Wednesday, September 1, 2021

Humans have evolved an independent psychological “engine” to respond to each kind of evolutionary problem (Lust, Hunger, Fear, Disgust, Attract, Love, Nurture, Hoard, Create, Affiliate, Status, Justice, Curiosity, & Play)

Psychometric Analysis of a Postulated Set of Evolved Human Motives. Robert Aunger, Dugald Foster, and Val Curtis. Front Psychol. 2021; 12: 680229, Jul 29 2021, doi: 10.3389/fpsyg.2021.680229

Abstract: Many different general systems of human motives have been postulated in the psychological literature. However, as yet, no consensus on which motives should be nominated, nor how many there are, has emerged. Recently, we deduced the existence of a number of motives using a logical argument derived from evolutionary theory; that humans have evolved an independent psychological “engine” to respond to each kind of evolutionary problem set by a dimension of the human niche, or life-way. Here, we confirm the existence of 14 out of 15 of these postulated motives using factor analysis on a web-based sample of 500 respondents from the UK: Lust, Hunger, Fear, Disgust, Attract, Love, Nurture, Hoard, Create, Affiliate, Status, Justice, Curiosity, and Play. The items which loaded most strongly for each factor confirmed the expected core value of each motive. Comfort did not emerge, perhaps because it is more about satisfying specific physiological requirements than a cluster of activities linked semantically by the concept of attaining “comfort.” We believe this analysis can form the foundation of a scale for use in applied psychological work ranging from personality testing to personnel selection to public health program design.

Keywords: motive, motivation, evolutionary pscyhology, factor analysis, behavior determination


In previous work, we postulated that 15 different motives evolved to bias human behavior toward achieving goals that helped our ancestors to survive and reproduce in our ancestral niche. Here, we sought to test our theoretical predictions empirically by exploring whether our candidate motives can be identified through dimension-reducing (psychometric) techniques. The confirmatory factor analysis suggested that 14 of our 15 hypothesized human motives are dissociable and discreet. Measures of fit (CFI, RMSEA, internal consistency) were acceptable or good.

The fifteenth motive, Comfort, could not be identified as a robust factor using this dataset. This could be because our items simply did not correctly identify the “core” issue associated with this motive (the items which loaded heavily on this factor concerned being lazy—having a lie in, staying in dressing gown all day—rather than sensitivity to pain, hot/cold, touch or loud noises). However, we think it more likely that this hypothesized motive may not be a unitary construct but, in fact, represent a variety of primitive and reflexive responses to physiological stimuli such as light, heat, acidity, wetness or pain. The fact that such perceptions require the use of different senses may mean there is no unified psychological mechanism to be picked up by a factor analysis.

Below we reflect on what the results of the analysis can tell us about each of the other postulated motives, with special reference to the top three loading items, as these figure in the reduced 42-item scale we hope others will take forward (see Table 6). We begin by outlining the motives related to somatic needs.

Hunger: Most questions about the hunger motive had high factor loadings and high degrees of agreement, with the exception of “I can go without eating for ages and not think about it.” The three highest loading items concerned the enjoyment of eating, shopping for and anticipation of meals, though caring about food, setting aside time to eat and the pleasure of eating also had high factor loadings. From an evolutionary perspective it seems uncontroversial to suggest that the hunger motive works to drive behavior that provides the immediate, or anticipated, rewards of eating. Food seeking drives (sometimes called instincts or needs) were common in earlier motive schemas—e.g., (James, 1890) and (Maslow, 1943)—but tends not to feature in more recent ones.

Fear: Only two fear-related questions had high factor loadings; these were dislike of roller coasters and being able to stand up to a threat from someone else. Unwillingness to go skydiving had moderate factor loadings. There were minor gender differences in the high loading factors and younger people scored more highly on fear (with the exception of the roller-coaster item). Most of the other questions related to imaginary events or non-specific threats that many people may not have actually experienced, such as encounters with predators. It seems that the higher loading questions may concern the unpleasant nature (negative reward) of fearful events that have actually been experienced. Fear or safety and security feature in most motives schemas (Aunger and Curtis, 2013).

Disgust: The three highest factor loading items concerned food: “I would be disgusted to find mold on some food I was eating,” “Smelling milk that has gone off makes me nauseous,” and “I always keep my kitchen free from any germs”. The fourth food-related item (“I would not eat any food that had passed its sell-by date”) also loaded highly. Though there was strong agreement about not sharing toothbrushes or not cleaning someone's infected wound, these items had lower factor loadings. Again, it seems that the most strongly loading items on this factor concerned events where participants were likely to have had direct experience of unpleasant effects of contact with disgusting stimuli, potentially being made nauseous or sick in connection with foodstuffs. This is consistent with the well-known “Garcia effect” (Garcia and Koelling, 1966), which accounts for strong food aversions based on bad experiences with food.

