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First Names, Cognitive Ability and Social Status in Denmark

  • Ulster Institute for Social Research

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It is well established that general intelligence varies in the population and is causal for variation in later life outcomes, in particular for social status and education. We linked IQ-test scores from the Danish draft test (Børge Prien Prøven, BPP) to social status for a list of 265 relatively common names in Denmark (85% male). Intelligence at the level of first name was strongly related to social status, r = .64. Ten names in the dataset were non-western, Muslim names. These names averaged an IQ of 81 (range 76-87) compared with 98 for the western, mostly Danish ones. Nonwestern names were also lower in social status, with a mean SES score of 2.66 standard deviations below that of western names. Mediation analysis showed that 30% of this very large gap can be explained by the IQ gap. Reasons for this relatively low level of mediation are discussed.
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MANKIND QUARTERLY 2019 59:4 521-531
First Names, Cognitive Ability and Social Status in
Emil O. W. Kirkegaard*
Ulster Institute for Social Research, London, UK
* Email:
It is well established that general intelligence varies in the
population and is causal for variation in later life outcomes, in
particular for social status and education. We linked IQ-test scores
from the Danish draft test (Børge Prien Prøven, BPP) to social status
for a list of 265 relatively common names in Denmark (85% male).
Intelligence at the level of first name was strongly related to social
status, r = .64. Ten names in the dataset were non-western, Muslim
names. These names averaged an IQ of 81 (range 76-87) compared
with 98 for the western, mostly Danish ones. Nonwestern names
were also lower in social status, with a mean SES score of 2.66
standard deviations below that of western names. Mediation
analysis showed that 30% of this very large gap can be explained by
the IQ gap. Reasons for this relatively low level of mediation are
Key Words: Denmark, Immigration, Military testing, Intelligence
It is well established that general intelligence (henceforth, intelligence) varies
in the population and this is known to be causal for later life social status.
Evidence for this causal claim comes from a variety of research designs including
parent-child and sibling comparisons, longitudinal studies, analysis of job
requirements, and studies using measured DNA-based (genomic) estimates of
intelligence (Gottfredson, 1997; Herrnstein & Murray, 1994; C. Murray, 2002;
Marioni et al., 2014; Rindermann, 2018; Strenze, 2007, 2015; Trzaskowski et al.,
Similarly, groups within a given country are known to differ in intelligence,
and their relative social status mostly reflects these differences. This is true for
geographic/regional differences, race/ethnic groups, and social status/class
differences (Herrnstein & Murray, 1994; Lynn, 2008; Lynn, Fuerst & Kirkegaard,
2018). Previous research has shown that names, both first and last, are related
to these social divisions (Clark, 2015; Fryer & Levitt, 2004; Fuerst, 2015; Kandt,
Cheshire & Longley, 2016; Liddell & Lycett, 1998; Lopes, 2017; Monasterio,
2017). In particular, many names have very strong racial/ethnic links. A first name
like Zhang (Chinese) or Ahmed (Muslim/Arab) is unlikely to belong to a person of
predominantly European ancestry. However, to our knowledge, the average
intelligence level of names and how these relate to social status differences
between names has not been studied. These relations are central to
understanding group differences in outcomes, which have been attributed to
various causes such as discrimination, stereotyping, and socio-economic
Indeed, a relatively large research literature in psychology and economics is
concerned with the causal impact of names on e.g. job applications or housing
discrimination (Carpusor & Loges, 2006; Christopher, 1998; Edelman, Luca &
Svirsky, 2017; Fryer & Levitt, 2004). These studies generally do not consider the
possibility that names might differ in average intelligence and that employers and
others are rationally using these as Bayesian priors or base rates to evaluate risks
and benefits of employing people (Jussim, 2012; Tetlock et al., 2000; for a
contrary view, see Uhlmann, Brescoll & Machery, 2010). Published summary
statistics for first names could be fruitfully used in future resumé studies as
proxies for peoples likely stereotypes.
Here, we examine data from first names of persons living in Denmark to see
how the average intelligence of first names relates to social status and ethnicity.
A key question from previous studies of immigrant social status in Denmark was
the degree to which intelligence would mediate the social status gap between
natives and foreigners (e.g. Kirkegaard & Fuerst, 2014). The present dataset
allowed an estimation of this.
