Sunday, January 24, 2021

Reasoning under Rawls' veil-of-ignorance mitigates self-serving bias in resource allocation during the COVID-19 crisis

Veil-of-ignorance reasoning mitigates self-serving bias in resource allocation during the COVID-19 crisis. Karen Huanga   Regan M. Bernhardb   Netta Barak-Correnc   Max H. Bazermand   Joshua D. Greenee. Judgment and Decision Making, Vol. 16, No. 1, January 2021, pp. 1-19. http://journal.sjdm.org/20/201205/jdm201205.html

Abstract: The COVID-19 crisis has forced healthcare professionals to make tragic decisions concerning which patients to save. Furthermore, The COVID-19 crisis has foregrounded the influence of self-serving bias in debates on how to allocate scarce resources. A utilitarian principle favors allocating scarce resources such as ventilators toward younger patients, as this is expected to save more years of life. Some view this as ageist, instead favoring age-neutral principles, such as “first come, first served”. Which approach is fairer? The “veil of ignorance” is a moral reasoning device designed to promote impartial decision-making by reducing decision-makers’ use of potentially biasing information about who will benefit most or least from the available options. Veil-of-ignorance reasoning was originally applied by philosophers and economists to foundational questions concerning the overall organization of society. Here we apply veil-of-ignorance reasoning to the COVID-19 ventilator dilemma, asking participants which policy they would prefer if they did not know whether they were younger or older. Two studies (pre-registered; online samples; Study 1, N=414; Study 2 replication, N=1,276) show that veil-of-ignorance reasoning shifts preferences toward saving younger patients. The effect on older participants is dramatic, reversing their opposition toward favoring the young, thereby eliminating self-serving bias. These findings provide guidance on how to remove self-serving biases to healthcare policymakers and frontline personnel charged with allocating scarce medical resources during times of crisis.

Keywords: fairness; self-serving bias; procedural justice; bioethics; COVID-19

4  General Discussion

In two pre-registered studies, we show that veil-of-ignorance reasoning favors allocating scarce medical resources to younger patients in response to the COVID-19 ventilator dilemma. Participants who first engaged in veil-of-ignorance reasoning, compared to participants who did not engage in veil-of-ignorance reasoning, were subsequently more likely to approve of a utilitarian policy that maximizes the number of life-years saved. These findings, predicted based on prior research (Huang, Greene & Bazerman, 2019), make three further contributions.

First, and most straightforwardly, these results apply directly to an ongoing crisis in which competing claims to fairness must be resolved. While the ventilator shortage in the developed world is currently less acute than many feared, it is likely that the COVID-19 crisis will continue to generate moral dilemmas of a similar form. These may be due to limited resources of other kinds such as medical personnel (Bernstein, 2020), the further spread of the disease in the developing world (Woodyatt, 2020), or structurally similar dilemmas arising from the distribution of vaccines (Emanuel, 2020b; Sun, 2020b; Ahuja, 2020). Moreover, it is likely that bioethical dilemmas of this general form will arise in future public health crises. The present research indicates that VOI reasoning can be a useful tool, grounded in a principle of impartiality, for decision-makers confronting difficult decisions during such crises.

Second, the present results underscore the power of VOI reasoning to eliminate self-serving bias. Self-serving bias is pervasive, and few interventions have been shown to effectively mitigate it. We demonstrate an effective intervention to mitigate self-serving bias in moral dilemmas. In Study 2, few older participants (33%) in the control condition favored prioritizing younger patients. But after engaging in veil-of-ignorance reasoning, most older participants (62%) favored doing so, just like younger participants. Indeed, the VOI manipulation completely eliminated self-serving bias among older participants, despite a sizable effect in the control condition.

Third, the present results demonstrate that VOI reasoning can be applied not only to dilemmas varying numbers of lives saved (Huang, Greene & Bazerman, 2019), but also to dilemmas varying numbers of life-years saved. As noted previously, this is important for bioethical decision-making, in which QALYs are commonly – but controversially – regarded as a legitimate factor in the allocation of medical resources (Cropper, Aydede & Portney, 1994; Johannesson & Johansson, 1997; Rodriguez & Pinto, 2000; Busschbach, Hessing & Charro, 1993; Tsuchiya, Dolan & Shaw, 2003; Lewis & Charny, 1989). Likewise, age may also prove to be an important and contentious factor for decisions involving new technologies, such as AVs (Awad et. al., 2018), which may access information about age in new ways. Of course, the “quality” in QALYs depends on who makes those judgments, for what purposes, and under what circumstances (e.g., Ubel, Loewenstein & Jepson, 2003; Loewenstein & Ubel, 2008; Ne’eman, 2020).

The present experiments use a simple control condition, as in Experiments 1–3 of Huang, Greene and Bazerman (2019). In that prior work, Experiments 4–7 employed more sophisticated controls aimed at distinguishing the distinctive effects of veil-of-ignorance reasoning from component factors such as perspective taking, numerical reasoning, and anchoring. That work showed that the veil-of-ignorance effect depends critically on assigning probabilities that align with principles of impartiality. Here we employ a simple control because our aim is to assess the net effect of veil-of-ignorance reasoning, not to distinguish it from its components. For present purposes, we assume that the mechanisms behind the present results are comparable to those responsible for our prior results, which were the bases for our pre-registered hypotheses.

The empirical findings, of course, cannot provide definite answers for the normative questions raised by this dilemma. Nevertheless, healthcare professionals confronting distributional dilemmas must adjudicate between competing claims of fairness in the absence of definitive answers. Our starting point is neither that policies should favor the young over the old, nor that physicians should generalize freely from our findings to prioritize patients based on specific features such as identity, ability, or socioeconomic status (Ne’eman, 2020). Rather, we show that veil-of-ignorance reasoning could provide a widely respected and transparent standard for adjudicating claims of fairness. This procedure will result in different policies — some of those policies may favor the young, while other policies may favor others — depending on the specific context and circumstances of the dilemma involved. Insofar as one respects the veil-of-ignorance standard for impartiality, our findings provide concrete guidance on how to remove self-serving biases from decisions made by policy-makers and front-line professionals charged with allocating scarce resources during this crisis, and others that may follow.