A set of needs are linked to the need for mortal individuals to reproduce themselves. In humans, this includes the need to solve problems associated with sexual reproduction and dependent offspring.

Lust: 61% of people agreed or strongly agreed that the sheer pleasure of sex is one of life's great rewards; 61% also agreed or strongly agreed that they hoped that they would still be having sex when they got old. These questions had the highest factor loadings, alongside liking to experiment with sexual positions. The questions with lower factor loadings were less directly concerned with the pleasures of sex and more about potentially socially tabooed activities such as one-night stands, early loss of virginity and use of pornography. The core of the lust motive seems thus to be most closely concerned with the directly rewarding nature of sexual activity. This is consistent with evolution having designed the lust motive to drive behavior that maximizes the pleasure derived from this crucial behavior.

Attract: Seven out of 10 factors loaded highly (LF > 0.6), suggesting that the analysis has captured an important dissociable psychological factor. The three highest loading questions were: “I like to dress provocatively,” “My friends would say I'm a flirt” and “I like to hang out where I might meet desirable partners,” which have close links to actually finding of a sexual partner. Other high loading items concerned more remote solutions; getting an operation to enhance one's appearance, dieting and exercise, or learning about mating strategies through self-education. Taken together, these items mention a wide range of tactics for attracting the attention and interest of potential partners. Few researchers have proposed attract as a separate motive from love and lust, though Chulef et al. suggest physical appearance is a goal (Chulef et al., 2001). But we believe this result indicates that there is an intermediate goal between immediate satisfaction of sexual cravings (Lust) and long-term pair-bonding (Love).

Love: The three highest loading items for the postulated “Love” factor concerned the pleasures of having a life partner (“I am happiest when I am with a person I love,” “I'd rather spend time with my partner than do anything else,” and “Finding your ideal life partner is the best thing that can happen to you”). Three other questions concerning valuing and investing in a partner also loaded highly. Less central were issues concerning dependability and cheating. Again, the core of this motive seems to concern the rewarding aspects of being in a loving relationship. In human evolutionary history, with highly dependent offspring, reproduction tended to be more successful with two parents, so a strong motive to invest in forming and maintaining a pair bond over a long period would have been adaptive (Rotkirch, 2018). Since the high loading items cover willingness to sacrifice for, the central importance of the pair-bond, and a variety of rewards from being in, and maintaining, such a relationship, this factor should adequately represent all the aspects of this important motivation.

Nurture: Uniquely, almost all of the items loaded highly on this factor. though the top three were “Doing the little things that are needed to make sure a child is safe and secure give me satisfaction,” “The smile of a child is one of the most beautiful things on the planet,” and “Being a parent is the most important role one can play in life.” Others concerned a willingness to defend a child under threat, despite great potential cost, and a willingness to do alloparenting just for pleasure. Questions that loaded poorly concerned caring for other relatives and the importance of a career versus having children. The results suggest that nurture is one of the most evolutionarily important motives, given that it should be tightly correlated with reproductive success, and that, given the amount of sustained investment that is required to rear a child, the rewards of nurturance must be correspondingly high. What might be missing is expression of the desire to see a child successfully reared to a (high status) adulthood, as the ultimate reward of good nurturing.

There is also a suite of motives related to human social life.

Affiliate: We proposed that those ancestors with a strong desire for gaining social acceptance would have had an adaptive advantage in the highly social human niche. The highest loading factors (which loaded negatively) were: “I spend a lot of time keeping in contact with my friends,” “I can't say I know a lot of people,” and “I prefer to work in a team,” which present a somewhat heterogeneous set of indicators of the core value, which suggest we did not identify the core value in this case. On reflection, we did not include any items that concerned the immediate rewards of social behavior (e.g., “I'm happy when I'm with a close friend”), which we suspect might have worked better at identifying the unique qualities of this motive, nor did we identify directly the benefits of working together, collaboratively, which should be central to the appeal of this motive. The items were instead mostly about feelings associated with being in groups or in some cases difficulties that might be associated with trying to maintain relationships.

Status: Our proposal from theory was that ancestors who found behaviors related to improving their social position rewarding would have been likely to have enhanced success in securing access to crucial resources. There were seven items with a factor loading above 0.5. These included “I enjoy showing off things that tell people I'm important,” “Holding a well-respected position in society is important to me,” and “Much of what I do is designed to improve my social position”. Items that loaded poorly on this factor concerned being competitive and being in charge. Whilst most of the questions clearly did load together, we provided few items about the rewards of being deferred to or socially recognized (e.g., “It's nice to be admired,” “I'm happy to be complemented when I've done good work”) which may have been more central to this motive. One question, that loaded strongly, comes close, however, by saying “People in my social group look up to me”.

