ANN. REV. ENV'T & RESOURCES 169, 189 (2007).
81. Our focus here is on individuals and households, although many of the behavioral insights are relevant to the behavior of small businesses, large corporations, and nonprofit organizations as well. Of course, behavioral analysis could just provide policymakers with a means to "avoid painful but more effective solutions rooted in traditional economics, " such as removing subsidies or introducing taxes. George Loewenstein & Peter Ubel, Economics Behaving Badly, N. Y. TIMES, July 15, 2010, at A31, available at 2010 WLNR 14148206;
82. see also Gregory Mitchell, Why Law and Economics' Perfect Rationality Should Not Be Traded for Behavioral Law and Economics' Equal Incompetence, 91 GEO. L. J. 67, 72 (2002) (positing that a middle ground between perfect rationality and equal incompetence illuminates ways the legal system may foster rational or counter-irrational behavior). We note that behavioral measures need not displace traditional regulatory measures, however. In many cases, behavioral measures may supplement traditional measures or may fill gaps when public support is lacking for such measures.
83. See, e.g., Paul C. Stern, Blind Spots in Policy Analysis: What Economics Doesn't Say About Energy Use, 5 J. POL'Y ANALYSIS & MGMT. 200, 210-11 (1986) (noting that when the monetary value of price incentives for energy efficiency investments are held constant, participation rates can vary by a factor of ten due to non-price-related factors).
84. See, e.g., W. Ross Morrow et al., Analysis of Policies to Reduce Oil Consumption and Greenhouse-Gas Emissions from the U. S. Transportation Sector, 38 ENERGY POL'Y 1305, 1317-18 (2010) (concluding that a price of gasoline between $5.00 and $7.00 per gallon would be necessary to achieve a fourteen percent U. S. reduction in greenhouse gas emissions below 2005 levels by 2025).
85. See, e.g., Robert B. Cialdini, Crafting Normative Messages to Protect the Environment, 12 CURRENT DIRECTIONS PSYCHOL. SCI. 105, 108-09 (2003) (noting that public education campaigns that communicate that an undesirable behavior is "regrettably frequent" can lead to an increase in the undesirable behavior by sending the descriptively normative message that the behavior is common and therefore acceptable);
86. Michael P. Vandenbergh, Beyond Elegance: A Testable Typology of Social Norms in Corporate Environmental Compliance, 22 STAN. ENVTL. L. J. 55, 104-05, 115 (2003) (discussing studies on the unintended effects of regulatory interventions on tax compliance); Viscusi, supra note 22, at 326-27 (discussing unintended consequences of childresistant bottle caps).
87. For a discussion of the interpretations of the rational-actor model, see Korobkin & Ulen, supra note 19, at 1070-74.
88. For a discussion of the assumptions and variations of rational choice theory, see Andrew M. Colman, Cooperation, Psychological Game Theory, and Limitations of Rationality in Social Interaction, 26 BEHAV. & BRAIN SCI. 139, 139-43 (2003)
89. and Korobkin & Ulen, supra note 19, at 1060-66.
90. For a more detailed discussion of rational choice theory, see GARY S. BECKER, THE ECONOMIC APPROACH TO HUMAN BEHAVIOR 3-14 (1976);
91. Colman, supra note 50, at 139-43;
92. and Korobkin & Ulen, supra note 19, at 1060-66.
93. See Adler, supra note 20, at 158-59;
94. Korobkin & Ulen, supra note 19, at 1064-65;
95. see also Ann E. Carlson, Recycling Norms, 89 CALIF. L. REV. 1231, 1237-38 & n. 12 (2001) (noting that measuring utility entirely based on monetary incentives is often described as a "thick" approach to utility).
96. Korobkin & Ulen, supra note 19, at 1065.
97. See, e.g., Loewenstein et al., supra note 8, at 661 (noting that the position that individuals act only according to pure self-interest is a minority position within economics);
98. Posner, supra note 19, at 1551-52 (explaining his broadly defined interpretation of rational action as well as the point that the economic analysis of law has "long ago abandoned the model of hyper rational, emotionless, unsocial, supremely egoistic, nonstrategic man (or woman) ").
99. See Robert E. Scott, The Limits of Behavioral Theories of Law and Social Norms, 86 VA. L. REV. 1603, 1622 n. 39 (2000);
100. see also Loewenstein & Ubel, supra note 45, at A31.
101. See Korobkin & Ulen, supra note 19, at 1057 n. 18 (positing that aggregate behavior follows predictions of rational choice theory even where individuals deviate from that behavior, so long as those deviations are symmetrically distributed).
102. See Carlson, supra note 52, at 1237-38 (noting that this is often described as a "thin" approach to utility). For a discussion of thin conceptions of utility
103. see Jolls et al., supra note 2, at 1479 (discussing "bounded selfinterest")
104. and Korobkin & Ulen, supra note 19, at 1061-62.
105. See Robyn M. Dawes, Social Dilemmas, 31 ANN. REV. PSYCHOL. 169, 175-78 (1980) (discussing an expanded definition of utility that includes nonmonetary outcomes);
106. Posner, supra note 19, at 1551-52.
107. William Samuelson & Richard Zeckhauser, Status Quo Bias in Decision Making, 1 J. RISK & UNCERTAINTY 7, 31-33 (1988).
108. In a meta-analysis of over one hundred social dilemma experiments, David Sally found an average cooperation rate of forty-seven percent within one-shot Prisoner's Dilemma games, although cooperation varied widely depending on the situational variables manipulated in the studies. David Sally, Conversation and Cooperation in Social Dilemmas: A Meta-Analysis of Experiments From 1958 to 1992, 7 RATIONALITY & SOC'Y 58, 60-62 (1995). In their review of this literature, Robyn Dawes and Richard Thaler state that cooperation rates in one-shot social dilemmas typically range between forty and sixty percent, even though rational choice theory (where utility is measured by monetary self-interest) would predict a zero percent cooperation rate.
109. Robyn M. Dawes & Richard H. Thaler, Anomalies: Cooperation, 2 J. ECON. PERSP. 187, 188-89 (1988).
110. See Robyn M. Dawes & David M. Messick, Social Dilemmas, 35 INT'L J. PSYCHOL. 111, 114 (2000) (noting that social identification with others involved in social dilemmas leads to greater levels of cooperation);
111. Peter Kollock, Social Dilemmas: The Anatomy of Cooperation, 24 ANN. REV. SOC. 183, 195-97 (1998) (reviewing literature on the influence of reciprocity norms on decisionmaking in social dilemmas).
112. For example, Solomon Asch demonstrated that roughly one-third of individuals will give an obviously incorrect answer to a simple line judgment task when that answer is given by the others in the room. Solomon E. Asch, Effects of Group Pressure Upon the Modification and Distortion of Judgments, in GROUPS, LEADERSHIP AND MEN 177, 177-81, 186 (Howard Guetzkow ed., 1951).
113. Geoffrey Cohen has found that support of a welfare policy among liberals and conservatives depends more on whether the policy is endorsed by a Republican or Democrat than on the actual content of the policy. Geoffrey L. Cohen, Party Over Policy: The Dominating Impact of Group Influence on Political Beliefs, 85 J. PERS. & SOC. PSYCHOL. 808, 819 (2003).
