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.

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.

Self-esteem's importance is higher in women (vs men); and there are cultural differences, it is higher in Euro-Canadians (vs Asian-Canadians)

Naïve beliefs about self-esteem's importance. Thomas I.Vaughan-Johnston, Jill A.Jacobson. Personality and Individual Differences, Volume 173, April 2021, 110635. https://doi.org/10.1016/j.paid.2021.110635

Highlights

• Beliefs about self-esteem's importance are measured via SEI scale.

• SEI shows stability across weeks to months.

• SEI is higher in women (vs men); Euro-Canadians (vs Asian-Canadians).

• SEI relates to more contingent self-worth and extrinsic motivation.

• SEI related to sensitivity to social acceptance vs rejection.

Abstract: The importance of having high self-esteem is frequently debated in academic and public domains, and believing that high self-esteem causes good outcomes has recently been introduced as an impactful individual difference variable. For example, naïve theories about self-esteem's causal influence (e.g., believing that high self-esteem protects one's health) is related to an increased pursuit of self-enhancement. However, several critical qualities of the self-esteem importance scale (Vaughan-Johnson & Jacobson, 2020) remain unexamined, and we explore these questions across four main and two supplementary studies (total N = 1997). Self-esteem importance beliefs were stable across time and distinct from other self and motivational constructs. Consistent with expectations derived from prior research and theory, we found cultural (European-Canadian vs. Asian-Canadian) and gender differences on self-esteem importance. Finally, we demonstrate that high scorers on the self-esteem importance scale anticipate heightened responses to rejection vs. acceptance scenarios. Thus, self-esteem importance beliefs are chronologically stable, are relatively independent from past self-related variables, reflect known group differences from past research, and are linked with an amplified sensitivity to social threat versus reward. These findings support key theoretical claims made about the self-esteem importance construct, and suggest likely unintended consequences of promoting self-esteem's consequentiality.

Keywords: Self-esteemImportanceNaïve theoriesSelf-enhancement

Religiosity is associated with a more feminine intelligence profile: Evidence from the National Longitudinal Study of Youth, 1979

Religiosity is associated with a more feminine intelligence profile: Evidence from the National Longitudinal Study of Youth, 1979. Edward Dutton, Gerhard Meisenberg. Personality and Individual Differences, Volume 173, April 2021, 110640. https://doi.org/10.1016/j.paid.2021.110640

Abstract: Many studies have found a small negative correlation between religiousness and intelligence measured by IQ tests, and many others have found that females are more religious than males. Still other studies have demonstrated that the IQ profile of females is different from that of males, with females tending to be higher than males in some abilities and lower in others. This raises the intriguing question of whether religiousness may be correlated with a more stereotypically female intelligence profile. We tested whether this was the case using the NLSY 79 (N = 12,686). The NLSY shows that religiousness, using the proxy of regular church attendance, is not only higher among females but is also associated with a female profile of abilities even among males (r = 0.92). We argue that this is potentially consistent with evidence that Autism Spectrum Disorder is negatively associated with religiosity.

Keywords: ReligionIntelligenceAutism spectrum disorderMale brainGender

Individuals avoid asking sensitive questions due to concerns about others’ discomfort and about impression management, overestimating the interpersonal costs of asking such questions (a forecasting error)

The (better than expected) consequences of asking sensitive questions. Einav Hart, Eric M. Van Epps, Maurice E. Schweitzer. Organizational Behavior and Human Decision Processes, Volume 162, January 2021, Pages 136-154. https://doi.org/10.1016/j.obhdp.2020.10.014

Ungated iteration, from 2019: Hart, Einav and VanEpps, Eric and Schweitzer, Maurice E., I Didn’t Want to Offend You: The Cost of Avoiding Sensitive Questions (June 24, 2019). SSRN. https://www.bipartisanalliance.com/2019/09/we-avoid-asking-sensitive-questions-we.html

Rolf Degen's take: https://twitter.com/DegenRolf/status/1352186061036904448

Highlights

• Individuals avoid asking sensitive questions in both face-to-face and computer-mediated conversations.

• Individuals avoid asking sensitive questions due to concerns about others’ discomfort and about impression management.

• Askers significantly overestimate the interpersonal costs of asking sensitive questions.

• Reticence to asking sensitive questions reflects conversational forecasting errors.