Justice: There was strong agreement in our data concerning morally-related questions, and clear support in the pattern of responses for our central hypothesis that the Justice motive promotes third party punishment. This is the central mechanism underlying morality in evolutionary models and the consequent ability it confers to cooperate on a large scale, which uniquely characterizes human sociality (Fehr and Fischbacher, 2004Jordan et al., 2016). The top three loading items were “I would scold anyone who was inconsiderate to others,” “I get angry when I see someone take advantage of others” and “I am not afraid to stand up for the right thing”. Lower loading items concerned attitudes to politics, criminality and direct revenge (“an eye for an eye”).

Other motives concern goals that improve an individual's situation with respect to the physical or biological environment.

Hoard: The items that loaded highest on this factor were “I always like to keep plenty of spare items around just in case I need them,” “I feel secure when I'm surrounded by stuff that might come in handy,” and “I'm always buying things that I don't really need”. The highest loading question corresponds closely the hypothesized purpose of the motive in driving behavior that ensured that resources were available for times of scarcity. The top two items refer to the immediate rewards of owning “stuff,” whilst the lower loading items are more distal or abstract (e.g., saving up for the future). Recent motives schemas tend not refer to “hoard” as a motive, though Nohria et al. suggested possession of resources to be a drive (Nohria et al., 2001). Starch and McDougall suggested similar constructs (McDougall, 1908Starch, 1923).

Create: We hypothesized that ancestors who found constructing things such as tools and housing rewarding would have improved their niches, thus putting themselves and their families into a relatively good position for survival and reproduction. The highest loading factors were consistent with this supposition. For example, “I constantly make small improvements to the things I own,” “I like coming up with new inventions,” and “I would like to build my own house” loaded most strongly. There was also strong agreement and high loading for the item concerning the appreciation of good workmanship. Low loading items concerned tidying and watching plants grow. Again, the core of this factor seems to revolve around the pleasurable rewards of constructive behavior. Few recent schemas except Chuleff include constructs related to “create,” though Starch (Starch, 1923), Murray (Murray, 1938) and Maslow (Maslow, 1943) propose needs for aesthetics, beauty and order, which might be seen as an evolved appreciation for highly constructed environments.

Finally, a couple of motives describe how individuals can improve their own mental representations of the world around them or develop skills that enable them to better achieve the goals related to other motives.

Curiosity: If Curiosity is essentially about updating one's mental map of the world and storing knowledge about where opportunities and threats lie, as we postulate (Aunger and Curtis, 2013), then it makes sense that the top scoring three items on this factor concerned the direct pleasure of finding things out. These items were: “I am fascinated by going to places I haven't visited before,” “I get a lot of pleasure from discovering how things work,” and “It would be a great thrill to discover something no one has ever known before.” Closely linked, and weighted, was the claim that “I am interested in everything,” which is a somewhat more vague, and less generously rewarded, statement of the same tendency. Again, central to the curiosity motive seems to relate to directly experienced, pleasurable rewards, rather than meeting abstract and distal objectives (studying the genetics of flies, reading fiction or non-fiction).

Play: Items concerning the pleasurable rewards of experimental play behavior loaded most highly on this factor. “I love to learn new skills,” “I've always enjoyed play acting,” and “I enjoy contemplating new ideas.” The importance of having fun also loaded highly. The lower loading items concerned losing oneself in reading, sport as a major part of life and playing pranks, which appear to be more distal or abstract aspects of the play motive. There was no difference in the items by gender and little by age, though the play-acting item was agreed to by more younger people. The findings support the notion that the immediate “fun” rewards of experimental, skill-building activity reinforce playful behavior, which would have been adaptive for humans learning to live in their ancestral niches.

Relationships Between Motives

We can also look at pair-wise relationships between factors by estimating their inter-correlation (see Table 4). Nearly all inter-correlations between the factors are statistically significant, presumaby due to the large sample size; the exceptions being Lust and Disgust (p = 0.5), Lust and Nurture (p = 0.2), Fear and Disgust (p = 0.2) and Disgust and Curiosity (p = 0.9). It is obviously interesting to note that Lust does not “mix” with Disgust or Nurture (confusing Lust with either of these can certainly be counter-productive), while Disgust and Curiosity differ at a fundamental level in behavioral terms (one being avoidant, the other involving approach).

We can also look at those correlations which are absolutely large (i.e., |r| > 0.6) for indicators of interesting relationships. Play has the highest average correlation with other motives, and relationships with six others at values >0.6: Fear, Hoard, Create, Status, Justice, and Curiosity. The correlation with Create is negative, indicating a difference between practicing a skill and actually producing something. You also can't Play safely unless you are (at least somewhat) Fearful, and can't Hoard the resources needed to engage in practice, while Curiosity can help motivate Playful behavior. The significant relationship with Justice is interesting, suggesting that a concern with fairness can be associated with learning social skills through Play.

On the other hand, Status and Affiliation appear to be opposites (due to a strong negative correlation): aggressively pursuing higher status within a group can apparently work against efforts to be a “good citizen” or member of that group. Curiosity is also inconsistent with a desire to Create a better environment, perhaps because exploration distracts from the focus needed to make something here and now.

