Tuesday, August 3, 2021

The Wealth Inequality of Nations: Wealth inequality varies greatly across countries, and there is no clear correlation with countries’ levels of income inequality

The Wealth Inequality of Nations. Fabian T. Pfeffer, Nora Waitkus. American Sociological Review, July 30, 2021. https://doi.org/10.1177/00031224211027800

Abstract: Comparative research on income inequality has produced several frameworks to study the institutional determinants of income stratification. In contrast, no such framework and much less empirical evidence exist to explain cross-national differences in wealth inequality. This situation is particularly lamentable as cross-national patterns of inequality in wealth diverge sharply from those in income. We seek to pave the way for new explanations of cross-national differences in wealth inequality by tracing them to the influence of different wealth components. Drawing on the literatures on financialization and housing, we argue that housing equity should be the central building block of the comparative analysis of wealth inequality. Using harmonized data on 15 countries included in the Luxembourg Wealth Study (LWS), we demonstrate a lack of association between national levels of income and wealth inequality and concentration. Using decomposition approaches, we then estimate the degree to which national levels of wealth inequality and concentration relate to cross-national differences in wealth portfolios and the distribution of specific asset components. Considering the role of housing equity, financial assets, non-housing real assets, and non-housing debt, we show that cross-national variation in wealth inequality and concentration is centrally determined by the distribution of housing equity.