Abstract: Within a conversation, individuals balance competing objectives, such as the motive to gather information and the motive to create a favorable impression. Across five experimental studies (N = 1427), we show that individuals avoid asking sensitive questions because they believe that asking sensitive questions will make their conversational partners uncomfortable and cause them to form negative perceptions. We introduce the Communication Motives and Expectations Model and we demonstrate that the aversion to asking sensitive questions is often misguided. Question askers systematically overestimate the impression management and interpersonal costs of asking sensitive questions. In conversations with friends and with strangers and in both face-to-face and computer-mediated conversations, respondents formed similarly favorable impressions of conversational partners who asked sensitive questions (e.g., “How much is your salary?”) as they did of conversational partners who asked non-sensitive questions (e.g., “How do you get to work?”). We assert that individuals make a potentially costly mistake when they avoid asking sensitive questions, as they overestimate the interpersonal costs of asking sensitive questions.

Keywords: ConversationQuestionsStrategic information exchangesImpression managementCommunication Motives and Expectations Model

Placed in the correct configuration relative to a metal fork, a metal knife appears transparent, with some observers experiencing a bistable percept in which transparency alternates with reflective appearance

The Fork-and-Knife Illusion. Blaise Balas, Benjamin Balas. Perception, January 20, 2021. https://doi.org/10.1177/0301006620988847

Abstract: We describe a transparency illusion that can be observed with an ordinary metal knife and fork. Placed in the correct configuration relative to the fork, the metal knife appears transparent, with some observers experiencing a bistable percept in which transparency alternates with reflective appearance. The effect is related to other illusory percepts that follow from careful placement of mirrored surfaces, but to our knowledge, it is unique in that the key feature of the illusion is how the mirrored surface (in this case, the knife) is perceived rather than how a mirror induces altered perception of other objects and surfaces. We describe conditions that do and do not affect the strength of the illusion and point out its connections to previously reported phenomena.

Keywords: visual illusions, transparency, material perception

 

Trade in sex is legal in Denmark, but a majority of respondents hold negative attitudes towards it, women finding transactional sex less acceptable than men do

Predicting Attitudes Towards Transactional Sex: The Interactive Relationship Between Gender and Attitudes on Sexual Behaviour. Michael A. Hansen & Isabelle Johansson. Sexuality Research and Social Policy, Jan 20 2021. https://rd.springer.com/article/10.1007/s13178-020-00527-w

Abstract

Introduction: This article explores explanations for attitudes towards the acceptability of transactional sex. The sparse research investigating attitudes towards transactional sex uncovers a link between gender equality, or feminism, and a lack of support for the trade in sex. However, there are no research agendas that attempt to explain variance in attitudes towards transactional sex where support for gender equality is widespread throughout a population.

Methods: We estimate regression models utilizing the 2017 Danish Values Survey (Den Danske Værdiundersøgelse) in order to predict views on the acceptability of transactional sex.

Results: While the trade in sex is legal in Denmark, we find that a majority of respondents hold negative attitudes towards transactional sex, which conveys a lack of congruence between public opinion and policy. Further, gender is a powerful predictor of attitudes towards transactional sex, with women finding it less acceptable. In addition, the analysis uncovers that general attitudes towards sexual behaviour are the largest predictor of views on the acceptability of transactional sex. That being said, we find that men’s views on the acceptability of transactional sex are more of a function of their general attitudes towards sexual behaviour than they are for women.

Conclusions: The findings indicate that, unlike men, women appear to differentiate between their attitudes towards general sexual behaviour and their views on sexual behaviour that they may associate with negative societal implications.

Conclusion

In this study, we asked which are the influential factors on individual level attitudes towards the acceptability of transactional sex. At the beginning of this article, we argued that a better understanding of people’s attitudes towards the trade in sex is needed because the existing literature is limited. Another reason we pointed to for further research into this topic is that sex workers may face serious hardships as a result of negativity towards transactional sex. Moreover, we argued that a focus on individual level attitudes could assist in broadening the current debate regarding policies and how to best approach the sex trade and its related issues. Questions concerning policy are undoubtedly important ones, but so are questions about what shapes people’s attitudes towards transactional sex. By understanding what predicts individual level attitudes towards transactional sex, policy-makers and other key actors may be better equipped to address sex trade-related issues.

