The life and times of individuals scoring high and low on dispositional greed

Accepted Manuscript The life and times of individuals scoring high and low on dispositional greed Patrick Mussel, Johannes Hewig PII: DOI: Reference:

S0092-6566(16)30082-4 http://dx.doi.org/10.1016/j.jrp.2016.07.002 YJRPE 3579

To appear in:

Journal of Research in Personality

Received Date: Revised Date: Accepted Date:

12 March 2016 5 July 2016 10 July 2016

Please cite this article as: Mussel, P., Hewig, J., The life and times of individuals scoring high and low on dispositional greed, Journal of Research in Personality (2016), doi: http://dx.doi.org/10.1016/j.jrp.2016.07.002

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Title: The life and times of individuals scoring high and low on dispositional greed Authors: Patrick Mussel1*, Johannes Hewig1

Affiliation: 1

Julius Maximilians University Würzburg, Department of Psychology I, Differential

Psychology, Personality Psychology, and Psychological Diagnostics, Marcusstr. 9-11, 97070 Würzburg, Germany.

*Correspondence to: [email protected].

Acknowledgments This research was supported by a Schumpeter-Fellowship awarded by the VolkswagenStiftung (85650; II/86486). The funding source had no other role other than financial support.

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Title: The life and times of individuals scoring high and low on dispositional greed

Abstract: Greed is a variable which might explain and predict a range of real-life criteria. Although often consulted as explanation in the public media, related scientific research has only recently begun. We approached greed from a personality psychology perspective regarding its nomological net and the prediction of theoretically related criteria. We found that a wide array of indicators, including behavior in economic games and risk games, as well as self-reported money investment and aimed at income, can be meaningfully predicted by dispositional greed, over and above the Big Five. Additionally, we found that dispositional greed is substantially related to psychopathy. According to our results, dispositional greed is an important variable which might explain unique variance with regard to theoretically related behaviors.

Running head: Dispositional greed Keywords: Greed; psychopathy; materialism; Big Five; economic games

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Boaz Weinstein, Hedge fund manager and founder of Saba Capital, has an excessive desire for money. At age 27, he was promoted to managing director at Deutsche Bank—the youngest managing director in the bank's history—and became co-head of global credit trading. By taking excessive risks with complex financial derivatives, he earned his employer fabulous earnings. Weinstein is also a passionate blackjack and poker player. He once won a Maserati in a poker tournament sponsored by Warren Buffett, an American business magnate and investor. However, for what he became most famous is far less favorable: In 2008, during the financial crisis, his unit lost 18% on $10 billion capital, almost half of the total losses of Deutsche Bank during the worst year of the financial crisis. The greedy behavior of individuals like Boaz Weinstein—agents operating in investment, credit, and real estate departments of financial firms—is commonly seen as contributing factor to what was initiated by the subprime mortgage crisis in the United States of America and the debt crisis in Europe, and ultimately evolved into a global economy crisis, affecting the real economy with profit shrinkage, downsizing, unemployment, and insolvency. Driven by vast income and excessive bonuses, some of these agents took excessive risks and made reckless decisions to increase their revenue. Scientific research has begun to investigate greed in diverse areas and with regard to diverse goals and perspectives. Examples include studies investigating the influence of greed on economic bargaining (Wang & Murnighan, 2011); the influence of greedy behavior shown in the children's television program from a pedagogical perspective (Kort-Butler, 2012); the influence of education on greed (Wang, Malhotra, & Murnighan, 2011); societal and organizational values which may contribute or inhibit greed (Bruhn & Lowrey, 2012); greed as a motive for deception (Tunley, 2011) and corruption (Burke, 2009); the relation between greed and cooperative

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behavior (Eek & Biel, 2003; Simpson, 2003), greed in the context of justice and attribution theories (Gilliland & Anderson, 2011); greed as a consequence of priming the concept of money (Vohs, Mead, & Goode, 2006; Piff, Stancato, Cote, Mendoza-Denton, & Keltner, 2012); the relation with subclinical (Wilson & McCarthy, 2011) and clinical manifestations of psychopathy (Waska, 2004); the influence of greed on rebellion and civil war (Regan & Norton, 2005); and the role of greed in Christianity (Tickle, 2004) and Buddhism (Kaza, 2005). However, from a personality psychology perspective, our knowledge regarding the nature of the construct of greed and its relevance for diverse outcomes is still limited. One reason for this lack of research is that until recently, a validated measure for assessing greed had not been available. However, more recently, presumably inspired by the events of the financial crisis, several measures have been developed (Krekels, & Pandelaere, 2015; Mussel & Hewig, 2014; Mussel, Reiter, Osinsky, & Hewig, 2014; Seuntjens, Zeelenberg, van de Ven, & Breugelmans, 2015b; Veselka, Giammarco, & Vernon, 2014). For example, the GR€€D scale by Mussel and Hewig (2014) is a 12-item self-report measure including items such as “I will always try to increase my income and my assets”, “I have a great appetite for more”, or “I would stop at nothing to get what I want”. The availability of such measures now allows research on this potentially important construct. In the present study, following a brief discussion of the construct of greed and recent findings, we investigate dispositional greed more closely with regard to its nomological net and behavioral consequences. The defining feature of dispositional greed is the desire to get more. For example, Seuntjens et al. (2015b) referred to greed is an insatiable hunger for more, and Krekels & Pandelaere (2015) as “an insatiable desire for more resources, monetary or other”, thereby noticing that greed is mostly, but not exclusively related to materialistic or monetary objects.

