There is a vast array of empirical data related to the BE movement which applies to many different fields. This chapter will focus on a selection of BE research findings, specifically on those that are likely to have implications for the immunity policy, namely:
- Complex Decision-Making
- The Availability and Representativeness Heuristics - Overconfidence Bias
- Context of Decision Making
75 See Richard A Posner, A Failure of Capitalism - The Crisis of '08 and the Descent into Depression
(Harvard University Press, 1st ed, 2009).
76 Ibid.
77 Catherine Herfeld, 'The Potentials and Limitations of Rational Choice Theory: An Interview with
Gary Becker' (2012) 5 Eramus Journal for Philosophy and Economics 73, 75.
78 See, eg, Productivity Commission, 'Behavioural Economics and Public Policy' (Australian
Government Productivity Commission Roundtable Proceedings, 2007) 67, 131; Judith Mehta, 'Behavioural Economics in Competition and Consumer Policy' (University of East Anglia, 2013); Lunn, above n 61; Competition and Markets Authority, above n 62.
58 - Habit and Traditions
(a) Complex Decision Making
The first finding relates the complexity of a problem and its ability to affect an individual’s ability to maximise their utility. This aspect of the BE Approach is closely related to Simon’s notion of bounded rationality, discussed above.
Essentially, when a decision-maker is faced with a complex problem, it requires a significant amount of cognitive effort to comply with the predictions of rational choice theory; so instead, studies have shown that a decision maker will employ simplified strategies in order to minimise effort to make selections.79 The notion that decision makers simplify complex scenarios in order to make decisions contradicts the rational actor model, as this does not necessarily maximise their utility. In particular, as choices become difficult, consumers naturally tend to defer decisions, often indefinitely.80 For example, one study found that individuals were less likely to select a house that maximised their utility (defined by questions the subjects were earlier asked about their preferences) from among five alternatives, as the number of attributes presented to the subjects was increased beyond ten.81
If this idea is accepted, then it would seem that complexity affects an individual’s ability to maximise their utility. If this concept is applied to the context of a decision maker in the process of deciding whether or not to apply for immunity, a rational actor model would predict that the decision maker would compute all the possibilities available, with the assumption that the decision maker is in fact aware of all of these possibilities and then will systemically undertake a cost-benefit analysis to find the solution with the greatest utility.
79 See Charles Schwenk, 'Cognitive Simplication Processes in Strategic Decision-Making' (1984) 5 Strategic Management Journal 111; Irene Duhaime and Charles Schwenk, 'Conjectures on Cognitive
Simplication in Acquisition and Divestment' (1985) 10 The Academy of Management Review 287.
80 See S Iyengar and M Leppar, 'When Choice is Demotivating: Can One Desire Too Much of a Good
Thing?' (2000) 79 Journal of Personality and Social Psychology 995; E Shafir, I Simonson and A Tversky, 'Reason-Based Choice' (1993) 49 Cognition 11.
81 Naresh K Malhotra, 'Information Load and Consumer Decision Making' (1982) 8 Journal of Consumer Research 419, 422-423.
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However, immunity related decisions are not a straight forward exercise and the decision to apply often involves competing and complex considerations.82 For example, if a cartel participant is involved in an international cartel across a number of jurisdictions, then the decision to apply for immunity becomes multi- jurisdictional. Not only will an immunity applicant need to identify each jurisdiction that the cartel may have affected, but also there is no guarantee that if the applicant is successful in one jurisdiction it will be granted immunity in any other jurisdiction.
This could mean that the evidence provided by the immunity applicant in one jurisdiction where they are granted immunity could be used against the immunity applicant in another jurisdiction, in which the cartel participant did not seek or was not successfully granted immunity. This could also lead to a number of civil claims lodged by third parties who have also been affected by the operation of the cartel in all of the affected jurisdictions.83 Therefore, as this example shows, the options available to the cartel participant are significantly more complex and varied than the rational actor assumptions predict.