Keywords: wealth, income, housing, inequality, comparison


While advanced capitalist societies are marked by high levels of inequality in household
wealth as well as concentration of wealth in the hands of a few, considerable variation
exists in the extent of national levels of wealth inequality and concentration. Yet, current
knowledge about national patterns and determinants of wealth inequality is limited and,
as we have argued here, will rely on fundamentally different explanatory approaches than
those developed over decades in a laborious field of research on international differences in
income inequality. International differences in income inequality tell us close to nothing about
international differences in wealth inequality, as we have shown here. In fact, many countries
that we customarily describe as comparatively egalitarian using income-based comparisons
– such as Scandinavian countries – can be classified as anything but in terms of their levels
of wealth inequality. Many countries that were henceforth thought of as similarly unequal –
for instance, Germany and Greece – are far apart from each other in terms of their level of
wealth inequality (with Germany displaying very high levels). As such, prior institutional
explanations of inequality hold little promise in elucidating the international ranking of
wealth inequality and the vast cross-national variation in wealth stratification remains in
urgent need of explanation.
This contribution takes but one first step in this direction by carefully investigating the
role of different asset components in accounting for the overall distribution of wealth. We
surmise that any potential institutional explanations of wealth inequality need to rest on a
careful consideration of the operative components of wealth. That is, we first need a clear
understanding of how the distribution of different types of assets relates to nations’ overall
level of wealth inequality and concentration. Is wealth inequality, for instance, largely a
reflection of the spread of debt, financial liabilities, and general exposure to financial markets,
as emerging theories of financialization may suggest? Or, do we best understand the degree
of wealth concentration in a given country as the concentration of capital held in real assets,
reflected, for instance, in the hoarding of wealth among a business elite? Our empirical
findings, instead, consistently point in a different direction: Cross-national differences in
wealth inequality and concentration chiefly reflect the level of inequality in and concentration
of housing equity. While simple indicators of home ownership rates, typically used to capture
the overall importance of housing assets in a given country, suggest that broader access to
home ownership may dampen wealth inequality and concentration, the overall distribution
of housing equity, of which the prevalence of home ownership is just one aspect, is the central
element accounting for overall wealth inequality. A country’s distribution of housing equity
explains its overall level of wealth inequality and concentration to a substantial degree,
including both the outlying position of the United States as well as the overall variation
across many different countries. This is not to say that the strong concentration of financial
assets and business equity at the top of the wealth distribution in most countries would be
unimportant. In fact, a focus on financial assets and business equity is likely central to the
understanding of elite closure and the continued and accelerating wealth accumulation of
the top one percent (Piketty 2014; Carney and Nason 2018). But, based on the evidence
presented here, our understanding of wealth inequality among the remaining 99 percent relies
on increased attention to the structure and dynamics of housing and mortgage markets.
Our two main findings – the non-correlation of income inequality and wealth inequality,
on the one side, and the centrality of housing equity, on the other side – are thus connected:
The reason why cross-national differences in income inequality do not predict cross-national
differences in wealth inequality is that the latter are most centrally driven by housing equity.
In turn, the distribution of housing equity, we argue, is crucially determined by financialization
and housing market dynamics, i.e., in institutional spheres outside of the labor market
and the classical realms of the welfare state. Work on comparative stratification and welfare
state regimes, therefore, will have to expand its view to these additional institutional factors
to make sense of a dimension of particularly profound and lasting inequality. Ideally, such
future work will draw on both qualitative and quantitative indicators of financialized housing
markets, such as housing and mortgage market regulations.
It seems unfortunate that one of the most ambitious theoretical and empirical studies on
the determinants of wealth inequality, Piketty’s Capital (2014), also mostly disregards the
role of housing as a driver of wealth inequality (see also Bonnet et al. 2014; Fuller et al. 2019;
Rognlie 2015), and the proposed “rule” of growing wealth inequality (r > g) at best discounts
the importance of a careful analysis of the institutional determinants of wealth inequality
(see also Acemoglu and Robinson 2015). An alternative, theoretically ambitious effort that
focuses on the role of housing may, instead, naturally align with the rapidly expanding
literature on financialization that has forcefully argued for the central role of mortgage
lending. At the backdrop of the findings presented here, one way to bring the literature on
financialization and the literature on wealth into closer conversation would be to establish a
clear empirical link between different lending regimes and the structure of national housing
markets. Doing so would also promise to ameliorate the surprising disconnect between the
scholarships on wealth and debt (see also Dwyer 2018). The comparative study of lending
regimes is at an early stage but has produced some interesting initial insights: For instance,
in a comparison of the mortgage debt structure in six European countries, van Gunten and
Navot (2018) show that differences in the distribution of mortgage debt is best captured by
the degree of credit intensity, i.e., the expansion of credit among those already holding it,
rather than differences in mortgage market participation (which also makes the distribution
of mortgage credit largely independent from national home ownership rates). This pattern
chimes well with our finding of the dominant role of the distribution of housing equity,
rather than home ownership rates, in explaining overall wealth inequality. However, in
the U.S., mortgage debt has also expanded into new population groups as the “predatory
inclusion” of minority households grew through new and exploitative mortgage products
(Rugh and Massey 2010; Taylor 2019). Future research should thus expand its comparative
range to understand different modes of housing market financialization (see also Blackwell
and Kohl 2018). Some of this research may also pursue a meso-level approach, popular in
some financialization studies, to compare the role of banks and asset management firms, the
real estate industry, or other intermediaries involved in expanding and intensifying mortgage
credit (Baradaran 2017; Jorda et al. 2016; Taylor 2019; Braun 2020).
To pursue an explanatory agenda, comparative wealth research will also be able to fruitfully
draw on research on recent housing markets dynamics. For instance, Adkins et al.
(2020) proposes property price inflation as the foundation of a new logic of inequality: Having
access to home ownership in areas experiencing such inflation determines individuals’
economic well-being over and above their employment. The extent to which homes out-earn
the individuals who own them, of course, also varies vastly within countries. Geographic
polarization of home ownership and housing prices has been documented in several countries
(e.g., Levin and Pryce 2011; Baldenius et al. 2020), in some taking the shape of run-away
home values in “superstar” cities, where transnational wealth elites store and invest vast
fortunes and drive up home prices in the process (Fernandez et al. 2016). Outside of these
zones of wealth storage and accumulation, asset prices are depressed and yield lower wealth
returns, for instance, in U.S. minority neighborhoods (Killewald and Bryan 2016; LaBriola
2020). Future research may seek to relate national-level wealth inequality and concentration
to regional and other spatial inequalities within countries. Recent contributions that
have pursued similar questions in the context of the income distribution in the U.S. have
shown that national-level trends in income inequality are the main driver of regional income
inequality (Manduca 2019) and that the distribution of income across and within U.S. geographies
has large, causal effects on the economic well-being of the next generation (Chetty
and Hendren 2018). If the variation in local housing markets is at least as large as that in
local labor markets, one may hypothesize that geographic variation in wealth levels and inequality
may be even more pronounced and consequential for the distribution of opportunity
among the next generation. For most nations, this vital analysis of within-country variation
in wealth levels, inequality, and persistence, however, awaits the development of a new data
data infrastructure to assess the distribution of wealth at the sub-national level, for instance,
based on full-population tax data or other administrative records. Finally, complementary
to a focus on recent housing market dynamics, a comparative-historical approach to uncover
the institutional foundations of countries’ housing and mortgage markets can draw on recent
work that not only documents high long-term wealth returns on housing (Jorda et al. 2019;
Blackwell and Kohl 2019) but also great cross-national variation in housing price trajectories
(Knoll et al. 2017). We remind the reader that our data are chiefly drawn from the period
following the Great Recession. And although our stability analyses based on immediate
pre-recession measures for a few countries suggest that our main conclusions are stable, we
believe that the cross-national variation in the impact of the housing crisis provides new
analytic opportunities.
We believe that future wealth research stands to learn a lot from a focus on countries at
either end of the international ranking of wealth inequality. As some of the most wealthegalitarian
countries in our analysis, post-socialist nations and their radical shift in home
ownership regulations during market transition provide promising analytic opportunities
(Marcuse 1996; Zavisca 2008; Tsenkova 2017; Song and Xie 2014; Xie and Jin 2015). At the
same time, we expect our results to trigger additional interest in analyzing countries with
the highest level of wealth inequality and concentration. Likely, the unfortunate leadership
position of the U.S. in the international ranking of wealth inequality will not come as a
surprise to most comparative stratification scholars; the degree to which the U.S. outranks
its peer countries in terms of wealth concentration may. We have gone to great lengths
to rule out that the high wealth concentration estimate for the U.S. is simply a product
of (putatively) superior data quality. It is also not exclusively a reflection of deep racial
inequalities in wealth; even among white U.S. households the level of wealth concentration
is exceptional in comparative perspective. The next two most wealth-unequal countries in
our analysis, Sweden and Norway, in contrast may cause more surprise and critique – even
though we are not the first to document high wealth levels for these countries (e.g., Roine
and Waldenstroem 2009; Jaentti et al. 2013). After all, comparative stratification research
has long and rightfully held up Scandinavia as the egalitarian poster-child based on its
national income distributions. The analysis of wealth considerably complicates this image
and invites scholars to revisit the assessment of Scandinavian egalitarianism. High wealth
stratification in Scandinavian countries may well be a long-term reflection of its much less
egalitarian history (see e.g., Piketty 2020) as well as the more recent neo-liberal turn in their
politics (Fagerberg et al. 1990; Ryner 1999). Critics may still wonder whether high wealth
inequality takes on fundamentally different social significance in a context with comparatively
generous systems of public insurance that may make wealth less central to maintaining more
stable lives. In contrast, we submit that wealth inequality in such contexts is still highly
consequential for a range of outcomes, in particular, for the intergenerational reproduction
of inequality: Recent contributions have highlighted the independent role of wealth in the
distribution of educational opportunity and the intergenerational transmission of advantage
in Sweden and Norway (Haellsten and Pfeffer 2017; Adermon et al. 2018; Hansen 2014;
Galster and Wessel 2019).
At the same time, concerns about the public insurance context of different wealth inequality
regimes do point to an important area for future research: As acknowledged before,
the inclusion of (estimated present values of) public pension entitlements is certain to provide
lower estimates of inequality in Scandinavia and other contexts. We have pointed out
that our analysis, in line with most other wealth research, applies a definition of net worth
that does not include public pensions nor most other forms of employer-provided pensions.
We have focused on assets available to working-age households. Unlike the marketable assets
included in our analyses, pension wealth is inaccessible (to varying degrees depending on the
type of pension) to households until older ages. Measures of wealth that include the present
values of pensions, i.e. “augmented net worth,” thus shift the analytic question.13 Although
harmonized measures of augmented net worth will be enormously difficult to construct for
a broad range of countries given cross-national differences in pension systems, future comparative
studies of augmented net worth inequality may provide a different country ranking.
Institutional explanations of such ranking will likely also profit from direct connections to
the literatures reviewed here as the financialization of pension systems complements that of
housing markets (Dixon 2008; Schwartz 2012; van Gunten and Kohl 2020).
Finally, we are convinced that the analysis of wealth inequality stands to gain from
future expansion of its comparative scope to other national contexts (see also Davies 2008).
As typical of most “medium-N” and “large-N” cross-national comparisons, our sample of
countries is a reflection of data availability, which in turn is based on various historical and
political contingencies that prohibit inference to other countries (see Ebbinghaus 2005). In
this sense, we provide an initial descriptive approach that awaits expansion to other countries
as the availability of LWS and other wealth data continues to expand (see Killewald et al.
2017; Zucman 2019). The findings reported here may also facilitate the meaningful selection
of a smaller number of comparative cases (Ebbinghaus 2005) that, in a “small-N” comparison,
would help elucidate the institutional foundations of distinct housing markets and their
relationship to overall wealth. The inability to draw firm causal conclusions based on either
type of comparative approach should not keep us from taking the next significant step in
filling the lacuna of evidence on the potential sources of national levels of wealth inequality.