Comparison With Other Schemas

Many alternative motive schemas have been published throughout the history of psychology. Whilst these approaches have produced many similar candidate motives [indeed, those we have defined have been among the more popular ones throughout the history of study on this topic (Aunger and Curtis, 2013)], they also demonstrate considerable disagreement. Part of this lack of agreement concerns what can and cannot be classed as a motive in the first place. We have argued that motives should be seen as a set of evolved mechanisms that achieve goals over the relatively short term through action sequences guided by dopaminergic responses (Aunger and Curtis, 2015). This distinguishes motives from more ancient automated reflexes, and from more recently evolved cognitively planned objectives which require the involvement of consciousness and foreword thinking, as means of controlling the production of behavior. Hence pain avoidance, for example, is ancient and reflexive, whilst “autonomy” (Deci and Ryan, 2000) and “self-actualisation” (Maslow, 1943) are more recently evolved consciously elaborated objectives. As a consequence, we would not class them as motives. Our data support this notion, showing that more abstract and distal objectives do not load so closely to the immediately “rewarding core” of each motive.

Three previous efforts used evolutionary logic to produce lists of human motives, as we did: (Schwartz, 1992Bernard et al., 2005Kenrick et al., 2010). Schwartz is by far the most widely used of these schemes. He used a similar logic to ours in his original study of “universal human values” (Schwartz, 1992). He first argued that human values arise because individuals are biological organisms, engage in coordinated social interaction, and that their groups have survival and welfare needs. From these “universal human requirements,” he further deduced eight “motivational types” (prosocial, restrictive conformity, enjoyment, achievement, maturity, self-direction, security, and power), to which he suggested adding tradition, stimulation and spirituality (the last of which was not empirically supported). He then further argued that these ten values could be organized under four higher-level categories, and also arranged in a circumflex, based on possible pairings to achieve these higher goals (which suggested which values a particular value had on either side of itself).

Unfortunately, the results of these three efforts were considerably different from each other, and from ours. Table 7 compares these lists. While there is some overlap, a number of discrepancies also arise between the three typologies. These discrepancies can be largely accounted for by the different starting-points of the authors. Schwartz's intention was to develop a list of values that could be used to compare cultures and behavioral orientations across the world. Kenrick et al. began with a desire to update Maslow's hierarchy of human needs, and Bernard et al. with an a priori claim that human motives relate to five ever-expanding realms: “(a) the self-protection domain of the single system; (b) the mating domain of the dyadic system; (c) the relationship maintenance and parental care domain of the small, kin system; (d) the coalition domain of the large, nonkin system; and (e) the “memetic” domain of the large, symbolic, cultural system.” As a consequence, Bernard et al. tend to include more cultural (“memetic”) motives, while Kenrick et al. leave out the motives to improve mental abilities (Curiosity, Play), as well as Justice and Lust, because these don't appear in Maslow's triangle. Schwartz's orientation toward values rather than motives per se means that his list contains generic constructs such as “stimulation” and “achievement,” which characterize any goal-oriented activity, but simultaneously lacks specific, basic needs such as sex or love.


Table 7. Four evolutionary motive typologies.

Our own starting point was to provide an account of the universal, fundamental goals any individual should exhibit—that is, we began our investigation with the desire to identify the means by which humans would need to survive and reproduce, given the features of the human niche (Aunger and Curtis, 2013). This means our list covers much of the ground of the others, including social needs, but not the needs of groups, considered as agents independent of the individuals within them (e.g., group survival is not considered a separate need, as it was by Schwartz). We believe this is a strong foundation on which to build such an important claim about human nature, because evolutionary theory is so well-supported, as the intellectual foundation of the discipline of biology, and by implication psychology, given the fruitful and robust application of evolutionary thinking to psychology already over the past 50 years or so. Certainly, deducing the set of human motives from straightforward theoretical principles should be preferable to inducing them from some select set of data (as in a linguistic corpus) or group of previous studies, as others have done.

Of course, the evolutionary orientation does not distinguish this study from the others just mentioned. Neither does the fact that we use psychometric techniques to validate our list (All of these others have done the same: Schwartz and Boehnke, 2004Bernard and Lac, 2014Neel et al., 2016). Using a dimension-reduction statistical technique like factor analysis can produce outcomes that are interpretable from a wide range of starting points. Rather, what we believe we have accomplished here is to have produced empirical support for the existence of a particular set of motives—a very specific choice from among the wide variety of previously postulated motives—that were chosen on the basis of their consistency with a single, theoretically strong proposition that is more general yet parsimonious than the foundations of these other studies, based as it is simply on the claim that human motivation has evolved to solve the problems set by the dimensions of the human niche.