(b) Availability and Representativeness
Representativeness refers to the situation in which probabilities are evaluated by the degree to which A is representative of B by the degree to which A resembles B.84 An example can be derived from the research of Cornell psychologist Tom Gilovich, who in 1991 conducted research on the experience of London residents during the German bombing campaigns of World War II. When newspapers released pictures on where the bombs had landed, they evidently appeared to depict ‘clusters’ around the River Thames and also the northwest sector of the map.85
This generated great concern among London residents who believed that this cluster pattern indicated that the Germans were able to aim their bombs with great
82 See Chapter V, Motivations for Seeking Immunity, pg 126; see, eg, Andreas Stephan and Ali
Nikpay, 'Leniency Theory and Complex Realities' (University of East Anglia & Centre for Competition Policy - CCP Working Paper 14-8, 2014)
<http://competitionpolicy.ac.uk/documents/8158338/8199490/CCP+Working+Paper+14- 8.pdf/3a273397-457c-4109-8920-d79c6709774b>.
83 See Chapter VII, Confidentiality Across Borders, pg 261. 84 Kahneman, Slovic and Tversky, above n 66, 4.
85 Howard Kunreuther, 'The Changing Societal Consequences of Risks from Natural Hazards' (1979)
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precision. However, a detailed statistical analysis revealed that the distribution of the bomb strikes was indeed random.86 Kahneman and Tversky assert that this approach to the judgment of probability can lead to serious errors, because similarity, or representativeness, is not influenced by several factors that should affect judgments of probability, according to the rational actor model.87
The Availability Heuristic refers to the way in which people assess the likelihood of risks by asking how readily examples come to mind. The more readily these relevant examples are to the individual, they are far more likely to be concerned then if they cannot recall such examples. For instances, an individual may assess the risk of heart attack among middle aged people by recalling the number of
heart attacks that have occurred in people they know.88 Closely related to this heuristic are the concepts of Accessibility and
Salience, meaning that if you have personally experienced a heart attack then you are more than likely to believe it will happen then if you saw a story on the news about a person having a heart attack, and the likelihood of this happening again would be affected by how recently the heart attack occurred. Therefore, the Availability heuristic in risk assessment can have a substantial impact on the way the public perceives and reacts to risk and taking precautions. For instance, a person is more likely to purchase flood insurance when they know someone who has experienced a flood.89
In the context of criminal enforcement, according to the rational actor model, and the predictions of Gary Becker, criminals will maximise their utility by committing crimes only if the expected benefits exceed the expected costs. According to this theory, in order to deter crime, society must raise the expected costs above the expected benefits of the crime.90 This is usually achieved by increasing the severity of the punishment, such as lengthening gaol terms or imposing higher monetary fines.91
86 Thaler and Sunstein, above n 72, 28.
87 Kahneman, Slovic and Tversky, above n 66. 88 Ibid 11.
89 Thaler and Sunstein, above n 72, 25.
90 Raymond Paternoster, 'How Much Do We Really Know About Criminal Deterrence? ' (2010) 100 Journal of Criminal Law & Criminology 765, 766.
91 See, eg, Christopher Harding, 'Cartel Deterrence: The Search for Evidence and Argument' (2011) 56 The Antitrust Bulletin 345.
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However, if the Availability heuristic is applied, when calculating the anticipated costs of crime, the types of events that are more salient to these potential criminals could significantly impact the analysis conducted by these criminals.92 Therefore, in order to determine which deterrence mechanism will be the most effective, it must be understood whether the criminals are likely to over or underestimate the frequency and the severity of punishment that is actually imposed. In Australia, there is yet to be a criminal cartel case but the potential gaol sentence for cartel conduct is a maximum of 10 years.93 Therefore, at least at the time of writing, cartel participants are likely to underestimate the severity of punishment, due to the lack of criminal prosecutions in Australia. The situation could be much different in the United States, where individual imprisonment sentences have been increasing over the past decade, and along with it, the length of the gaol sentences.94
Because the severity of the punishment for cartel conduct is not yet a significant factor in Australia, at least for criminal cartel activity, increasing the frequency of punishment is likely to be more effective, ‘under the assumption that if a criminal knows or knows of someone who has been imprisoned for a particular crime, this information is likely to be available and to cause him to overestimate the likelihood that he will be arrested and convicted if he commits the same crime.’95 As mentioned, this cannot yet be assessed in Australia, but in the civil context at least, increasing the frequency of punishment, ie the number of cartels that are discovered and prosecuted is likely to cause potential cartel participants to overestimate the likelihood that they will be detected and held liable.