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Indeed, greed may be directed towards diverse objectives, such as power, status, food, or sex (Balot, 2001). However, it is mainly seen as a materialistic type of desire and associated with the acquisition of money, as a value by itself or as an instrumental value for obtaining material goods (Bruhn & Lowrey, 2011; Wang & Murnighan, 2011). When asking lay persons to list as many exemplars of greed as they could think of, Seuntjens et al. (2015a) report that concepts related to materialism were reported in 177 cases and related to money in 77 cases, whereas concepts related to lust in only 4 cases. Food-related concepts were not mentioned at all. The Merriam-Webster (2013) dictionary definition of greed as “a selfish and excessive desire for more of something (as money) than is needed” shares the aspect of acquisitiveness, and additionally implements a normative component to which greed behavior is related, which may, however, not easily be determined. Similarly, Johnson’s (1999) definition of greed as a desire to acquire and accumulate more than is needed also shares the problem of defining how much is actually needed. Balot (2001) used the term greed to refer to acquisitiveness or an excessive desire to get more. As with the notion of a normative level of what is needed, it is also difficult to define where "excessive" begins (Wang et al., 2011). According to the results of a prototype analysis, Seuntjens, et al. (2015a) defined greed as the dissatisfaction of not having enough, combined with the desire to acquire more, thereby assuming that greed may be the result of either approaching the positive consequence of obtaining desired goods as well as withdrawing from the negative state of not having these goods. The definition by Mussel and Hewig (2014) of greed as a desire to get more at all costs also focuses on the element of acquisitiveness, thereby emphasizing that greedy behavior, as opposed to mere accumulation of desired goods, is characterized by hazarding potentially negative consequences that result from one’s own actions for other entities, whereby this entity

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might be a single person, a group, an organization, or society as a whole. An example for the latter are the vast sums of money for banking bailout and economic growth packages that governments were forced to pay during the financial crisis in the recent past, which was exacerbated by excessive risk taking by agents operating in investment departments of financial firms or stock exchanges. Regarding its nomological net, greed can be related to envy as both refer to a motivation of obtaining certain goods which one currently does not possess (Smith, Parrott, Diener, Hoyle, & Kim, 1999; Van de Ven, Zeelenberg, & Pieters, 2009). However, envy always refers to a social comparison with another person, specifically when someone else is better off than oneself; in comparison, greed is more individualistic irrespective of a social comparison (Seuntjens et al. 20015b). Similarly, greed shares the element of an appreciation of a desired good with the constructs miserliness or stinginess. However, whereas greed refers to accumulating more, thus far not obtained objects, miserliness or stinginess both refer to things which someone already possesses and does not want to lose. A major difference between these constructs concerns to accompanying emotional-motivational processes, as miserliness or stinginess implies the fear of losing what one already possesses, whereas greed relates to a positively connoted expectation of obtaining an appreciated object (Hur, Jeong, Schermer, & Rushton, 2011). Greed is also related to the concepts of status and power. In a capitalistic society, income is a major determinant of socio-economic status which becomes visible for others through expensive and prestigious objects. Thus, the desire for gathering more money or obtaining prestigious possessions might be a means to an end for individuals striving strongly for status. Additionally, research on Machiavellianism has pointed towards the relation between the agentic

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motives of power and money in the context of self-beneficial goal pursuit (Christie & Geis, 1970; Rauthmann, 2012). Therefore, greed can be brought into a conceptual relationship with materialism, and strong correlations between greed and materialistic values are in line with this assumption (Seuntjens, Zeelenberg, van de Ven, & Breugelmans, 2015b). Materialism refers to the propensity to enjoy buying things, above what would be necessary, and to appreciate one's property and belongings (Richins & Dawson, 1992) and is related to the "love for money", as conceptualized by Tang (1992). However, high levels of materialism do not necessarily imply greedy behavior. For example, a wealthy person might be more likely to show benevolence compared to an ascetic (Wang et al., 2011). Additionally, a materialistic orientation might be characterized by feeling satisfied when, for example, buying expensive clothes, whereas greed is rather composed by feeling unsatisfied considering all the things that are not yet possessed. Therefore, while greed appears to be highly related to materialism, both concepts are not equivalent (Seuntjens et al., 2015b). When greedy behavior comes at the expense of others, it might be related to ruthlessness or callousness, traits which have been described in research on psychopathy (Lilienfeld & Andrews, 1996; Lilienfeld & Fowler, 2006; Patrick, Fowles, & Krueger, 2009). Greedy individuals might justify the rightness of their actions by the instrumental value that their behavior has for obtaining desired goods, whereby shared norms, moral standards, rules, and laws are qualified. Recently, there is increasing interest in investigating the impact of personality traits with regard to non-self-report measures especially in economic games such as the Dictator game (Güth, Schmittberger, & Schwarze, 1982) or public good dilemmas (e.g., Eek & Biel, 2003). In a