This study was restricted to people living in Great Britain. Obviously, it is desirable when making claims about the universal nature of human motivation to base that argument on evidence that is less WEIRD (i.e., from a Western, Educated, Industrialized, Rich, and Democratic population) (Henrich et al., 2010). Replication with a multi-cultural sample would therefore be desirable. The limited sample size might also have constrained the ability of factor analysis to strongly identify 15 different factors, suggesting that a larger sample might identify the Comfort motive effectively (also suggested by the scree plot analysis). This possibility should also be tested.

Men of dark personality were more attractive in the context of short-term relationship, after controlling for the basic personality traits

HEXACO and Dark Triad Personality Traits as Predictors of Male Attractiveness in Different Relationship Contexts. Ana Butkovic, Katarina Vatavuk, Anja Wertag. Psychological Topics, Vol. 30 No. 2 (2021).

Abstract: This study aimed to further investigate the perceived attractiveness of the Dark Triad (DT) personality in different types of relationships (i.e. friendship, short-term and long-term relationship) controlling for basic personality traits from the HEXACO model. The participants were 167 female students (M = 20.82 years, SD = 1.54) who rated personality and attractiveness of a man with highly expressed DT characteristics (n = 91) or a low-scoring DT character (n = 76) presented in a vignette. In line with recent findings, we observed a high negative correlation between the Honesty-Humility factor and DT personality (r = -.88, p < .001). As hypothesized, there was a significant difference in attractiveness ratings for the two characters in the context of different interpersonal relationships, with high DT character rated as significantly more attractive than the low DT character in the context of short-term mating. Furthermore, the hierarchical regression analysis showed that DT personality had a unique contribution in predicting attractiveness in the context of short-term relationship, after controlling for the basic personality traits.

Keywords: attractiveness, interpersonal relationships, Dark Triad, HEXACO

From 2019... What if rising concentration were an indication of more competition, not less?

What if rising concentration were an indication of more competition, not less? Geoffrey Manne. December 14 2019.


An oft-repeated claim of conferences, media, and left-wing think tanks is that lax antitrust enforcement has led to a substantial increase in concentration in the US economy of late, strangling the economy, harming workers, and saddling consumers with greater markups in the process. But what if rising concentration (and the current level of antitrust enforcement) were an indication of more competition, not less?

By now the concentration-as-antitrust-bogeyman story is virtually conventional wisdom, echoed, of course, by political candidates such as Elizabeth Warren trying to cash in on the need for a government response to such dire circumstances:

In industry after industry — airlines, banking, health care, agriculture, tech — a handful of corporate giants control more and more. The big guys are locking out smaller, newer competitors. They are crushing innovation. Even if you don’t see the gears turning, this massive concentration means prices go up and quality goes down for everything from air travel to internet service.  


Most recently, several working papers looking at the data on concentration in detail and attempting to identify the likely cause for the observed data, show precisely the opposite relationship. The reason for increased concentration appears to be technological, not anticompetitive. And, as might be expected from that cause, its effects are beneficial. Indeed, the story is both intuitive and positive.

What’s more, while national concentration does appear to be increasing in some sectors of the economy, it’s not actually so clear that the same is true for local concentration — which is often the relevant antitrust market.

The most recent — and, I believe, most significant — corrective to the conventional story comes from economists Chang-Tai Hsieh of the University of Chicago and Esteban Rossi-Hansberg of Princeton University. As they write in a recent paper titled, “The Industrial Revolution in Services”: 

We show that new technologies have enabled firms that adopt them to scale production over a large number of establishments dispersed across space. Firms that adopt this technology grow by increasing the number of local markets that they serve, but on average are smaller in the markets that they do serve. Unlike Henry Ford’s revolution in manufacturing more than a hundred years ago when manufacturing firms grew by concentrating production in a given location, the new industrial revolution in non-traded sectors takes the form of horizontal expansion across more locations. At the same time, multi-product firms are forced to exit industries where their productivity is low or where the new technology has had no effect. Empirically we see that top firms in the overall economy are more focused and have larger market shares in their chosen sectors, but their size as a share of employment in the overall economy has not changed. (pp. 42-43) (emphasis added).

This makes perfect sense. And it has the benefit of not second-guessing structural changes made in response to technological change. Rather, it points to technological change as doing what it regularly does: improving productivity.

The implementation of new technology seems to be conferring benefits — it’s just that these benefits are not evenly distributed across all firms and industries. But the assumption that larger firms are causing harm (or even that there is any harm in the first place, whatever the cause) is unmerited. 

What the authors find is that the apparent rise in national concentration doesn’t tell the relevant story, and the data certainly aren’t consistent with assumptions that anticompetitive conduct is either a cause or a result of structural changes in the economy.

Hsieh and Rossi-Hansberg point out that increased concentration is not happening everywhere, but is being driven by just three industries:

First, we show that the phenomena of rising concentration . . . is only seen in three broad sectors – services, wholesale, and retail. . . . [T]op firms have become more efficient over time, but our evidence indicates that this is only true for top firms in these three sectors. In manufacturing, for example, concentration has fallen.