Those of higher agreeableness, women and the old see time flowing speedier

Age, Personal Characteristics, and the Speed of Psychological Time. Audrey-Anne Gagnon-Harvey, Jamie McArthur, Émie Tétreault, Daniel Fortin-Guichard, and Simon Grondin. Timing & Time Perception, Jan 19 2021. https://doi.org/10.1163/22134468-bja10024

Rolf Degen's take: (20) Rolf Degen on Twitter: "For women and for people with nice personality traits, time passes even more quickly as they age. https://t.co/0EC6pZdcsh https://t.co/sOVCxLUS88"

Abstract: Adults often report the impression that time seems to pass more and more quickly as they get older. The purpose of this study is to identify how individual characteristics relate to this impression of acceleration. To do so, 894 participants aged 15 to 97 completed a questionnaire that surveyed sociodemographic characteristics, impulsivity, anxiety, personality, and relation to time. They also indicated how fast different lapses of time seemed to have passed: yesterday, the past week, the past month, the past year, the past three years, the past five years, and the past 10 years. For each period, except for one year, adolescents found that time passes more slowly than participants from older groups (18–29 years, 30–59 years, and 60 years and over). A composite score for all these periods also indicates that female participants found that time passes more rapidly than males. However, a multiple linear regression analysis reveals that the variables that best predict the impression that time passes faster as we get older are high anxiety, the belief in the phenomenon of temporal compression, as well as conscientiousness and agreeableness personality traits, with other factors explaining little variance. These results add further weight to the impression that time seems to pass more quickly as we age, but also indicate that other variables than age play a critical role in explaining this impression.

Keywords: Speed of psychological time; time perception; individual differences; aging


An updated review of the efficacy of dolphin‐assisted therapy for autism and developmental disabilities... It seems it has no therapeutic value

Third time's the charm or three strikes you're out? An updated review of the efficacy of dolphin‐assisted therapy for autism and developmental disabilities. Lori Marino  Scott O. Lilienfeld. Journal of Clinical Psychology, January 22 2021. https://doi.org/10.1002/jclp.23110

Abstract

Context: Dolphin‐assisted therapy (DAT) is a popular form of animal‐assisted therapy for autism spectrum disorders and other psychological conditions.

Objective: In this review, our third, we analyze the most recent DAT studies in terms of construct and internal validity criteria to determine if there is empirical support for DAT.

Method: To ensure a systematic review, we searched for peer‐reviewed studies on DAT by submitting relevant search terms to Google Scholar from 2007 to 2020, conducted a further search of all DAT papers in several peer‐reviewed journals, and reviewed reference sections of DAT articles to ensure a thorough review of the literature between 2007 and the present.

Results: The DAT literature continues to be marked by several weaknesses in both internal and construct validity that preclude confident inferences regarding the intervention's efficacy.

Conclusion: There is still insufficient evidence that DAT has therapeutic value.


Saturday, January 23, 2021

East German unhappiness: Churchliness and satisfaction with democracy are important explanations of the unhappiness rooted in the mentality gap between West Germans and East Germans

An anatomy of East German unhappiness: The role of circumstances and mentality, 1990–2018. Philipp Biermann, Heinz Welsch. Journal of Economic Behavior & Organization, Volume 181, January 2021, Pages 1-18. https://doi.org/10.1016/j.jebo.2020.11.027

Rolf Degen's take: https://twitter.com/DegenRolf/status/1352962608777846784

Highlights

• We decompose the satisfaction gap between East and West Germany into objective circumstances and subjective mentality.

• We use about 419,000 observations from the German socio-economic Panel, 1990–2018.

• Circumstances and mentality contribute in the proportion 55: 45%.

• The mentality gap is driven by birth cohorts socialized under different political regimes.

• Churchliness and satisfaction with democracy mediate the mentality-related gap.

• Within-person preference/mentality changes occur as individuals adjust to politico-economic shocks.

Abstract: We decompose the satisfaction gap between East and West Germany into objective circumstances and subjective mentality, the latter capturing the way circumstances are being evaluated. Using the methodology proposed by Senik (2014) we find circumstances and mentality to contribute in the proportion 55: 45%. The mentality-related gap is driven by birth cohorts socialized under different political regimes – communist and liberal-capitalist – and disappears for the youngest cohort group. Results point towards churchliness and satisfaction with democracy being important explanations of the mentality gap. Within-person changes of the mentality gap occurred as aspirations or worries concerning politico-economic shocks were adjusted.

Keywords: GermanyHappinessLife satisfactionReunificationMentalityCommunism


US Data: There is little evidence that psychological distress is worsening over time; yet, treatment seeking has increased over the past 20 years

Changes in Mental Health and Treatment, 1997–2017. Amy L. Johnson. Journal of Health and Social Behavior, January 22, 2021. https://doi.org/10.1177/0022146520984136

Abstract: Mental health outcomes have shown dramatic changes over the past half-century, yet these trends are still underexplored. I utilize an age-period-cohort analysis of the National Health Interview Survey from 1997 to 2017 (N = 627,058) to disentangle trends in mental health outcomes in the United States over time. Specifically, I leverage the contrast between reported psychological distress and rates of mental health treatment to isolate which has changed, how, and for whom. There is little evidence that psychological distress is worsening over time. Yet, treatment seeking has increased over the past 20 years. The increase in treatment seeking is best modeled as a period effect, providing initial evidence that the historical context has influenced responses to mental health over time for Americans of all ages and birth cohorts. I conclude with potential mechanisms and implications for future mental health research.

Keywords: APC analysis, medicalization, mental health treatment, psychological distress, sociology of mental health


Women are significantly more often classified as conditionally cooperative than men, while men are more likely to be free riders

Gender and cooperative preferences. Nadja C. Furtner et al. Journal of Economic Behavior & Organization, Volume 181, January 2021, Pages 39-48. https://doi.org/10.1016/j.jebo.2020.11.030

Rolf Degen's take: https://twitter.com/DegenRolf/status/1352945444024946690

Abstract: Evidence of gender differences in cooperation in social dilemmas is inconclusive. This paper experimentally elicits unconditional contributions, a contribution vector (cooperative preferences), and beliefs about the level of others’ contributions in variants of the public goods game. We show that existing inconclusive results can be understood when controlling for beliefs and underlying cooperative preferences. Robustness checks of our original data from Germany, based on data from six countries around the world, confirm our main empirical results: Women are significantly more often classified as conditionally cooperative than men, while men are more likely to be free riders. Beliefs play an important role in shaping unconditional contributions, supporting the view that these are more malleable or sensitive to subtle cues in women than in men.

Keywords: Public goodsConditional cooperationGenderExperiment

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Men are more likely to be either perfectly selfish or perfectly selfless, whereas women are more likely to be in-between.

Those who experience schadenfreude about politics are more likely to express an intention to vote for candidates who promise to pass policies that “disproportionately harm” supporters of the opposing political party

Partisan Schadenfreude and the Demand for Candidate Cruelty. Steven W. Webster Adam N. Glynn Matthew P. Motta. January 6, 2021. http://stevenwwebster.com/research/schad.pdf

Rolf Degen's take: https://twitter.com/DegenRolf/status/1352862610534912003

Abstract: Americans are increasingly and durably divided along partisan lines. Yet, little is known about how partisan conflict influences extreme attitudes and behaviors. In this study, we examine whether Americans experience partisan schadenfreude—that is, taking “joy in the suffering” of partisan others—when bad things happen to those with whom they disagree politically. Analyzing attitudes on climate change, health care, taxation, and the coronavirus pandemic, we find that a sizable portion of the mass public engages in partisan schadenfreude and that these attitudes are most likely to be expressed by the most ideologically extreme Americans. Finally, we demonstrate that partisan schadenfreude is predictive of the demand for candidate cruelty: those who experience schadenfreude about politics are more likely to express an intention to vote for candidates who promise to pass policies that “disproportionately harm” supporters of the opposing political party. In sum, our results suggest that partisan schadenfreude is both widespread and consequential for American political behavior.