Mice carrying the humanized Foxp2 allele were using higher frequencies and more complex syllable types than mice of the corresponding wildtype inbred strain

A humanized version of Foxp2 affects ultrasonic vocalization in adult female and male mice. Sophie von Merten, Christine Pfeifle, Sven Künzel, Svenja Hoier, Diethard Tautz. Genes, Brain and Behavior, August 2 2021. https://doi.org/10.1111/gbb.12764

Abstract: The transcription factor FoxP2 is involved in setting up the neuronal circuitry for vocal learning in mammals and birds and is thought to have played a special role in the evolution of human speech and language. It has been shown that an allele with a humanized version of the murine Foxp2 gene changes the ultrasonic vocalization of mouse pups compared to pups of the wild-type inbred strain. Here we tested if this humanized allele would also affect the ultrasonic vocalization of adult female and male mice. In a previous study, in which only male vocalization was considered and the mice were recorded under a restricted spatial and temporal regime, no difference in adult vocalization between genotypes was found. Here, we use a different test paradigm in which both female and male vocalizations are recorded in extended social contact. We found differences in temporal, spectral and syntactical parameters between the genotypes in both sexes, and between sexes. Mice carrying the humanized Foxp2 allele were using higher frequencies and more complex syllable types than mice of the corresponding wildtype inbred strain. Our results support the notion that the humanized Foxp2 allele has a differential effect on mouse ultrasonic vocalization. As mice carrying the humanized version of the Foxp2 gene show effects opposite to those of mice carrying disrupted or mutated alleles of this gene, we conclude that this mouse line represents an important model for the study of human speech and language evolution.

Promising behavioral evidence suggests that we may become more prosocial as we age; Reduced reward activity in the brain in response to self-gains & increased reward activity to others' gains may underlie age-related changes in altruism

Neurocomputational models of altruistic decision-making and social motives: Advances, pitfalls, and future directions. Anita Tusche, Lisa M. Bas. WIREs Cognitive Science, August 2 2021. https://doi.org/10.1002/wcs.1571

Abstract: This article discusses insights from computational models and social neuroscience into motivations, precursors, and mechanisms of altruistic decision-making and other-regard. We introduce theoretical and methodological tools for researchers who wish to adopt a multilevel, computational approach to study behaviors that promote others' welfare. Using examples from recent studies, we outline multiple mental and neural processes relevant to altruism. To this end, we integrate evidence from neuroimaging, psychology, economics, and formalized mathematical models. We introduce basic mechanisms—pertinent to a broad range of value-based decisions—and social emotions and cognitions commonly recruited when our decisions involve other people. Regarding the latter, we discuss how decomposing distinct facets of social processes can advance altruistic models and the development of novel, targeted interventions. We propose that an accelerated synthesis of computational approaches and social neuroscience represents a critical step towards a more comprehensive understanding of altruistic decision-making. We discuss the utility of this approach to study lifespan differences in social preference in late adulthood, a crucial future direction in aging global populations. Finally, we review potential pitfalls and recommendations for researchers interested in applying a computational approach to their research.


6.1 Integrating social affect and cognition into neurocomputational models of altruism

Significant strides have been made in research on human altruism. Fast-growing fields like neuroeconomics have pushed applications of a neurocomputational framework to understand social decision-making. Research in social neuroscience has started to unravel the impact of distinct facets of affective and cognitive social processes on prosocial behaviors. Integrating these two research lines provides an exciting path forward. We propose two tangible advancements.

First, a computational framework can help to reduce the ambiguity of concepts studied in social and affective research on altruistic choice. Despite significant progress, conceptual and neural components of social affect and cognition are still underspecified. Social processes relevant to altruism (e.g., empathy) represent complex, multilevel phenomena (e.g., the valence and arousal associated with an affective state). To date, we know little about how these components are encoded in the brain and, more importantly, contribute to decision-making. Mapping parameters of computational models on discrete components of the social process may offer crucial insights (Roberts & Hutcherson, 2019). This mapping can be direct, linking a specific model parameter to a concept, or indirect through a mediating psychological mechanism (Figure 3). This operationalization in a neurocomputational framework enables researchers to test predictions of the models, which in turn can inform theories (for a review on how computational modeling approaches like DDMs enable studies on affect, see Roberts & Hutcherson, 2019). Neurocomputational frameworks of social affect and cognition are still in their infancy. However, recent work in the domain of social learning (Lockwood & Klein-Flügge, 2020; Rosenthal et al., 2019) and strategic decision-making (Hill et al., 2017; Rusch et al., 2020) highlights the potential for neurocomputational approaches to study social processes in altruism.