Data from the Danish military draft intelligence test, Børge Priens Prøve
(Teasdale, 2009), were obtained for a sample of 65,137 persons who took the
test between 2009 and 2011. Most people who took the test were men who
attended the military testing session shortly after turning 18 (mean age = 20), and
a small number of volunteer women. We then computed average scores for each
name that occurred at least 20 times in the dataset, which amounted to a total of
265 names (226 male) covering data from 65,137 persons. We used IQ norm
data from a different study of 22k persons setting the Danish group of names to
M = 100, SD = 15 (Institut for Militærpsykologi, 2013; see Kirkegaard, 2013 for an
English language explanation).
Social status
We used previously published name data (n = 1,903) for age adjusted social
status in Denmark (Kirkegaard & Tranberg, 2015). The data originate from the
Danish statistics agency (Danmarks Statistik, DST) who sold data about
indicators of social status by first name to the magazine Ugebladet A4 (‘The
Weekly A4’). The values are derived from whole population statistics covering
every person legally residing in Denmark (~5.6 million). The magazine published
the name data as part of an interactive tool on their website
( which allows anyone to see the
summary statistics for each name entered into a field. The data cover income,
unemployment, criminality, marital status, typical professions, and home
ownership among other things. The complete dataset from the website was
obtained with an automated downloading tool. Social status was conceptualized
as a general factor akin to general intelligence (Howe et al., 2012; Kirkegaard,
2014; Kirkegaard & Fuerst, 2017; Vyas & Kumaranayake, 2006) and extracted
using factor analysis from the five available numerical indicators (the non-
numerical indicators were not used as they were not amenable to factor analysis).
These were first adjusted for age using a polynomial regression model. The factor
score was then standardized to a mean of 0 and standard deviation of 1 for the
entire sample of names.
Name origin
Origin status was manually coded for each name by researcher judgment.
When in doubt, we consulted online name websites such as There were only 10 nonwestern names that occurred
more than 20 times, so we opted for a simple binary variable for modeling
purposes. All the nonwestern names were Muslim/Arabic: Ahmet, Mohamad,
Mehmet, Ahmed, Mohammed, Mustafa, Ahmad, Mohamed, Mohammad, and Ali.
Analyses were done in R 3.5.1. An R notebook can be found in the
supplementary materials at
The average IQs for western and nonwestern names were 98 and 81,
weighted by the population sizes of the names (98 and 82 unweighted,
respectively). Figure 1 shows the weighted correlation between intelligence and
general social status. Weighting was by square root of sample size, a reasonable
compromise between n-weighted and unweighted analysis, see discussion in
Fuerst and Kirkegaard (2016).
Figure 1. Scatterplot of intelligence and general social status for 264 first names
of people residing in Denmark. Point size shows the relative sample size.
The unweighted correlation was similar, r = .67 (scatterplot in the
supplementary materials). If the Muslim names in the bottom left are excluded,
the correlation is decreased to r = .42 (unweighted r = .39). Among the non-
western names (n = 10), the correlation was r = .69 (unweighted r = .76).
It is obvious from the plot that the nonwestern names fall substantially below
the regression line, indicating an omitted variable. We carried out a formal
mediation analysis using the mediation package for R (Tingley et al., 2014). This
showed that 30% [95% bootstrapped CI: 20%-40%] of the social status difference
between the western and nonwestern groups was mediated by the observed IQ
difference. Similarly, a simple regression showed that taking IQ into account, the
nonwestern names had a beta of -1.73, i.e. they fared much worse than their
measured intelligence level would predict.
Discussion and conclusion
Using summary statistics derived from large datasets of first names in
Denmark, we found that these show large variation in average intelligence level.
This variation in average IQ was strongly related to variation in average social
status, with a correlation of r = .63 (weighted). Nonwestern names fared poorly
both in terms of average intelligence level (mean = 81) and in social status (mean
= -1.85). Mediation analysis showed that the low social status could be about 30%
explained by the observed IQ scores. This study thus confirms the finding of lower
cognitive ability among immigrants in Denmark previously reported (Bleses &
Jensen, 2016; Kirkegaard, 2013; Rindermann & Thompson, 2016; Robie et al.,
The relatively low level of mediation was somewhat surprising considering
that Denmark is generally considered a fairly just and meritocratic country
(Charron, Dahlström & Lapuente, 2016). There are many potential causes for why
we observed the relatively low level of mediation. The most important cause is
probably the acclimatization delay. When a person settles in another country it
takes several decades to reach ones full potential. One reason is that the vast
majority of immigrants lack Danish skills and do not understand the local culture.
