Tuesday, September 14, 2021

Asocial free-ranging squirrels: Bolder individuals maintained larger core areas than shyer individuals; more proactive and sociable personality types had greater access to a preferred resource

Bridging animal personality with space use and resource use in a free-ranging population of an asocial ground squirrel. Jaclyn R. Aliperti et al. Animal Behaviour, September 10 2021. https://doi.org/10.1016/j.anbehav.2021.07.019


• Bolder individuals maintained larger core areas than shyer individuals.

• More active and bolder individuals moved faster under natural conditions.

• More proactive and sociable personality types had greater access to a preferred resource.

• Among-individual variation in activity and sociability was positively correlated.

• Our data support personality-dependent use of space and resources in nature.

Abstract: Consistent individual differences in behaviour, or personality, likely influence patterns of space use and resource use in wild animals. However, studies on personality-dependent space use in natural ecosystems remain rare due to the difficulty of obtaining paired data sets on spatial dynamics and repeated personality measures from marked animals. We used repeated standardized assays (open field, mirror image stimulation, flight initiation distance and behaviour in trap) to perform the first characterization of personality in a free-ranging population of golden-mantled ground squirrels, Callospermophilus lateralis. We then used multilevel modelling to determine whether personality influenced 95% home range size, 50% core area size, movement speed or use of a preferred resource (‘perches’, vision-enhancing prominences such as rocks, which enhance survival) in nature. Data collected over 3 years showed that individual squirrels consistently differed in activity, sociability, boldness and aggressiveness (adjusted repeatability 0.16–0.44) and that activity was correlated with sociability (posterior mean correlation [95% credible interval] = 0.65 [0.39, 0.87]). We did not find an effect of personality on home range size, but bolder individuals maintained larger core areas than shyer individuals. More active and bolder individuals moved faster under natural conditions compared to their less active and shyer conspecifics. Individuals that scored higher for all four personality traits had more perches in both their home ranges and core areas compared to individuals with lower personality scores. Our results are indicative of personality-dependent space use and resource use in this study system. We hope our study will inspire future research that links animal personality with spatial ecology to inform wildlife management in natural ecosystems.

Keywords: animal personalityanimal temperamentbehavioural typeCallospermophilus lateralisground squirrelmovementrepeatabilityresource usesociabilityspace use

Contrary to many scholars’ intuitions, social aggregates like ethnic, linguistic, and religious groups, as well as diverse socio-demographic categories, add negligible explained variance to that already captured by nations

On “Nationology”: The Gravitational Field of National Culture. Plamen Akaliyski et al. Journal of Cross-Cultural Psychology, September 11, 2021. https://doi.org/10.1177/00220221211044780

Abstract: Nations have been questioned as meaningful units for analyzing culture due to their allegedly limited variance-capturing power and large internal heterogeneity. Against this skepticism, we argue that culture is by definition a collective phenomenon and focusing on individual differences contradicts the very concept of culture. Through the “miracle of aggregation,” we can eliminate random noise and arbitrary variation at the individual level in order to distill the central cultural tendencies of nations. Accordingly, we depict national culture as a gravitational field that socializes individuals into the orbit of a nation’s central cultural tendency. Even though individuals are also exposed to other gravitational forces, subcultures in turn gravitate within the limited orbit of their national culture. Using data from the World Values Survey, we show that individual values cluster in concentric circles around their nation’s cultural gravity center. We reveal the miracle of aggregation by demonstrating that nations capture the bulk of the variation in the individuals’ cultural values once they are aggregated into lower-level territorial units such as towns and sub-national regions. We visualize the gravitational force of national cultures by plotting various intra-national groups from five large countries that form distinct national clusters. Contrary to many scholars’ intuitions, alternative social aggregates, such as ethnic, linguistic, and religious groups, as well as diverse socio-demographic categories, add negligible explained variance to that already captured by nations.

Keywords: culture, nation, identity, units of analysis, cultural homogeneity

The Bayesian brain: Agents set the balance between prior knowledge and incoming evidence based on how reliable or ‘precise’ these different sources of information are — lending the most weight to that which is most reliable

Precision and the Bayesian brain. Daniel Yon, Chris D. Frith. Current Biology, V 31, Issue 17, PR1026-R1032, Sep 13 2021. https://doi.org/10.1016/j.cub.2021.07.044

Summary: Scientific thinking about the minds of humans and other animals has been transformed by the idea that the brain is Bayesian. A cornerstone of this idea is that agents set the balance between prior knowledge and incoming evidence based on how reliable or ‘precise’ these different sources of information are — lending the most weight to that which is most reliable. This concept of precision has crept into several branches of cognitive science and is a lynchpin of emerging ideas in computational psychiatry — where unusual beliefs or experiences are explained as abnormalities in how the brain estimates precision. But what precisely is precision? In this Primer we explain how precision has found its way into classic and contemporary models of perception, learning, self-awareness, and social interaction. We also chart how ideas around precision are beginning to change in radical ways, meaning we must get more precise about how precision works.

