Nations and intelligence
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The significance of apparent variation in IQ scores between different nations has been a controversial topic within psychometrics.
In 2002, Richard Lynn and Tatu Vanhanen attempted to estimate the IQ score between nations across the world in their book IQ and the Wealth of Nations. Its methods and conclusions have been criticized by a number of researchers.
- 1 Studies of national cognitive ability
- 2 Implications
- 3 Limitations and criticisms
- 4 Correlates with national IQ
- 5 Causes of the national differences
- 6 See also
- 7 References
- 8 External links
Studies of national cognitive ability
IQ of various European countries
The 1981 article "Average IQ values in various European countries" by Vinko Buj is the only international IQ study that has compared IQs using the same IQ test over a short time period. It was probably completed in the 1970s and compared the capital cities or biggest towns in 21 European countries and Ghana.
Researchers believe the data from this study are of dubious quality: except for a two-page-long publication, nothing about the study detail nor the author is known. The author didn't work at a university. However, according to the Croatian newspaper website Slobodna Dalmacija, Vinko Buj spent many years in training in Germany, specializing in clinical (medical) psychology in 1977, and later received his doctorate of psychological sciences at the University of Hamburg. Nevertheless, the data yielded correlations with student assessment studies of only around -.10 to .07. Hence, the figures in the study do not seem to be ideal for studies on differences within Europe.
Lynn and Vanhanen
In the 2002 book IQ and the Wealth of Nations, and the 2006 book IQ and Global Inequality, Richard Lynn and Tatu Vanhanen created estimates of average IQs for 113 nations and estimated the IQs of 79 other nations based on neighboring nations and other manners. They also created an estimate of "quality of human conditions" for each nation based on gross national product per capita, adult literacy rate, the fraction of the population enrolled in secondary education, life expectancy, and rate of democratization. Lynn and Vanhanen found a substantial correlation between the national IQ scores they created and these various socioeconomic factors. They conclude that national IQ influences these measures of well-being and that national differences in IQ are heavily influenced by genetics, although they also allow for some environmental contributions. They regard nutrition as the most important environmental factor, and education a secondary factor.
Though the collection has been praised as "landmark" by Heiner Rindermann, the books and their argument have been roundly criticized on methodological and analytical grounds: for some countries, test samples were very small or unrepresentative, different tests were used by different researchers conducting the test surveys, measurements of intelligence stem from different years (although the authors tried to correct for this), and missing data was estimated by using unweighted arithmetic means used for neighboring countries with similar people.
In a 2010 paper, Lynn updated his estimates of national IQs from IQ and Global Inequality and presented new estimated national IQs for 25 countries, which had previously only been estimated from neighboring nations. Lynn and Vanhanen updated their estimates again in the 2013 book Intelligence: A Unifying Construct for the Social Sciences.
International student assessment studies
Regarding several methodology issues of IQ and the Wealth of Nations, Hunt and Wittmann compared contemporary educational data from the Program for International Student Assessment with national wealth. They concluded that Lynn and Vanhanen's empirical conclusion is correct, but they questioned the simple explanation that national intelligence causes national wealth.
In 2010, Lynn and Meisenberg integrated all the international studies of reading comprehension, math and science understanding and showed that they are perfectly correlated with national IQs. Lynn and Vanhanen's national IQ estimates were validated.
Estimation of Africans' IQ
Wicherts and colleagues
In 2009, Jelte M. Wicherts, Conor V. Dolan, and Han L.J. van der Maas conducted a new analysis of IQ in sub-Saharan Africa, which was critical of many of Lynn and Vanhanen's methods. Wicherts et al. concluded that Lynn and Vanhanen had relied on unsystematic methodology by failing to publish their criteria for including or excluding studies. They found that Lynn and Vanhanen's exclusion of studies had depressed their IQ estimate for sub-Saharan Africa and, after including studies excluded in "IQ and Global Inequality", the average IQ for sub-Saharan Africa was found to be 82, lower than the average in Western countries, but higher than Lynn and Vanhanen's estimate of 67. Wicherts at al. conclude that this difference is likely due to sub-Saharan Africa having limited access to modern advances in education, nutrition and health care.