Second, rising concentration in these sectors is entirely driven by an increase [in] the number of local markets served by the top firms. (p. 4) (emphasis added).

These findings are a gloss on a (then) working paper — The Fall of the Labor Share and the Rise of Superstar Firms — by David Autor, David Dorn, Lawrence F. Katz, Christina Patterson, and John Van Reenan (now forthcoming in the QJE). Autor et al. (2019) finds that concentration is rising, and that it is the result of increased productivity:

If globalization or technological changes push sales towards the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms, which have high markups and a low labor share of value-added.

We empirically assess seven predictions of this hypothesis: (i) industry sales will increasingly concentrate in a small number of firms; (ii) industries where concentration rises most will have the largest declines in the labor share; (iii) the fall in the labor share will be driven largely by reallocation rather than a fall in the unweighted mean labor share across all  firms; (iv) the between-firm reallocation component of the fall in the labor share will be greatest in the sectors with the largest increases in market concentration; (v) the industries that are becoming more concentrated will exhibit faster growth of productivity; (vi) the aggregate markup will rise more than the typical firm’s markup; and (vii) these patterns should be observed not only in U.S. firms, but also internationally. We find support for all of these predictions. (emphasis added).

This is alone is quite important (and seemingly often overlooked). Autor et al. (2019) finds that rising concentration is a result of increased productivity that weeds out less-efficient producers. This is a good thing. 

But Hsieh & Rossi-Hansberg drill down into the data to find something perhaps even more significant: the rise in concentration itself is limited to just a few sectors, and, where it is observed, it is predominantly a function of more efficient firms competing in more — and more localized — markets. This means that competition is increasing, not decreasing, whether it is accompanied by an increase in concentration or not. 

No matter how may times and under how many monikers the antitrust populists try to revive it, the Structure-Conduct-Performance paradigm remains as moribund as ever. Indeed, on this point, as one of the new antitrust agonists’ own, Fiona Scott Morton, has written (along with co-authors Martin Gaynor and Steven Berry):

In short, there is no well-defined “causal effect of concentration on price,” but rather a set of hypotheses that can explain observed correlations of the joint outcomes of price, measured markups, market share, and concentration. As Bresnahan (1989) argued three decades ago, no clear interpretation of the impact of concentration is possible without a clear focus on equilibrium oligopoly demand and “supply,” where supply includes the list of the marginal cost functions of the firms and the nature of oligopoly competition. 

Some of the recent literature on concentration, profits, and markups has simply reasserted the relevance of the old-style structure-conduct-performance correlations. For economists trained in subfields outside industrial organization, such correlations can be attractive. 

Our own view, based on the well-established mainstream wisdom in the field of industrial organization for several decades, is that regressions of market outcomes on measures of industry structure like the Herfindahl-Hirschman Index should be given little weight in policy debates. Such correlations will not produce information about the causal estimates that policy demands. It is these causal relationships that will help us understand what, if anything, may be causing markups to rise. (emphasis added).

Indeed! And one reason for the enduring irrelevance of market concentration measures is well laid out in Hsieh and Rossi-Hansberg’s paper:

This evidence is consistent with our view that increasing concentration is driven by new ICT-enabled technologies that ultimately raise aggregate industry TFP. It is not consistent with the view that concentration is due to declining competition or entry barriers . . . , as these forces will result in a decline in industry employment. (pp. 4-5) (emphasis added)

The net effect is that there is essentially no change in concentration by the top firms in the economy as a whole. The “super-star” firms of today’s economy are larger in their chosen sectors and have unleashed productivity growth in these sectors, but they are not any larger as a share of the aggregate economy. (p. 5) (emphasis added)

Thus, to begin with, the claim that increased concentration leads to monopsony in labor markets (and thus unemployment) appears to be false. Hsieh and Rossi-Hansberg again:

[W]e find that total employment rises substantially in industries with rising concentration. This is true even when we look at total employment of the smaller firms in these industries. (p. 4)

[S]ectors with more top firm concentration are the ones where total industry employment (as a share of aggregate employment) has also grown. The employment share of industries with increased top firm concentration grew from 70% in 1977 to 85% in 2013. (p. 9)

Firms throughout the size distribution increase employment in sectors with increasing concentration, not only the top 10% firms in the industry, although by definition the increase is larger among the top firms. (p. 10) (emphasis added)

Again, what actually appears to be happening is that national-level growth in concentration is actually being driven by increased competition in certain industries at the local level:

93% of the growth in concentration comes from growth in the number of cities served by top firms, and only 7% comes from increased employment per city. . . . [A]verage employment per county and per establishment of top firms falls. So necessarily more than 100% of concentration growth has to come from the increase in the number of counties and establishments served by the top firms. (p.13)