Since many immigrants have been in Denmark for only a couple of years, a delay
in attainment is to be expected. In particular when moving from less industrialized
societies, it is conceivable that ones intellectual capacity is estimated in
accordance with features of the country of origin. In cases where the immigrants
intelligence is on a par with the host country, it will take some time for the
immigrant to prove himself, and hence achieve social status congruent with his
level of intelligence. The Danish statistical agency conducted their own analysis
using individual level data which showed that the unemployment gap to native
Danes was markedly lower for people who had been in Denmark for more than
15 years than for those who had arrived in the last two years (Bjerre, Mortensen
& Drescher, 2016). This adjustment, however, confounds within country of origin
differences. It is possible, for example, that people who left Iraq more than 15
years ago are differently selected on employment related traits than those who
left less than five years ago. One would have to use repeated measurement data
to assess this confound.
Second, it is possible that the Danish IQ test underestimates the intelligence
level of non-westerners. As the test is given in Danish, people with poor Danish
language skills might suffer a penalty.1 However, those who actually took the test
in the present study are expected to be native speakers of Danish, because
military duty is reserved to people who are Danish citizens when they turn 18.
Only very few first-generation immigrants would fit in this category, and those
1 For discussion of the immigrant-native cognitive test score gaps in the Netherlands and
the moderating effect of Dutch language ability, see Helms-Lorenz, van de Vijver and
Poortinga, 2003; te Nijenhuis and van der Flier, 2001, 2003; te Nijenhuis et al., 2004.
would also have had to come to Denmark at a very early age. There is one single
empirical study of test bias for this test (n = 21,167 Westerners, n = 1,474 non-
westerners). It used a relatively simple design of comparing the subtest scores.
The test has 4 subtests, of which 2 are verbally loaded; verbal: vocabulary and
letter matrices; non-verbal: figures and number series (Teasdale, 2009). However,
the Danish-nonwestern gap size was about the same for each subtest, consistent
with approximately zero language bias (Institut for Militærpsykologi, 2013).
Third, Islamic beliefs and Arab/Middle Eastern culture probably have a
negative causal effect on social status attainment that is partially independent of
intelligence. This could be due to a preference for small business in order to be
self-sufficient (i.e. autarky) and consequently avoidance of other industries. In an
economic perspective, this would lead to a misallocation of skills and thus to lower
wages. Anti-integration attitudes which are common among Muslims probably
cause them to avoid contributing to Danish society as much as their intelligence
level would allow them to do (Koopmans, 2015). A detailed review of economic
studies of Islam and Muslims can be found in Kuran (2018).
Fourth, another possibility is that Danish society is biased against non-
western people such that these are unable to attain the status level that is
congruent with their intelligence level. Such causes are thought to exist for
instance in the legal system, where immigrants might receive harsher penalties
for the samecrimes, controlling for all measured confounders (Sweden: Kihlberg
& Myrin, 2016; Shannon & Törnqvist, 2008). However, in general, Scandinavian
societies are very welcoming to foreigners, with hundreds of millions of US dollars
spent every year on various integration programs which have been running for
more than four decades (Andersson & Jespersen, 2018; Sanandaji, 2017).
Hence, if anything, the net effect of Danish biases can be expected to be small
and perhaps even positive, and cannot thus explain the observed negative
residual. More generally speaking, it is difficult to find any substantial associations
between immigration policies and integration outcomes (Ersanilli & Koopmans,
Generally speaking, despite the dire situation of the European mass
immigration project (Andersson & Jespersen, 2018; D. Murray, 2017; Sanandaji,
2017; Sarrazin, 2012), there is a remarkable lack of detailed studies that examine
the most likely explanations for why most immigrants do not perform as well in
host nations as in their origin nations (for a partial exception, see Koopmans,
2016). The reasons will involve some model that includes differences in
intelligence, language, culture and religion. There is a strong need for large-scale
individual-level datasets that allow direct testing of competing models.