Precise and imprecise percepts

Imagine you are walking a particularly disobedient dog. After being let off the leash he leaps into the bushes, and you have to dive in to fetch him out. But you are not entirely sure where he is. You hear the sound of twigs cracking to the left, but you see the leaves shake to the right. Where should you jump in to catch him?
Locating your dog based on a combination of sight and sound is an example of a general class of multisensory integration problems where our perceptual systems have to triangulate different sensory signals. In our example, the visual signal (shaking leaves to the right) and the auditory signal (cracking twigs to the left) both tell us something about one feature of the environment (the dog’s location), and so it makes sense to combine them. But how? A simple approach could be for our brain to average them together — if sight says right and sound says left, we should dive in straight ahead.
But simple averaging turns out to be suboptimal when some signals are more reliable than others. For example, the spatial acuity of vision is much greater than that of hearing, meaning visual estimates of location are considerably more precise than auditory ones. This insight was formalised in Marc Ernst and Martin Banks’ Bayesian model of multisensory integration, which assumes that our perceptual systems combine different signals according to their reliability or uncertainty. Agents are thought to achieve this by keeping track of the noise or variance in different sensory modalities — with low noise taken as an index of high precision — and affording a higher weight to those channels that are more precise.
This idea of ‘precision-weighting’ provides a good account of near-optimal cue integration seen in humans and other animals. Typically, we won’t jump straight to catch the dog, but will veer off to the right as our brains give more credence to the more precise visual signal. Importantly, this idea can also explain why perception sometimes errs: such as when we are fooled by a ventriloquist’s dummy. It is common to say that the ventriloquist ‘throws their voice’ so it appears to be coming from the silent puppet. In fact, the illusion of the speaking doll emerges because our perceptual systems infer that the visual and auditory signals come from a common source, but give more weight to what we see than what we hear as we try to pinpoint where this source is located. The perceptual experience is false — the voice is not coming from the dummy — but this can still be thought of as an optimal inference from the brain’s perspective, given that coincident sensory signals often do come from a common source, and visual information about the location of these sources is typically so much more precise.

The Psychological and Socio-Political Consequences of Infectious Diseases: Authoritarianism, Governance, and Nonzoonotic (Human-to-Human) Infection Transmission

The Psychological and Socio-Political Consequences of Infectious Diseases: Authoritarianism, Governance, and Nonzoonotic (Human-to-Human) Infection Transmission. Leor Zmigrod, Tobias Ebert, Friedrich M. Götz, Peter Jason Rentfrow. Journal of Social and Political Psychology, Volume 9 (2), Sep 9 2021. https://jspp.psychopen.eu/index.php/jspp/article/view/7297

Abstract: What are the socio-political consequences of infectious diseases? Humans have evolved to avoid disease and infection, resulting in a set of psychological mechanisms that promote disease-avoidance, referred to as the behavioral immune system (BIS). One manifestation of the BIS is the cautious avoidance of unfamiliar, foreign, or potentially contaminating stimuli. Specifically, when disease infection risk is salient or prevalent, authoritarian attitudes can emerge that seek to avoid and reject foreign outgroups while favoring homogenous, familiar ingroups. In the largest study conducted on the topic to date (N > 240,000), elevated regional levels of infectious pathogens were related to more authoritarian attitudes on three geographical levels: across U.S. metropolitan regions, U.S. states, and cross-culturally across 47 countries. The link between pathogen prevalence and authoritarian psychological dispositions predicted conservative voting behavior in the 2016 U.S. Presidential Election and more authoritarian governance and state laws, in which one group of people imposes asymmetrical laws on others in a hierarchical structure. Furthermore, cross-cultural analysis illustrated that the relationship between infectious diseases and authoritarianism was pronounced for infectious diseases that can be acquired from other humans (nonzoonotic), and does not generalize to other infectious diseases that can only be acquired from non-human species (zoonotic diseases). At a time of heightened awareness of infectious diseases, the current findings are important reminders that public health and ecology can have ramifications for socio-political attitudes by shaping how citizens vote and are governed.