Mapping affective science concepts to estimates of computational models. Reprinted from Roberts and Hutcherson (2019) (Fig. 1), Copyright 2019, with permission from Elsevier

This brings us to our second point. There is a wide agreement that multiple computational processes occur in parallel during altruistic decision-making. Our understanding of where these processes are computed in the brain has advanced significantly over the last decade. For instance, we highlighted several brain regions involved in value computation, cognitive control, and social processes like empathy or mentalizing in altruism (Figure 2). We also reviewed prior evidence on the neural underpinnings of key variables that guide value computations during altruistic choice (e.g., gains for oneself or others). How these components are integrated in the brain to produce coherent behaviors is less established (Suzuki & O'Doherty, 2020). Examining patterns of connectivity between brain areas that encode distinct choice-relevant computations may shed light on this question. Simply put, brain areas involved in altruistic choice do not act in isolation. They are embedded in interconnected networks. There is a trend in neuroimaging research to move away from narrow localization towards analyzing distributed brain networks. Suppose we aim to probe how other-regard is integrated into altruistic decision-making. Researchers can examine connectivity patterns between brain regions that perform other-regarding computations (e.g., TPJ) and those believed to encode the integrated subjective value of available choice options (e.g., VMPFC, Figure 2) (Hare et al., 2010; Park et al., 2017). Several analysis tools exist to examine functional connectivity patterns in the brain (e.g., psycho-physiological interaction analysis [PPI], Friston et al., 1997; dynamical causal modeling [DCM], Friston et al., 2003). Meta-analytic evidence suggests that PPI represents a reliable methodological approach to examine functional integration in the brain (Smith et al., 2016). Likewise, empirical evidence highlights the test–retest reliability of the DCM approach to study connectivity patterns in the brain (Frässle et al., 2015). One significant advantage of DCM is that it allows inferences about the directionality of the connectivity (e.g., from brain area A to area B). Functional and structural properties of neural networks can also be linked to estimates of formal models of social preferences. This approach has been shown to reveal social motives that guide altruistic decisions. For example, in a study that used DCM, functional coupling from the MCC to AI has been linked to empathy-driven altruistic motivations (modified dictator game) (Hein et al., 2016). Positive connectivity from the AI to VS has been linked to prosocial decisions driven by reciprocity motives. Reciprocity in this context refers to the motivation to respond in kind (i.e., the desire or expectation that a generous behavior will be returned). In other words, the results suggest that distinct social motives have different neurophysiological representations in the brain at the level of functional networks (Hein et al., 2016). These results echo our earlier argument: while resulting behaviors (generous choice) look alike, underlying social motives can be revealed through a multi-disciplinary computational framework. More generally, the combination of computational modeling, neuroimaging, and connectivity analysis will likely advance studies on how distinct computations are integrated in the brain to guide behaviors (for a general discussion beyond altruism, see Suzuki & O'Doherty, 2020). This approach may also inform us about how network configurations change due to situational or dispositional differences in empathy and mentalizing in altruism (or other key computational variables).

6.2 Neurocomputational models of altruism across the lifespan

Other-regarding behaviors emerge during infancy (Dunfield et al., 2011), and lifespan changes in childhood and adolescence have inspired a good deal of research (for an overview, see Eisenberg et al., 2007). Only recently, the field has started to examine age-related changes in altruism in late adulthood. Understanding other-regard in the elderly is essential for one apparent reason: global populations continue to grow older. By 2050, one in six people may be aged 65 or older (Kamiya et al., 2020). Consequently, changes in social preferences in late adulthood have significant social and economic consequences. Promising behavioral evidence suggests that we may become more prosocial as we age (for a recent overview, see Mayr & Freund, 2020, but see Bailey et al., 2020; Rieger & Mata, 2015; Wiepking & James, 2013). This effect holds when researchers control for differences in wealth across age groups (Kettner & Waichman, 2016). For example, charitable giving and volunteering increase across adulthood up to 70 years (Freund & Blanchard-Fields, 2014). While intriguing, these findings do not tell us why and how other-regard changes across the adult lifespan. We argue that an interdisciplinary, computational framework is uniquely suited to provide answers to these questions.

Preliminary research on altruism in the elderly draws on various measures like donations (Bekkers & Wiepking, 2011), surveys (Bekkers, 2010), and economic games (e.g., dictator game) (Engel, 2011; Kettner & Waichman, 2016; Matsumoto et al., 2016; Rosi et al., 2019) (for a review of age-related changes in economic games, see Lim & Yu, 2015). However, studies combining the perspectives and analysis tools from neuroscience, psychology, and behavioral economics are still rare. To illustrate the potential of a multi-level approach, we turn to the example of a recent study that bridged this gap. The results suggest that reduced reward activity in the brain in response to self-gains and increased reward activity to others' gains may underlie age-related changes in altruism (Hubbard et al., 2016). In other words, neural evidence suggests that the elderly may genuinely care more about others' well-being. We propose that incorporating formal models can provide even more insight into other-regard. For instance, formal models could quantify age-related changes in contributions of gains for oneself and others and link these estimates of model parameters to the brain's functional and structural properties. Model-based approaches also allow researchers to delineate the role of distinct social motives (e.g., maximizing others' gain vs. fairness). A recent behavioral study combined data from an economic game and computational modeling to examine age-related differences in other-regarding motives (Cho et al., 2020). The study used formal models (Dufwenberg & Kirchsteiger, 2004; Fehr & Schmidt, 1999) to delineate how young and older adults take intention- and outcome-based fairness into consideration during social decision-making. The parameter estimates of formal models suggest that older adults focus more on fair outcomes to guide their decisions and less on other's intentions. These findings explain why observable behaviors change as we grow older. Specifically, the results illuminate age-related changes in the relative importance of choice features and motives. In sum, we propose that an interdisciplinary, neurocomputational framework can advance our understanding of age-related changes in altruism.