Regarding variation in social status and first names in the native Danish
population, there does not appear to exist much systematic research. It is hoped
that the publication of this article will create some further interest in the topic.
We want to thank Thomas Lill Madsen for sharing the summary statistics of
the military draft IQ with us, without which this study would not be possible.
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... The purpose of the present study was to test this general model of social inequality. A number of prior studies have been done on immigration outcomes in Denmark (Kirkegaard, 2013(Kirkegaard, , 2015(Kirkegaard, , 2017(Kirkegaard, , 2019a. However, none of these have included a measure of migration selection, thus there was a need to examine the effects of this covariate. ...
... Murray, 2002). We did not have a measure of the average intelligence of the different origin groups, however, prior research shows that there are large cognitive gaps, whether these are measured with tests labeled "intelligence tests" or something else (Kirkegaard, 2013(Kirkegaard, , 2019aRindermann & Thompson, 2016). Furthermore, it is known that there are strong genetic correlations between educational achievement tests, i.e. tests of academic content taught in school, and intelligence tests that don't involve such content (Krapohl et al., 2014). ...
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This paper presents a method for classifying the ancestry of Brazilian surnames based on historical sources. The information obtained forms the basis for applying fuzzy matching and machine learning classification algorithms to more than 46 million workers in 5 categories: Iberian, Italian, Japanese, German and East European. The vast majority (96.7%) of the single surnames were identified using a fuzzy matching and the rest using a method proposed by Cavnar and Trenkle (1994). A comparison of the results of the procedures with data on foreigners in the 1920 Census and with the geographic distribution of non-Iberian surnames underscores the accuracy of the procedure. The study shows that surname ancestry is associated with significant differences in wages and schooling.
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Following the increasing availability of DNA-sequenced data, the genetic structure of populations can now be inferred and studied in unprecedented detail. Across social science, this innovation is shaping new bio-social research agendas, attracting substantial investment in the collection of genetic, biological and social data for large population samples. Yet genetic samples are special because the precise populations that they represent are uncertain and ill-defined. Unlike most social surveys, a genetic sample's representativeness of the population cannot be established by conventional procedures of statistical inference, and the implications for population-wide generalisations about bio-social phenomena are little understood. In this paper, we seek to address these problems by linking surname data to a censored and geographically uneven sample of DNA scans, collected for the People of the British Isles study. Based on a combination of global and local spatial correspondence measures, we identify eight regions in Great Britain that are most likely to represent the geography of genetic structure of Great Britain's long-settled population. We discuss the implications of this regionalisation for bio-social investigations. We conclude that, as the often highly selective collection of DNA and biomarkers becomes a more common practice, geography is crucial to understanding variation in genetic information within diverse populations. © 2016 Royal Geographical Society (with the Institute of British Geographers).
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Since the late nineteenth century, the presence of an independent and meritocratic bureaucracy has been posited as an advantage for effective bureaucratic behaviour and a means of limiting patrimonial networks and corruption, among other benefits. There is little consensus on how the features of an independent and meritocratic bureaucracy should be measured across countries, however, and broad empirical studies are therefore rare. What is more, the few such studies that exist have advanced measures which are constructed exclusively on expert surveys. Although these have indeed contributed to the knowledge in the field, the data on which they are built come with problems. This paper proposes a set of novel measures that complement existing measures and thus fill important gaps in this burgeoning literature. The measures we present are not based on expert assessments but on perceptions of public sector employees’ and citizens’. We create two measures—that can be combined into one—from a recent survey (2013) of over 85,000 citizens in 24 European countries. One is purely based on the assessments from public sector employees’ and the other is based on perceptions of citizens working outside the public sector. The paper also discusses the survey and explores the external validity of the measures provided here, showing correlations with alternative measures based on expert opinions, as well as variables from the literature that we would expect to correlate highly with a meritocratic bureaucracy.