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dictator game, two participants play against each other, the proposer and the receiver. The proposer divides a sum of money between himself and the responder. The responder has to accept whatever the proposer offers. Greedy individuals have been found to keep more money for themselves as they strive for acquiring more money, even though such a decision comes at the expense of the responder who will, correspondingly, get less (Seuntjens et al., 2015b). Similarly, in the public goods dilemmas, people interact with interdependent others. Each individual has to make a decision on how much to take from an attractive resource to which all have access. In this framework, greedy behavior would be characterized by taking all (or most) of the resource for themselves at the expense of others. Often, such behavior violates norms that are shared by members of a culture, an organization or a group, such as norms for fairness or equality (Cozzolino, Staples, Meyers, & Samboceti, 2004). In this regard, greed has been defined as excessively self-interested behavior that goes against prevailing norms (Wang & Murnighan, 2011), and as unfair behavior, harming the rules of competition (Bruhn & Lowrey, 2012). Seuntjens et al. (2015b) found support for an influence of dispositional greed on harvesting in a public goods dilemma, which was moderated by the desire to obtain as much of the resource as possible for oneself, rather than because of the expectancy that others will overharvest. The authors speculate that greed might unfold morally negative consequences when striving for desired goods comes at the expense of others, whereas the consequences are neutral or even beneficial in situations where no such interdependencies exist. Divergent findings have been reported for the association between greed and risk-taking. Mussel, Reiter, Osinsky and Hewig (2014) found greed to predict risk-taking using the balloon analogue task (Lejuez et al., 2003). Contrary, Seuntjens et al. (2015a) found no association between greed and risk aversion. One reason for these divergent results might be due to the

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operationalization of risk-taking propensity. The self-assessed risk aversion measure used by Seuntjens et al. might more strongly relate to a general appreciation vs. aversion of situations associated with risk, i.e. situations characterized with uncertainty. While greedy and non-greedy individuals might be equally attracted by such situations, they might well differ in their decisionmaking when outcomes of risky decisions, compared to less risky decisions, are associated with higher potential gains. Additionally, the risky behavior of greedy individuals might be due to differences in the evaluation of the outcome of the decision. Support for this notion comes from the study by Mussel et al. (2014) who recorded neural responses to wins and losses while participants took the task. They found that the feedback-related negativity, a negative deflection in the EEG typically modulated by the valence of an outcome stimulus, was moderated by greed. More specifically, while individuals with low levels in dispositional greed showed the typical stronger neural response to losses, compared to wins, this effect diminished for individuals with high levels of greed. A diminished feedback-related negativity might indicate difficulties in learning from experience, especially from mistakes, punishment, or negative events (Holroyd & Coles, 2002; Boksem, Tops, Kostermans, & De Cremer, 2008), and might therefore contribute to risky decisions in the future. In the present study, we further investigated individual differences in greed with regard to diverse behaviors theoretically related to greed. Therefore, we obtained six indicators of greedy behavior: The amount taken from a resource in a common goods paradigm; the money kept for oneself in a Dictator game; risk-taking; emotional reactivity to a loss and win of money; aimedat income; and self-reported investment of money. The rational for considering these indicators and detailed information on the experimental setup are given below in the method and results sections.

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Furthermore, we included additional measures to investigate the nomological net of greed. Specifically, a measure of the Big Five was included to investigate correlations with the currently most established and agreed upon model of personality. Additionally, a measure of psychopathy was included to investigate the proposed relation between greed and psychopathy, as discussed above.

Sample and procedure. Data were collected in three studies with a total of 200 participants (N=71, 70, and 59, for the three studies). Participants were recruited via postings (both hard copy and online) and consisted of students of psychology of the University of Würzburg, students of other disciplines as well as non-students. They participated voluntarily in the present study and received course credit or a small financial incentive (€ 6.70). Participants were between 17 and 57 years old (M=23, SD=5.3), 76% were female. All participants gave information on the GR€€D scale (Mussel & Hewig, 2014). Additional data was obtained in at least two of the three studies, as noted below. Post hoc power analyses revealed a power of 1-β=.92 for an expected population effect size of ρ=.22 (Seuntjens et al., 2015b) and α=.05. After receiving verbal instructions about the experiment, participants gave written informed consent for participation. Participants were informed that they played against the participant who took the experiment most recently and that they could win money on a fictive bank account across several tasks; their task was to obtain as much money as possible.

Personality measures.

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The 12-item GR€€D scale (Mussel & Hewig, 2014; Mussel et al., 2014) was administered. Items are depicted in the Supplemental Online Material. Internal consistency was .89. Additionally, the Big Five Aspect Scale (BFAS, DeYoung, Quilty & Peterson, 2007) was administered in two samples (N=129). The BFAS consists of 100 items, which assess the five domains of the Big Five with 20 items each and the 10 aspects, defined as lower order factors of the Big Five, with 10 items each. The Triarchic Model of Psychopathy Questionnaire (Patrick et al., 2009) was assessed in all three samples (N=200). It has 58 items which assess the three factors boldness, disinhibition, and meanness. Internal consistency estimates for the BFAS and the Psychopathy Questionnaire were generally acceptable, as depicted in Table 1.