114. See Stephen J. Hoch & George F. Loewenstein, Time-Inconsistent Preferences and Consumer Self-Control, 17 J. CONSUMER RES. 492, 497 (1991) (discussing the impact of temporal proximity on consumer preferences);
115. Kahneman & Tversky, supra note 2, at 143-44 (discussing how the framing of possible outcomes may change individual preferences);
116. Amos Tversky & Daniel Kahneman, The Framing of Decisions and the Psychology of Choice, 211 SCIENCE 453, 453-58 (1985) (discussing how the framing of prospects, contingencies, and outcomes can lead to preference reversals).
117. See, e.g., Amos Tversky & Daniel Kahneman, Judgment Under Uncertainty: Heuristics and Biases, in JUDGMENT UNDER UNCERTAINTY: HEURISTICS AND BIASES 3, 3-20 (Daniel Kahneman et al. eds., 1982) (reviewing several judgmental heuristics and the cognitive biases they tend to produce). For a review of cognitive heuristics in decisionmaking
118. see Daniel Kahneman, Maps of Bounded Rationality: Psychology for Behavioral Economics, 93 AM. ECON. REV. 1449 (2003).
119. Jessica Nolan and her coauthors found that while individuals believed that the behavior of their neighbors had little impact on their own energy-use behaviors, the data showed that descriptive norms were the strongest predictor of actual behavior. Jessica M. Nolan et al., Normative Social Influence Is Underdetected, 34 PERSONALITY SOC. PSYCHOL. BULL. 913, 920-21 (2008).
120. See Wilson & Dowlatabadi, supra note 45, at 172 (analyzing rational choice as a building block of economic theory).
121. See, e.g., Rabin, supra note 2, at 12 (listing multiple theories of economically relevant psychology that he does not apply to his analysis).
122. See Bernice A. Pescosolido, Beyond Rational Choice: The Social Dynamics of How People Seek Help, 97 AM. J. SOC. 1096, 1102 (1992) (describing how certain actions or choices are targeted for testing, while others are ignored).
123. See, e.g., Eric A. Posner, Law and Social Norms: The Case of Tax Compliance, 86 VA. L. REV. 1781, 1788-89 (2000) (concluding that the effects of personal norms are not valuable for explaining tax behavior);
124. Scott, supra note 55, at 1622 n. 39 (explaining that personal norms are not consistent with environmental behavior).
125. See, e.g., Wilson & Dowlatabadi, supra note 45, at 172 (describing rational choice theory as background to economics and policy decisions).
126. See, e.g., Rabin, supra note 2, at 12 (listing a multitude of psychology theories that researchers use to explain behavior).
127. This problem has been noted by multiple researchers within psychology and is sometimes referred to as the "jangle fallacy." See, e.g., Jack Block, Three Tasks for Personality Psychology, in DEVELOPMENTAL SCIENCE AND THE HOLISTIC APPROACH 155, 156-57 (Lars R. Bergman et al. eds., 2000);
128. see also Michael W. Katzko, The Rhetoric of Psychological Research and the Problem of Unification in Psychology, 57 AM. PSYCHOL. 262, 264-69 (2002).
129. See Stern, supra note 46, at 200-01 (explaining how policy analysts use the simplified rational-actor theory).
130. See, e.g., Morrow et al., supra note 47, at 1307-08 (examining several federal programs using financial incentives to influence individual behavior).
131. See LOREN LUTZENHISER ET AL., CAL. INST. FOR ENERGY AND ENV'T, BEHAVIOR AND ENERGY PROGRAM, BEHAVIORAL ASSUMPTIONS UNDERLYING CALIFORNIA RESIDENTIAL SECTOR ENERGY EFFICIENCY PROGRAMS 20-24 (2009), available at http://uc-ciee.org/pubs/ref-behavior.html;
132. MICHAEL J. SULLIVAN, CAL. INST. FOR ENERGY AND ENV'T, BEHAVIOR AND ENERGY PROGRAM, BEHAVIORAL ASSUMPTIONS UNDERLYING ENERGY EFFICIENCY PROGRAMS FOR BUSINESSES 21-24 (2009), available at http://uc-ciee.org/pubs/ref-behavior.html (concluding that rational decision models lead to an overemphasis on information-and price-based approaches);
133. Wiener, supra note 35, at 704-35 (discussing economic theory and other instruments of regulation).
134. 5See Wilson & Dowlatabadi, supra note 45, at 172.
135. Id.
136. See Marilyn A. Brown, Market Failures and Barriers as a Basis for Clean Energy Policies, 29 ENERGY POL'Y 1197, 1198-99 (2001);
137. Charles, supra note 3, at 810-11.
138. See Thomas A. Heberlein & G. Keith Warriner, The Influence of Price and Attitude on Shifting Residential Electricity Consumption From On-to Off-Peak Periods, 4 J. ECON. PSYCHOL. 107, 125 (1983);
139. Nolan et al., supra note 65, at 921.
140. See Rosenthal, supra note 13, at A3.
141. See Stern, supra note 45, at 210-11.
142. See id.
143. See Wilson & Dowlatabadi, supra note 46, at 174 (explaining how individual preferences are not fixed).
144. Id. at 174-75 (discussing the importance of framing the decisions available to consumers in intervention programs).
145. See generally id. at 175 (emphasizing how consumers are influenced more by comfort and fulfilled desires than by energy efficiency when renovating their homes).
146. For a workplace example, see Amanda R. Carrico & Manuel Riemer, Motivating Pro-Environmental Behavior in an Organizational Setting: The use of Feedback and Peer Education to Reduce Energy use (2009) (unpublished abstract) (on file with author). For a dormitory example, see John E. Petersen et al., Dormitory Residents Reduce Electricity Consumption When Exposed to Real-Time Visual Feedback and Incentives, 8 INT'L. J. SUSTAINABILITY HIGHER EDUC. 16, 29 (2007). For a military base example
147. see Andrea H. McMakin et al., Motivating Residents to Conserve Energy Without Financial Incentives, 34 ENVTL. BEHAV. 848, 856 (2002).
148. See McMakin et al., supra note 86, at 849;
149. Petersen et al., supra note 86, at 18;
150. Carrico & Riemer, supra note 86.
151. For a review, see Wokje Abrahamse et al., A Review of Intervention Studies Aimed at Household Energy Conservation, 25 J. ENV'T PSYCH. 273, 278-79 (2005).
152. See, e.g., infra note 122 and accompanying text.
153. See Abhijit Banerjee & Barry D. Solomon, Eco-Labeling for Energy Efficiency and Sustainability: A Meta-Evaluation of US Programs, 31 ENERGY POL'Y 109, 111-12 (2003) (describing the purpose of various energy conservation policies).
154. See NAT'L RESEARCH COUNCIL, ENERGY USE: THE HUMAN DIMENSION 184 (1984) (explaining how individual behavior associated with energy use is often not incorporated into policy analysis, but should be in new programs and policies).
155. See, e.g., Brown, supra note 78, at 1198
156. (citing a study where the majority of consumers did not purchase the energy efficient appliances, but instead purchased cheaper appliances that consumed more energy in the long run).