A nationally representative survey from Denmark inquiring about views on prostitution provided us with the possibility to explore attitudes in a country where it is legal to engage in transactional sex. Since the Danish population is quite ideologically homogenous (Holtug 2012), the case of Denmark made it possible to move beyond some of the explanations that scholars have provided when looking at divergent attitudes towards transactional sex, namely gender equality and traditional values. As our analysis demonstrates, there is a lack of variance in Denmark when exploring these explanations for differences in attitudes towards transactional sex. That being said, we were able to build on the findings of previous studies regarding gender (the one socio-demographic factor following a clear pattern in the literature) to look more closely at how gender interacts with attitudes towards general sexual behaviour. The results from Denmark indicate that diverging attitudes towards transactional sex may persist even when an increasing share of the population holds liberal attitudes and commits to gender equality. Other countries witnessing similar ideologically developments may want to consider this observation.

The findings that we present suggest that the majority of Danes (54%) hold negative attitudes towards the trade in sex. There is thus a lack of congruency between public opinion and policy in Denmark where it is legal to sell and pay for sexual services. Since negativity towards the sex trade may have adverse effects on sex workers’ lives, this incongruence is food for thought for anyone engaging in sex trade-related policy debates. That being said, in comparison with other Scandinavian countries, a larger proportion of Danes hold tolerant attitudes towards prostitution (EVS/WVS 2020). A useful next step would be to study the topic in a comparative context to see if further incongruences between public opinion and policy exist across Scandinavia.

We find that gender is the most important socio-demographic predictor of attitudes towards prostitution, with women finding it less acceptable than men. The most powerful attitudinal predictor is attitudes towards general sexual conduct. The interaction between gender and attitudes towards sexual behaviour is notable. On average, men who view non-committal sex as completely acceptable are twice as likely as their female counterparts to view prostitution as completely acceptable. The reason why women tend to hold more negative attitudes towards transactional may be because women are more prone to relate prostitution to negative societal implications, like the perpetuation of traditional gender roles and unequal power relations between men and women (Basow and Campanile 1990; Bernardo Ródenas 2001; Valor-Segura et al. 2011). Such associations may also explain why women are more likely to distinguish their attitudes towards general sexual behaviour from their attitudes towards transactional sex. Along the same line, the reason why men tend to be more positive towards transactional sex than women may be explained by the absence of negative associations ascribed to the trade in sex vis-à-vis men’s position in society. The fact that the sex trade largely caters to men may also play a role in accounting for this gender gap in attitudes.

While our findings contribute to gender theorizing, it would be fruitful to pursue further research into the gendered dynamics at play in determining individual level attitudes towards transactional sex in order to grasp their full make-up. One suggestion moving forward would be to pay close attention to how such attitudes interact with gender and attitudes towards other societal issues both nationally and cross-nationally, as attitudes towards transactional sex are likely to differ between countries. A second suggestion for future research into attitudes towards transactional sex is to include more nuanced survey questions in order to capture the complexity of the issue. A third suggestion is for qualitative studies to continue to deepen our understanding of the links between diversity of experiences, opinions and attitudes towards transactional sex, including those of people who do not conform to binary identity categories. 

We find that all analyzed dietary indices have a heritable component, suggesting that there is a genetic predisposition regulating what you eat

Genetic and Environmental Influences of Dietary Indices in a UK Female Twin Cohort. Olatz Mompeo et al. Twin Research and Human Genetics, January 18 2021. https://www.cambridge.org/core/journals/twin-research-and-human-genetics/article/abs/genetic-and-environmental-influences-of-dietary-indices-in-a-uk-female-twin-cohort/48632224BDF4C60E69FDE67F8E21A1C7

Abstract: A healthy diet is associated with the improvement or maintenance of health parameters, and several indices have been proposed to assess diet quality comprehensively. Twin studies have found that some specific foods, nutrients and food patterns have a heritable component; however, the heritability of overall dietary intake has not yet been estimated. Here, we compute heritability estimates of the nine most common dietary indices utilized in nutritional epidemiology. We analyzed 2590 female twins from TwinsUK (653 monozygotic [MZ] and 642 dizygotic [DZ] pairs) who completed a 131-item food frequency questionnaire (FFQ). Heritability estimates were computed using structural equation models (SEM) adjusting for body mass index (BMI), smoking status, Index of Multiple Deprivation (IMD), physical activity, menopausal status, energy and alcohol intake. The AE model was the best-fitting model for most of the analyzed dietary scores (seven out of nine), with heritability estimates ranging from 10.1% (95% CI [.02, .18]) for the Dietary Reference Values (DRV) to 42.7% (95% CI [.36, .49]) for the Alternative Healthy Eating Index (A-HEI). The ACE model was the best-fitting model for the Healthy Diet Indicator (HDI) and Healthy Eating Index 2010 (HEI-2010) with heritability estimates of 5.4% (95% CI [−.17, .28]) and 25.4% (95% CI [.05, .46]), respectively. Here, we find that all analyzed dietary indices have a heritable component, suggesting that there is a genetic predisposition regulating what you eat. Future studies should explore genes underlying dietary indices to further understand the genetic disposition toward diet-related health parameters.