Behavioral criteria. We obtained behavioral data from several experimental procedures. Across all three samples (N=200), participants played a common goods game (Eek & Biel, 2003). Participants had to make a decision of how much to take from a common resource, a fish farm jointly cultivated with a partner. Participants played three rounds of a common goods dilemma. They were told that they would be playing against another participant (the partner), but that the response of the partner would not be revealed before the end of the experiment. Therefore, the subject who participated in the experiment before was chosen as the partner (there was no deception for this task nor for any other task). For each round, they had to make a decision about

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how many units of fish (between 0 and 5) to take from a jointly cultivated fish farm. The revenue depended on the decision of both the participant and the partner. For a medium decision (two units of fish) of both partners, the overall revenue was maximal. If the participant (but not the partner) took more than two units, the participant would increase his and, at the same time, decrease the revenue of the partner (defecting). However, if his partner also took more than two units, the revenue of both partners would decrease (Bruins, Liebrand, & Wilke, 1989; Simpson, 2003). Additionally, in two samples (N=130), we administered a dicator game (Güth et al., 1982; Stahl, 1972). As noted above, in a dictator game, two participants play against each other, the proposer and the receiver. The proposer divides a sum of money between himself and the responder, and the responder has to accept whatever the proposer offers. Participants in the present study made five offers in the role of the proposer to another participant of the experiment. For each offer, participants had to split the fictive amount of € 100; whatever they kept for themselves was added to their fictive account. Participants in these two samples (N=130) also played three short risk games. In each game, participants had to make a number of decisions between a low-risk and a high-risk alternative. In the first game, participants had to choose one of two options which differed with regards to probability and potential gains. An example for one option would be: “With a probability of 80%, you win 22 Euro and with a probability of 20%, you lose 45 Euro”. Each participant played 35 trials. On average, participants chose the risky option in 38% (SD = 17%); internal consistency across the 35 trials was .81. In the second game, participants had to choose one of two quotations from the perspective of an entrepreneur who offers a certain product or service which differed in potential gains, but also in the probability that the quotation would be

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accepted. Each participant played 33 trials. On average, participants chose the risky option in 44% (SD=16%), the internal consistency across the 33 trials was .79. In the third risk game, participants invested money in a fictive shares profile. They had to make a decision about how much money to invest in a stock by choosing one of two options (e.g. invest either € 2100 or € 6200). Unknown to the participants, stock price changes were actual changes, taken from the day-to-day change of the Dow Jones between 9.6.2011 and 2.8.2011. This period was characterized by a strong rise in stock rates, followed by a steep decline, similar to a stock market bubble. Each participant played 36 trials. On average, participants chose the risky option in 48% (SD=21%), internal consistency across the 36 trials was .89. All three riskgames were presented on a computer via Presentation 12.2 software (Neurobehavioral Systems Inc., Albany, CA, USA). Participants gave their response by pressing one of two buttons. A risktaking index was computed as the percentage of risky decisions per game. Additionally, we investigated whether greed would predict emotional reactions to either monetary wins or monetary losses. Participants from two samples (N=130) filled in the Trait Positive and Negative Affective Schedule (PANAS, Watson, Clark, & Tellegen, 1988) on three occasions. The PANAS is a 20-item inventory—10 items for positive affect (PA) and 10 items for negative affect (NA)—that asks people to rate various mood-related words (e.g., NA: hostile, distressed; PA: interested, enthusiastic). At the beginning of the experiment, participants were instructed to report how they felt “in general” to capture trait affect using a 7-point scale (very slightly or not at all to very much). Additionally, participants filled in the PANAS as a state measure after the dictator game and after the stock risk-game. Therefore, the same 20 items were given with a different instruction, stating that individuals should report how they feel "at this moment".

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Participants from two samples (N=130) were asked to report whether they pursued different kinds of money investments, ranging from very common low-risk investments to rare high-risk investments. Seven kinds of investment were considered: savings bank book, life- and pension funds, building loan contract, precious metals (such as gold), exchange-traded funds, stocks, and stock options. For each investment category, participants indicated whether they pursued that particular investment or not. Finally, participants indicated their aimed-at annual income in ten years from now on a seven point scale: € 15,000, € 20,000, € 30,000, € 45,000, € 60,000, € 100,000; additionally, the seventh option was "more".

Results On average and across all games, participants earned 1626 Euro (SD=544) on their fictive account. Individuals scoring above the median on the GR€€D scale (median=2.75) earned on average 1657 Euro, participants scoring below the median 1597 Euro. Construct-related evidence can be found in Table 1. We found a strong negative correlation between greed and agreeableness. None of the other four Big Five domains was significantly correlated with greed. At the aspect level, we found a reverse pattern for the two aspects of the domain extraversion: While assertiveness was positively correlated with greed, the correlation with enthusiasm was negative. Interestingly, we observed a high correlation between greed and meanness, a factor of the Triarchic Model of Psychopathy Questionnaire. Additionally, greed was moderately correlated with disinhibition.

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Common goods game. Common goods games are characterized by a decision between a selfish choice, which maximizes personal gains at the expense of others, and a cooperative choice, which maximizes the overall benefit for all players (Dawes, 1980). We expected that greedy individuals would make more selfish decisions compared to less greedy individuals (Eek & Biel, 2003). On average, participants took 2.6 (SD=0.58) units of fish from the common resource. Internal consistency across the three rounds was α=.64. As expected, we found a positive correlation between greed and selfish behavior in the common goods paradigm (r=.22, p=.001): Individuals scoring high, compared to low, on greed significantly more often defected in the common goods paradigm by taking more for themselves from a common resource.

Dictator game. Dictator games are frequently used in game theory to simulate behavior in a negotiation context between parties with an unequal amount of power (Sanfey, 2007). Rational choice theory (Neumann & v. Morgenstern, 1947) would predict that proposers keep all the money for themselves to maximize their personal revenue; however, individuals often deviate from these predictions, offering some money (up to half of the total amount, or even more, e.g., Forsythe, Horowitz, Savin, & Sefton, 1994) to the receiver, which has been interpreted as a concern for fairness, cooperation and reciprocity (Bowles & Gintis, 2004; Fehr & Gächter, 2002). Therefore, we propose that greedy individuals would take more money for themselves compared to less greedy individuals.