157. See, e.g., Mathias Binswanger, Technological Progress and Sustainable Development: What About the Rebound Effect?, 36 ECOLOGICAL ECON. 119, 130 (2001);
158. Horace Herring, Energy Efficiency-A Critical View, 31 ENERGY 10, 12 (2006).
159. For a review, see Jack N. Barkenbus, Putting Energy Efficiency in a Sustainability Context, 48 ENVIRONMENT 10, 12 (2006).
160. According to surveys conducted by the Energy Information Administration, thirteen percent of households surveyed in 1987 owned two or more refrigerators compared to twenty-two percent of those surveyed in 2005. See U. S. DEP'T OF ENERGY, ENERGY INFO. ADMIN., RESIDENTIAL ENERGY CONSUMPTION SURVEY, PRESENCE OF APPLIANCES (1987), available at http://www.eia.doe.gov/emeu/recs/recspubuse87/ 87publicuse.html;
161. U. S. DEP'T OF ENERGY, ENERGY INFO. ADMIN., RESIDENTIAL ENERGY CONSUMPTION SURVEY, KITCHEN APPLIANCES (2005), available at http://www.eia.doe. gov/emeu/recs/recspubuse05/pubuse05.html.
162. See Peter Behr, Md.'s Veto of Advance Meter Deployment Stuns Smart Grid Advocates, CLIMATE WIRE (June 23, 2010), http://www.eenews.net/public/ climatewire/2010/06/23/1.
163. See id. ("While some state utility commissions are willing to back smart meter deployment, they are reluctant to approve new 'dynamic' electricity rate plans that allow prices to rise during the day when power demand peaks."). The utility later modified the program and obtained regulatory approval. See Peter Behr, Md. Smart Meter Plan Advances with Consumer Benefits as a Measure, CLIMATE WIRE (Aug. 18, 2010), http://www.eenews.net/cw/(search "ClimateWire" for "Md. Smart Meter Plan Advances"; then follow "Grid" hyperlink) ("The commission emphasized, 'the success of this initiative, and the likelihood that customers will actually see the benefits this project promises, depend centrally on the success of the company's customer education and communication effort.'").
164. See, e.g., NAT'L RESEARCH COUNCIL, supra note 91, at 39-41 (demonstrating how feedback on energy use, without cost savings, may be insufficient to get customers to change their energy usage).
165. Nearly identical incentive programs directed toward home efficiency improvements within similar geographic areas have varied by a factor of ten. For a review, see Stern, supra note 46, at 210-11. Differential success rates of these programs have been primarily attributed to marketing and implementation of the program.
166. Id.
167. Eric Hirst, The Hood River Conservation Project: A Unique Research and Demonstration Effort, 13 ENERGY & BUILDINGS 3, 8 (1989).
168. For a review of California's Flex Your Power campaign in response to the energy crisis of 2001, see Sylvia L. Bender et al., Using Mass Media to Influence Energy Consumption Behavior: California's 2001 Flex Your Power Campaign as a Case Study 8. 15, 8.17 (2002), available at http://citeseerx.ist. psu.edu/viewdoc/download?doi=10.1.1.156.8308&rep=rep1&type=pdf (examining the campaign's formulation, implementation, and strategic evolution of its themes). For a brief description of California's utility-sponsored demand side management programs, including programs targeted at promoting efficiency adoption and energy curtailment
169. see Elsia O. Galawish, DSM Accomplishments in California: PG&E's Experience, 9 RENEWABLE ENERGY 1295, 1296 (1996).
170. See Charles, supra note 3, at 805.
171. Id.
172. James Sweeney & Anant Sudarshan, Deconstructing the "Rosenfeld Curve" 1 (June 1, 2008) (unpublished manuscript), available at http://piee.stanford.edu/cgi-bin/docs/publications/Deconstructing-the-Rosenfeld- Curve.pdf.
173. See OFFICE OF MGMT. & BUDGET, supra note 5, at 1.
174. See, e.g., id. (noting OMB recommendation to agencies to consider "behaviorally informed approaches to regulation");
175. OIRA Disclosure Memo, supra note 5, at 2-12 (providing guidance to agencies).
176. Cf. Adler, supra note 20, at 142-43 (noting the importance of bounded rationality for regulatory decisionmakers);
177. Jolls et al., supra note 2, at 1508-45 (providing a general framework for use of behavioral economics in development of legal prescriptions).
178. See Adler, supra note 20, at 155-57.
179. LOUIS KAPLOW & STEVEN SHAVELL, FAIRNESS VERSUS WELFARE 18 (2002).
180. See Adler, supra note 20, at 158-59;
181. Scott, supra note 55, at 1621-22.
182. Amanda R. Carrico et al., Costly Myths: An Analysis of Idling Beliefs and Behavior in Personal Motor Vehicles, 37 ENERGY POL'Y 2881, 2885 (2009).
183. U. S. ENVTL. PROT. AGENCY, YOUR CAR AND CLEAN AIR: WHAT YOU CAN DO TO REDUCE POLLUTION 3 (1994), available at http://www.epa.gov/OMS/consumer/18- youdo.pdf.
184. See Catherine M. Sharkey, Preemption By Preamble: Federal Agencies and the Federalization of Tort Law, 56 DEPAUL L. REV. 227, 230 (2007) (discussing mandatory agency safety requirements such as "product performance, design, labeling, warnings, and instructions").
185. MCKENZIE-MOHR ASSOCS., ANTI-IDLING FINAL REPORT 4 (2003), available at http://www.greatersudbury.ca/content/earthcare/documents/Sudbury-finalreport. pdf.
186. OIRA recently described these types of informational regulatory tools as "summary disclosure." 2010 OIRA Disclosure Memo, supra note 5, at 3-6 (identifying the seven principles for agency use of summary disclosure as a regulatory tool). It may be important not only to provide more information, but also to attend to the way in which the information is provided. Jolls et al., supra note 2, at 1533-34.
187. NAT'L RESEARCH COUNCIL, supra note 91, at 36-37
188. (citing studies that show that most energy users are ill informed of appliance energy usage under aggregate billing systems).
189. Id. at 36 (explaining how energy bills are received infrequently and aggregate energy use into one total).
190. See id. at 36-38;
191. Willett Kempton & Laura Montgomery, Folk Quantification of Energy, 7 ENERGY 817, 817 (1982).
192. OIRA recently recognized that agencies "should take steps to provide people with relevant information when they are actually making the decision or taking the action in question. " 2010 OIRA Disclosure Memo, supra note 5, at 4 (stating that Principle Four is that "[d]isclosed information should be properly placed and timed").
193. Shahzeen Z. Attari et al., Public Perceptions of Energy Consumption and Savings, 107 PROC. NAT'L ACAD. SCI. 16, 054, at 16, 055 (2010);
194. Willett Kempton et al., Do Consumers Know "What Works" in Energy Conservation?, 9 MARRIAGE FAM. REV. 115, 115-33 (1985).
195. See ELECTRIC POWER RESEARCH INST., RESIDENTIAL ELECTRICITY use FEEDBACK: A RESEARCH SYNTHESIS AND ECONOMIC FRAMEWORK 2-5 (2009) (reviewing studies on various forms of monitoring and feedback for home energy consumers); Abrahamse et al., supra note 88, at 278 (same).
196. Lou McClelland & Stuart W. Cook, Energy Conservation Effects of Continuous In-Home Feedback in All-Electric Homes, 9 J. ENVTL. SYS. 169, 169-73 (1979).
