Nations and intelligence
The relationship between nations and intelligence is a controversial area of study concerning differences between nations in average intelligence test scores, their possible causes, and their correlation with measures of social well-being and economic prosperity.
Richard Lynn and Tatu Vanhanen have constructed IQ estimates for many countries using literature reviews, international student assessment studies and other methodologies to create estimates. Other researchers have criticized these estimates on theoretical and methodological grounds, and performed new analyses which corrected some of Lynn and Vanhanen's errors. Subsequent research by psychologists such as Earl B. Hunt, Jelte Wicherts and Heiner Rindermann has focused on identifying the causes of national differences in cognitive ability, and understanding the nature of their relationship to factors such as GDP, life expectancy, and democratic governments.
- 1 Background
- 2 Studies of national cognitive ability
- 3 Limitations and criticisms of the data sets
- 4 Correlations with national IQ
- 5 Causes of the national differences
- 6 See also
- 7 References
- 8 External links
Earl B. Hunt writes that economists traditionally view differences in wealth between nations in terms of human capital, which is a general term for the abilities of the workforce. However, some researchers have argued that differences in average intelligence between nations also play a role. Richard Lynn and Tatu Vanhanen raised many questions about this field with their books IQ and the Wealth of Nations and IQ and Global Inequality, which led to further investigations from other researchers, some of them highly critical of Lynn and Vanhanen's methods and conclusions.
According to Hunt, international studies of intelligence are important because they measure which populations possess the cognitive skills that are necessary in a post-industrial world. He also writes 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.
Studies of national cognitive ability
"Average IQ values in various European countries"
The 1981 article "Average IQ values in various European countries" by Vinko Buj is the only international IQ study that over a short time period has compared IQs using the same IQ test. It was probably done in the 1970s in the capital cities or in the biggest town in 21 European countries and Ghana. Rindermann (2007) states that it is of dubious quality with scant information regarding how it was done. The correlations with the other measures of national intelligence, except the PISA student assessment study, are good.
Lynn and Vanhanen's findings
In IQ and the Wealth of Nations, and subsequently IQ and Global Inequality, Richard Lynn and Tatu Vanhanen obtained estimates of average IQs for 113 nations by searching past publications. They estimated IQs of 79 other nations based on neighboring nations. They also created an estimate of "quality of human conditions" for each nation based on gross national product per capita, adult literacy rate, fraction of the population to enroll in secondary education, life expectancy, and rate of democratization. Lynn and Vanhanen found a substantial correlation between national IQ 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 to it. They regard nutrition as the most important environmental factor, and education a secondary factor.
In a 2010 paper, Lynn updated his estimates of national IQs from IQ and Global Inequality, and presented new calculated 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.
Several negative reviews of the book have been published in the scholarly literature. Susan Barnett and Wendy Williams wrote that "we see an edifice built on layer upon layer of arbitrary assumptions and selective data manipulation. The data on which the entire book is based are of questionable validity and are used in ways that cannot be justified." They also wrote that cross country comparisons are "virtually meaningless."
Wicherts, Dolana and Van Der Maas' analysis
In 2009 Jelte M. Wicherts, Conor V. Dolana, 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 that including studies excluded in "IQ and Global Inequality" resulted in average IQ of 82 for sub-Saharan Africa, 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.
International student assessment studies
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 finds evidence for 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 leads to increased well-being later on.
Limitations and criticisms of the data sets
Limitations and criticisms of the IQ-data collections
Rindermann (2007) writes that the mixture of many different tests and the not always clear 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 for an estimation 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 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".
As noted above, the article "A systematic literature review of the average IQ of sub-Saharan Africans" (2009) argued that a number of studies showing higher IQ values for sub-Saharan Africa had been excluded by "IQ and Global Inequality". Regarding four studies comparing and finding agreement between Lynn's estimated national IQs and the student assessment tests, they disagree regarding sub-Saharan Africa but write "these four studies appear to validate national IQs in other parts of the world." Richard Lynn and Gerhard Meisenberg (2009) replied that "critical evaluation of the studies presented by WDM shows that many of these are based on unrepresentative elite samples" and that a further literature review, including taking into account results in mathematics, science, and reading, gave "an IQ of 68 as the best reading of the IQ in sub-Saharan Africa". Wicherts and colleagues (2010) in another reply made several examinations of unrepresentativeness and stated: "In light of all the available IQ data of over 37,000 African testtakers, only the use of unsystematic methods to exclude the vast majority of data could result in a mean IQ close to 70. On the basis of sound methods, the average IQ remains close to 80." Consequently some later studies using IQ data have checked their results against data from both sources.
With regards to Croatia, Lynn used data which Pitirim Sorokin conducted in 1952, which collected the IQs of 299 children ages thirteen to sixteen.
Limitations and criticisms 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 national organizers sometimes differ in implementation and exclusion rates differ.
Correlations with national IQ
Hunt writes that despite the limitations of Lynn and Vanhanen's data, their conclusions about the correlation between IQ and measures of social well-being probably are correct. This is partially driven by large differences in prosperity and intelligence test scores between regions of the world, with the values highest for North America, Europe and Northeast Asia, lowest for sub-Saharan Africa and South Asia, and in between 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. A 2013 regression analysis by Gregory B. Christainsen examined the question of how much national IQ influenced national wealth, and how much the causality occurred in the opposite direction. This analysis concluded that national IQ primarily influenced national wealth, rather than the reverse.
Causes of the national differences
Since the 20th century, there have been worldwide continual increases in measured IQ. This rise has been correlated with degrees of rising education levels, and as such may provide a partial explanation for observed differences in average IQ scores between nations. One recent study suggests that the Flynn effect has ended in some developed nations such as Denmark and Norway, and suggests that this is due to immigration from countries with lower education levels or due to changes in education policies within the countries. 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.