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On average, participants kept € 61 (SD=€ 14) for themselves. Internal consistency across the five offers was α = .91. As expected, greedy individuals kept more money for themselves, compared to less greedy individuals (r=.32, p=.001). Therefore, greed significantly predicted selfish compared to fair and cooperative behavior.

Risk taking. Risk-taking behavior generally involves a situation with uncertain outcome which has some potential for loss or damage (Leigh, 1999). In financial risk-taking games, a decision must typically be made between a low-risk option, which implies no or limited chances of a win, but also no or limited chances of a loss, and a high-risk option, which implies possible high wins, but also the chance of high losses (e.g. Lejuez et al., 2003). We expected greedy individuals to take higher risks in order to maximize the chances of higher wins compared to individuals with lower levels of greed. The three risk-taking indicators were positively correlated (between .24 and .44). An overall risk indicator was computed by averaging the standardized risky decision indices across the three games. Across the three games, greed significantly predicted risk-taking (r=.17, p=.01). Individuals scoring higher on greed more often made risky decisions, defined as decisions with high outcome variance.

Emotional reactions to wins and losses Monetary wins and losses are conditioned reinforcers which generally elicit positive and negative emotional reactions, respectively (Lea & Webley, 2006). However, there are individual

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differences with regards to the extent that such emotions are elicited (Tang, Kim & Tang, 2002). Based on the definition of greed, we expected greedy individuals to report stronger negative emotional response after losses and stronger positive emotional responses after wins compared to individuals with lower levels of greed. As noted above, the stock market rate followed a pattern similar to a stock market bubble. Specifically, the last 8 trials were losses. As participants' choice was to invest either a relatively small or high amount of money, they suffered from the stock decline in all trials regardless of their decision, that is, they actually lost money in all of the last eight trials from their fictive account. The emotional reaction to losses was defined as specific negative affect to losses controlled for trait negative affect, computed as the residual from regressing state negative affect on trait negative affect. As expected, individuals with high, compared to low, levels of greed reported significantly stronger negative affect after a series of trials with losses, each of which was associated with a loss of money on the personal fictive account (r=.20, p=.01). We used the dictator game to assess affective reactions in response to monetary wins. Specifically, in each of the five rounds of the dictator game, participants received € 100 for their fictive account and could keep as much as they wanted for themselves. The emotional reaction to wins was defined as specific positive affect in response to wins controlled for trait positive affect, computed as the residual from regressing state positive affect on trait positive affect. As expected, greed significantly predicted emotional reactions to wins (r=.15, p=.02).

Self-reported money investment

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We expected greedy individuals to more often pursue different kinds of monetary investments, especially high-risk investments, and to aim at higher annual income compared to individuals with lower levels of greed. Regarding self-reported money investment, we found a significant correlation between greed and the investment of money in stocks (r=.17, p=.02) as well as a significant correlation between greed and investment in savings bank book (r=.14, p=.03). Stocks are characterized by the chance of relatively high gains but, at the same time, relatively high chances of losses. None of the other kinds of investment were predicted by greed (life- and pension funds: r=-.03; building loan contract: r=.09; precious metals (such as gold): r=.03; exchange-traded funds: r=08; stock options: r=.01, all ps>.17). While this may not be surprising for relatively secure investments, such as building loans, the non-significant correlation especially with stock options, an even more risky form of money investment was rather surprising. However, closer inspection of the data revealed that only one participant reported investment in stock options. An aggregated measure consisting of the total number of monetary investments was significantly predicted by greed, as was an aggregated measure weighted by riskiness (both r=.14, p=.03). Our last criterion was personal goals with regard to money. As expected, greed significantly predicted aimed-at income (r=.25, p=.001). Next, we investigated the prediction of greedy behavior by dispositional greed in the context of the Big Five and psychopathy. We computed an overall indicator variable of greedy behavior by aggregating across the z-standardized variables of greedy decisions in the dictator game and the common goods game, risky decisions, positive affect as a response to wins and negative affect in response to losses, aggregated money investment (unweighted) and aimed at income. We computed three separate multiple regressions, with the Big five domains, the Big

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Five aspects or psychopathy entered in Step 1, respectively, and greed entered as additional predictor in Step 2. As can be seen from Table 2, in all three analyses, greed had incremental validity over these groups of variables; accordingly, the beta weight for greed was significant in the context of the Big Five domains, the Big Five aspects, and psychopathy. When greed was entered as the only predictor in Step 1, we found a large and significant correlation with greedy behavior (R=.48, p<.001). However, neither the Big Five domains, nor the Big Five aspects, nor psychopathy showed significant incremental validity (see Table 3). Thus, the variance accounted by these variables in greedy behavior could be fully explained by dispositional greed. 1

Discussion The purpose of the present study was to investigate the construct of greed, a personality trait with potentially high relevance for real-world outcomes, with regard to its nomological net and implications regarding diverse behavioral indicators. We found convincing evidence that greed predicts a range of theoretically related criteria. Individuals scoring high, compared to low, on greed made more selfish decisions in a common goods game, kept more money for themselves in a dictator game, took higher risks across three risk-games, reported stronger negative affect after a loss of money and more positive affect after a win of money, more often invested money in stocks and saving accounts, and had higher goals regarding their aimed-at income. At the construct level, greed was strongly associated with (low levels of) agreeableness,

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We also used structure equation modelling to investigate the influence of dispositional greed on greedy behavior in the context of the Big Five and Psychopathy on a latent level, i.e. controlling for error variance. As outlined in detail in the Supplemental Material Online, results from structure equation modeling are in line with the results from multiple regression analyses.