197. See Jack N. Barkenbus, Eco-Driving: An Overlooked Climate Change Initiative, 38 ENERGY POL'Y 762, 765-66 (2010) (showing a ten-percent gain in fuel economy);
198. Mascha van der Voort et al., A Prototype of Fuel-Efficiency Support Tool, 9 C. TRANSP. RES. 279, 279 (2001) (showing a sixteen-percent gain);
199. Press Release, Scania Grp., Scania Takes Eco-Driving to a New Level with Its Latest Digital Performance Coaching Technology (Sept. 17, 2009), available at http://www.scania.com/media/pressreleases/n09025en.aspx.
200. See Behr, supra note 96.
201. See, e.g., ARIELY, supra note 2, at xxix-xxx;
202. Rabin, supra note 2, at 13-32;
203. Tversky & Kahneman, supra note 63, at 452.
204. See Kenneth Gillingham et al., Energy Efficiency Economics and Policy, 1 ANN. REV. RESOURCE ECON. 597, 605-07 (2009);
205. Jerry A. Hausman, Individual Discount Rates and the Purchase and Utilization of Energy-Using Durables, 10 BELL J. ECON. 33, 50 (1979);
206. Richard Howarth & Alan H. Sanstad, Discount Rates and Energy Efficiency, 13 CONTEMP. ECON. POL'Y 101, 101 (1995);
207. Jonathan G. Koomey & Alan H. Sanstad, Technical Evidence for Assessing the Performance of Markets Affecting Energy Efficiency, 22 ENERGY POL'Y 826, 828-30 (1994);
208. Peter Kooreman, Individual Discounting, Energy Conservation, and Household Demand for Lighting, 18 RESOURCE & ENERGY ECON. 103, 112 (1996).
209. See Adam B. Jaffe et al., The Economics of Energy Efficiency, in ENCYCLOPEDIA OF ENERGY 79, 85-86 (Cutler Cleveland ed., 2004);
210. Ronald J. Sutherland, Market Barriers to Energy-Efficiency Investments, 12 ENERGY J. 15, 31 (1991).
211. See Daniel C. Feiler & Jack B. Soll, A Blind Spot in Driving Decisions: How Neglecting Costs Puts Us in Overdrive, 98 CLIMATIC CHANGE 285, 289 (2010);
212. Owen D. Jones & Timothy H. Goldsmith, Law and Behavioral Biology, 105 COLUM. L. REV. 405, 444-45 (2005).
213. See Willet Kempton et al., I Always Turn It on "Super": User Decisions About When and How to Operate Room Air Conditioners, 18 ENERGY & BUILDINGS 177, 189-90 (1992);
214. Kempton & Montgomery, supra note 118, at 826.
215. Feiler & Soll, supra note 127, at 289.
216. OIRA recently recognized the importance of considering cognitive costs during regulatory development. See 2010 OIRA Disclosure Memo, supra note 5, at 4, 10 (noting that "[p]eople have limited time and attention" and thus "may not participate in important programs simply because the required steps for participation are complex and daunting; agencies can often improve outcomes by reducing unnecessary paperwork burdens and simplifying choices").
217. Glenda Wall, Barriers to Individual Environmental Action: The Influence of Attitudes and Social Experiences, 32 CANADIAN REV. SOC. & ANTHROPOLOGY 465, 477 (1995).
218. Timothy D. Ludwig et al., Increasing Recycling in Academic Buildings: A Systematic Replication, 31 J. APPLIED BEHAV. ANALYSIS 683, 683 (1998).
219. Eric J. Johnson & Daniel Goldstein, Do Defaults Save Lives?, 302 SCIENCE 1338, 1339 (2003). OIRA recently included default settings among the alternatives that agencies should consider when designing regulatory options. 2010 OIRA Disclosure Memo, supra note 5, at 9 (noting that regulatory outcomes "sometimes... can be achieved by selecting appropriate starting points or 'default rules'").
220. Paul C. Stern, Information, Incentives, and Proenvironmental Consumer Behavior, 22 J. CONSUMER POL'Y. 461, 469 (1999).
221. Paul C. Stern et al., The Effectiveness of Incentives for Residential Energy Conservation, 10 EVALUATION REV. 147, 159 (1986) [hereinafter Stern et al., Effectiveness of Incentives];
222. Paul C. Stern, Gerald T. Gardner, Michael P. Vandenbergh, Thomas Dietz & Jonathan M. Gilligan, Design Principles for Carbon Emissions Reduction Programs, 44 ENVTL. SCI. & TECH. 4847, 4848 (2010) [hereinafter Stern et al., Design Principles].
223. 49 U. S. C. § 32901 (2010).
224. See, e.g., Lee Schipper, Op-Ed., When It Comes to Being Green, Cash for Clunkers Is a Lemon, WASH. POST, http://www.washingtonpost.com/wp-dyn/content/ graphic/2009/08/08/GR2009080802658.html (last visited Nov. 29, 2010).
225. See 49 U. S. C. § 32901 (b).
226. See id.
227. See id. §32901 (c) - (d).
228. See Michael P. Vandenbergh et al., Implementing the Behavioral Wedge: Designing and Adopting Effective Carbon Emissions Reduction Programs, 40 ENVTL. L. REP. 10, 547, at 10, 551 (2010).
229. For a more detailed review, see Stern et al., Design Principles, supra note 135, at 4847-48.
230. See Kahneman & Tversky, supra note 2, at 343-44;
231. Tversky & Kahneman, supra note 63, at 453. OIRA recently noted the need for agencies to consider framing and loss aversion in the design of summary disclosure regulatory measures.
232. See 2010 OIRA Disclosure Memo, supra note 5, at 4 ("[I]f a potential outcome is presented as a loss, for example, people may pay more attention than if it is presented as a gain. ").
233. Irwin P. Levin & Gary J. Gaeth, How Consumers Are Affected by the Framing of Attribute Information Before and After Consuming the Product, 15 J. CONSUMER RES. 374, 375-77 (1988).
234. See Kahneman & Tversky, supra note 2, at 342;
235. Tversky & Kahneman, supra note 63, at 456.
236. See, e.g., Tversky & Kahneman, supra note 63, at 453 ("The definition of rationality has been much debated, but there is general agreement that rational choices should satisfy some elementary requirements of consistency and coherence.").
237. See, e.g., id. at 454.
238. See, e.g., Robert B. Cialdini et al., Empathy-Based Helping: Is It Selflessly or Selfishly Motivated?, 52 J. PERSONALITY & SOC. PSYCHOL. 749, 749-50 (1987) (arguing that the empathy for another in need leads to the experience of sadness in the observer, motivating him or her to relieve that sadness through helping, and providing data to suggest that empathy is associated with sadness and those who were led to believe that helping would not reduce empathy were less likely to help others).
239. See Howard Margolis, Free Riding Versus Cooperation, in STRATEGY AND CHOICE 84, 90 (Richard J. Zeckhauser ed., 1991) ("[T]he possibilities... could come either from imposing a risk of punishment on those who fail to cooperate or offering the promise of reward for those who do.");
240. cf. Jon Elster, Social Norms and Economic Theory, J. ECON. PERSP., Fall 1989, at 99, 100 (noting that social norms are "enforced by members of the general community" and are "sustained by the approval and disapproval of others" and providing several examples).