The net effect is a decrease in the power of top firms relative to the economy as a whole, as the largest firms specialize more, and are dominant in fewer industries:

Top firms produce in more industries than the average firm, but less so in 2013 compared to 1977. The number of industries of a top 0.001% firm (relative to the average firm) fell from 35 in 1977 to 17 in 2013. The corresponding number for a top 0.01% firm is 21 industries in 1977 and 9 industries in 2013. (p. 17)

Thus, summing up, technology has led to increased productivity as well as greater specialization by large firms, especially in relatively concentrated industries (exactly the opposite of the pessimistic stories):  

[T]op firms are now more specialized, are larger in the chosen industries, and these are precisely the industries that have experienced concentration growth. (p. 18)

Unsurprisingly (except to some…), the increase in concentration in certain industries does not translate into an increase in concentration in the economy as a whole. In other words, workers can shift jobs between industries, and there is enough geographic and firm mobility to prevent monopsony. (Despite rampant assumptions that increased concentration is constraining labor competition everywhere…).

Although the employment share of top firms in an average industry has increased substantially, the employment share of the top firms in the aggregate economy has not. (p. 15)


None of this should be so surprising. Has antitrust enforcement gotten more lax, leading to greater concentration? According to Vita and Osinski (2018), not so much. And how about the stagnant rate of new firms? Are incumbent monopolists killing off new startups? The more likely — albeit mundane — explanation, according to Hopenhayn et al. (2018), is that increased average firm age is due to an aging labor force. Lastly, the paper from Hsieh and Rossi-Hansberg discussed above is only the latest in a series of papers, including Bessen (2017), Van Reenen (2018), and Autor et al. (2019), that shows a rise in fixed costs due to investments in proprietary information technology, which correlates with increased concentration. 

So what is the upshot of all this?

First, as noted, employment has not decreased because of increased concentration; quite the opposite. Employment has increased in the industries that have experienced the most concentration at the national level.

Second, this result suggests that the rise in concentrated industries has not led to increased market power over labor.

Third, concentration itself needs to be understood more precisely. It is not explained by a simple narrative that the economy as a whole has experienced a great deal of concentration and this has been detrimental for consumers and workers. Specific industries have experienced national level concentration, but simultaneously those same industries have become more specialized and expanded competition into local markets. 

Surprisingly (because their paper has been around for a while and yet this conclusion is rarely recited by advocates for more intervention — although they happily use the paper to support claims of rising concentration), Autor et al. (2019) finds the same thing:

Our formal model, detailed below, generates superstar effects from increases in the toughness of product market competition that raise the market share of the most productive firms in each sector at the expense of less productive competitors. . . . An alternative perspective on the rise of superstar firms is that they reflect a diminution of competition, due to a weakening of U.S. antitrust enforcement (Dottling, Gutierrez and Philippon, 2018). Our findings on the similarity of trends in the U.S. and Europe, where antitrust authorities have acted more aggressively on large firms (Gutierrez and Philippon, 2018), combined with the fact that the concentrating sectors appear to be growing more productive and innovative, suggests that this is unlikely to be the primary explanation, although it may important in some specific industries (see Cooper et al, 2019, on healthcare for example). (emphasis added).


From 2020... Recall and recognition of visual objects share common memory sources

Tell me what you saw: The usefulness of verbal descriptions for others. Deborah H Tan, Yuhong V Jiang. Quarterly Journal of Experimental Psychology, April 20, 2020.

Abstract: Describing what one saw to another person is common in everyday experience, such as spatial navigation and crime investigations. Past studies have examined the effects of recounting on one’s own memory, neglecting an important function of memory recall in social communication. Here we report surprisingly low utility of one’s verbal descriptions for others, even when visual memory for the stimuli has high capacity. Participants described photographs of common objects they had seen to enable judges to identify the target object from a foil in the same basic-level category. When describing from perception, participants were able to provide useful descriptions, allowing judges to accurately identify the target objects 87% of the time. Judges’ accuracy decreased to just 57% when participants provided descriptions from memory acquired minutes ago, and to near chance (51.8%) when the verbal descriptions were based on memory acquired 24 hours ago. Comparison of participants’ own identification accuracy with judges’ accuracy suggests the presence of a common source of errors. This finding suggests that recall and recognition of visual objects share common memory sources. In addition, the low utility of one’s verbal descriptions constrains theories about the extension of one’s memory to the external world and has implications for eyewitness identification and laws governing it.

Keywords: Visual memory, misinformation, verbal recall utility

They Are Not Little Emperors: Only Children Are Just as Altruistic as Non-Only Children

They Are Not Little Emperors: Only Children Are Just as Altruistic as Non-Only Children. Xuegang Zheng et al. Social Psychological and Personality Science, August 31, 2021.