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a Big Five domain, and meanness, a factor from the Triarchic Model of Psychopathy Questionnaire. Analysis of the nomological net of greed showed that greed can be clearly localized within the domain agreeableness of the Big Five framework. Low scores on agreeableness are characterized by egocentrism and mistrust, thus individuals with low scores on this domain are generally less popular with others because they are less likely to help or act cooperatively. While we consider investigating the nomological net of greed with regard to the currently most agreed upon model of personality, the Big Five (Digman, 1990), as an important first step, future research would benefit from taking alternative models of personality into account. Particularly, investigating relations with the HEXACO model of personality (Lee & Ashton, 2004) would be very interesting. The honesty/humility-factor of the HEXACO-model consists of four facets, one of them labeled greed-avoidance. Relations of greed with this facet, as compared to the factor honesty-humility as well as the factor agreeableness from the HEXACO model would be interesting. This pertains also to the amount of variance that greed, compared to broadband models of personality, explains in behavioral criteria, such as those obtained in the present study. While somewhat beyond the scope of the current manuscript, such research might also points towards limitations of the Big Five model, compared to alternative models of broadband personality. We were surprised to find such a large positive correlation between greed and dimension meanness of the triarchic psychopathy model. Defining elements of meanness include deficient empathy, disdain for and lack of close attachments with others, rebelliousness, excitement seeking, exploitativeness, and empowerment through cruelty; therefore, meanness “can be viewed as agentic disaffiliation, which is a motivational style in which pleasure and satisfaction

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are actively sought without regard for and at the expense of others” (Patrick et al., 2009, p. 927). Strikingly, at the level of item content, there is no overlap between greed and meanness. Indeed, none of the items of the GR€€D scale (nor those of other existing scales) does even address interpersonal issues. Therefore, there is no obvious reason why individuals who strive for obtaining more money would also feel indifferent when they see others suffer, hurt others to see them suffer, act dishonest, or mock others. However, the relation between greed and meanness might indicate that a strong focus on obtaining and increasing desired goods is somehow incompatible with a strong desire for interpersonal closeness, empathy, or altruism. This interpretation bears some resemblance to the structure of values (Schwartz & Bilsky, 1987). In his model of universal values, Schwartz (1992) postulated a circumplex model describing the structure of values across cultures. Accordingly, benevolence, which includes related concepts such as being honest, forgiving, and helpful, occurred diametrically opposite to power and achievement, which includes related concepts such as being successful and ambitious. In this model, values on opposite sides are considered as mutually exclusive. Greed, defined as a desire to get more at all costs (Mussel & Hewig, 2014), reflects the tendency to blank out possibly negative consequences that might arise for another entity from their excessive striving after desired goods. Our findings also add empirical support to a relation that has previously been articulated in the literature. For example, Montgomery (2011) associated greed in the financial market with blatant egoism at the expense of other people, which he called a sort of psychopathic maladaptiveness. Wilson and McCarthy (2011) made a comparison between greed and the organizational psychopath. The authors found that commerce students, compared to a range of different academic degrees, reported higher levels of sub-clinical psychopathy. Also, as reported

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by Noll et al. (2012), investment bankers and psychopaths behave similarly in social dilemma situations, where both have been found to defect more than a comparison group. Therefore, our results might be interpreted as further evidence that the excessive, self-interested striving for material goods implies a sort of callousness or ruthlessness which includes that personal benefits are achieved at the expense of others. So, from a moral point of view, greed is not good. This negative aspect of greed is especially interesting as it is seemingly at odds with economic theories on greed. As noted above, in economic theory, greed is seen as a desirable and inevitable feature of a well-regulated, well-balanced economy. Krekels and Pandelaere (2015) found greed to be positively associated with competitiveness and production orientation, suggesting that greed may be advantageous four getting ahead in profession. Similarly, the negative connotation on greed is at odds with how to appraise the consequences of greedy behavior. Earning a lot of money is generally perceived as an indicator of success, which implies autonomy and independence and strongly influences social status. However, the occurrence of such outcomes per se says nothing about how they were obtained. It seems reasonable not to call a person as greedy, only because he or she obtained a lot of money. If, however, the striving for desired goods was at the expense of others, we would call such behavior as greedy, and we consider such behavior not as good – despite the positive attributes that are associated with the outcome itself. An interesting finding of the present research was to show that greed predicts a wide array of criteria theoretically related to its definition, which supports the notion that greed is a potentially important variable for predicting diverse behavior. We obtained several measures including self-report and non-self-report measures to assess risk-taking, economical decisionmaking, affective reactions to loss of money, self-reported money investment, and economic