241. See Margolis, supra note 149, at 90-95.
242. See, e.g., ROBERT M. AXELROD, THE EVOLUTION OF COOPERATION 146-54 (1984) (discussing the roles of labels, hierarchies, stereotypes, and reputation).
243. Cf. Calabresi & Melamed, supra note 21, at 1116 (noting how the use of a legal analytical framework identified the overlooked importance of an entitlement in the case of a polluter protected by a liability rule).
244. See supra notes 109-45 and accompanying text.
245. DANIEL KATZ & FLOYD HENRY ALLPORT, STUDENTS' ATTITUDES 152-53 (1931).
246. Id.
247. Id.
248. In addition to the example of college drinking that follows, social scientists have speculated that pluralistic ignorance was responsible for the widespread public support for segregation among white Americans during the 1960's, Hubert J. O'Gorman, Pluralistic Ignorance and White Estimates of White Support for Racial Segregation, 39 PUB. OPINION Q. 313, 330 (1975), as well as the support of communism within the Soviet Union
249. TIMUR KURAN, PRIVATE TRUTHS, PUBLIC LIES 118-27 (1995).
250. Deborah A. Prentice & Dale T. Miller, Pluralistic Ignorance and Alcohol use on Campuses: Some Consequences of Misperceiving the Social Norm, 64 J. PERSONALITY & SOC. PSYCHOL. 243, 245 (1993);
251. Christine M. Schroeder & Deborah A. Prentice, Exposing Pluralistic Ignorance to Reduce Alcohol use Among College Students, 28 J. APPLIED SOC. PSYCHOL. 2150, 2170-74 (1998).
252. Schroeder & Prentice, supra note 158, at 2170-74.
253. Id.
254. Asch, supra note 62, at 181-82.
255. Noah J. Goldstein et al., A Room with a Viewpoint: Using Social Norms to Motivate Environmental Conservation in Hotels, 35 J. CONSUMER RES. 472, 479-80 (2008) (finding that prescriptive norms increased participation in hotel energy conservation programs);
256. P. Wesley Schultz, Changing Behavior With Normative Feedback Interventions: A Field Experiment on Curbside Recycling, 21 BASIC & APPLIED SOC. PSYCHOL. 25, 31-33 (1998) [hereinafter Schultz, Changing Behavior] (finding that individual feedback increased curbside recycling);
257. P. Wesley Schultz et al., The Constructive, Destructive, and Reconstructive Power of Social Norms, 18 PSYCHOL. SCI. 429, 432 (2007) [hereinafter Schultz et al., Power of Social Norms] (finding that providing residents with normative feedback decreased home energy usage).
258. Ian Ayres et al., Evidence from Two Large Field Experiments that Peer Comparison Feedback Can Reduce Residential Energy Usage 5 (Nat'l Bureau of Econ. Research, Working Paper No. 15, 386, 2009), available at http://www.nber.org/ papers/w15386.
259. Id.
260. Id.
261. see also Robert B. Cialdini et al., A Focus Theory of Normative Conduct: A Theoretical Refinement and Reevaluation of the Role of Norms in Human Behavior, 24 ADVANCES EXPERIMENTAL SOC. PSYCHOL. 202, 208-09 (1991) (noting the perverse side effect of an antilittering campaign that implicitly acknowledged that many people litter).
262. Cf. Richard H. McAdams, The Origin, Development, and Regulation of Norms, 96 MICH. L. REV. 338, 340 (1997)
263. (citing law and economics research that acknowledges the occasional trumping power of internalized norms over external incentives);
264. Posner, supra note 69, at 1781 (acknowledging the role of internalized norms in tax compliance).
265. Robert B. Cialdini, Crafting Normative Messages to Protect the Environment, 12 CURRENT DIRECTIONS PSYCHOL. SCI. 105, 107 (2003).
266. Id.
267. Id.
268. See, e.g., Icek Ajzen, The Theory of Planned Behavior, 50 ORGANIZATIONAL BEHAV. & HUM. DECISION PROCESSES 179, 180 (1991) (noting the relatively poor predictive power of dispositions as well as general attitudes in predicting specific behaviors).
269. See MCKENZIE-MOHR & SMITH, supra note 6, at 122-32.
270. Id.
271. See Uri Gneezy & Aldo Rustichini, A Fine Is a Price, 29 J. LEGAL STUD. 1, 3-8 (2000).
272. See Samuel Bowles, Policies Designed for Self-Interested Citizens May Undermine "The Moral Sentiments": Evidence from Economic Experiments, 320 SCIENCE 1605, 1609 (2008);
273. Edward L. Deci et al., A Meta-Analytic Review of Experiments Examining the Effects of Extrinsic Rewards on Intrinsic Motivation, 125 PSYCHOL. BULL. 627, 658-59 (1999);
274. Bruno S. Frey, Motivation as a Limit to Pricing, 14 J. ECON. PSYCHOL. 635, 658 (1993);
275. Ann E. Tenbrunsel & David M. Messick, Sanctioning Systems, Decision Frames, and Cooperation, 44 ADMIN. SCI. Q. 684, 704 (1999).
276. See Gneezy & Rustichini, supra note 173, at 3-8.
277. See LURA CONSULTING, THE CARROT, THE STICK, AND THE COMBO: A RECIPE FOR REDUCING VEHICLE IDLING IN CANADIAN COMMUNITIES 6-7 (2005), available at http://oee.nrcan.gc.ca/communities-government/transportation/ municipal-communities/reports/carrot-stick-combo/carrot-stick-combo.pdf (advising that both voluntary and regulatory approaches should be used in tandem);
278. David T. Levy et al., The Effects of Tobacco Control Policies on Smoking Rates: A Tobacco Control Scorecard, 10 J. PUB. HEALTH MGMT. PRAC. 338, 346-49 (2004) ("[T]he most successful tobacco control strategies appear to involve multiple policies implemented as part of a comprehensive strategy.").
279. See Rosenthal, supra note 13, at A3. Similarly, combining public education with regulatory measures has also been successfully used to reduce vehicle idling in a number of Canadian communities. See LURA CONSULTING, supra note 176, at 8-20.
280. See Rosenthal, supra note 13, at A3 ("And then something happened that was bigger than the sum of these parts.").
281. Id.
282. See infra Parts II. A.2.b.i-iii.
283. See discussion infra Part II. A.2.b.i.
284. See discussion infra Part II. A.2.b.ii.
285. See discussion infra Part II. A.2.b.iii.
286. See Susanne Göckeritz et al., Descriptive Normative Beliefs and Conservation Behavior: The Moderating Roles of Personal Involvement and Injunctive Normative Beliefs, 40 EUR. J. SOC. PSYCHOL. 514, 517 (2010) (describing the moderating effect of personal involvement on behavioral change and information processing).
287. David J. Hardisty et al., A Dirty Word or a Dirty World? Attribute Framing, Political Affiliation, and Query Theory, 21 PSYCHOL. SCI. 86, 88 (2010);
288. see also 2010 OIRA Disclosure Memo, supra note 5, at 4 ("Agencies should be aware of the importance of how information is presented....").