Social neuroscience offers another window into lifespan changes of altruism and why the elderly may genuinely care more about others' welfare. Popular accounts suggest that the motivation to make strong emotional connections with others increases in older people (socioemotional selectivity theory; Carstensen et al., 2003). Consequently, researchers have examined emotional processes relevant to altruism throughout adulthood. This includes the emotional consequences of helping others (Bjälkebring et al., 2016) and emotional precursors of social decisions like empathy. Older individuals report greater empathy and empathic concern for others than their middle-aged and young counterparts (Sun et al., 2018; Sze et al., 2012), which partly accounts for age-related increases in prosocial behavior (Sze et al., 2012) (for a nuanced review on age-related changes in facets of empathy and mentalizing, see Beadle & De la Vega, 2019). These findings fit into a growing body of evidence that distinct facets of social cognition age differently. Empathy seems to be intact in old age, and empathic concern for others' well-being is even elevated (Reiter et al., 2017; Wieck & Kunzmann, 2015). Other components such as mentalizing or meta-cognition decline in late adulthood (Reiter et al., 2017; for evidence on age-differences when inferring others' intentions, see Reiter et al., 2021). Neuroimaging evidence on the aging brain provides insights into the neurobiological underpinning of these differential trajectories of social processes in late adulthood and decision-making (for reviews, see Beadle & De la Vega, 2019; Lighthall, 2020). Research on this topic is still in its infancy. Preliminary evidence suggests that core brain areas involved in affective processing seem to maintain their structural integrity during healthy aging (Mather, 2012). In light of this evidence, it would seem plausible that older adults rely more heavily on affective processes to guide altruistic decisions. Consistent with this notion, empathy-inducing messages increased altruism in a dictator game in the elderly more than in younger adults (Beadle et al., 2015). In sum, neuroimaging studies, together with formal models of altruism, are uniquely suited to elucidate the origins of process-specific inputs into social decisions in the elderly.

Unveiling the neural underpinnings of optimism: Two key brain areas were linked to optimism, one involved in imagining the future & processing of self-referential information, another for response inhibition & processing relevant cues

Unveiling the neural underpinnings of optimism: a systematic review. Fatima Erthal, Aline Bastos, Liliane Vilete, Leticia Oliveira, Mirtes Pereira, Mauro Mendlowicz, Eliane Volchan & Ivan Figueira. Cognitive, Affective, & Behavioral Neuroscience, Aug 2 2021. https://rd.springer.com/article/10.3758/s13415-021-00931-8

Abstract: Optimism is a personality trait strongly associated with physical and psychological well-being, with correlates in nonhuman species. Optimistic individuals hold positive expectancies for their future, have better physical and psychological health, recover faster after heart disease and other ailments, and cope more effectively with stress and anxiety. We performed a systematic review of neuroimaging studies focusing on neural correlates of optimism. A search identified 14 papers eligible for inclusion. Two key brain areas were linked to optimism: the anterior cingulate cortex (ACC), involved in imagining the future and processing of self-referential information; and the inferior frontal gyrus (IFG), involved in response inhibition and processing relevant cues. ACC activity was positively correlated with trait optimism and with the probability estimations of future positive events. Behavioral measures of optimistic tendencies investigated through the belief update task correlated positively with IFG activity. Elucidating the neural underpinnings of optimism may inform both the development of prevention and treatment strategies for several mental disorders negatively associated with optimism, such as depression, as well as help to foster new resilience promotion interventions targeting healthy, vulnerable, and mentally ill individuals.

Economic Development and Modernization in Africa Homogenize National Cultures

Economic Development and Modernization in Africa Homogenize National Cultures. Michael Minkov, Anneli Kaasa, Christian Welzel. Journal of Cross-Cultural Psychology, July 26, 2021. https://doi.org/10.1177/00220221211035495

Abstract: The nation-building literature of the early 1960s argued that decolonized countries need to overcome pre-colonial ethnic identities and generate national cultures. Africa is the most critical test case of this aspect of modernization theory as it has by far the largest ethnolinguistic fractionalization. We use data from the Afrobarometer to compare the cultures of 85 ethnolinguistic groups, each represented by at least 100 respondents, from 25 African countries. We compared these groups and their nations on items that address cultural modernization and emancipation: ideologies concerning inclusive-exclusive society (gender egalitarianism, homophobia, and xenophobia), submissiveness to authority, and the societal role of religion. Previous research has shown that these are some of the most important markers of cultural differences in the modern world. Hierarchical cluster analysis yielded very homogeneous national clusters and not a single ethnolinguistic cluster cutting across national borders (such as Yoruba of Benin and Yoruba of Nigeria, Ewe of Ghana, and Ewe of Togo, etc.). Only three ethnolinguistic groups (3.5%) remained unattached to their national cluster, regardless of the clustering method. The variation between nations (F values) was often considerably greater than the variation between ethnolinguistic groups. Medial distances between the groups of each country correlated highly with GDP per person (r = −.54), percentage men employed in agriculture (r = .64), percentage men employed in services (r = −.63), and phone subscriptions per person (r = −.61). In conclusion, economic development and modernization diminish cultural differences between ethnolinguistic groups within nations, highlighting those between them.

Keywords: national culture, ethnolinguistic culture, modernization, Africa

Gender and evaluation criteria for tenure and promotion: At the top quality level, there are no differences between males and females in the probabilities of preferring bibliometric criteria

What should be rewarded? Gender and evaluation criteria for tenure and promotion. Laura Cruz-Castro, Luis Sanz-Menendez. Journal of Informetrics, Volume 15, Issue 3, August 2021, 101196. https://doi.org/10.1016/j.joi.2021.101196


• Both interest-based and cognitive factors account for the preference of bibliometrics as evaluation criteria.

• Individual research quality influences positively the preference for bibliometrics.

• Differences in probabilities across genders are significant but small.

• At the top quality level, there are no differences between males and females in the probabilities of preferring bibliometric criteria

Abstract: Criteria for assessing candidates are essential elements for the functioning of evaluation practices in academia. This article addresses a relevant issue of academia: the preference for evaluation criteria for tenure and promotion, as reported by female and male academics employed at Spanish universities. We use survey data from 4,460 faculty members, testing whether there are differences in the evaluation criteria that women and men prefer and exploring the factors that account for such preferences. Our focus is on bibliometric evaluation criteria. We propose an analytical model that considers the influence of career and quality factors, values about universalism and the mission of universities, and beliefs about meritocracy in the context of the academic evaluation system. We use a binary logistic model to explain the preference for bibliometric criteria and develop the comparisons by gender using predicted probabilities and marginal effects for estimating the difference. We find that female academics do not have the same preferences as men and report lower preferences for bibliometrics. However, women at the highest research quality levels have similar probabilities than males to prefer bibliometric criteria for evaluation.