Leftists Possess More National Consensus in Europe in One of Two Data Sets (as it happens in the US)

Leftists Possess More National Consensus in Europe in One of Two Data Sets. Mark J. Brandt et al. Social Psychological and Personality Science, September 13, 2021. https://doi.org/10.1177/19485506211041825

Abstract: A regularity in the U.S. American politics is that liberals have more policy consensus than do conservatives, and both ideological groups have more consensus than moderates. One explanation for this is that conservatives’ local conformity paradoxically results in less consensus than liberals at the national level. If so, then the liberal consensus effect should also be observed in other countries. We test this using data from Europe. In the European Social Survey (country N = 38, participant N = 376,129), we find that on average leftists have more consensus than do rightists; however, we do not find this using the Eurobarometer (country N = 18, participant N = 375,830). In both data sources, we also observe variation in ideological differences between countries. These results suggest that there is a liberal/leftist consensus effect on average, that can be found in Europe and the United States, but there are also exceptions.

Keywords: ideology, consensus, belief systems, Europe, ideological differences

Older adults were significantly less likely to cheat and had higher ratings of honesty–humility compared to younger adults; greater honesty–humility predicted lower cheating behavior

Examining honesty–humility and cheating behaviors across younger and older adults. Alison M. O’Connor et al. International Journal of Behavioral Development, September 13, 2021. https://doi.org/10.1177/01650254211039022

Abstract: Self-report research indicates that dishonesty decreases across adulthood; however, behavioral measures of dishonesty have yet to be examined across younger and older adults. The present study examined younger and older adults’ cheating behaviors in relation to their self-reported honesty–humility. Younger (N = 112) and older adults (N = 85) completed a matrix task where they had the opportunity to falsely inflate their performance. Participants also completed the self-report measure of honesty–humility from the HEXACO-PI-R. Older adults were significantly less likely to cheat and had higher ratings of honesty–humility compared to younger adults. Greater honesty–humility predicted lower cheating behavior. These results demonstrate that older adults show greater rates of honesty and humility compared to younger adults using both behavioral and self-report methods.

Keywords: Deception, cheating, aging, honesty, HEXACO

An Industrial Organization Perspective on Productivity

An Industrial Organization Perspective on Productivity. Jan De Loecker & Chad Syverson. NBER Working Paper 29229, Sep 2021. https://www.nber.org/papers/w29229

Abstract: This chapter overviews productivity research from an industrial organization perspective. We focus on what is known and what still needs to be learned about the productivity levels and dynamics of individual producers, but also how these interact through markets and industries to influence productivity aggregates. We overview productivity concepts, facts, data, measurement, analysis, and open questions.


This chapter focuses on the implications and applications of productivity analysis within Industrial Organization. There is a long tradition in IO of studying productivityrelated topics like allocative eciency, technological change, regulatory effects, cost effciencies in merger analysis, and returns to scale, to name a few. The term productivity is, however, more often than not used in a fairly loose sense, usually referring to a measure of performance. In this chapter we make an explicit distinction between productivity in a strict production eciency sense, on the one hand, and performance on the other. The study of production eciency, the rate at which a producer can convert a bundle of inputs into a unit of output, is in essence about the technical relationship between output and inputs. Performance captures a variety of measures, but as this chapter will highlight, it is intimately related to eciency. However, the distinction can be crucial when analyzing the very topics listed above.

1.1 Background and Focus

While having a long history in economics, the past few decades have seen the productivity analysis of individual producers and the corresponding industry- and economy-wide aggregates become a central topic in both academic and policy circles. This renewed interest has paralleled at least three main developments.

First, over the last two decades the access to micro data has exploded. At the turn of the century, only a few large-scale producer-level datasets existed, with limited access to researchers. In contrast, the current list of countries for which micro census data is available (in manufacturing, at least) contains a rather large share of the world. In addition, private data providers have emerged offering comprehensive accounting data capturing typical variables used in productivity analysis, through the reporting of balance sheets and income and loss statements.

Second, accompanying the increased access to micro data has been a renewed interest in the estimation and identification of production functions. These are of course key objects of interest for most productivity analyses, both for their own sake as well as supplyside inputs into equilibrium analysis. This research has focused on obtaining reliable productivity measures for sets of producers when, as is the case, the researcher cannot directly observe productivity but producers can. This leads to two well-known biases, the simultaneity and selection biases, that researchers must face.