22

goals. These criteria are quite diverse (reflected on the empirical level by an average correlation of r=.06). However, for different reasons, these criteria are all theoretically related to greed: units taken from a common resource reflect gain-maximization at the expense of others; money kept for oneself in the dictator-game reflects selfishly keeping more money for oneself and uncooperative decision-making in a negotiation context between parties with an unequal amount of power; risk-taking reflects the hypothesized tendency to accept large losses for the possibility of receiving high gains; negative emotional reactions to losses and positive emotional reactions to wins reflect the higher relevance of obtaining or losing money; investment in stocks reflects real-life, high-risk money investment; and the aimed-at income reflects the striving for money and luxury. The consistent pattern of predicting criteria which are derived from the definition of greed supports the present conceptualization and measurement of greed. Given the correlational pattern with the Big Five and psychopathy, as outlined above, it was important to investigate whether these highly researched variables would account for the variance explained by dispositional greed. Results from multiple regression analysis suggest, however, that these variables cannot explain additional variance in greedy behavior, above dispositional greed. However, vices versa, dispositional greed showed incremental above the Big Five – both on the domain and the aspect level – and psychopathy. Therefore, while dispositional greed can be well aligned within the Big Five framework and is moderately to highly correlated with sub-dimensions of psychopathy, it explains unique variance in theoretically related criteria and might, therefore, meaningfully complement these variables in research and applied settings associated with assessing and predicting greedy behavior. The present research was initialized by the events that occurred during the financial crisis in the recent past, especially the reckless behavior of individual agents operating in financial

23

departments, individuals like Boaz Weinstein who, as noted in the introduction, contributed to the dynamic of the crisis by taking excessive risks for the chance of fabulous earnings, which ultimately resulted in tremendous losses. We approached the construct of greed from a personality psychology perspective as it has the potential to explain and predict such behavior. However, while greed might be a construct of particular importance for this particular group of individuals, we consider behavioral implications of this construct (like construct and criterionrelated validity) not to be restricted to this group, but to pertain to the general population. Therefore, we investigated this construct on the basis of a (sufficiently) representative sample of the population, including both students and non-students from a wide age range, which also counteracts possible range restriction typically found for subgroups of the general population. Criterion-related evidence supports this approach, showing that greed meaningfully predicts theoretically related variables in this sample. Nonetheless, the investigation of special populations remains an interesting field for future studies. Other open research questions include: are there mean differences in greed for individuals in certain professions (e.g. agents operating in financial departments), compared to the general population (e.g. Krekels & Pandelaere, 2015)? If so, were they already present when these individuals chose their career, or did they rather develop during education and professional life? To what extent does social desirability influence test scores on greed measures? Are there differences between countries and cultures? How do organizational culture, values, and norms (like social cohesion or profit maximization) influence greed, or do such variables possibly interact with greed (e.g., Bruhn & Lowrey, 2012)? If so, might organizational culture provide a protective factor against the reckless behavior of individuals with high levels of greed? How does greed relate to performance, is it a detrimental factor, leading to counterproductive work

24

behavior, or might it contribute positively to certain performance outcomes, possibly due to high ambition and power motivation? Are such relations moderated by the type of performance criterion (e.g. supervisory performance ratings, employee performance ratings, career success)? How do individuals with high levels of trait greed experience greedy behavior, especially behavior objectively rated as negative, such as striving for desired goods at the expense of others? How does a feeling of never having enough affect emotions and cognition, or variables like life satisfaction? Can we influence trait greed by interventions to prevent negative consequences? Research on the important construct of greed is just about to begin.

25

Acknowledgement This research was supported by a Schumpeter-Fellowship by the VolkswagenStiftung (85650; II/86486;

https://www.volkswagenstiftung.de/en/funding/completed-

initiatives/schumpeterfellowships. html). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Table 1: Construct and criterion-related validity for the GR€€D scale N M SD 1 Greed 200 2.90 0.99 Big Five Aspect Scale 2 Neuroticism 129 3.65 0.95 129 3.54 0.94 3 Neuroticism – Volatility 4 Neuroticism – Withdrawal 129 3.77 1.14 129 4.84 0.72 5 Extraversion 6 Extraversion – Assertiveness 129 4.68 0.87 129 5.01 0.87 7 Extraversion – Enthusiasm 8 Openness 129 5.20 0.64 129 5.16 0.74 9 Openness – Intellect 10 Openness - Aesthetic Openness 129 5.25 0.85 129 5.53 0.62 11 Agreeableness 12 Agreeableness – Compassion 129 5.91 0.84 129 5.15 0.71 13 Agreeableness – Politeness 14 Conscientiousness 129 4.52 0.71 129 4.34 0.85 15 Conscientiousness - Industriousness 16 Conscientiousness – Orderliness 129 4.69 0.92 Triarchic Model of Psychopathy Questionnaire 200 4.19 0.72 17 Boldness 18 Disinhibition 200 2.33 0.61 200 2.15 0.61 19 Meanness Theoretically related criteria 200 2.56 0.60 20 Common goods game 21 Dictator game 130 0.61 0.14 128 0.00 0.74 22 Risk taking 23 Emotional reactions to wins 130 0.00 1.00 130 0.00 1.00 24 Emotional reactions to losses 25 Self-reported money investment 125 1.77 1.12

α .89

1

2

3

.92 .82 .90 .85 .84 .81 .79 .77 .75 .83 .89 .69 .83 .82 .79

.16 .16 .13 .07 .32 -.20 -.15 -.06 -.17 -.62 -.52 -.48 .08 -.07 .19

.90 .93 -.10 -.09 -.07 -.07 -.28 .14 .00 .15 -.18 -.20 -.45 .11

.67 .08 .05 .08 -.06 -.27 .15 -.06 .17 -.32 -.20 -.36 .01

-.24 -.20 .82 -.19 .82 -.06 .37 -.24 .26 .11 .33 .06 .12 .11 .42 -.03 -.29 -.16 -.01 -.46 .19 .17 -.19