Keywords: Bibliometric assessmentResearch evaluationMerit criteriaTenure and promotionValue JudgmentGender disparitiesAcademic values and beliefsPreferencesBibliometric evaluation criteria

5. Discussion

Our empirical findings do not support the existence of a dominant preferred academic evaluation criterion for tenure and promotion. In the views of Spanish academics, it does not appear that any single criterion suffices for getting tenure and promotion. Reported preferences for evaluation criteria fit only imperfectly with the norms of scientific meritocracy and the Mertonian rule, but this does not mean that they are random or meaningless.

As indicated by Musselin (2013), two points lead to some relativization of the universalistic scientific reward principle: first, selection processes are rarely driven exclusively by the research criterion; candidates’ teaching experience is systematically taken into account; second, since candidates’ scientific production is not likely to be directly evaluated, peers prefer to give credence to standardized indicators that allow them to assess scientific value indirectly, especially the number of publications and citations.

Our general model to address the preferences is consistent, but other explanatory variables should be incorporated17. Analytically, both interest-based and cognitive variables are needed to account for preferences and their relevance is supported by the empirical data.

It is interesting that academics who have developed their career in a single university (inbred) do not show significantly different preferences regarding bibliometric criteria than their more mobile counterparts. Among the career factors, full professorship and PhD abroad strongly predict the preference for bibliometric criteria. This relationship may reflect the circumstance that full professors, once having obtained that rank (Ridgeway, 2014) , will no longer take part in competitions for jobs (except in the unlikely event of moving to a different university), and thus they do not view their potential colleagues as future competitors, thereby reducing the risk of adverse selection (Carmichael, 1988). This ‘competition’ explanation is consistent with previous research reporting lower levels of conflict in decisions regarding tenure for departments with a larger number of full professors (Hern and Anderson 2002).

Overall, the results reveal that individual research quality, as a variable that could be related with self-interest, when controlling for other covariates, does play a relevant role in accounting for the preference of bibliometric criteria in evaluation; those with higher research quality are more in favor of bibliometric criteria, a finding consistent with recent research (Langfelt, Reymert and Aksnes 2020Reymert, Jungblut, & Borlaug, 2021).

Academics integrate concerns about the university and the operation of academic evaluation into their preferences. The idea that teaching and training is the principal university mission stands out as one of the strongest predictors for not including bibliometric criteria among the evaluation preferences. In general, those who believe that the level of demand for merit requirements in place at the national accreditation agency are poor tend to prefer bibliometrics. Such a relationship may indicate the belief that the use of bibliometric criteria could be a way of palliating some of these shortcomings. Additionally, the belief that the current accreditation system is the best to assure a merit-based selection influences the preference for bibliometric criteria positively, possibly because standardized metrics increase trust in accreditation procedures (Sanz-Menéndez & Cruz-Castro 2019).

At this point we have to acknowledge that the relationship to values may operate both ways, and that having a preference for bibliometric criteria may influence the negative appraisal of a system that has been criticized in the past as suffering from cronyism (Bosch, 2001).

Central to our research questions, the analysis has revealed that female academics do not have the same preferences for evaluation criteria as men, and tend to prefer bibliometric less than their male counterparts; the marginal effect of gender is 7.8%, but for women at the highest level of quality the probabilities of preferring bibliometrics are almost the same than for males. This finding is consistent with recent evidence from Langfelt, Reymert and Aksnes (2020) showing that the use of bibliometrics in peer evaluation is higher among reviewers with higher scores on these metrics.

There are some plausible lines of interpretation of the differences. It might be the case, as found by (van den Brink and Benschop, 2012), that despite the gender neutrality of academic evaluation criteria, women at low to medium levels of quality perceive they would be disadvantaged if evaluated by certain criteria, if opportunities to develop and perform along them are unequally distributed ex ante. The literature on publications and productivity and impact differences by gender is substantial. Classical sociology of science and recent bibliometric research have extensively addressed the issue. The general empirical claim has been that men on average publish more papers and receive more citations than female scientists (Thelwall, 2018) . This could be a potential source of differences in attitudes or preference towards the use of bibliometric criteria in tenure and promotion evaluation. A trend towards closing the gap has also been reported in the literature (Xie & Shauman 2003) as well as the finding that productivity of both men and women increases with scientific rank (Long et al. 1993). Regarding impact, according to Lariviere and Sugimoto (2017) the average impact factor of journals for men and women are much closer to parity than citations and, systematically, the gap in citations is much greater than the gap in impact factors, and always in favor of men. In other words, even when women publish their work in high impact factor journals, this work is cited less (Abramo et al. 2015), both in absolute and relative terms, but there is recent evidence that contradicts these findings (Thelwall 2018Nielsen 2017).

It could also be the case, as reported by Niederle & Vesterlund (2011) in experimental studies, that women display different attitudes and responses than men toward competition even after controlling for performance, as they also found that men tend to be overconfident they will win in competitive environments, and women have a stronger tendency not to enter competitions. Much of the literature reports contradictory findings about females shying away from competition, and one of the reasons for this lack of consensus is that studies seldom consider feedback effects (Heilman et al. 2019). As some authors have highlighted, some academic evaluation practices and criteria (bibliometrics in our case) may be unappealing to women because of past histories of committees not hiring or not promoting women into high ranks, which lead to lower expectations of success (Fernández-Mateo and Kaplan 2018).

Two interesting empirical findings of our research are first, that both men and women at higher levels of quality prefer bibliometric evaluation criteria more than their colleagues at lower levels of research quality and, second, that the marginal effect of gender is almost non existing at higher levels of quality, meaning that there are no differences in probabilities of bibliometric preference for males and females at the top level of quality18.

A potential explanation for the first result could be connected with the efforts required by women to arrive at the highest level of quality recognition. Women at the top of research quality in our study have developed their careers in the 1990s or earlier, when there was a tight labor market, higher levels of competition and increased levels of evaluation requirements (Cruz-Castro and Sanz-Menéndez 2010); this generation could have interiorized the situation and give bibliometric criteria a more relevant role in evaluation (Sanz-Menéndez 1995). A different line of interpretation could be that women at the top assume the values and preferences of the “male dominated science system” (Derks et al. 2016).