289. Hardisty et al., supra note 185, at 86, 89.
290. Dan M. Kahan et al., The Second National Risk and Culture Study 4-6 (Oct. 3, 2007) (unpublished manuscript), available at http://papers.ssrn.com/sol3/ papers.cfm?abstract-id=1017189.
291. See id. at 2, 16.
292. Ola Svenson, Differentiation and Consolidation Theory of Human Decision Making: A Frame of Reference for the Study of Pre-and Post-Decision Processes, 80 ACTA PSYCHOLOGICA 143, 145-46 (1992).
293. Id.
294. David L. Ronis et al., Attitudes, Decisions, and Habits as Determinants of Repeated Behavior, in ATTITUDE STRUCTURE AND FUNCTION 213, 219 (Anthony R. Pratkanis et al. eds., 1989). For a discussion of habits in law and economics noting the work of Kenneth Arrow and concluding that habits "can be incorporated into a theory by supposing that people choose goods with an eye towards minimizing changes in their consumption"
295. see Jolls et al., supra note 2, at 1478.
296. See Henk Aarts et al., Predicting Behavior from Actions in the Past: Repeated Decision Making or a Matter of Habit?, 28 J. APPLIED SOC. PSYCHOL. 1355, 1358-61 (1998);
297. Michel Laroche et al., The Influence of Culture on Pro-Environmental Knowledge, Attitudes, and Behavior: A Canadian Perspective, 23 ADVANCES CONSUMER RES. 196, 196 (1996).
298. In the case of motor vehicle idling, it was once considered more costeffective to idle for a period of time before driving or while waiting. See Carrico et al., supra note 111, at 2882. With improvements in modern fuel-injection engines, that is no longer the case.
299. See id. However, many individuals are acting based on outdated information and old habits.
300. See id.
301. For a discussion of this technology, see id. at 2887.
302. See LEON FESTINGER, A THEORY OF COGNITIVE DISSONANCE 2-3 (1957).
303. See id. at 3.
304. See id. at 2.
305. See id. at 18-23.
306. See id. at 2.
307. See id.
308. See Chris Ann Dickerson et al., Using Cognitive Dissonance to Encourage Water Conservation, 22 J. APPLIED SOC. PSYCHOL. 841, 852 (1992);
309. S. J. Kantola et al., Cognitive Dissonance and Energy Conservation, 69 J. APPLIED PSYCHOL. 416, 421 (1984).
310. See Dickerson et al., supra note 201, at 841.
311. See Richard D. Katzev & Theodore R. Johnson, Comparing the Effects of Monetary Incentives and Foot-in-the-Door Strategies in Promoting Residential Electricity Conservation, 14 J. APPL. SOC. PSYCHOL. 12, 24-25 (1984);
312. Michael S. Pallak & William Cummings, Commitment and Voluntary Energy Conservation, 2 PERSONALITY & SOC. PSYCHOL. BULL. 27, 27, 29 (1976).
313. See Elizabeth G. Warner, Ask the Experts: Monthly Pledge Systems-A Fundraising Idea for Nonprofits?, NONPROFIT WORLD, May-June, 1994, 4, 4-5 (explaining how monthly pledge systems can be easily set up and provide significant increases in revenue and core donor involvement).
314. See Clive Seligman & John M. Darley, Feedback as a Means of Decreasing Residential Energy Consumption, 62 J. APPLIED PSYCHOL. 363, 366-67 (1977).
315. See discussion supra Part II. A.2.b.
316. OIRA has recently noted the importance of understanding the effects of informational regulatory tools on subpopulations. For example, it has noted that with regard to default rules it may be important for agencies to "distinguish among, and to suit the diverse situations of, members of the affected group. For example, geographic or demographic information (such as age) might be taken into account if it helps to increase the likelihood that the default rule will be suited to the situations of those to whom it applies."
317. OIRA Disclosure Memo, supra note 5, at 11.
318. Socio-ecological frameworks have been relied upon by researchers working in the areas of developmental psychology, community psychology, health psychology, and public health. See, e.g., URIE BRONFENBRENNER, THE ECOLOGY OF HUMAN DEVELOPMENT (1979) (applying an ecological framework to the field of developmental psychology). For an example in public health literature applying an ecological framework in identifying environmental influences on physical activity
319. see James F. Sallis et al., An Ecological Approach to Creating Active Living Communities, 27 ANN. REV. PUB. HEALTH 297 (2006).
320. See, e.g., BRONFENBRENNER, supra note 208, at 3-4 (describing his conceptual framework as "a set of nested structures, each inside the next, like a set of Russian dolls").
321. Id.
322. See supra notes 177-79 and accompanying text.
323. See, e.g., Congestion Mitigation and Air Quality (CMAQ) Improvement Program, FED. HIGHWAY ADMIN., http://www.fhwa.dot.gov/environment/cmaqpgs/(last modified Sept. 22, 2009) (discussing the traffic-grant program, which includes guidelines limiting spending to areas such as carpooling that have high-technical potential but low-behavioral plasticity).
324. See, e.g., J. Thomas Rosch, Comm'r, Fed. Trade Comm'n, Behavioral Economics: Observations Regarding Issues That Lie Ahead, Address at the Vienna Competition Conference (June 9, 2010), available at http://ftc.gov/speeches/ rosch/100609viennaremarks.pdf (discussing the case for using principles of behavioral economics in antitrust merger review). For commentary on Rosch's speech
325. see Geoffrey Manne, Commissioner Rosch's Really Weak Case for "Behavioral Antitrust, " TRUTH ON MARKET (July 16, 2010, 12:46 PM), http://truthonthemarket.com/2010/07/16/commissioner-roschs-really-weak-case-for- behavioral-antitrust/.
326. See also EMP. BENEFITS SEC. ADMIN., U. S. DEP'T OF LABOR & IRS, AUTOMATIC ENROLLMENT 401 (K) PLANS FOR SMALL BUSINESSES 3 (Feb. 2010), available at http://www.dol.gov/ebsa/pdf/automaticenrollment401kplans.pdf (describing incentives for small businesses to switch to automatic enrollment of employees in 401 (k) plans, with opt-out provisions);
327. William Samuelson & Richard Zeckhauser, Status Quo Bias in Decision Making, 1 J. RISK & UNCERTAINTY 7, 26-31 (1988) (identifying status quo bias in health insurance purchases);
328. Edmund L. Andrews, Obama Outlines New Initiatives Intended to Make It Easier to Save for Retirement, N. Y. TIMES, Sept. 6, 2009, at A20
329. available at 2009 WL 17481341. In this Part, we apply the monetary and social prongs of our proposed framework to electric car recharging and tankless water heater purchases, but in the interest of brevity we do not apply a social ecological framework to these actions.
330. See Nathan S. Lewis, Powering the Planet, Keynote Speech at the California Clean Innovation Conference (May 11, 2007), in 2 ENGINEERING & SCI. 12, 19 (2007) ("[L]owering demand... is going to pay off much sooner than clean energy supplies.");
331. S. Pacala & R. Socolow, Stabilization Wedges: Solving the Climate Problem for the Next 50 Years with Current Technologies, 305 SCIENCE 968, 969 (2004) ("Improvements in efficiency and conservation probably offer the greatest potential....").