More adolescents with browsing-induced envy experienced negative effects on well-being than adolescents with no browsing-induced envy

Valkenburg, Patti M., Ine Beyens, J. Loes Pouwels, Irene I. van Driel, and Loes Keijsers. 2021. “Social Media Browsing and Adolescent Well-being: Challenging the “passive Social Media Use Hypothesis”” PsyArXiv. January 8. doi:10.31234/osf.io/gzu3y

Rolf Degen's take: https://twitter.com/DegenRolf/status/1352852621418233856

Abstract: A recurring hypothesis in the literature is that “passive” social media use (browsing) leads to negative effects on well-being. This preregistered study investigated a rival hypothesis, which states that the effects of browsing on well-being depend on person-specific susceptibilities to envy, inspiration, and enjoyment. We conducted a three-week experience sampling study among 353 adolescents (13-15 years, 126 assessments per adolescent). Using a novel, N=1 method of analysis, we found sizeable heterogeneity in the associations of browsing with envy, inspiration, and enjoyment (e.g., for envy ranging from β = -.44 to β = +.71). The passivity hypothesis was confirmed for 20% of adolescents and rejected for 80%. More adolescents with browsing-induced envy experienced negative effects on well-being (25%) than adolescents with no browsing-induced envy (13%). Conversely, more adolescents with browsing-induced enjoyment experienced positive effects on well-being (47%) than adolescents with no browsing-induced enjoyment (9%).




Experienced well-being rises with income, even above $75,000 per year

Experienced well-being rises with income, even above $75,000 per year. Matthew A. Killingsworth. Proceedings of the National Academy of Sciences, January 26, 2021 118 (4) e2016976118; https://doi.org/10.1073/pnas.2016976118

Significance: Past research has found that experienced well-being does not increase above incomes of $75,000/y. This finding has been the focus of substantial attention from researchers and the general public, yet is based on a dataset with a measure of experienced well-being that may or may not be indicative of actual emotional experience (retrospective, dichotomous reports). Here, over one million real-time reports of experienced well-being from a large US sample show evidence that experienced well-being rises linearly with log income, with an equally steep slope above $80,000 as below it. This suggests that higher incomes may still have potential to improve people’s day-to-day well-being, rather than having already reached a plateau for many people in wealthy countries.

Abstract: What is the relationship between money and well-being? Research distinguishes between two forms of well-being: people’s feelings during the moments of life (experienced well-being) and people’s evaluation of their lives when they pause and reflect (evaluative well-being). Drawing on 1,725,994 experience-sampling reports from 33,391 employed US adults, the present results show that both experienced and evaluative well-being increased linearly with log(income), with an equally steep slope for higher earners as for lower earners. There was no evidence for an experienced well-being plateau above $75,000/y, contrary to some influential past research. There was also no evidence of an income threshold at which experienced and evaluative well-being diverged, suggesting that higher incomes are associated with both feeling better day-to-day and being more satisfied with life overall.

Keywords: well-beinghappinessincomesatiationexperience sampling


One way to assess the extent to which results from the current sample are generalizable is to assess the degree to which the current sample of people “behave like” a representative sample in terms of key variables that are shared across the current study and previous studies of representative samples. One such variable is evaluative well-being, which can be effectively measured without experience sampling and whose relationship with income has been widely studied in representative samples. Results from representative samples in the United States and around the world generally find that evaluative well-being rises approximately linearly with log(income), without a plateau (10). The 2010 study finding a plateau in experienced well-being likewise found that evaluative well-being rose linearly with log(income), without a plateau (11). In the current study, evaluative well-being rose linearly with log(income), without a plateau (Fig. 1 and SI Appendix, Fig. S1), following the same trajectory that has been repeatedly observed in representative samples [although see one recent exception (12)]. This suggests that the general form of the relationship between well-being and income found here matches the population as a whole, and offers a reason to expect results for experienced well-being to generalize as well. Additionally, while the sample was not recruited with the intent of being representative, the actual distribution of incomes values is a close match to the US census distribution (SI Appendix, Table S8). Finally, after controlling for other demographic variables, including age, gender, marriage, and education level, the relationship between income and experienced well-being remains statistically significant and with a majority of the effect intact, including when analyzed across all income levels, below and up to $80,000, and above $80,000 (all values of P < 0.00001; SI Appendix, Table S9). A concern that sample bias might explain the current results seems even less plausible after a close inspection of the relationship between well-being and income. If the sample just happened to include some unusually happy people with large incomes, there are many possible patterns of results that this could generate, most of which would be noisy patterns even if they did trend upward overall. The actual results from this study, however, show an almost perfectly linear relationship between well-being and log(income), as shown in Fig. 1 and SI Appendix, Fig. S1. Accordingly, if sample bias were the explanation for this study’s results, the sample would have to be biased in exactly the way necessary to produce the linear relationship that is observed between well-being and log(income). This is not strictly impossible, but it seems highly improbable.

Do the present data offer any insight into why income is correlated with well-being? The answer to this question is necessarily speculative, since the factors linking well-being to income are likely numerous, complex, and interrelated. One possibility is that people spend money to reduce suffering and increase enjoyment, and that marginal dollars are differentially deployed against these aims depending on one’s income. The difference between positive and negative feelings described above provides some evidence in favor of this: Compared to variation in incomes above $80,000, larger incomes below $80,000 had a stronger association with reduced negative feelings, consistent with the possibility that moving from low to moderate income might be especially useful in avoiding (or mitigating) causes of suffering. Perhaps low earners have many avoidable sources of suffering, but as one earns more, there are fewer sources of suffering whose avoidance can be purchased. In contrast, positive feelings rose more evenly across the entire income range, and even had a directionally steeper association with income above $80,000. Another possibility, not incompatible with the first, is that larger incomes give people more control over their lives. People’s sense of control, measured with the question “To what extent do you feel in control of your life?,” was able to account for 74% of the association between income and experienced well-being (b = 0.105 with no covariates vs. b = 0.027 with sense of control over one’s life as a covariate, in the same participants, Pmediation < 0.00001). Financial insecurity, measured with the question “Did you have trouble coping with regular bills during the last 15 days?,” also played a role and was able to account for 38% of the association between income and experienced well-being (Pmediation < 0.00001). Although higher incomes could hypothetically allow a person to “buy” more time and feel less rushed (22), time poverty, measured with the question, “Do you have too little time to do what you’re currently doing?,” actually increased with income (P < 0.00001). It was a small but significantly negative mediator of the association between income and experienced well-being (Pmediation < 0.00001), such that the association between income and experienced well-being was significantly steeper when time poverty was held constant.