Keywords: Dietary index heritability twin study and food preference

Rolf Degen summarizing... Across countries, men tend to exhibit lower total fertility rates than women

Male–Female Fertility Differentials Across 17 High-Income Countries: Insights From A New Data Resource. Christian Dudel & Sebastian Klüsener. European Journal of Population, Jan 20 2021. https://rd.springer.com/article/10.1007/s10680-020-09575-9

Rolf Degen's take: https://twitter.com/DegenRolf/status/1351884721870041088

Abstract: Obtaining cross-country comparative perspectives on male fertility has long been difficult, as male fertility is usually less well registered than female fertility. Recent methodological advancements in imputing missing paternal ages at childbirth enable us to provide a new database on male fertility. This new resource covers more than 330 million live births and is based on a consistent and well-tested set of methods. These methods allow us to handle missing information on the paternal age, which is missing for roughly 10% of births. The data resource is made available in the Human Fertility Collection and allows for the first time a comparative perspective on male fertility in high-income countries using high-quality birth register data. We analyze trends in male–female fertility quantum and tempo differentials across 17 high-income countries, dating as back as far as the late 1960s for some countries, and with data available for the majority of countries from the 1980s onward. Using descriptive and counterfactual analysis methods, we find substantial variation both across countries and over time. Related to the quantum we demonstrate that disparities between male and female period fertility rates are driven to a large degree by the interplay of parental age and cohort size differences. For parental age differences at childbirth, we observe a development toward smaller disparities, except in Eastern Europe. This observation fits with expectations based on gender theories. However, variation across countries also seems to be driven by factors other than gender equality.

Conclusions and Perspectives

Based on a new, extensive database on male fertility in 17 high-income countries, we explore trends in the differences in the quantum and timing of male and female fertility. We find that, first, the level of male fertility relative to the level of female fertility can vary considerably across countries and over time. Male fertility, as measured by the total fertility rate (TFR), can be both higher and lower than female fertility; although in recent years it has generally been lower rather than higher. This observation is consistent with the results of Schoumaker (2019) based on survey and census data, and our further analysis for a subset of six countries shows that it also holds for cohort fertility rates (CFRs).

Our counterfactual calculations provide evidence for the claim that temporal fluctuations in the ratio between male and female TFR are often driven by age differences between partners and differences in postponement behavior, and our analysis of CFRs also supports this conclusion. Our second main finding is that age differences between fathers and mothers stayed constant or decreased in most of the countries in our study, except in the Eastern European countries and eastern Germany. While this general tendency is in line with expectations based on gender theories, the differences that currently exist across countries seem to be affected by more factors than just differences in gender equality levels.

While our findings indicate that male fertility has generally been lower than female fertility in recent years, this trend does not seem to hold globally. Schoumaker (2017, 2019) showed that in contexts in which polygyny is practiced and populations are rapidly growing, male fertility levels can sometimes be twice as high as female fertility levels. His results suggest that this pattern is driven to a large extent by age differences between couples. This finding is in line with the results of our counterfactual analysis, which indicate that extreme cases tend to disappear when the fathers are assigned to the same cohort as the mothers, and that large gender differentials in fertility levels are often driven by differences in fertility timing. At the other extreme, the lowest TFR ratio reported in the literature is for England and Wales in 1973, at around 0.89 (Schoen 1985). The value we have found for eastern Germany, 0.84, is below this level, and might indicate that eastern German males have been experiencing what Schoen (1985) called a “birth squeeze”: i.e., in eastern Germany, the unequal number of men and women in the reproductive age range is having an impact on the fertility of men. Generally, the variation in TFR ratios we observe across countries and over time is not negligible. Country groups with cultural and/or political similarities seem to have more similar trend patterns. This finding requires further investigation.

The mean age differences between men and women we have detected in our data are close to the orders of magnitude found in other studies (e.g., Kolk 2015). They are, however, lower than the high values observed in some African countries, where mean differences of more than 10 years have been estimated (Schoumaker 2017). Nevertheless, the variation across countries and over time in our 17 high-income countries is substantial. This heterogeneity of age differences is somewhat puzzling. In particular, our findings suggest that while European countries that score high on the gender equality index have smaller age differences, Japan does not seem to fit this picture. Even though Japan scores low on gender inequality indices (World Economic Forum 2017), the age differences among parents in this country are the lowest we have found in our study. This finding requires further investigation. Another factor that might be important is the cross-country variation in the share of migrants and the parental age differences that prevail in their countries of origin. We are, however, unable to study this potential factor, given that for most of the countries and years in our sample, we are unable to separate births by nationality or migration background status. We thus leave the exploration of this question to future research.