Controversially, the two books argued for a large genetic explanation. Such a role of genetics may or may not be related to race which is itself a controversial topic. Lynn argued further for this in the books Race Differences in Intelligence: An Evolutionary Analysis (2006) and The Global Bell Curve: Race, IQ, and Inequality Worldwide (2008).
Kanazawa (2008) also argues for a genetic role. He 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 variance in national IQ.
In contrast, Wicherts, Borsbooma, and Dolana (2010) criticized this and some other 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. "In addition, we show that national IQs are strongly confounded with the current developmental status of countries. National IQs correlate with all the variables that have been suggested to have caused the Flynn Effect in the developed world."
Eppig, Fincher, and Thornhill (2010) states that distance from Africa, temperature, and most importantly by a large margin, prevalence of infectious disease predict national IQs. Education, literacy, GDP, and nutrition were not important as independent factors (however, 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."
- Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. Page 436-437.
- Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. Page 443-445.
- Rindermann,H. (2007). The g-factor of international cognitive ability comparisons: The homogeneity of results in PISA, TIMSS, PIRLS and IQ-tests across nations. European Journal of Personality, 21, 6 67−706 http://onlinelibrary.wiley.com/doi/10.1002/per.634/abstract
- Buj, V. (1981). Average IQ values in various European countries. Personality and Individual Differences, 2, 168–169
- Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. Page 437-439.
- Mankind Quarterly, Vol. 50, No. 4 (Summer 2010) pp. 275-296, "National IQs updated for 41 Nations", Richard Lynn. http://www.mankindquarterly.org/summer2010_lynn.html
- Richard Lynn and Tatu Vanhanen. Intelligence: A Unifying Construct for the Social Sciences. Ulster Institute for Social Research, 2013.
- Barnett, Susan M. and Williams, Wendy (August 2004). "National Intelligence and the Emperor's New Clothes". Contemporary Psychology: APA Review of Books 49 (4): 389–396. doi:10.1037/004367.
- Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. Page 439-440.
- Jelte M. Wicherts, Conor V. Dolana, and Han L.J. van der Maas, A systematic literature review of the average IQ of sub-Saharan Africans, Intelligence, Volume 38, Issue 1, January–February 2010, Pages 1-20, http://dx.doi.org/10.1016/j.intell.2009.05.002
- Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. Page 440-443.
- "The average IQ of sub-Saharan Africans: Comments on Wicherts, Dolan, and van der Maas", Richard Lynna and Gerhard Meisenberg, Intelligence, Volume 38, Issue 1, January–February 2010, Pages 21-29 http://dx.doi.org/10.1016/j.intell.2009.09.009
- The dangers of unsystematic selection methods and the representativeness of 46 samples of African test-takers, Jelte M. Wicherts, Conor V. Dolana and Han L.J. van der Maas, Intelligence Volume 38, Issue 1, January–February 2010, Pages 30-37
- Christopher Eppig, Corey L. Fincher, and Randy Thornhill, Parasite prevalence and the worldwide distribution of cognitive ability Proc R Soc B 2010: rspb.2010.0973v1-rspb20100973. http://rspb.royalsocietypublishing.org/content/early/2010/06/29/rspb.2010.0973.abstract
- IQ in the Utility Function: Cognitive skills, time preference, and cross-country differences in savings rates, Garett Jones and Marta Podemska, (Presented at Canadian Economics Association meetings, June 2010) http://mason.gmu.edu/~gjonesb/
- Case for Non-Biased Intelligence Testing Against Black Africans Has Not Been Made: A Comment on Rushton, Skuy, and Bons (2004) 1*, Leah K. Hamilton1, Betty R. Onyura1 and Andrew S. Winston International Journal of Selection and Assessment Volume 14 Issue 3 Page 278 - September 2006
- Culture-Fair Cognitive Ability Assessment Steven P. Verney Assessment, Vol. 12, No. 3, 303-319 (2005)
- The attack of the psychometricians. DENNY BORSBOOM. PSYCHOMETRIKA VOL 71, NO 3, 425–440. SEPTEMBER 2006.
- Hunt, Earl. Human Intelligence. Cambridge University Press, 2011. Page 436-437.
- Hunt, Earl and Wittman, Werner. "National Intelligence and national prospertity." Intelligence 36:1, 2008.
- Christainsen, Gregory. "IQ and the wealth of nations: How much reverse causality?" Intelligence 41:5, 2013.
- Teasdale TW, Owen DR (2008). "Secular declines in cognitive test scores: A reversal of the Flynn Effect" (PDF). Intelligence 36 (2): 121–6. doi:10.1016/j.intell.2007.01.007.
- Temperature and evolutionary novelty as forces behind the evolution of general intelligence, Satoshi Kanazawa, Intelligence, Volume 36, Issue 2, March–April 2008, Pages 99-108 http://dx.doi.org/10.1016/j.intell.2007.04.001
- Why national IQs do not support evolutionary theories of intelligence, Jelte M. Wicherts, Denny Borsbooma and Conor V. Dolana, Personality and Individual Differences, Volume 48, Issue 2, January 2010, Pages 91-96, http://dx.doi.org/10.1016/j.paid.2009.05.028
- Christopher Eppig, Corey L. Fincher, and Randy Thornhill Parasite prevalence and the worldwide distribution of cognitive ability Proc R Soc B 2010: rspb.2010.0973v1-rspb20100973. http://rspb.royalsocietypublishing.org/content/early/2010/06/29/rspb.2010.0973.abstract