There was also evidence that the strength of the association between income and experienced well-being was systematically larger for some people and smaller for others. The importance of money, measured with the question “To what extent is money important to you?,” was only modestly related to income (r = 0.12, P < 0.00001) yet had a sizable statistical interaction with income in predicting experienced well-being (P < 0.00001). Based on the size of the interaction term, results estimate that the association between income and experienced well-being was over four times as steep when comparing people 1 SD above vs. 1 SD below the mean in money importance (b+1SD = 0.149 vs. b−1SD = 0.035). Whether people who rate money as relatively unimportant simply do not care about money, have found that “the best things in life are free,” or have tried and failed to spend money to improve their lives is unclear, but this result shows that there is something systematic causing income to matter more for some people’s well-being than for others. The importance of money on its own was virtually unrelated to experienced well-being (r = 0.02, P = 0.06), so it was not better or worse overall to think money was important; instead, low earners were happier if they thought money was unimportant and high earners were happier if they thought money was important. A question that asked participants “To what extent do you think money is indicative of success in life?” similarly showed that the association between income and well-being was steeper for people who equated money and success (P < 0.00001). Unlike money importance, however, the more people equated money and success, the lower their experienced well-being was on average (P < 0.00001), and there did not appear to be any income level at which equating money and success was associated with greater experienced well-being. Detailed results for these and other mediators and moderators are available in SI Appendix, including SI Appendix, Tables S5 and S6.

When interpreting these results, it bears repeating that well-being rose approximately linearly with log(income), not raw income. This means that two households earning $20,000 and $60,000, respectively, would be expected to exhibit the same difference in well-being as two households earning $60,000 and $180,000, respectively. The logarithmic relationship implies that marginal dollars do matter less the more one earns, while proportional differences in income have a constant association with well-being regardless of income.

Taken together, the current results show that larger incomes were robustly associated with greater well-being. Contrary to past research, there was no evidence for a plateau around $75,000, with experienced well-being instead continuing to climb across the income range. There was also no income threshold at which experienced and evaluative well-being diverged; instead, higher incomes were associated with both feeling better moment-to-moment and being more satisfied with life overall. While there may be some point beyond which money loses its power to improve well-being, the current results suggest that point may lie higher than previously thought.

Having Children Speeds up the Subjective Passage of Lifetime in Parents

Having Children Speeds up the Subjective Passage of Lifetime in Parents. Marc Wittmann and Nathalie Mella. Timing & Time Perception, Jan 13 2021. https://doi.org/10.1163/22134468-bja10023

Abstract: A widely reproduced finding across numerous studies of different cultures is that adults perceive the most recent 10 years of their lives to have passed particularly fast, and that this perceived speed increases as they grow older. Potential explanatory factors for this effect are believed to be more routines in life as we age as well as an increase in time pressure during middle adult age, both factors that would lead to a reduced autobiographical memory load. Fewer contextual changes in life are known to cause the passage of time to be perceived as faster. Taking advantage of the database created for the study that first captured this age effect on subjective time (), we investigated the role that having children plays in the subjective speeding of time. Adults aged between 20 and 59 who had children reported that time over the last 10 years passed subjectively more quickly than adults of the same age group without children. Factors such as education or gender did not influence subjective time. A small correlation effect could be seen in the fact that parents with more children reported that time passed more quickly. Experienced time pressure was not a differentiating factor between the two groups, as time pressure was associated with a faster passage of time in all adults. Future systematic studies will have to reveal what factors on autobiographical memory and time might be accountable for this clear effect that raising children has on perceived time.

Keywords: Passage of time judgement (PTJ); ageing; routine; time pressure; retrospective time


I will defend your right to free speech, provided I agree with you: Users protest against a social network ban only when this affects an in‐group user; the effect is smaller when an in‐group aggressor targets a high warmth out‐group user

“I will defend your right to free speech, provided I agree with you”: How social media users react (or not) to online out‐group aggression. Paolo Antonetti  Benedetta Crisafulli. Psychology & Marketing, January 22 2021. https://doi.org/10.1002/mar.21447

Rolf Degen's take: https://twitter.com/DegenRolf/status/1352661538621022212

Abstract: Social networking sites (SNS) routinely ban aggressive users. Such bans are sometimes perceived as a limitation to the right to free speech. While research has examined SNS users' perceptions of online aggression, little is known about how observers make trade‐offs between free speech and the desire to punish aggression. By focusing on reactions to an SNS ban, this study explores under what circumstances users consider the protection of the right to free speech as more important than the suppression of aggression. We propose a model of moderated mediation that explains under what circumstances online aggression increases the acceptance of a ban. When posts display aggression, the ban is less likely to be perceived as violating free speech and as unfair. Consequently, aggression reduces the likelihood that users will protest through negative word of mouth. Moreover, users protest against an SNS ban only when this affects an in‐group user (rather than an out‐group user). This in‐group bias, however, diminishes when an in‐group aggressor targets a high warmth out‐group user. The study raises managerial implications for the effective management of aggressive interactions on SNS and for the persuasive communication of a decision to ban a user engaging in aggressive behavior.



Friday, January 22, 2021

Preferences for pink & blue were tested in children aged 4–11 years in three small‐scale societies; pairing of female & ping seems a cultural phenomenon & is not driven by an essential preference for pink in girls

Cultural Components of Sex Differences in Color Preference. Jac T. M. Davis  Ellen Robertson  Sheina Lew‐Levy  Karri Neldner  Rohan Kapitany  Mark Nielsen  Melissa Hines. Child Development, January 21 2021. https://doi.org/10.1111/cdev.13528

Abstract: Preferences for pink and blue were tested in children aged 4–11 years in three small‐scale societies: Shipibo villages in the Peruvian Amazon, kastom villages in the highlands of Tanna Island, Vanuatu, and BaYaka foragers in the northern Republic of Congo; and compared to children from an Australian global city (total N = 232). No sex differences were found in preference for pink in any of the three societies not influenced by global culture (ds − 0.31–0.23), in contrast to a female preference for pink in the global city (d = 1.24). Results suggest that the pairing of female and pink is a cultural phenomenon and is not driven by an essential preference for pink in girls.

3 Discussion

We found no significant differences between boys’ and girls’ preference for pink in three small‐scale societies in Peru, Vanuatu, and the northern Congo. We found that girls liked pink more than boys did in a global city, confirming earlier research (Jonauskaite et al., 2019; Mohebbi, 2014; Weisgram et al., 2014; Yeung & Wong, 2018). These results support theories that link color preferences to individual experience (Palmer & Schloss, 2010) and gender cognitions (Bem, 1981; Carter & Levy, 1988; Liben & Bigler, 2002; Martin & Halverson, 1981). That is, culture, not inherent biological dispositions, influences the gender difference in children’s preference for pink.