Abstract: Negative stereotypes about only children (OC) have caused widespread concern. However, relatively little is known about the accuracy of these stereotypes, especially regarding altruistic behaviors. In Study 1 (N = 337), participants rated the altruism of OC and non-only children (NOC) on three measurements on the basis of the participants’ perceptions. Results revealed that participants rated OC as less altruistic, and the stereotype primarily came from NOC raters. Results of Study 2 (N = 391) did not reveal any difference between OC and NOC in altruism. In Study 3 (N = 99), a social discounting task was applied to further investigate whether OC and NOC displayed different degrees of altruistic behavior toward various social distances. No differences were found among individuals at close or distant social distances. Ultimately, this research indicates that the negative stereotype regarding the altruistic behavior of OC is an incorrect prejudice.

Keywords: altruism, stereotype, only children, development, social discounting

Gender-equality paradox (greater social and economic gender equality predicts increased gender differentiation): Authors find given names are more phonetically gendered in more gender-equal societies

The Gender-Equality Paradox and Optimal Distinctiveness: More Gender-Equal Societies Have More Gendered Names. Allon Vishkin, Michael L. Slepian, Adam D. Galinsky. Social Psychological and Personality Science, August 31, 2021.

Abstract: Findings in several domains have documented a gender-equality paradox, where greater social and economic gender equality predicts increased gender differentiation. Many of these findings have used subjective rating scales and thus have been dismissed as artifactual due to different reference groups in more versus less gender-equal societies. Although recent research has documented the gender-equality paradox using an objective criterion—pursuit of degrees in STEM—the robustness of this finding has also been challenged. The current investigation offers evidence for the gender-equality paradox using an objective marker of gender differentiation: baby names. We find given names are more phonetically gendered in more gender-equal societies, with female names being more likely unvoiced (a softer sound) and male names being more likely voiced (a harder sound). We offer a theoretical explanation based on optimal distinctiveness theory to explain why increasing gender equality might motivate a preference for greater gender differentiation.

Keywords: gender, gender equality, stereotypes, optimal distinctiveness theory

Suicidality and Mood: The Impact of Trends, Seasons, Day of the Week, and Time of Day on Implicit and Explicit Cognitions

Freichel, René, and Brian O'Shea. 2021. “Suicidality and Mood: The Impact of Trends, Seasons, Day of the Week, and Time of Day on Implicit and Explicit Cognitions.” PsyArXiv. August 31. doi:10.31234/

Abstract: Decades of research have established seasonality effects on completed and attempted suicides, with an increase in rates during spring and early summer. Using more than six years of data (April 2012 – November 2018), we used new Prophet models to forecast mood and explicit and implicit measures of self-harm among an online community sample residing in the US and UK (N > 7,975). We decomposed the time series into trends across the years, within years (seasons), weekly, and daily seasonal patterns. Across all outcomes, the long-term changes across the years and the seasonal patterns show the strongest variation on explicit and implicit cognitions, followed by the time of day (negative cognitions peaking around 4 am – 5 am), with the day of the week showing the weakest effects. The data show a general increase of negative cognitions across the six years, paralleling trends in suicide rates and depression prevalence in the US and UK. Autoregressive-integrated moving average (ARIMA) models showed seasonality effects for mood and desire to die among US, UK, and Canadian respondents (N > 10,445), particularly in the group of respondents who previously made a suicide attempt. Negative cognitions were generally the lowest in summer (June) and peaked in winter (December). These negative cognitions precede the rise in suicidal behaviors during spring and early summer. We discuss potential reasons for lagged effects of negative cognitions on suicidal behavior and implicit cognitions, which may be crucial for theoretical advancements. Our findings have implications for the clinical risk assessment of patients with a history of suicide attempts and public policies regarding the availability of health services.

What Do We Talk About When We Talk About Culture? There is a Missing Link Between the Natural and the Social Sciences

What Do We Talk About When We Talk About Culture? There is a Missing Link Between the Natural and the Social Sciences. Andrea Zagaria. Integrative Psychological and Behavioral Science, Aug 27 2021.

Abstract: The article by Wells is a chance to ponder on the different conceptions of culture endorsed by the natural sciences and by the social sciences. The standard definition of culture among biologists/natural scientists usually focuses on transmission of behaviors (e.g. “tradition of socially learned behaviors”), while on the other hand anthropologists and social scientists focus more on the symbolic aspect of culture (e.g.“webs of significance”). This differential emphasis likely reflects a difference in ontology (what culture is) and in its epistemology (how it can be studied). Natural scientists typically prefer to focus on how cultural traits change quantitatively, while social scientists are much more focused with the process of symbolic interpretation, which typically involves the ability to account for meaning and sense-making (thus, it is more qualitative-grounded). These two conceptions of culture are both valid but incomplete, if they do not take into account the counterpart. The scientific conundrum that has to be solved is how these two different onto-epistemologies can be successfully linked together. A speculative hypothesis is put forward.