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We conducted novel analyses regarding the association between continental racial ancestry, cognitive ability and socioeconomic outcomes across 6 datasets: states of Mexico, states of the United States, states of Brazil, departments of Colombia, sovereign nations and all units together. We find that European ancestry is consistently and usually strongly positively correlated with cognitive ability and socioeconomic outcomes (mean r for cognitive ability = .708; for socioeconomic well-being = .643) (Sections 3-8). In most cases, including another ancestry component, in addition to European ancestry, did not increase predictive power (Section 9). At the national level, the association between European ancestry and outcomes was robust to controls for natural-environmental factors (Section 10). This was not always the case at the regional level (Section 18). It was found that genetic distance did not have predictive power independent of European ancestry (Section 10). Automatic modeling using best subset selection and lasso regression agreed in most cases that European ancestry was a non-redundant predictor (Section 11). Results were robust across 4 different ways of weighting the analyses (Section 12). It was found that the effect of European ancestry on socioeconomic outcomes was mostly mediated by cognitive ability (Section 13). We failed to find evidence of international colorism or culturalism (i.e., neither skin reflectance nor self-reported race/ethnicity showed incremental predictive ability once genomic ancestry had been taken into account) (Section 14). The association between European ancestry and cognitive outcomes was robust across a number of alternative measures of cognitive ability (Section 15). It was found that the general socioeconomic factor was not structurally different in the American sample as compared to the worldwide sample, thus justifying the use of that measure. Using Jensen's method of correlated vectors, it was found that the association between European ancestry and socioeconomic outcomes was stronger on more S factor loaded outcomes, r = .75 (Section 16). There was some evidence that tourist expenditure helped explain the relatively high socioeconomic performance of Caribbean states (Section 17).
This essay critically evaluates the analytic literature concerned with causal connections between Islam and economic performance. It focuses on works since 1997, when this literature was last surveyed comprehensively. Among the findings are the following: Ramadan fasting by pregnant women harms prenatal development; Islamic charities mainly benefit the middle class; Islam affects educational outcomes less through Islamic schooling than through structural factors that handicap learning as a whole; Islamic finance has a negligible effect on Muslim financial behavior; and low generalized trust depresses Muslim trade. The last feature reflects the Muslim world's delay in transitioning from personal to impersonal exchange. The delay resulted from the persistent simplicity of the private enterprises formed under Islamic law. Weak property rights reinforced the private sector's stagnation by driving capital from commerce to rigid waqfs. Waqfs limited economic development through their inflexibility and democratization by keeping civil society embryonic. Parts of the Muslim world conquered by Arab armies are especially undemocratic, which suggests that early Islamic institutions were particularly critical to the persistence of authoritarian patterns of governance. States have contributed to the persistence of authoritarianism by treating Islam as an instrument of governance. As the world started to industrialize, non-Muslim subjects of Muslim-governed states pulled ahead of their Muslim neighbors, partly by exercising the choice of law they enjoyed under Islamic law in favor of a Western legal system. © 2018 American Academy of Pediatric Dentistry. All rights reserved.
Differences in intelligence have previously been found to be related to a wide range of inter-individual and international social outcomes. There is evidence indicating that intelligence differences are also related to different regional outcomes within nations. A quantitative and narrative review is provided for twenty-two countries (number of regions in parentheses): Argentina (24 to 437), Brazil (27 to 31), British Isles (12 to 392), to 79), Spain (15 to 48), Switzerland (47), Turkey (12), the USA (30 to 3100), and Vietnam (61). Between regions, intelligence is significantly associated with a wide range of economic, social, and demographic phenomena, including income (r unweighted = .56), educational attainment (r unweighted = .59), health (r unweighted = .49), general socioeconomic status (r unweighted = .55), and negatively with fertility (r unweighted = −.51) and crime (r unweighted = −.20). Proposed causal models for these differences are noted. It is concluded that regional differences in intelligence within nations warrant further focus; methodological concerns that need to be addressed in future research are detailed.
Cambridge Core - Cognition - Cognitive Capitalism - by Heiner Rindermann
In an experiment on Airbnb, we find that applications from guests with distinctively African American names are 16 percent less likely to be accepted relative to identical guests with distinctively white names. Discrimination occurs among landlords of all sizes, including small landlords sharing the property and larger landlords with multiple properties. It is most pronounced among hosts who have never had an African American guest, suggesting only a subset of hosts discriminate. While rental markets have achieved significant reductions in discrimination in recent decades, our results suggest that Airbnb's current design choices facilitate discrimination and raise the possibility of erasing some of these civil rights gains.