332. See, e.g., FLORIAN BRESSAND ET AL., MCKINSEY GLOBAL INST., CURBING GLOBAL ENERGY DEMAND GROWTH: THE ENERGY PRODUCTIVITY OPPORTUNITY 57 (2007) (noting that the residential sector provides the "largest energy productivity opportunities" globally);
333. HANNAH CHOI GRANADE ET AL., MCKINSEY & CO., UNLOCKING ENERGY EFFICIENCY IN THE U. S. ECONOMY 10 (2009) ("The residential sector... offers a slightly disproportionate thirtyfive percent of the end-use efficiency potential.").
334. 2 Emissions, 33 ENERGY POL'Y 197, 197 (2005);
335. Gerald T. Gardner & Paul C. Stern, The Short List: The Most Effective Actions U. S. Households Can Take to Curb Climate Change, 50 ENVIRONMENT, no. 5, 2008 at 12, 16;
336. Michael P. Vandenbergh & Anne C. Steinemann, The Carbon-Neutral Individual, 82 N. Y. U. L. REV. 1673, 1694 (2007).
337. Dietz et al., supra note 33, at 18, 452.
338. Id. at 18, 452-53.
339. See BRESSAND et AL., supra note 215, at 57;
340. Allcott & Mullainathan, supra note 6, at 1204-05;
341. Michael P. Vandenbergh et al., Individual Carbon Emissions: The Low-Hanging Fruit, 55 UCLA L. REV. 1701, 1758 (2008).
342. For a summary of the household energy efficiency measures in the American Recovery and Reinvestment Act of 2009, Pub. L. No. 111-5, 123 Stat. 115, which incorporates the Energy Improvement and Extension Act of 2008, Pub. L. No. 110-343, 122 Stat. 3807
343. see U. S. GOV'T ACCOUNTABILITY OFFICE, GAO-10-383, RECOVERY ACT: PROJECT SELECTION AND STARTS ARE INFLUENCED BY CERTAIN FEDERAL REQUIREMENTS AND OTHER FACTORS (2010), available at http://www.gao.gov/products/GAO-10-383.
344. See Richard York et al., Bridging Environmental Science with Environmental Policy: Plasticity of Population, Affluence, and Technology, 83 SOC. SCI. Q. 18, 31 (2002) ("Plasticity is a tool for bridging science with policy.").
345. See Vandenbergh et al., supra note 141, at 10, 551.
346. Too much of the discussion to date has focused on behaviors that have high-technical potential but low plasticity, such as shifting from individually driven cars to carpooling. See Dietz et al., supra note 33, at 18, 453.
347. See discussion infra Part III. A and Part III. B.
348. Cf. Vandenbergh et al., supra note 141, at 10, 551.
349. A. ELGOWAINY ET AL., ARGONNE NAT'L LAB. CTR. FOR TRANSP. RESEARCH, ENERGY SYS. DIV., WELL TO WHEELS ENERGY use AND GREENHOUSE GAS EMISSIONS: ANALYSIS OF PLUG-IN HYBRID ELECTRIC VEHICLES 7 (2009) (discussing greenhouse gas emissions).
350. RYAN W. MCCARTHY ET AL., UNIV. OF CAL., DAVIS INST. OF TRANSP. STUDIES, INTERACTIONS BETWEEN ELECTRIC-DRIVE VEHICLES AND THE POWER SECTOR IN CALIFORNIA 7 (2009) (discussing greenhouse gas emissions and demand for energy by time of day).
351. See ELGOWAINY et AL., supra note 226, at 7;
352. MCCARTHY et AL., supra note 227, at 7;
353. NAT'L RESEARCH COUNCIL OF THE NAT'L ACADS., TRANSITIONS TO ALTERNATIVE TRANSPORTATION TECHNOLOGIES-PLUG-IN HYBRID ELECTRIC VEHICLES 2 (2010) (discussing costs and power transmission capacity).
354. See, e.g., BETTINA KAMPMAN ET AL., CE DELFT, GREEN POWER FOR ELECTRIC CARS 41-42 (2010) (noting the importance of recharging time for capacity and other impacts);
355. K. PARKS ET AL., NAT'L RENEWABLE ENERGY LAB., COSTS AND EMISSIONS ASSOCIATED WITH PLUG-IN HYBRID ELECTRIC VEHICLE CHARGING IN THE XCEL ENERGY COLORADO SERVICE TERRITORY 24 (2007) (concluding that the costs and air pollution emissions of recharging plug-in hybrids varies substantially based on the time of charging).
356. See, e.g., Smart Grid Policy, 74 Fed. Reg. 13, 152, 13, 156 (Mar. 26, 2009) (to be codified at 18 C. F. R. ch. 1) ("If charging takes place during peak periods it could require a large investment in new generation, demand response resources and/or transmission capacity to meet the resulting higher peak loads. However, charging off-peak could actually improve the operation of the electric system, for example by improving existing generation asset utilization or by providing an electricity storage solution to address the potential for over-generation by variable resources in off-peak periods.").
357. Table 1 is based on data presented in STANTON W. HADLEY & ALEXANDRA TSVETKOVA, OAK RIDGE NAT'L LAB., POTENTIAL IMPACTS OF PLUG-IN HYBRID ELECTRIC VEHICLES ON REGIONAL POWER GENERATION 18-19, 48-50 (2008). The regions identified in the left-hand column of the table are as follows: ECAR-East Central Area Reliability Coordination Agreement; ERCOT-Electric Reliability Council of Texas; MAAC-Mid-Atlantic Area Council; MAIN-Mid-America Interconnected Network; MAPP-Mid-Continent Area Power Pool; NPCC-NY-Northeast Power Coordinating Council/NY; NPCC-NE-Northeast Power Coordinating Council/New England; FRCC-Florida Reliability Coordinating Council; SERC-Southeastern Electric Reliability Council; SPP-Southwest Power Pool; WECC-NW-Western Electricity Coordinating Council/Northwest Power Pool Area; WECC-RMP/ANM-Western Electricity Coordinating Council/Rocky Mountain Power Area and Arizona-New Mexico-Southern Nevada Power Area; WECC-CA-Western Electricity Coordinating Council/California.
358. See id. at xiv, xvi fig. ES-1 (noting that the regions are as specified by the Energy Information Administration in the Annual Energy Outlook 2007).
359. See, e.g., Do You Own an Electric Vehicle (EV)?, S. CAL. EDISON, http://www.sce.com/CustomerService/rates/residential/electric-vehicles.htm (last visited Nov. 29, 2010) (offering time-of-use rates for electric vehicle users);
360. Residential Electric Vehicle Services, L. A. DEP'T WATER & POWER, http://www.ladwp.com/ladwp/cms/ladwp002056.jsp (last visited Nov. 29, 2010) (offering a discounted rate for off-peak electric vehicle charging).
361. See, e.g., Do You Own an Electric Vehicle (EV)?, supra note 232 (using such a strategy).
362. See, e.g., HADLEY & TSVETKOVA, supra note 231, at 23 (concluding that "simple time-of-day charging could easily place all end-of-day charging requirements into peak periods").