Third is the prominent role of productivity analysis in forming and executing economic policy. While policymakers still mostly focus on industry- or economy-wide aggregates, there is increasing recognition that this analysis is often most informative when built from the ground up using micro data. The melding of data, methods, and economically oriented policy analysis has spurred informative interactions among microeconomists, macroeconomists, and policymakers that have created many insights into productivity.  Our intent in this chapter is to organize and review the intellectual underlayment of this burgeoning literature. There are many facets. Our coverage includes key conceptual issues, facts about micro-level productivity, models of markets with heterogeneous productivity producers, measurement and data, productivity estimation, the positive and normative implications of the static and dynamic allocation of activity across heterogeneous producers, and an overview of what we expect to be active areas of work in the near future. We do this while taking stock of several decades of empirical work on productivity using micro data. We will unavoidably miss certain dimensions, and simple space constraints mean we cannot do justice to many contributions and insights from this extensive literature. We do hope, however, to offer a structured view on the field of productivity and how Industrial Organization scholars have contributed.

1.2 Productivity Conceptualized

Productivity is conceptualized in a number of related ways. All productivity metrics in one form or another measure how much output producers obtain from a given set of inputs. As such they are measures of the ecacy of the supply side of the economy (though \ecacy" need not always be synonymous with social welfare).  An interpretation of productivity as an economic primitive is as a factor-neutral (aka Hicks-neutral) shifter of the production function.1 Consider the general production function Q = Omega * F(.), where Q is output and F() is a function of observable inputs capital such as capital, labor and intermediate inputs.  Omega is productivity, the factor-neutral shifter.  It reflects variations in output not explained by shifts in the observable inputs that act through F(). A higher value of Omega implies the producer will obtain more output from a given set of inputs. That is, it denotes a shift in the production function's isoquants down and to the left.

A second conceptualization is empirical: productivity as a ratio of output to inputs.  This is tightly related to the production-function-shifter interpretation above. This can be seen by isolating productivity from the production function: Omega = Q / F(.) . A is clearly an output-to-input ratio. Here, where output is divided by a combination of observable inputs, the productivity concept is named total factor productivity (TFP) (it is also sometimes called multifactor productivity, MFP). There are also single-factor productivity measures, where output is divided by the amount of a single input, most commonly labor; i.e., labor productivity. Because single-factor productivity measures can be affected not just by shifts in TFP but factor intensity decisions as well, TFP measures are often conceptually preferable. On the other hand, labor productivity is often easier to measure than TFP.

A third conceptualization is of productivity as a shifter of the producer's cost curve.  Higher productivity shifts down the cost curve; that is, at the producer's cost-minimizing combination of inputs, its total cost of producing a given quantity is lower, the higher is its TFP level. This productivity conceptualization is related to the other two because the cost function is the value function of the producer's cost minimization problem, which takes the production function as its constraint. This cost function shifts down when productivity rises.

Because it plays such an important role in the producer's production technology, measuring productivity and its influence on outcomes is the subject of an enormous literature.

This work has found in many disparate settings that, as an empirical matter, productivity is hugely important in explaining the fortunes of producers, their workers, their suppliers, and their customers. We survey work on both the measurement and effects of productivity below.

Survey data show that up to 44% of the public support politically motivated violence; but estimates of support for partisan violence are too large; large majority support charging suspects who commit acts of political violence

Westwood, Sean, Justin Grimmer, Matthew Tyler, and Clayton M. Nall. 2021. “Political Violence.” OSF Preprints. September 14. doi:10.31219/osf.io/a8m3n

Abstract: Political scientists, pundits, and citizens worry that America is entering a new period of violent partisan conflict. Provocative survey data show that up to 44% of the public support politically motivated violence in hypothetical scenarios. Yet, despite media attention, political violence is rare, amounting to a little more than 1% of violent hate crimes in the United States. We reconcile these seemingly conflicting facts with three large survey experiments (N=3,041), demonstrating that self-reported attitudes on political violence are biased upwards because of disengaged respondents, differing interpretations about questions relating to political violence, and personal dispositions towards violence that are unrelated to politics. Our estimates show that, depending on how the question is asked, existing estimates of support for partisan violence are 30-900% too large, and nearly all respondents support charging suspects who commit acts of political violence with a criminal offenses. These findings suggest that although recent acts of political violence dominate the news, they do not portend a new era of violent conflict.