However, the discovery of cartels rests very heavily on the use of the immunity policy; hence the perception of the immunity policy and its use is likely to have a significant bearing on a potential cartel participant’s estimation of the likelihood of conviction. This consideration becomes even more critical when there is speculation that the authorities are placing too much reliance on the immunity policy as its sole source of cartel detection. That could suggest to potential cartel
92 Korobkin and Ulen, above n 2, 1068.
93 Competition and Consumer Act 2010 (Cth) Part IV.
94 Caron Beaton-Wells and Brent Fisse, Australian Cartel Regulation: Law Policy and Practice in an International Context (Cambridge University Press, 1 ed, 2011) 507.
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participants that if you do not come forward on your own accord, then there is a strong likelihood that the cartel will not be detected at all.96
(c) Over Confidence Bias
Even when people may be aware of the actual probability distribution of a particular event occurring, their predictions as to the likelihood of that particular event happening to them are subject to what is called ‘Over Confidence’ bias. This encompasses the belief that good things are more than average likely to happen to us and consequently, bad things are less likely than average to happen to us.97
Related to the Over Confidence bias is the ‘confirmatory’ or ‘self-serving’ bias; the term used to describe the observation that actors often interpret information in ways that serve their interests or preconceived notions.98 For instance, studies have shown that within the corporate context, managers exhibit ‘undue confidence in their firms’ ability to overcome obstacles and a self-serving perception of information that might objectively signal future problems’ which could potentially mislead those who would invest in their firms’ securities.99
In applying this research to the position of a cartel participant, it is likely that an individual involved in a cartel will exhibit Over Confidence bias in relation to the success or predicted success of the operation of the cartel, and therefore this would adversely affect their decision to apply for immunity. Closely related to this argument is the prospect that even if a cartel member is aware that other cartels have failed, the Over Confidence bias will lead them to believe that the cartel they are involved in will not fail. This is also supported by evidence that many cartel
96 Megan Dixon, Ethan Kate and Janet McDavid, 'Too Much of a Good Thing?: Is Heavy Reliance on
Leniency Eroding Cartel Enforcement in the United States?', 2014
<https://www.competitionpolicyinternational.com/too-much-of-a-good-thing-is-heavy-reliance-on- leniency-eroding-cartel-enforcement-in-the-united-states/>; OECD, 'Ex officio Cartel Investigations and the Use of Screens to Detect Cartels' (Organisation for Economic Cooperation and Development, 2013) 5; Stephan and Nikpay, above n 82, 13.
97 See generally Christine Jolls, 'Behavioral Economic Analysis of Redistributive Legal Rules' (1998)
51 Vanderbilt Law Review 1653.
98 Korobkin and Ulen, above n 2, 1055. 99 Ibid 1056.
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members do not apply for immunity unless the cartel has already failed.100 Although it has been acknowledged by those conducting the studies of BE that the Over Confidence bias is not a universal phenomenon, it is argued that the bias is prevalent, often massive and difficult to eliminate. This is particularly challenging because confidence controls action.101
(d) Context of Decision Making
As discussed previously,102 advocates of the rational actor model base their assumptions on a decision-maker maximising their utility in a lacuna, devoid of any context that may affect their decisions. In contrast, BE studies acknowledge that decisions are often inextricably bound to the context in which they are made, and can affect the decision that the decision-maker ultimately makes.103
One of the most important findings to emerge from the BE Approach relates to the way in which individuals view gains and losses. These concepts fall within the category of ‘Framing’ and ‘Reference Points.’ As mentioned previously, the studies conducted by Kahneman & Tversky have shown that when a decision is framed in terms of ‘losses’ then an individual is more likely to exhibit ‘risk seeking’ behaviour, whilst if a decision is framed in terms of ‘gains’ then an individual is more likely to be ‘risk averse.’104
Applying these findings to the immunity policy, it would seem that the way in which the immunity decision is framed is crucial in influencing decision-making behaviour. If the decision to apply for immunity is seen as a ‘gains’ decision, presumably in the form that the applicant will ‘gain’ immunity and thus are not prosecuted, then cartel participants are likely to be risk-averse, meaning that they are more likely to decide to apply for immunity then risk being exposed and prosecuted. However, if the decision to apply for immunity is seen as ‘loss,’ due to the possibility
100 See, eg, Andreas Stephan, 'An Empirical Assessment of the European Leniency Notice' (2009) 5 Journal of Competition Law and Economics 537; Office of Fair Trading, 'The Impact of Competition
Interventions on Compliance and Deterrence' (Office of Fair Trading, 2011) 36.