Our findings contradict essentialist positions that pink is linked to female gender through neural color processing or through evolved preferences linked to foraging or mate choices (Alexander, 2003; Ellis & Ficek, 2001; Hurlbert & Owen, 2015). Supporting our findings, other research indicates that children are not born with sex differences in their color preferences, and that infants show no sex differences in preference for pink until they reach at least 2.5 years of age (Franklin, Gibbons, Chittenden, Alvarez, & Taylor, 2012; Jadva et al., 2010; LoBue & DeLoache, 2011; Wong & Hines, 2015; Zemach et al., 2007). Additionally, some studies of adults in societies with limited access to global culture have found no female preference for pink (Groyecka et al., 2019; Sorokowski et al., 2014), although, as noted before, the female preference for pink over blue may be characteristic of children, rather than adults. Thus, our findings provide additional evidence that the pairing of female and pink is a cultural phenomenon and is not innate.

Results suggest that color preferences are the behavioral expression of a complex interaction between underlying biology and cultural context. Genetic, hormonal, and neural indications may predispose children to display gendered behaviors and preferences, such as color preferences (Arnold, 2009; De Vries & Simerly, 2002; Hines, 2010), but the specific expression of these preferences, such as a female preference for pink, may be learned from cultural setting and individual experience (Bandura, 2002; Carter & Levy, 1988; Martin & Ruble, 2004; Palmer & Schloss, 2010). Children in all cultures are exposed to gender role information that influences their preferences and behavior, but not all cultures include information about the color pink. In our study, male and female roles were well defined and separate in the Vanuatu kastom culture (Douglas, 2002; Lindstrom, 2008), while BaYaka (Lewis, 2017) and Shipibo (Hern, 1992) villages were traditionally egalitarian for men and women, although still with typical male and female activities (Ember & Ember, 2003). However, pink was not used in these societies as a marker for female gender. In contrast, in many industrialized settings, boys and girls grow up surrounded by gender color‐coding in marketing, toys, clothing, room decorations, and online (Auster & Mansbach, 2012; Black, Tomlinson, & Korobkova, 2016; Cunningham & Macrae, 2011; Koller, 2008; LoBue & DeLoache, 2011; Pomerleau et al., 1990; Weisgram et al., 2014). Social and cognitive theories would predict that children absorb and integrate this gender color‐coding with a wealth of other gender role information that influences them to show gender differences in color preferences. Indeed, our results suggest that it is cultural norms that influence children’s adoption of gendered preferences and behaviors, such as a female preference for pink.

The specific patterns of color preference seen in our study further suggest that global culture, as well as influencing girls to prefer pink, may influence boys to avoid it. We found that in three small‐scale societies, boys and girls were equally likely to choose a pink option over a blue one. But we found that, like boys in other large industrialized cities (Chiu et al., 2006; Jonauskaite et al., 2019; Mohebbi, 2014; Weisgram et al., 2014; Zentner, 2001), in a large Australian city, boys avoided pink options. This finding supports previous reports that children avoid culturally defined opposite‐sex behaviors (Golombok et al., 2008; Ruble, Martin, & Berenbaum, 2007). Previous research additionally finds that boys increasingly avoid pink choices with age (LoBue & DeLoache, 2011; Wong & Hines, 2015), and this pattern appeared in the boys from our City sample but not in any small‐scale samples, supporting the view that culture may influence boys to avoid girl‐type activities in general and pink specifically. Thus, our findings, in combination with previous research, suggest that the pairing of pink with female gender in global culture might influence boys to avoid options that are colored pink.

It is important to address the cultural bias of color‐coding items for boys and girls. Multiple researchers have suggested that gender‐coding toys by color may affect child development (Martin & Halverson, 1981; Weisgram et al., 2014; Wong & Hines, 2015; Yeung & Wong, 2018). For example, differences in boys’ and girls’ play with toys, that are usually color coded, have been hypothesized to cause sex differences in adult social and spatial skills (Auster & Mansbach, 2012; Martin & Halverson, 1981; Pomerleau et al., 1990). Additionally, cross‐cultural research suggests that sex differences in adult social and spatial skills may also relate to culture (Henrich, Heine, & Norenzayan, 2010; Henrich et al., 2012; Trumble, Gaulin, Dunbar, Kaplan, & Gurven, 2016; Vashro & Cashdan, 2015). Together, this evidence suggests that color‐coding items for boys and girls are not only unnecessary, but may be constraining, as children use these cues to signal what they may be interested in, and what they may want to avoid.

Our study combined children’s responses to red and pink. This choice followed essentialist research that tends to group red with pink as “reddish hues” when explaining sex differences in color preference (Hurlbert & Owen, 2015). Yet, as described in non‐essentialist research (Javda et al., 2010), toys marketed to boys tend to be blue and red, and those marketed to girls tend to be pink, so there may be a cultural reason to consider pink separately from more general “reddish hues.” Our study’s results indicated that sex differences are likely related to the specific color pink, and not to reddish hues in general. Although essentialist viewpoints tend to group pink with red according to hue, our results suggest instead that pink is a separate color that functions as a cultural marker for female gender.

This research investigated children’s preference for pink in small‐scale societies with limited access to global culture via mass media, mass communication, and mass‐produced children’s toys. Results suggested that the pairing of female and pink is a cultural phenomenon and is not driven by an essential preference for pink in girls. Instead, children showed a diversity of preferences with culture. This diversity points to the complex flexibility of underlying biology to drive the development of sex‐typed color preferences in non‐essential, context‐appropriate ways.

If we recover around $3 billion/y from criminals, whilst imposing compliance costs of $300 billion, it is reasonable to ask if the real target of anti-money laundering laws is legitimate enterprises rather than criminal enterprises

Anti-money laundering: The world's least effective policy experiment? Together, we can fix it. Ronald F. Pol. Policy Design and Practice, Volume 3, 2020 - Issue 1, Pages 73-94, Feb 25 2020. https://doi.org/10.1080/25741292.2020.1725366

Abstract: This paper uses anti-money laundering as a case study to illustrate the benefits of cross-disciplinary engagement when major policymaking functions develop separately from public policy design principles. It finds that the anti-money laundering policy intervention has less than 0.1 percent impact on criminal finances, compliance costs exceed recovered criminal funds more than a hundred times over, and banks, taxpayers and ordinary citizens are penalized more than criminal enterprises. The data are poorly validated and methodological inconsistencies rife, so findings cannot be definitive, but there is a huge gap between policy intent and results. The scale of the problem not addressed by “solutions” repeatedly “fixing” the same perceived issues suggest that blaming banks for not “properly” implementing anti-money laundering laws is a convenient fiction. Fundamental problems may lie instead with the design of the core policy prescription itself. With an important policymaking function operating largely as an independent silo of specialist knowledge, this paper suggests that active engagement with critical, diverse perspectives, and deeper connections between the anti-money laundering movement and other disciplines (notably, policy effectiveness, outcomes and evaluation principles of public policy) should contribute to better results.

Keywords: Public policyevaluationpolicy success/failureglobal governanceanti-money launderingAML/CFT


6. How big is the problem?

This section extends a line of research showing that authorities intercept a tiny proportion of criminal funds, and introduces a wider perspective with available evidence about compliance costs and penalties.