Although differences by rank, values and beliefs matter, according to our data they follow similar patterns for women and men. These findings are also relevant for the analytical model. As mentioned, we need to account for structural, career, and cognitive variables to understand preferences for evaluation criteria in general, but when it comes to understanding the differences between female and male academics, probably the most important factors of those included in the explotatory model are structural and related to gender segmentation across quality levels and fields. However, females in different fields of science are more homogeneous, in comparison with males, in the probabilities to prefer bibliometric indicators.

We should acknowledge some caveats and limitations of the present study and the survey we have used (Sanz-Menéndez & Cruz-Castro (2019) provides more information). Although Spanish universities operate under the same national framework, they are under the political authority of their regional governments and these have diverse policies for universities and science, affecting the orientation and strategies of universities within their regions. We have addressed our research topic with a national survey (more ambitious than previous organization-focused case studies) and have not considered, this time, regional diversity; we leave this for future research, when factors related to the singularities of different universities could also be incorporated.

The definition of indicators used in the model to measure the three sets of explanatory variables could be further improved. Our analysis aims to be a contribution in the understanding of academic evaluation; further research could compare female and male preferences with the real operational processes of the tenure and promotion committees and with the explicit or formal criteria defined for this purpose.

Why women historically & cross-culturally have tended to be under-represented as leaders within human groups and organizations, given that we lack evidence that women leaders consistently perform worse than men?

An Evolutionary Explanation for the Female Leadership Paradox. Jennifer E. Smith et al. Front. Ecol. Evol., July 30 2021. https://doi.org/10.3389/fevo.2021.676805

Abstract: Social influence is distributed unequally between males and females in many mammalian societies. In human societies, gender inequality is particularly evident in access to leadership positions. Understanding why women historically and cross-culturally have tended to be under-represented as leaders within human groups and organizations represents a paradox because we lack evidence that women leaders consistently perform worse than men. We also know that women exercise overt influence in collective group-decisions within small-scale human societies, and that female leadership is pervasive in particular contexts across non-human mammalian societies. Here, we offer a transdisciplinary perspective on this female leadership paradox. Synthesis of social science and biological literatures suggests that females and males, on average, differ in why and how they compete for access to political leadership in mixed-gender groups. These differences are influenced by sexual selection and are moderated by socioecological variation across development and, particularly in human societies, by culturally transmitted norms and institutions. The interplay of these forces contributes to the emergence of female leaders within and across species. Furthermore, females may regularly exercise influence on group decisions in less conspicuous ways and different domains than males, and these underappreciated forms of leadership require more study. We offer a comprehensive framework for studying inequality between females and males in access to leadership positions, and we discuss the implications of this approach for understanding the female leadership paradox and for redressing gender inequality in leadership in humans.

Developmental Origins of Sex Differences in Leadership

A developmental perspective will help us to understand the ways that leadership roles are shaped across the lifespan by sexually selected motivations and by cultural transmission of norms and institutions. In general, juvenile mammals tend to initiate collective movements less often and are less often involved in leading intergroup conflicts than adults (Fichtel et al., 2011Majolo et al., 2020). In fish, followers are most likely to use social information from large (female) rather than small (male) demonstrators when making collective foraging decisions (Duffy et al., 2009). However, despite increased documentation that animals are selective in what, when and whom they copy (Kendal et al., 2018), we know little about how leadership and followership emerge across ontogeny in non-human animals.

Because individuals with high social rank in the dominance hierarchy may also impose a disproportionate influence in collective decision-making in some mammalian species (Van Vugt and Smith, 2019), understanding the mechanisms of dominance rank acquisition is also relevant and informative in this context. In many Old World monkeys, female dominance rank is determined by maternal rank inheritance, whereby daughters adopt the ranks below their mother in an age-reversed order (Harcourt and de Waal, 1992), but virtually all adult males, who acquire their rank based on size and strength, dominate all females (Pereira, 1995). In spotted hyenas, maternal rank inheritance is also implemented via this same associative learning of repeated social support from others (Holekamp and Smale, 1991Vullioud et al., 2019), and high-ranking adult females emerge most often as leaders in resolving within-group conflicts, collective movements, and initiating intergroup conflicts (Boydston et al., 2001Smith et al., 2010). In ring-tailed lemurs, female dominance over all males emerges spontaneously around puberty via male submission (Pereira, 1995). Thus, there exists great inter-specific diversity across mammals in the ways that socially powerful positions such as high dominance rank can be achieved. Similar patterns may apply to leadership emergence but will require explicit study.

In studies of children in WEIRD human societies, gender differences in social network attributes and group size preferences emerge early and perpetuate into adulthood (Rose and Rudolph, 2006Benenson and Abadzi, 2020). For example, girls have been observed to have smaller same-gender play groups (Ladd, 1983Ladd and Profilet, 1996) and less dense social networks than boys (Benenson, 19901993). However, these trends can be strongly shaped by the preferences of a few popular youth who strongly favor boy companions; preferences for friends based on gender can be weak or absent for unpopular youth (Ladd, 1983). Furthermore, gender differences in social network size vary with age. A study of Europeans found that men have more social contacts than women, particularly in young adulthood, but then this gender difference reverses in middle age as the numbers of contacts for both genders precipitously decline and as reproductive priorities shift (Bhattacharya et al., 2016). In smaller-scale societies with higher fertility levels, women may tend to engage in more broad social networking as they approach middle age, perhaps because they have fewer dependent offspring in the household (Werner, 1984Brown, 1985von Rueden et al., 2018). In small-scale societies, children can be more likely to socialize in mixed-gender groups, which can weaken gender differences in behavior (Lew-Levy et al., 2019). A study of BaYaka and Hadza hunter-gatherer children finds that play within mixed-gender groups increases as the available pool of playmates decreases, and mixed-gender socialization may explain smaller gender differences in rough-and-tumble and other forms of play compared to WEIRD samples (Lew-Levy et al., 2019). Much more cross-cultural work is needed to determine variability in social networking and leadership emergence within networks by gender across the lifespan.