101 Dale Griffin and Amos Tversky, 'The Weighing of Evidence and the Determinants of Confidence'
(1992) 24 Cognitive Psychology 411, 432.
102 See Chapter II, A Theoretical Breakdown of the Immunity Policy, pg 47. 103 Kahneman, Slovic and Tversky, above n 66, 545-547.
104 A Tversky and Daniel Kahneman, 'The Framing of Decisions and the Psychology of Choice'
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of diminished cartel profits or potential civil or criminal liability, including possible follow-on damages actions, then the immunity applicant is more likely to exhibit ‘risk-seeking’ behaviour. It has been argued by some commentators, such as Jeffry Rachlinski, that plaintiffs are likely to perceive litigation options as ‘gains’ since they stand to receive money, whereas defendants are likely to perceive their options as ‘losses.’105
Therefore, it is possible that cartel participants are likely to view the decision to apply for immunity as a loss decision, which is likely to make them more risk- seeking, ie ‘take their chances.’ This finding contradicts the rational actor model, which would predict a decision maker’s decision as being independent of the framing and reference effects propounded by the BE Approach.
Studies have shown that mood and emotion can also affect individual decision-making. According to Schwarz, our feelings ‘may influence which information comes to mind and is considered in forming a judgment, or serve as a source of information in their own right.’106 The impact that thoughts, feelings or moods can have on human decision-making is yet another consideration that is absent from the rational actor model. As mood can change the way an individual processes information, either positively or negatively, it can be argued that a cartel participant seeking immunity, is likely to not be acting within the assumptions of rational actor theory, and this could significantly impair their capacity to make a decision that maximises their utility.107
(e) Habits & Traditions
According to the predictions of rational choice theory, individual decision- makers base their decisions on a complete set of information, which is independent of behaviours, meaning that it is based on the assumption that the way an individual has acted in the past will not affect their current preference structure.108 However, BE advocates argue against this and claim that the way an actor has performed in a
105 Korobkin and Ulen, above n 2, 1105.
106 Kahneman, Slovic and Tversky, above n 66, 546.
107 For empirical support for this, see Chapter V, Motivations for Seeking Immunity, pg 126. 108 Korobkin and Ulen, above n 2, 1112.
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certain way in the past can increase the likelihood that they will act in a similar way in the future.
This is most effectively illustrated by the notion of ‘sunk costs’ and how it affects an individual’s decision-making process, despite the fact that it does not accord with the rational actor model. Many BE studies have shown how people regularly cite ‘sunk costs’ as a reason that they are pursuing a certain type of action, for instance in the decision to undertake an activity that they would prefer not to, on the basis that they had already bought a ticket to the particular sporting event or theatrical performance.109 In the context of a cartel, it is obvious that a cartel participant would have ‘sunk’ time, energy and presumably capital (at least at the outset) throughout the duration of the cartel and this could be another relevant factor in determining whether or not to seek immunity and potentially affect their willingness to give up on the cartel.
In addition, the ‘power of tradition’ is cited as having a powerful effect on human decision-making.110 The concept is derived from the notion that the utility individuals gain from conforming to a shared family, group or community practice, can outweigh the inherent value of the behaviour.111 In the context of cartels, there is the existence of group behaviour or mentality that is more likely to influence the decision making process, such as the decision to join a cartel, remain in a cartel or apply for immunity. According to behavioural economists, habits, traditions and addictions are much more difficult to manipulate than the rational actor model predicts.
This would help to explain scenarios where people engage in forms of self- blackmail, such as writing incriminating letters that may be sent in the event that something happens, in order to force them to make a particular decision and stick with it. This could explain why cartel participants tend to keep pieces of incriminating evidence of the cartels operation – almost like leverage or blackmail to
109 See H Arkes and C Blumer, 'The Psychology of Sunk Cost' (1985) 35 Organizational Behavior and Human Decision Processes 124; J Brockner and J Rubin, Entrapment in Escalating Conflicts: A Social Psychological Analysis. (Springer-Verlag, 1st ed, 1985); H Garland and S Newport, 'Effects of