.36 .43 .39 .30 -.22 .11 -.52 .11 .27 -.07

.18 .03 .76 .24 .83 .43 .09 .59 .20 .05 -.08 -.12 .10 .05 .20 -.23 -.04

.80 .82 .82

.13 .35 .58

-.50 .51 -.05

-.32 .52 -.06

-.57 .62 .41 .09 -.03 -.14

.71 .13 .13

.31 .31 .03 -.11 -.35 -.21

.64 .91 .83 .86 .75 .47

.22 .32 .17 .15 .20 .14

-.07 .00 .02 -.04 .15 -.05

-.05 .03 .07 .09 .09 -.04

-.08 -.07 -.02 .02 -.03 .05 -.15 .22 .18 -.02 -.04 .06

.03 .17 .12 .23 .01 .08

-.15 -.15 -.14 -.04 -.04 .02 .14 .00 -.04 -.22 .01 .12

4

5

6

7

8

32

26 Personal goals with regard to money 27 Aggregated criteria

124 130

3.85 0.03

1.21 0.47

.39

.25 .48

-.12 -.03

-.15 .02

-.08 -.07

.17 .13

.29 .28

-.01 .14 -.07 -.05

33

Table 1 (continued)

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

9

10

11

12

13

14

15

16

17

18

19

20

.27 .01 .08 -.08 .27 .43 .03 .37 -.32 -.14 -.02 .15 .04 .08 -.12 .18 .22 .16

.12 .22 -.05 -.09 -.07 -.08 .14 .11 -.19 -.21 -.19 -.01 -.07 -.22 .03 .01 -.21

.84 .76 -.02 .01 -.04 -.23 -.32 -.78 -.24 -.24 -.13 -.13 -.07 -.13 -.24 -.37

.28 -.11 -.05 -.13 -.02 -.12 -.75 -.31 -.21 -.07 .00 .00 -.07 -.15 -.25

.09 .07 .07 -.38 -.41 -.48 -.07 -.19 -.14 -.24 -.13 -.15 -.24 -.35

.79 .83 .03 -.48 -.06 .06 .31 -.14 .07 -.02 .01 .18 .15

.30 .33 -.52 -.11 .06 .23 -.10 .12 -.11 .02 .13 .11

-.26 -.27 -.08 .01 .20 .50 .04 .07 .05 .26 .12 -.07 -.12 .20 .18 -.01 .22 .04 .07 -.09 .05 .00 .16 .06 .16 .23 -.04 .12 .26 .10

.24 .20 .13 .02 .07 .11 .14 .31

.30 .19 .21 .20 .18 .12 .13 -.02 -.03 -.05 .13 .56 .60

Note: Correlations of r≥.18 (N=129) or r≥.14 (N=200) are significant on p<.05.

21

22

23

24

25

26

.16 .03 -.02 -.04 .06 -.03 .06 .02 .05 .51 .49 .40

.03 .30

.38

34

Table 2: Incremental validity of the GR€€D scale over Big Five domains, Big Five Aspects and Psychopathy on overall greedy behavior Significant predictors

Big Five domains Step 1 Agreeableness Extraversion

β

R

R2

adj. R2 ΔR2

.44

.196

.163

.196

.52

.266

.53

ΔF

dfN

dfD

Δp

6.0

5

123

.000

.230

.070 11.6

1

122

.001

.282

.222

.282

4.6

10

118

.000

.58

.332

.269

.049

8.6

1

117

.004

.37

.136

.115

.136

6.6

3

126

.000

.52

.270

.247

.134 23.0

1

125

.000

-.29 .14

Step 2 Greed

Big Five aspects Step 1 Intellect (I) Openness (O) Compassion (A)

.18

.14 -.18 -.13

Step 2 Intellect (O) Openness (O) Greed

Psychopathy Step 1 Boldness Meanness

.14 -.13 .16

.15 .20

Step 2 Boldness Greed

.13 .23

Note: For the Big Five domains, Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness were entered in Step 1, and Greed was entered additionally as sixth predictor in Step 2. To save space, only predictors with significant beta-weight are depicted. Likewise, for

35

the Big Five Aspects, the ten aspects (see Table 2) were entered in Step 1, and for Psychopathy, boldness, disinhibition, and meanness were entered in Step 1.

36

Table 3: Incremental validity of Big Five domains, Big Five Aspects and Psychopathy over greed on overall greedy behavior Significant predictors

β

R

R2

adj. R2 ΔR2

.48

.227

.220

.52

.266

.58

.52

ΔF

dfN

dfD

Δp

.227 37.2

1

127

.000

.223

.039

1.3

5

122

.265

.332

.269

.105

1.8

10

117

.061

.270

.247

.038

2.2

3

125

.094

Step 1 Greed

.23

Big Five domains Step 2

Big Five aspects Step 2

Psychopathy Step 2 Note: Three separate multiple regressions were computed. For each multiple regression, greed was entered as the only predictor in Step 1 (only depicted once). In Step 2, either the Big Five domains, or the 10 Big Five aspects, or the three psychopathy dimensions were entered, respectively. Beta-weights for Step 2 can be seen from Table 2.

37

Highlights Dispositional greed is significantly correlated with psychopathy Dispositional greed predicts a range of behavioral indicators of greedy behavior. Dispositional greed has incremental validity over the Big Five domains and aspects