Lynn and Meisenberg criticized their method of analysis, claiming that it was based on unrepresentative elite samples. They claimed that acceptably representative analysis samples reliably give an IQ of 68 as the average IQ in sub-Saharan Africa.
Jelte M. Wicherts, Conor V. Dolan, Jerry S. Carlson, and Han L.J. van der Maas replied that their selection of research is still unsystematic. They showed that figures calculated from some works considered representative by Lynn and Meisenberg still gives a higher IQ than the original estimates.
Rindermann (2007) states that the correlations between international student assessment studies and measures of national IQ are very high. Using the same statistical method used to measure the general intelligence factor (g) he found evidence that the "student achievement assessments and intelligence tests primarily measure a common cognitive ability". The international student assessment studies have the advantages of standardized testing over a short time period. A disadvantage is that unlike IQ-data collections, it does not include older people or more developing nations.
Rindermann's analysis found many of the same groupings and correlations found by Lynn and Vanhanen, with the lowest scores in sub-Saharan Africa, and a correlation of .60 between cognitive skill and GDP per capita. According to Hunt, due to there being far more data available, Rindermann's analysis was more reliable than those by Lynn and Vanhanen. By measuring the relationship between educational data and social well-being over time, this study also performed a causal analysis, finding that nations investing in education lead to increased well-being later on.
In 2013, Rindermann compared previous research on cognitive ability estimates for African IQ with new psychometric test studies, student assessment studies, variables correlate most strongly with intelligence outside Africa, and other indicators of cognitive ability. After correction, he made a guess for average African IQ of 75.
At the demographic level, there is an inverse statistical relationship between fertility and intelligence, and the intelligence difference is possibly partly genetic. Hence, assuming a 35% ratio of the national IQ difference due to genetic differences, Lynn and Harvey proposed that the data suggested a dysgenic decline in genotypic IQ of 0.86 IQ points for the years 1950–2000, and projected a 1.28 decline in IQ points for the years 2000–2050. Meisenberg calculated a 1.31 points decline per generation in genotypic intelligence among the young world population today. For such dysgenic trend, Woodley and Figueredo wrote of their "strong disinclinations" to endorse any "expansionist between-group military policies at the expense of other peoples".
Hunt wrote that genetics cannot be ruled out as a possible cause, but that education surely plays a major role, so one should not conclude that human capital in poor countries can never be improved.
Rindermann warned of the danger of such research being politically misused. He argued that people have to be treated as individuals and not as a mere representative of any group. He argued that both environmental and genetic (evolutionary, therefore past environmental) caused these differences. He emphasized the environmental effect on the improvement of intelligence and wrote "overcoming the most serious environmental obstacles as deficits in health care, nutrition and education could lead in Africa within one generation to a rise of 10 to 15 IQ."
Limitations and criticisms
Limitations of IQ test
Rindermann (2007) writes that the mixture of many different tests and the occasionally unclear representativeness of the samples seem to be the most serious problems. Furthermore, the measurement years vary, which is problematic because of the Flynn effect. Using the same adjustment for all nations is likely sometimes incorrect because, since the 1970s, developing nations have seen higher increases than the developed world. The method of averaging neighboring countries to estimate for the many nations that did not have measured IQs, while having a high correlation (0.92) with the measured results in the case of the 32 nations that changed from the estimated to the measured categories between the two books, is likely problematic since some research indicates that the absence of IQ tests indicates conditions such as poverty or war that may affect IQs. In addition, some errors in the data have been observed.
Limitations of the international student assessment studies
Rindermann (2007) writes that data from many developing nations are missing, which is the case for more nations than for IQ data. The Flynn effect has to be adjusted for. In some nations, school attendance is low. Even for the same test, the implementation and exclusion rates sometimes differed.