6.1. Europe’s anti-money laundering effort “almost completely ineffective”

In response to multiple banking scandals, European policymakers asserted the need to “better address money-laundering…threats” and “contribute to promoting the integrity of the EU’s financial system” (European Commission 2018).

Like FATF’s “high-level objective”, such descriptions lack a specific, measurable policy objective. Nor did subsequent policy proposals reassess the fundamental policy objective or meaningfully connect with public policy principles. With the capacity to identify failure seemingly locked in a bubble of industry-specific knowledge, proclaimed “loopholes” and “shortcomings” would be “fixed”, apparently, by extending and more rigorously applying the current policy model. For instance, the European Commission’s explanation for a series of bank scandals asserted that financial institutions didn’t fully comply with anti-money laundering obligations, and claimed that national authorities failed adequately to cooperate or apply rules consistently (European Commission 2019a, 2019b, 2019c). The proposed “solution” therefore seeks to improve interagency co-operation, even though such explanations appear grounded on unverified, untested, and possibly false assumptions.

Even irrespective an apparent paucity of independent verification, the perceived lack of international coordination does not accord with the industry’s own evidence base. According to FATF ratings, international cooperation is the most highly rated of 11 “effectiveness” measures (Pol 2019a, 2020). The proposed “solution” also fails to countenance the possibility that, if banks complied fully with anti-money laundering obligations, the current policy intervention might still have almost zero impact on crime (Pol 2019c). Nor is that prospect untenable, with evidence suggesting astonishingly poor results (detailed later in this section).

Blaming banks and (typically, “other”) regulatory agencies may, therefore, be a convenient fiction. With complex regulations and billions of transactions, and the benefit of hindsight, fault can always be found (and may reinforce repeatedly looking for culpability in the same, easy to find, places), but the real issue may not be the extent of bank compliance or agency cooperation repeated in the echo-chamber of anti-money laundering orthodoxy. More fundamental problems may lie instead with the policy design itself, particularly in light of available data illustrating the scale of the problem persistently unaddressed by responses continually “fixing” the same perceived issues.

An extensive European study, for example, estimated “criminal revenues from [a] selected number of illicit markets (heroin, cocaine, cannabis, ecstasy, amphetamines, ITTP [illicit tobacco trade], counterfeiting, MTIC [VAT] fraud and cargo theft)” of “at least” €110 billion annually (Europol 2016, 4; Savona and Riccardi 2015, 35). Described as “very conservative”, the study excluded “important illicit markets, such as [human] trafficking…[and] extortion, illegal gambling and other types of fraud” (Savona and Riccardi 2015, 35).

In terms of the impact on profit-motivated crime revealed by such studies, Europol says that authorities only confiscate about €1.2 billion of illicit funds annually (2016, 4). This suggests that the proportion of criminal funds recovered, termed the “success rate” of anti-money laundering efforts by the UN (UNODC 2011, 14, 119, 131), is just 1.1 percent (Europol 2016, 4, 11).

On its face, this is higher than the United Nations’ global success rate (0.2 percent) (UNODC 2011, 14, 119, 131). Those figures are not, however, directly comparable. The UN calculation involves an estimated $3.1 billion of criminal assets seized (2011, 119, 131), whereas Europol’s 1.1 percent is the proportion ultimately confiscated. The UN calculations also use amounts laundered as the denominator ($1.6 trillion) rather than total estimated criminal proceeds ($2.1 trillion in 2009) (UNODC 2011, 5, 7, 119, 131). Adjusting for consistency, illicit funds seized globally as a proportion of criminal proceeds ($3.1 billion/$2.1 trillion) is 0.15 percent. If as Europol reports (2016, 4, 11) about half the amount seized is ultimately confiscated, the equivalent UN “success rate” as the proportion of total proceeds of crime confiscated ($1.55 billion/$2.1 trillion) is 0.07 percent. In any event, the European confiscation rate appears higher, at 1.1 percent.

But, if “important” criminal activities excluded from Europe’s “very conservative” €110 billion estimate generate “only” another €10 billion, Europe’s success rate falls below one percent. Moreover, some of those uncounted markets are very profitable, which means that criminal revenues may be considerably higher, and the “real” success rate lower. For example, noting that “investment fraud schemes generate huge profits”, Europol (2017, 42) reported an investigation revealing fraud profits for one organized crime group up to €3 billion. In another illicit market outside the study, the International Labor Office estimated annual returns from forced labor and sex exploitation at $150.2 billion globally (€114.2 billion), with $46.9 billion (€35.6 billion) from Europe and other developed countries (ILO 2014, 13; Savona and Riccardi 2015, 57).


These reports suggest that European criminal revenues may be substantially higher than €110 billion, and the 1.1 percent success rate correspondingly lower. Nonetheless, at some undetermined fraction of one percent (Pol 2018b, 296):

…the proportion of criminal earnings seized by authorities does not even remotely approach tax rates commonly applied to legitimate businesses. At less than one percent, the disruption of criminal funds hardly constitutes a rounding error in the accounts of profit-motivated criminal enterprises. In terms of the capacity materially and substantially to disrupt criminal finances and the manifold harms caused by serious profit-motivated crime, current money laundering controls appear almost completely ineffective.

The “success rate” of Europe’s anti-money laundering effort is puny. Likewise, globally.


6.2. Global efforts no better

Based on 2009 data, the UN, with US State Department assistance, calculated the global success rate of money laundering controls at just 0.2 percent (UNODC 2011, 14, 119, 131), but, as noted above, the confiscation rate might be 0.07 percent. In other words, despite ubiquitous money laundering controls, criminals retain up to 99.93 percent of criminal proceeds.

With “mythical” numbers (Reuter 1984; Singer 1971) unsupported by “any empirical…proof” (Savona and Riccardi 2015, 34) often used as institutional “problem amplifiers” by agencies seeking power and resources (Levi 2016, 392), “official” estimates of criminal revenues vary widely in scale and reliability. But, according to the UN, an estimated $2.1 trillion in criminal proceeds was generated in 2009 (3.6 percent of global GDP) (UNODC 2011, 5, 127). At the same rate, global GDP of US$85.8 trillion suggests US$3.09 trillion illicit funds in 2018, illustrated in Figure 2.

Figure 2. UN-estimated global proceeds of crime, 3.6% GDP.

The UN estimated that authorities intercepted $3.1 billion of illicit funds in 2009, with more than 80 percent seized in North America (UNODC 2011, 119, 131). (The reference to North America seems to relate mostly to the United States. In 2009/2010, Canadian authorities successfully confiscated just C$59 million (FATF & APG 2016, 56), less than two percent of the total).