363. See, e.g., id. (noting the potential for "smart chargers");
364. PARKS et AL., supra note 229, at 8 (discussing use of timing devices to move charging to offpeak hours).
365. Abrahamse et al., supra note 88, at 276-77.
366. See id. at 278-81 (discussing the use of immediate feedback on motor vehicle and residential energy use).
367. See FARUQUI & WOOD, supra note 12, at 21 (suggesting both that consumers are often satisfied after being introduced to variable pricing due to greater savings and that greater education prior to implementation may help consumers to adopt such pricing schemes);
368. Behr, supra note 96 (discussing troubles with recent Maryland variable pricing and its smart meter initiative);
369. see also Guy R. Newsham & Brent G. Bowker, The Effect of Utility Time-Varying Pricing and Load Control Strategies on Residential Summer Peak Electricity Use: A Review, 38 ENERGY POL'Y 3289, 3294-95 (2010) (concluding that the effectiveness of variable pricing schemes may be improved by targeting consumers more likely to respond to such schemes and by offering them greater support services).
370. Behr, supra note 96 (discussing troubles with even less intrusive efforts).
371. Kempton et al., supra note 128, at 190;
372. see also Monica J. Nevius & Scott Pigg, Programmable Thermostats That Go Berserk? Taking a Social Perspective on Space Heating in Wisconsin 8.233, 8.241, Paper presented at the American Council for Energy-Efficient Economy Summer Study on Energy Efficiency in Buildings: Washington DC (Aug. 23-28, 2000), available at http://www.ecw.org/ecwresults/berserk.pdf (noting that a large proportion of individuals interviewed were not interested in using the programmable features of their thermostat, and many considered these features to be a hassle).
373. Cf. Stern, supra note 46, at 208-09 (discussing empirical studies of how consumers implicitly discount future values).
374. See Abrahamse et al., supra note 88, at 278-82 (discussing the effectiveness of feedback techniques on behavior).
375. See id. at 276-77 (discussing the effectiveness of information to promote proenvironmental behavior).
376. Ayres et al., supra note 163, at 14-15.
377. See id. (concluding that such information changed behavior in other energy-saving contexts).
378. See Gneezy & Rustichini, supra note 173, at 15-16 (cautioning that the production of information to consumers does not always have the intended consequences on behavior).
379. See Newsham & Bowker, supra note 238, at 3294-95 (arguing that similarly targeted strategies have worked to change the behavior of these kinds of people).
380. See Tversky & Kahneman, supra note 63, at 456 (noting that framing a problem in terms of loss is more likely to change behavior).
381. See Abrahamse et al., supra note 88, at 275-76 (discussing the successful use of commitment techniques to alter behavior).
382. Stern, supra note 134, at 468 (discussing the success of such incentives in inducing consumers to invest in their homes).
383. Id. (cautioning that such barriers can prevent acting on socially desirable behaviors).
384. Id. at 467-68 (noting that credibility can be an important factor in getting behavior to change).
385. This includes principles of product marketing as well as social marketing. For a detailed discussion of the utility of social marketing techniques, see MCKENZIE-MOHR & SMITH, supra note 6, at 82-92.
386. For a discussion of nonmonetary factors in encouraging participation on home efficiency incentive programs, including issues such as trust and credibility, see Stern, supra note 134, at 467-68
387. and Stern et al., Effectiveness of Incentives, supra note 135, at 161-63.
388. See John M. Darley & James R. Beniger, Diffusion of Energy-Conserving Innovations, 37 J. SOC. ISSUES 150, 159-66 (1981) (discussing the role of social networks in one's decision to adopt certain technologies).
389. In fact, this is the case particularly when the incentive package is attractive. See Stern et al., Effectiveness of Incentives, supra note 135, at 162.
390. Id. at 160.
391. See Stern, supra note 46, at 208-09 (discussing "anomalous" implications of consumer adoption decisions and offering possible explanations for such decisions).
392. See Feiler & Soll, supra note 127, at 289 (concluding that consumers ignore costs both when they are decoupled from benefits and when they are hard to keep track of).
393. Tversky & Kahneman, supra note 63, at 456.
394. See Paul C. Stern, Psychological Dimensions of Global Environmental Change, 43 ANN. REV. PSYCHOL. 269, 291 (1992)
395. (citing S. Yates, Using Prospect Theory to Create Persuasive Communications About Solar Water Heaters and Insulation (Jan. 1, 1982) (unpublished doctoral dissertation) (on file with University of California, Santa Cruz)) (noting the past success of framing investment decisions in terms of loss avoidance in changing investment behavior).
396. Stern et al., Design Principles, supra note 135, at 4848.
397. Id.
398. See, e.g., id. (noting the importance of low cognitive costs for effective household energy efficiency programs).
399. Cf. id. (indicating that the less consumers have to do to effectuate a program, the more likely it will be successful).
400. For work on social identity theory, see Henry Tajfel & John Turner, An Integrative Theory of Intergroup Conflict, in SOCIAL PSYCHOLOGY OF INTERGROUP RELATIONS 33, 40-47 (William G. Austin & Stephen Worchel eds., 1979).
401. See, e.g., JOHN C. TURNER, SOCIAL INFLUENCE 163 (1991) (noting that people are more influenced by ingroups to which they categorize themselves as belonging, and engage in behavior that exemplifies those ingroup norms).
402. See id. (noting that identification with an ingroup makes it more likely for an actor to behave in conformance with group norms).
403. See Cass R. Sunstein, Social Norms and Social Roles, 96 COLUM. L. REV. 903, 915 n. 41 (1996). (Pubitemid 126406323)
404. For work on normative messaging and its impact on behavior, see Goldstein et al., supra note 162, at 482;
405. Schultz, Changing Behavior, supra note 162, at 36;
406. Schultz et al., Power of Social Norms, supra note 162, at 434.
407. See Bowles, supra note 174, at 1605 (arguing that economic incentives that induce selfishness can be counterproductive);
408. Gneezy & Rustichini, supra note 173, at 10 (finding that when actors frame their actions in terms of economic consequences, they tend to act in ways that ignore the social consequences of those actions).
409. See Abrahamse et al., supra note 88, at 276 (discussing the successful use of goal-setting techniques in changing behavior).
410. See supra Part II. A.2.b.
411. For example, providing normative information in energy bills led to a reduction in energy use even though levels of energy consumption could not be directly observed by one's peers. Ayres et al., supra note 163, at 14-15.
412. See Vandenbergh, supra note 45, at 1105-06 (suggesting that personal norms may influence behaviors in situations where peers do not observe the harmful behavior).
413. See Hubert J. O'Gorman, The Discovery of Pluralistic Ignorance: An Ironic Lesson, 22 J. HIST. BEHAV. SCI. 333, 333-35 (1986) (discussing pluralistic ignorance and its potential effects).
414. See id. at 334
415. (citing analogous examples).
416. John Thogerson, A Cognitive Dissonance Interpretation of Consistencies and Inconsistencies in Environmentally Responsible Behavior, 24 J. ENVTL. PSYCHOL. 93, 94 (2004).
417. Cf. id. (indicating that individuals would prefer to act in conformance with such norms).
418. See Abrahamse et al., supra note 88, at 275-76 (discussing commitment strategies).
419. OIRA recently noted that it is important to use "[s]cientifically valid experiments" along with market surveys and focus groups to test the effects of summary disclosure, and that "[c]onsultation with experts can also be a valuable supplement to focus group testing." 2010 OIRA Disclosure Memo, supra note 5, at 5.