Gender differences in individual competitive behavior can also emerge early in development. Among young children, studies in WEIRD contexts find that boys tend to engage in more self-referencing behavior and are typically more likely to recognize and respect decision-making hierarchies within their groups, whereas girls are more likely to use indirect strategies, like ignoring, to compete for leadership positions (Hold-Cavell, 1996Benenson and Abadzi, 2020). At older ages, the most popular children (both boys and girls) are the ones who apply tactics consistent with a combination of prestige and dominance leadership styles, though boys in general are more likely to pursue more purely coercive and aggressive tactics (Hawley, 2014). Gender differences in physical aggression and risk-taking may peak in late adolescence and young adulthood, when young men are most intensely competing to establish mate value (Wilson and Daly, 1985). Young women tend to compete more than men by emphasizing aspects of their physical appearance that signal residual reproductive value to potential mates (Cashdan, 1998Campbell, 2013b).

Importantly, gender differences in social network building and in competition for leadership positions are shaped by norms of expected behavior (e.g., greater encouragement of boys to engage in team sports or girls to assist in childcare). Cross-culturally, manhood more than womanhood is described as something to be earned, and which can be gained or lost depending on display of competitive ability, skill, generosity, and leadership (Vandello et al., 2008). Societies that experience greater intergroup conflict are more likely to portray manhood as precarious in this way, and to impose costly initiation rites of passage on young men to test their manhood (Sosis et al., 2007) due to benefits to male coalition building in the context of war (Rodseth, 2012). These norms may also reflect evolved, gender-specific motivations, but, obviously, they are not determined by them (Henrich, 2015). For example, the more that prestigious political positions in society are monopolized by men, the more they may be likely to promote norms and build institutions that exacerbate and canalize average gender differences in competition, coalition-building, or even desire for political leadership.

Follower preferences in leaders also emerge early and can change over the lifespan. Even infants possess the ability to distinguish between bullies and leaders (Margoni et al., 2018). Harsh childhood conditions may favor long-lasting preferences for dominant-style leaders that rely upon the threat of punishment (Safra et al., 2017). Follower preferences may have effects on gender disparity in leadership well before aspiring leaders reach adulthood. In the United States, one study found that adolescent girls showed less ambition as political leaders than adolescent boys, likely in part because boys were more likely to be groomed and described as prospective leaders, by their family members, teachers, coaches, and other role models (Lawless and Fox, 2013). A recent study found no gender difference in interest in being a leader among 3- to 7-year-old children, but girls were less likely than boys to pick a same-gender peer as a leader (Mandalaywala and Rhodes, 2021). Like any social phenomenon, such favoritism toward boys is unlikely to be purely a social construction, but rather shaped by a complex interplay over evolutionary and historical timescales of evolved motivations with cultural transmission of institutions and norms, particularly a gendered division of labor.

Integrating Evolutionary and Social Science Perspectives

There are many benefits to viewing female leadership within a transdisciplinary perspective that integrates evolutionary and social science perspectives (Kappeler et al., 2019Smith et al., 2020). Social role theories of gender (Eagly and Karau, 2002) are often contrasted with sexual selection approaches to gender differences, but we argue that these perspectives are not incompatible. More specifically, we focused on two outcomes of the mutual influence of evolutionary, ecological, and cultural factors, which often act to constrain female political leadership. That is, female competition and cooperation in pursuit of leadership can differ on average from that by males, and followers often demonstrate preferences for male over female leaders. As discussed above, evolved trait differences in humans can help explain the emergence and persistence of institutions and cultural norms, which enforce greater behavioral similarity within genders, affect opportunities for leadership by gender, and shape stereotypical conceptions of leadership. Emergence of particular gender norms and gender differences in leadership are further contingent on historical and cross-society variation, in subsistence, in inheritance systems, and in other factors. Studies in more egalitarian hunter-gatherers and other small-scale societies often report women exercising considerable leadership via inter-individual conflict resolution and criticism of non-normative behavior, though women can be less likely than men to coordinate community-wide activities and men’s voices can be more numerous during community political discussions (Collier and Rosaldo, 1981von Rueden et al., 2018Garfield et al., 2019). The agricultural revolution was a principal influence on historical increases in political inequality and exacerbation of patriarchy (Kaplan et al., 2009Mattison et al., 2016Van Vugt and Smith, 2019von Rueden, 2020). This is partly due to the effects of agricultural innovation on gendered divisions of labor that further privileged men’s social networking and access to wealth (Coontz and Henderson, 1986Alesina et al., 2011) and to increased incentives for male coalition-building in the face of more frequent warfare (Hayden et al., 1986Rodseth, 2012). While women were more likely to hold formal political positions in those agricultural societies with matrilineal descent (Low, 1992), women’s leadership positions tended to be less numerous or less powerful than their male counterparts (Whyte, 1978). Men continue to hold more top positions of formal leadership in large-scale, industrialized societies, but this gender gap has decreased in recent decades where ecological and economic conditions promoted declines in fertility and shifts in norms concerning women’s education and labor force participation (Konner, 2015). There is evidence in WEIRD societies of large decreases in stereotypical associations of masculinity with competence and with leadership (Koenig et al., 2011Eagly et al., 2019) and a decrease in preference for male over female bosses (Brenan, 2017). The balance of political power between women and men is shaped by the interplay of evolved gender differences, socio-ecology, and changing cultural institutions and norms (Low, 2005).

Our comparative perspective elucidates that overt forms of political decision-making are only one way in which individuals exert leadership in collective group decisions. In many mammalian species, females often emerge as leaders in the context of group movement for foraging or danger avoidance, less via active communication than by moving first (Smith et al., 2020). In small-scale human societies, men’s politics may tend to be more public and aggrandizing but women frequently exert influence at the community level via less conspicuous means (Rosaldo, 1974). In a study of Tamil communities in south India, women were less likely than men to be identified as politically influential, partly because of less access to formal employment or material wealth. However, Tamil women may yield influence that is less visible through the more numerous support relationships they foster between community members (Power and Ready, 2018). In many human societies, men’s historical monopolization of formal political leadership has contributed to associations of “appropriate” leader qualities with forms of competition more often preferred by men (Rudman and Phelan, 2008Hoyt and Burnette, 2013). In addition to calling attention to gender inequality in overt forms of political leadership, scholars should devote more attention to more subtle forms of leadership displayed by women (and men) that can be as or more relevant to collective decision-making in human societies.