More recently, in 2017, total net deposits of $2.15 billion were paid into the US Treasury and Justice Department asset forfeiture funds (Department of Justice 2017; US Treasury 2017). If US asset forfeitures (sometimes called confiscations) represent 80 percent of the total, this suggests global forfeitures of $2.7 billion in 2017. At first glance, this appears lower than the UN’s $3.1 billion estimate for 2009. But the 2017 figure represents amounts confiscated, while the UN’s 2009 number represents sums seized, so a comparable 2009 estimation of global confiscations is $1.55 billion, using Europol’s empirical findings of a 50 percent difference between amounts initially seized and ultimately confiscated (Europol 2016, 4, 11). The $2.7 billion estimate therefore suggests a 74 percent increase in criminal asset confiscations between 2009 and 2017.

However, amounts seized and forfeited are highly variable, illustrated in Figure 3 (Department of Justice 2019b; US Treasury 2019). An alternative measure might use the average or median confiscated over an extended period, for example, $3.6 billion or $2.8 billion, respectively, over the period shown, but neither is necessarily more accurate than 2017 data alone, because earlier years include “unusually large” cases (Department of Justice 2019a, 2).

Figure 3. US asset forfeitures.

For some purposes, some cases, like settlements involving JP/Madoff ($3.9 billion), Poker Stars ($1.4 billion), Toyota ($1.2 billion), General Motors ($900 million) and Google ($500 million), might be excluded as dissimilar from “normal” crime. The impact of such spikes is significant, with “regular deposits” from criminal forfeitures “remarkably consistent”, at around $1 billion annually (Department of Justice 2019a, 2).

Nonetheless, if US forfeitures represent 80 percent of the total, average confiscations of $3.6 billion suggest global estimates around $4.5 billion. Or, using 2017 data for consistency (which, coincidentally, more closely accords with “regular” confiscations), suggests global forfeitures around $2.7 billion.

But whether global authorities successfully confiscated $4.5 billion or $2.7 billion of perhaps $2.9 trillion illicit funds generated in 2017, the success rate is trivial, at 0.16 or 0.09 percent, respectively.


6.3. Imperfect data, but stark clarity of policy effectiveness gap

These figures are far from definitive. Most estimates lack methodological clarity, few are validated, and there are obvious gaps. For example, simple extrapolation for global estimates ignores nuanced reality in more than 190 countries. Even in the few with available data, criminal asset forfeitures often use net amounts paid to the relevant government fund, excluding allocations to administrative costs. Confiscations from agencies not recorded in centralized databases may be missing. Authorities in many countries also frequently claim increasing forfeitures, but such claims are highly date-range specific. For example, Canadian forfeitures rose in each of the four years since 2009, then fell in two subsequent years. The total amount confiscated in 2014/2015 (C$77 million) was barely C$18 million more than 2009/2010 (FATF & APG 2016, 56). Much the same appears to have occurred in the United States between 2009 and 2017, illustrated in Figure 3. It is also difficult to reconcile European and global data. “Eighty percent” of forfeitures originating from North America do not match €1.2 billion from Europe.

Nonetheless, although detailed research is needed to validate such claims, it seems a reasonable hypothesis that forfeitures increased since 2009, at least on a rolling average basis. This paper generally uses a broad estimate of $3 billion confiscated globally.

Overall, data are poorly substantiated, so the apparent precision of subtle distinctions is illusory. Likewise, the seemingly cavalier rounding from $2.7 billion to $3 billion in the preceding paragraph. The real issue, however, is not the apparent precision of inherently imprecise estimates, but the “huge gap between the profits criminals [generate] and the amounts eventually seized and confiscated” (Europol 2016, 11).

Moreover, that gap is so large that imperfect illicit funds estimates have little or no effect on the proportion of criminal funds confiscated. Whether the “real” success rate is 0.1 percent, or ten times as much, it would be challenging to claim success in the detection and prevention of serious crime if up to 99.9 percent or “only” 99 percent of illicit funds remain in criminal hands; enabling, facilitating and rewarding the continued expansion of serious crime.

Anti-money laundering’s policy impact may be inconsequential, but policies also impose costs.


6.4. Burgeoning compliance cost

In the same year as the latest available asset forfeiture data noted above, the estimated annual cost of anti-money laundering compliance in four EU countries1 was $81.4 billion, according to LexisNexis (2017). Those countries represent 52.2 percent of European Union gross domestic product (GDP), according to the World Bank (2017). Simple GDP-based extrapolation suggests EU compliance costs of $156 billion (€144 billion).2

LexisNexis (2017, 2018a, 2018b) also examined compliance costs elsewhere. The estimated annual cost was $83.5 billion in five European countries,3 $25.3 billion in the United States, and $2.05 billion in South Africa, or $110.85 billion in the surveyed countries. According to World Bank data, those countries represent 36.5 percent of world GDP (2017). Again, simple extrapolation suggests global compliance costs in the order of $304 billion, or 0.38 percent GDP. [Some estimates are higher still. Thomson Reuters (2018, 4, 26) says that companies on average spend 3.1 percent of turnover combating financial crime, or $1.28 trillion globally].

Necessarily applying a broad brush, the current anti-money laundering policy prescription helps authorities intercept about $3 billion of an estimated $3 trillion in criminal funds generated annually (0.1 percent success rate), and costs banks and other businesses more than $300 billion in compliance costs, more than a hundred times the amounts recovered from criminals.

In Europe, the anti-money laundering movement apparently makes private businesses spend as much as €144 billion in compliance costs to help authorities confiscate up to €1.2 billion of more than €110 billion generated by criminals each year. This suggests a higher recovery rate, at 1.1 percent, but for reasons outlined above may be overstated, and offset by compliance costs 120 times the amount successfully recovered from criminals. (Bizarrely, by these estimates, compliance costs exceed total criminal funds).

Overall, estimated compliance costs are poorly validated, but whether they are $304 billion (based on LexisNexis research), closer to $1.28 trillion (per Thomson Reuters), or some other amount, the cost of compliance is high, and seems markedly to exceed amounts recovered from criminals.

Nevertheless, compliance cost estimates may yet be understated if they only include private sector operational costs. Public sector costs for the many policy, regulatory and enforcement agencies involved in anti-money laundering activities, and penalties for breach of anti-money laundering laws, add to the regime’s total cost.


6.5. Hidden costs of supranational and government agencies

The costs of approximately 80 international bodies and thousands of government agencies in 205 countries and jurisdictions with a role in anti-money laundering efforts are unknown. More precisely, costs information is available to each agency, but few seem to collate such data, despite being a crucial component of any rigorous cost-benefit analysis of the anti-money laundering experiment. Moreover, the value of illicit assets successfully recovered from criminals is also known by authorities in each jurisdiction. In any event, such data, notable for its perennial absence, would improve the accuracy of the inadequately substantiated estimates outlined above. Likewise, the costs of noncompliance.


6.6. Businesses and citizens penalized more than criminals

The combined value of anti-money laundering penalties in 2018 and 2019, mostly levied on banks, was $4.3 billion and $8.1 billion, respectively, according to Balani (2019; Burns 2019, 2020). Between 2002 and 2019, the combined value of 340 penalties was $34.7 billion, representing an average penalty of $102 million. Between 2002 and 2017, the average was $88 million.