Looking at gender differences in fertility postponement, we find that gender differences tend to decrease over time, except in Eastern Europe, where age differences have been increasing. In Eastern Europe, this process has been accompanied by a process of societal restoration (Fodor and Balogh 2010). We also find that in some countries (e.g., Finland and France), the mean age difference has been stable over the period for which we have data. Our comparison of countries suggests that the Danish case, described by Nordfalk et al. (2015), is among those with rather large gender differences in fertility postponement. More research is needed to explain this variation across countries.

It is difficult to assess to what degree the observed patterns reflect gender differences in fertility preferences with respect to both the quantum and the timing of fertility. Surveys in low-income countries designed to assess the ideal number of children tend to report that the ideal number is usually much higher than the number of children actually born (Esteve et al. 2020). Longitudinal research has also shown that individuals tend to adapt their family size ideals to the number of children they were able to have (e.g., Kuhnt et al. 2017). This implies that the ideal number of children is not only a reflection of people’s preferences, but is also moderated by triggers and constraints that affect their fertility biographies. For Europe, data from the Eurobarometer survey 2011 indicate that in most countries, men tend to report lower ideal family sizes than women (Testa 2012). These results are generally consistent with our findings, which show that men have lower fertility than women. In addition, our TFR estimates for 2011 are highly correlated across countries with the Eurobarometer results on ideal family size for both men and women (> 0.9). However, the Eurobarometer results also show that in most countries, the gaps between the ideal and the actual number of children are larger for men than for women (Testa 2012). This observation could be interpreted as providing support for the view that men might be less able than women to realize their fertility desires, which could, in turn, be a result of the sex ratio imbalances.

Regarding preferences on the timing of births, the Eurobarometer survey data show that across member states of the European Union (EU25), both the ideal age to become parent and the latest age at which a person should have children are higher for men than for women (Testa 2006). The ideal age to become a parent is on average around 2 years higher for men than it is for women (Testa 2006), with women setting the ideal age for men higher (about 27.5 years) than men themselves (around 27 years). For the latest age at which a person should have children, the gaps between women and men are even larger. Both women and men set the age deadline for women on average at around 41 years, while both men and women set the age deadline for men at around 46 years (Testa 2006). Billari et al. (2011) used data from the European Social Survey and found slightly higher mean numbers both for women (41.7 years) and men (47.3 years), with some variance across countries. These survey results are generally in line with the gaps we identified. They are also in line with our finding that fertility decreases for men as well after age 45, even though many men are biologically able to have children at ages above 45.

The main outcomes we study in this paper—the TFR and the mean age at childbirth—are not the only measures of the quantum and the tempo of fertility. For instance, the proportion of childless individuals and the age at first birth have also received considerable interest in the literature. While this research has mostly focused on women, a small number of studies have also included men (Paavilainen et al. 2016). However, one of the limitations of the register data we employ is that we cannot use them to calculate the number of childless individuals. In addition, analyses by parity, such as by first birth, are only possible for women, if at all, as none of the birth registers records the parity of the father. Moreover, the mean parental age difference is not the only measure of the extent to which the paternal and the maternal age differ (e.g., Kolk 2015). However, using other measures, such as the variance or the standard deviation of the age difference, requires information on the joint age distribution of mothers and fathers, which cannot be derived from the ASFRs we provide as part of the HFC.

The new database we created to study male fertility is not limited to the questions we have investigated in this paper. It can, for example, be used in macro-level investigations of associations between male fertility levels and important economic and social indicators, including gender equality measures. There are many influential publications that have studied these relationships among women (e.g., Brewster and Rindfuss 2000; Myrskylä et al. 2009), and comparing the outcomes for female fertility with the results for male fertility might provide important insights. Such analyses will likely further improve our understanding of the role of gender in current fertility trends. The database can also be used in comparative analyses of trends in the paternal age at childbirth. Advanced paternal age is an important predictor of health outcomes of children, and has been attracting increasing attention in recent years (e.g., Khandwala et al. 2017). Thus, the database offers many promising avenues for future research, and we invite other researchers to make use of this new data resource available as part of the Human Fertility Collection (2019).