In 2002, a book was published that had both a considerable impact on intelligence research and a substantial public reception. The name of this book was “IQ and the Wealth of Nations<\/em>“, written by the British psychologist Richard Lynn, Professor Emeritus at the University of Ulster, UK, and the Finnish professor of political science at the University of Tampere, Finland, Tatu Vanhanen (\u20202015), well known for creating the Vanhanen Index of Democratization (Lynn & Vanhanen, 2002; Lynn, 2017; Vanhanen, 2003). One highlight of this book was a list of average national IQs for 185 nations, of which 81 national IQs were collected and calculated directly from studies, the remaining 104 national IQs being estimated from the IQs of nearby and ethnically comparable countries. This list was expanded and improved over time, first in “Race Differences in Intelligence: An Evolutionary Analysis<\/em>” (Lynn, 2006) next in “The Global Bell Curve: Race, IQ, and Inequality Worldwide<\/em>” (Lynn, 2008), and finally in “Intelligence: A Unifying Construct for the Social Sciences<\/em>” (Lynn & Vanhanen, 2012a).<\/p>\n To calculate the national IQs, Lynn and Vanhanen collected IQ test results from samples that were as representative or applicable as possible of\/to their respective national populations, and set these results on a scale with the IQ of the UK at 100. This comparison IQ is often called the Greenwich IQ Mean, after Greenwich Mean Time. Some corrections were needed, in the main to adjust for the FLynn Effect, the increase of IQs ascending over time during the 20th<\/sup> century in many nations (Lynn, 1982; Flynn, 1984; Pietschnig & Voracek, 2015). If more than one measurement of IQ was available for a nation, the mean or median was calculated. IQs for other nations for which no measurements could be found were calculated as means of their adjacent nations.<\/p>\n Fig. 1 is based on the 2012 version and shows how the national IQ levels form geographic clusters, with the lowest scores, between 60 and 80, in Sub-Saharan Africa; middling scores, between 80 and 95, mostly in Arabian or Middle Eastern, South Asian, Oceanian and South American nations; high scores, between 95 and 102, in European nations or those with a population descended mostly from Europe; and finally very high scores, above 102, in Northeast Asian nations.<\/p>\n Fig. 1:\u00a0 <\/strong>National IQs as calculated or estimated by Lynn and Vanhanen (2012).<\/p>\n Such a non-random global pattern suggests that national IQs might be related to other unequally distributed factors; indeed, a large amount of significant correlates, summarized by Lynn and Vanhanen (2012b) have been found between national IQs and other international variables. Statistical relations were found between national IQs and variables in the fields of education (e.g. results from school assessment, literacy, etc.); cognitive outputs (e.g. scientific publications, patents, Nobel prizes, etc.); economics (e.g. GDP\/c in varying designs, economic growth, income, etc.); politics (e.g. democracy, freedom, corruption, etc.); social behavior (e.g. crime, suicide rate, happiness, modernization, etc.); medicine (e.g. infant mortality, HIV rates, fertility, etc.); geography (temperature, latitude); and anthropology (skin color).<\/p>\n In most cases, correlations were positive for those variables for which higher scores are usually considered desirable, and negative for variables for which lower scores are usually considered undesirable. On average, nations with higher IQs had stronger economies; were healthier, wealthier, and more educated; and were more modernized, politically stable, and peaceful (national suicide rates are an exception: suicides are less common in low-IQ nations). As the map suggests, there are strong positive correlations between national IQs and average skin brightness of a nation\u2019s population (.69 to .92), and between national IQ and a nation\u2019s mean latitude (.68 to .72). More recently, variables from population genetics joined in, such as population frequencies of intelligence-associated SNPs (e.g. Piffer, 2013, 2015), Y-chromosomal haplogroups (Rindermann, Woodley, & Stratford, 2012) or genetic distances in general (Le\u00f3n & Burga-Le\u00f3n, 2015; Becker & Rindermann, 2016).<\/p>\n Hunt and Sternberg (2006) called the list of national IQs “far from ideal” in a review of Templer and Arikawa\u2019s (2006) paper of correlations between national IQs, skin color, and income. They (Hunt and Sternberg) criticized the non-representativeness of the included samples; Lynn and Vanhanen\u2019s failure to weight the studies for sample size; and the practice of estimating some countries\u2019 IQs from the IQs of nearby and ethnically comparable countries.<\/p>\n Malloy (2013-2014) addressed Lynn and Vanhanen\u2019s work in great detail at the Human Varieties blog<\/a>. A huge amount of different measurements of IQ were collected for 15 nations or insular areas in Southeast Asia or the Caribbean. Some national means were very close to those from Lynn and Vanhanen; others showed large differences, especially Cambodia. I compared the national IQs from both sources (some numbers listed in the Malloy column were calculated by me from Malloy\u2019s data) in Table 1 and got a correlation of .47 (N\u00a0<\/em>= 12; p ><\/em>\u00a00.050) with and .79 (N\u00a0<\/em>= 11; p <<\/em>\u00a00.001) without Cambodia. On the one hand, these numbers suggest considerable reliability of Lynn and Vanhanen\u2019s results; on the other hand, some ambiguities, errors, and deviations were reported by Malloy, suggesting that Lynn and Vanhanen\u2019s IQs are not as reliable as have sometimes been believed.<\/p>\n![\"\"](\"http:\/\/viewoniq.org\/wp-content\/uploads\/2017\/12\/WORLD-IQLV-MAP-V1.2.bmp\")
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