Correlates with national IQ
Rindermann and Ceci describe the calculation of national IQs and their correlates as "a new development in the study of cognitive ability: following a century of conceptual and psychometric development in which individual and group (socioeconomic, age, and ethnic) differences were examined, researchers have turned their attention to national and international differences in cognitive competence. The goal is to use cognitive differences to understand and predict national differences in a variety of outcomes: societal development, rate of democratization, population health, productivity, gross domestic product (GDP), and wage inequality".
|educational level of young adults||0.64|
|quality and quantity of school education of pupils||0.59|
|number of books||0.42|
|quality and speed of bureaucracy||0.28|
|rule of law||0.27|
|rate of solved cases for homicide||0.22|
|speed of life||0.18|
|government spending ratio||-0.24|
|gini-coefficient, income inequality||-0.40|
In IQ and the Wealth of Nations, Lynn and Vanhanen claim that national IQs are correlated with per capita income at .73. However, when log GDP (1975 – 2003) were used, the correlations have increased to .82 for 81 nations. Further study confirmed the results for 185 countries (r =.65) and for 152 countries (r =.76).
Jones and Schneider (2010) write that a country’s average IQ score is a useful predictor of the wages that immigrants from that country earn in the U.S., whether or not one adjusts for immigrant education.
In a macro-level analysis of 126 nations, Kanazawa has shown that national IQ, rather than income inequality, or economic development has a significant effect on the health of the population, as indicated by life expectancy, infant mortality rate and the age-specific mortality rate of males and females aged 15–19.
Using path analyses, Rindermann and Meisenberg have shown cognitive abilities (seen as depending on education) show a strong negative effect on HIV-infection rates, whereas gross domestic product and modernization each has a small positive effect. A higher proportion of Muslims in the population reduces the HIV-infection rate.
Rushton and Templer have shown "violent crime was found to be lower in countries with higher IQs, higher life expectancies, lighter skin color, and lower rates of HIV/AIDS, although not with higher national incomes or higher rates of infant mortality."
In a 2006 paper, Templer and Arikawa examined the correlation between several traits with IQ. They have found the highest correlations were − 0.92 (rho = − 0.91) for skin color, − 0.76 (rho = − 0.76) for mean high winter temperature, − 0.66 (rho = − 0.68) for mean low winter temperature, and 0.63 (rho = 0.74) for real gross domestic product per capita. With regard to the controversial nature of the paper, the editor of the journal it was published in issued an editorial note explaining their decision to publish. Two papers that commented on Templer and Arikawa's paper along their reply were also published on that issue of Intelligence. Hunt and Sternberg commented that their "data collection and analyses are seriously flawed. Even if their methods were technically adequate and if the claimed correlations existed, the correlations would be uninterpretable and hence of no scientific value." Jensen commented that "the main limitation of such a study design is that correlations obtained from this type of analysis are completely non-informative regarding any causal or functional connection between individual differences in skin pigmentation and individual differences in IQ, nor are they informative regarding the causal basis of the correlation, e.g., simple genetic association due to cross-assortative mating for skin color and IQ versus a pleiotropic correlation in which both of the phenotypically distinct but correlated traits are manifested by one and the same gene." Templer and Arikawa praised the comment by Jensen, but regard the most of the contentions of Hunt and Sternberg as "absurd".
Causes of the national differences
Both genetic and environmental effects could explain national differences in IQ. It should be noted that genetic theories are not excluded by showing strong environmental effects and the environment is not excluded by assuming genetic effects.
Since the 20th century, there have been worldwide continual increases in measured IQ. It was termed the "Flynn effect". Nations that have recently begun to modernize, including Kenya, Sudan and the Caribbean nations, show extremely high rates of gain. Relatively earlier modernized nations, including Argentina, Brazil, China, Estonia, and Spain also shows high rates of gain. Conversely, for those nations that began modernization as far back as the 19th century, IQ gains were not so fast (UK, US), stopped (Denmark) or even began to decline (Sweden, Norway, and France). Wicherts et al. have suggested that national differences in IQ could be because African countries have not yet experienced the improvements that cause the Flynn effect in the developed world, such as improvements in nutrition and health, and educational attainment. Flynn also believes that the IQ gaps are fluid and will diminish greatly in the twenty-first century if no cataclysmic events happen.