By 2018 and 2019, average penalties rose considerably, to $147 million and $140 million, respectively. The researchers recorded more countries penalizing more businesses (“in 2019, penalties were handed out by 14 countries, compared to just three a decade ago in 2009”) and more penalties over a billion dollars, including two in 2019 alone. They attributed an “increased focus” on penalizing breaches of money laundering controls to “the severity with which it is viewed at a global level”, which they considered unsurprising “given [money laundering’s] negative economic and societal repercussions” (Burns 2020).

However, these findings appear consistent with other possibilities, for example, that “banks are a much easier target for regulators” (Pol 2019c) than criminals. If authorities recover around $3 billion per annum from criminals, whilst imposing compliance costs of $300 billion and penalizing businesses another $8 billion a year, it is reasonable to ask if the real target of anti-money laundering laws is legitimate enterprises rather than criminal enterprises.

It is reasonable also to ask whether ordinary citizens are harmed more than banks and criminals, at least financially, by laws ostensibly aimed at financial crime. After all, banks typically pass their costs on to shareholders and customers - in lower dividends, higher fees, lower interest rates for savers, and higher rates for borrowers. Moreover, taxpayers pay the costs of government, including scores of international agencies involved in the anti-money laundering agenda, and up to several dozen government agencies in each of 205 countries and jurisdictions. Individuals, communities, economies, and society also suffer the economic and social harms from serious crime.

These findings raise serious questions about the efficiency and effectiveness of the current policy model, but scholars rued that designers tasked with updating the anti-money laundering framework were told “not to pay attention to the costs of the system, direct or indirect.” Instead, it is simply “taken for granted that actions taken against money laundering and especially the financing of terrorism will have a positive welfare impact, both gross and net of costs” (Levi et al. 2018, 309). Likewise, the oft-proclaimed benefits of anti-money laundering efforts are seldom quantified or tested robustly, despite researchers “howl[ing] into the wind their warnings of unintended consequences, of law and regulations with costs far exceeding ephemeral benefits…only to be totally ignored” (Cochrane 2014, 2).

However, recognition that costs outweigh benefits, or that core objectives are not met, remains a pre-condition to start reshaping the policy paradigm for better outcomes. Change starts with acknowledging reality. In that regard, verifiable cost and recoveries information, readily available (albeit seldom produced), remains critically important if a rigorous “official” assessment of anti-money laundering effectiveness is ever undertaken. (Benefits attributable to anti-money laundering efforts, including social and economic benefits from less crime, should also be included).

In the meantime, irrespective of costs, the success rate of money laundering controls may be even less than noted above.


7. Whither policy effectiveness?

The trivial confiscation of 0.1 percent of criminal funds potentially overstates the policy impact of money laundering controls. That’s because criminal asset forfeitures often occur independently of anti-money laundering obligations. For example, confiscations frequently result from traditional policing methods such as drug trafficking investigations uncovering assets purchased with criminal funds. Empirical research in New Zealand found that conventional methods triggered 80 percent of confiscations involving lawyers, accountants and real estate agents facilitating illicit real estate transactions. Only 20 percent started with anti-money laundering’s key mechanism, legitimate businesses reporting suspicious transactions (Pol 2018b, 302).

Different percentages likely apply in different circumstances, but the success rate of money laundering controls is unrealistically high when it implicitly attributes all criminal asset confiscations to anti-money laundering efforts. For example, if 20 percent of forfeitures are attributable to money laundering controls, the global success rate may be one-fifth of 0.1 percent i.e. 0.02 percent, or one-fiftieth of one percent, illustrated in Table 1. Empirical research is necessary to identify appropriate proportions in relevant markets. In the meantime, Table 1 suggests a mid-point for indicative purposes, indicating that the global success rate of money laundering controls may be in the order of 0.05 percent (one-twentieth of one percent).


Table 1 Anti-money laundering: effective policies?


Notwithstanding its dismal success rate, the modern anti-money laundering model also has many success stories. In policy terms, progress on both the process and political dimensions in Figure 1 supports reexamining policy design to help transform failure on the remaining program dimension toward comprehensive success. In practical terms, criminal enterprises no longer holding $3 billion of illicit assets confiscated each year, and leaders less readily able to recapitalize illegal endeavors, are profoundly affected. Likewise, criminal activities are frequently disrupted and thwarted. This can be difficult to measure but may help lift success rates noted above.

In the meantime, however, if the impact of three decades of money laundering controls barely registers as a rounding error in criminal accounts and “Criminals, Inc” keep up to 99.95 percent of the earnings from misery, and reasonable prospects for better outcomes remain persistently unexplored, the harsh reality is that the current policy prescription inadvertently protects, supports and enables much of the serious profit-motivated crime that it seeks to counter. In any event, the anti-money laundering experiment remains a viable candidate for the title of least effective policy initiative, ever, anywhere (Cassara 2017, 2).

Moreover, if the modern anti-money laundering paradigm is characterized by a self-reinforcing continuous loop of policy failure, with “solutions” repeatedly “doing more of the same” producing much the same results, and with powerful stakeholder incentives maintaining the status-quo, it will be difficult to recalibrate for better outcomes. But not impossible. Key issues enabling policy success are commonplace in policy science, and the questions simple. What’s the “right” policy objective? Is there a robust, validated evidence-base to measure success? If not, what data are needed? Are policy objectives being met? If not, what policy design changes would help recalibrate for better outcomes? This paper suggests that active engagement with critical, diverse perspectives, and deeper connections with the rigor of policy science, would help contribute to better results.


Thursday, January 21, 2021

Moral condemnation of recreational drug use seems related to a genetic trait in order to make more difficult a sexual strategy of being more into casual sex vs being more into a committed relationship

Karinen, Annika, Laura Wesseldijk, Patrick Jern, and Joshua M. Tybur. 2021. “Sex, Drugs, and Genes: Illuminating the Moral Condemnation of Recreational Drugs.” PsyArXiv. January 21. doi:10.31234/osf.io/zj4wu

Abstract: Over the past decade, evolutionary psychologists have proposed that many moral stances function to promote self-interests, and behavioral geneticists have demonstrated that many moral stances have genetic bases. We integrate these perspectives by examining how moral condemnation of recreational drug use relates to sexual strategy (i.e., being more versus less open to sex outside of a committed relationship) in a sample of Finnish twins and siblings (N = 8,118). Twin modeling suggested that genetic factors accounted for 53%, 46%, and 41% of the variance in drug condemnation, sociosexuality, and sexual disgust sensitivity, respectively. Further, approximately 75% of the phenotypic covariance between drug condemnation and sexual strategy was accounted for by genes, and there was substantial overlap in the genetic effects underlying both drug condemnation and sexual strategy (rg = .41). Results suggest that some moral sentiments are calibrated to promote strategic sexual interests, which arise partially via genetic factors.