Hunt argues that the correlation between IQ and measures of social well-being is probably partially driven by large differences in prosperity and intelligence test scores between regions of the world, with the highest values for North America, Europe, and Northeast Asia, the lowest for sub-Saharan Africa and South Asia, and middle/average values for South America and the Middle East. However, substantial correlations between intelligence test scores and measures of well-being also exist when the analysis is limited to developed countries, where the IQ results are more likely to be accurate. Hunt and Wittman (2008) conclude that although the correlation between national IQ and economic well-being is clear, the direction of causality between them is more difficult to determine. They suggest some methods which could be used to determine the direction of causality in future studies.
Wicherts, Borsbooma, and Dolana (2010) have shown that national IQs are strongly confounded with the current developmental status of countries and correlate with all the variables that have been suggested to have caused the Flynn effect in the developed world. They have also criticized evolutionary studies for problems such as ignoring or assuming that the Flynn effect is equal worldwide and assuming that there have been no migrations and changes in climate over the course of evolution.
Eppig, Fincher, and Thornhill (2010) state that the distance from Africa, temperature, and most importantly by a large margin, the prevalence of infectious disease predict national IQs. Education, literacy, GDP, and nutrition were not important as independent factors (although the prevalence of infectious diseases is likely greatly affected by these factors). The authors argue that "from an energetics standpoint, a developing human will have difficulty building a brain and fighting off infectious diseases at the same time, as both are very metabolically costly tasks" and that "the Flynn effect may be caused in part by the decrease in the intensity of infectious diseases as nations develop."
There are several pieces of evidence suggesting the possibility of a genetic cause.
Kanazawa (2008) writes that cold climate and harsh winters (the study uses mean annual temperature) as well as environment novelty (the study uses three different measures of distance from the ancestral environment in sub-Saharan Africa: ordinary distance and differences in latitudes and longitudes) have been proposed as important factors behind the genetic evolution of human intelligence. The study found independent support for both theories and argues that they together explain half to two-thirds of the variance in national IQ.
A study conducted in South Africa has shown evolutionary-ethnic background is a more important predictor than SES. However, it can reflect environmental and cultural differences not covered by SES environmental and cultural differences.
Another study found that the impact of living conditions is of a much smaller magnitude than is suggested by just looking at correlations between average IQ scores and socioeconomic indicators. The study has found that after controlling for the test-takers' region of ancestry, the impact of parasitic diseases on average IQ is found to be statistically insignificant when test results from the Caribbean are included in the analysis. The author concludes that "differences in average IQ across world regions may change in the years ahead insofar as the strength of Flynn effects may not be uniform, but some regional differences in average g levels seem likely to continue indefinitely."
Using the GWAS method, several SNPs for intelligence have been found. A study found the average frequency and the factor score of nine GWAS hits are strongly correlated to country IQ (r = 0.91). However, this study employs a novel method that needs to be validated by further research.
Surveys of expert opinion
In a 2016 survey of 71 experts in intelligence "Genes were rated as the most important cause (17%), followed by educational quality (11.44%), health (10.88%), and educational quantity (10.20%). The sum of both education factors yielded the highest rating (21.64%). Of all factors, genes had by far the largest standard deviation (SD = 23.85; all other factors, SD < 10), indicating disagreement about the importance of genetic influences. Only 5 of 71 experts (7%) who responded to the genetic item thought that genes had no influence. If non-responses to the genetic item are converted to 0% (4 additional experts), 13% of experts doubted any genetic influence. The frequency of zero-percentage-ratings was larger for genes than for culture or education (about 1%), but experts who believed that genes had no influence were a minority: Around 90% of experts believed that genes had at least some influence on cross-national differences in cognitive ability."
- Ashkenazi Jewish intelligence
- Human capital flight
- Outline of human intelligence
- Race and intelligence
- Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. Page 436-437. 'Richard Lynn, whose work on sex and race/ethnic differences was discussed earlier in this chapter, and Tutu Vanhanen, a Finnish economist, invigorated the field with the publication of two challenging books and some related papers. I shall be highly critical of their empirical work, and even more so of their interpretations. They do deserve credit for raising important questions in a way that has resulted in interesting and important findings.'
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