IQ and Global Inequality


IQ and Global Inequality
IQ and Global Inequality

IQ and Global Inequality is a controversial 2006 book by psychologist Richard Lynn and political scientist Tatu Vanhanen.[1] IQ and Global Inequality is follow-up to their 2002 book IQ and the Wealth of Nations,[2] an expansion of the argument that international differences in current economic development are due in part to differences in average national intelligence as indicated by national IQ estimates, and a response to critics. The book was published by the controversial Washington Summit Publishers.

Lynn and Vanhanen's research on national IQs has attracted academic attention from several fields with both praise and criticism. Various authors have cited the book to reach further conclusions from the book's statements or to criticize or find support for the book's scores, methodology, and conclusions.[3][4][5][6][7][8] Several other data sets of estimated average national cognitive ability exist as explained in nations and intelligence.

Contents

Summary

Estimated national average IQs according to IQ and Global Inequality.
  ≤65
  70
  75
  80
  85
  90
  95
  100
  ≥105
  N/A
  • Chapter 1 summarizes theories of economic growth.
  • Chapter 2 defines and describes intelligence.
  • Chapter 3 argues that the scientific literature indicates that intelligence is a determinant of incomes and related phenomena among individuals within a number of countries.
  • Chapter 4 describes the collection and determination of national IQ, presenting calculated IQs for 113 countries and estimated IQs for an additional 79 countries. This represents all countries with population greater than 40,000.
  • Chapter 5 introduces a new statistic, the quality of human condition index (QHC) and 12 alternative variables that measure human conditions.
  • Chapter 7 focuses on the relationship between national IQ and QHC, which Lynn and Vanhanen report to be strongly correlated.
  • Chapter 8 examines the relationship between national IQ and 12 alternative variables, which Lynn and Vanhanen report are also correlated with national IQ.
  • Chapter 9 discusses the genetic and environmental contributions to differences in national intelligence, and argues that racial composition of the population is a major factor.
  • Chapter 10 considers the causal relationship between national IQ and important variables related to global inequality.
  • Chapter 11 discusses and responds to criticisms made to Lynn and Vanhanen's theory by reviewers.
  • Chapter 12 summarizes the book and discusses policy recommendations.

Significant correlations with higher national IQ were found for a number of factors: higher GDP/capita, higher adult literacy rate, higher gross tertiary education enrollment ratio, higher life expectancy at birth, higher level of democratization 2002 (Tatu Vanhanen's Index of Democratization), higher Human Development Index, higher Gender-related Development Index, higher economic growth rate, lower Gini index of inequality in income or consumption, lower population below the $2 a day international poverty line, lower measures of undernourishment, lower maternal mortality ratio, lower infant mortality rate, higher Corruption Perceptions Index, higher Economic Freedom of the World ratings, higher Index of Economic Freedom ratings, and more narrow population pyramid (MU Index).

Reception

The book received a mixed reception ranging from praise to dismissal.

In a review J. Philippe Rushton, President of the Pioneer fund that has been a long time funder of research by Lynn,[9][10] writes that the book extends and answers criticisms against the earlier work in several ways. The number of nations for which there were IQ tests available increased from 81 to 113. The correlation between IQ and income per person was 0.68 which is virtually identical to the one reported in the earlier book. The book compared the IQ values for the 32 new nations for which IQ tests were available with the estimations for these nations in the earlier book which was based on averaging neighboring nations values. The correlation of 0.91 was very high. Rushton thus conclude that this method is remarkably accurate.[5]

Rushton states that the authors also compared the results of the IQ tests for those nations were several were available (71 nations). They found a very high correlation of 0.95 and thus concluded that the IQ testing have a very high reliability regarding measuring IQ. The authors furthermore compared the national IQs to national scores of school students in tests of mathematics and science. The correlations were between 0.79 and 0.89. This, Rushton writes, establishes that the national IQs have very high validity as measures of national differences in cognitive ability.[5]

The authors argue for a substantial role of genetics and race in explaining these differences. They were led to this conclusion from observing racial clusters regarding national IQs. Thus, the six East Asian nations all have IQs in the range between 105 and 108. The 29 European nations all have IQs in the range between 92 and 102. The 19 nations of sub-Saharan Africa all have IQs in the range between 59 and 73. Rushton thus argues that "They show that there is remarkable consistency in the IQs of nations when these are classified into racial clusters." The book also argues for feedback between genes and environment. For instance, a genetically caused high national IQ leads to high per capita incomes which enables high quality nutrition, education and health care for children which enhance their intelligence.[5]

Kanazawa when commenting on using the book as a data source makes statements similar to Rushton's.[11]

The methods of the study were criticized by Richard E. Nisbett for relying on small and haphazard samples and for ignoring data that did not support the conclusions.[7]

In an article published in European Journal of Personality, Heiner Rindermann compared the IQ scores from the book to a large number of international student assessment studies on subjects such as reading, mathematics, science, and problem solving, and found them to be highly intercorrelated. Statistical analyses indicated that the results could be explained by an underlying general cognitive ability. More than 30 commentaries on Rindermann's findings were published in the same issue of the journal.[8]

The study A systematic literature review of the average IQ of sub-Saharan Africans by Jelte M. Wicherts and colleagues stated that:

"For instance, Lynn and Vanhanen (2006) accorded a national IQ of 69 to Nigeria on the basis of three samples (Fahrmeier, 1975; Ferron, 1965; Wober, 1969), but they did not consider other relevant published studies that indicated that average IQ in Nigeria is considerably higher than 70 (Maqsud, 1980a,b; Nenty & Dinero, 1981; Okunrotifa, 1976). As Lynn rightly remarked during the 2006 conference of the International Society for Intelligence Research (ISIR), performing a literature review involves making a lot of choices. Nonetheless, an important drawback of Lynn (and Vanhanen)'s reviews of the literature is that they are unsystematic."[6]

However, the study also did its own literature review on the average IQ of sub-Saharan Africans. It did not find as low a value as the book, below 70, but the estimated average value of 82 is still low compared to industrialized nations. Regarding four studies comparing and finding agreement between Lynn's estimated national IQs and the international 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."[6]

Richard Lynn and Gerhard Meisenberg in turn 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".[12] Wicherts and colleagues in yet another reply 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. Although this mean IQ is clearly lower than 100, we view it as unsurprising in light of the potential of the Flynn Effect in Africa (Wicherts, Borsboom, & Dolan, 2010) and common psychometric problems associated with the use of western IQ tests among Africans."[13]

Consequently, some later studies using average national IQ data have checked their results against both data sets.[14][15]

Jones and Schneider commenting on the differences to the earlier book write "LV (2002) assembled results from 183 conventional IQ tests, both verbal and visual, given in 81 countries across the entire 20th century;they used hundreds of IQ tests from 113 countries across centuries in LV (2006). They aggregated these results using best practice methods to create estimates of “national average IQ” for these countries. LV show in those works as well as in Lynn (2006) that the IQ gaps between regions of the world have not appreciably changed during the 20th century."[16]

In the summer of 2010 Lynn presented new calculated national IQs for 25 countries which had previously only been estimated from neighboring nations IQs and revised national IQs for 16 countries. "Numerous cultural, biological, economic, political and medical correlates of country-level intelligence have been demonstrated in previous studies. It is recommended that the new and updated IQs presented in this paper should be used as the best estimates of the average IQs for these countries by scholars investigating these correlates."[17]

Associations between national IQ and other factors

Quality of human conditions index

Richard Lynn and Tatu Vanhanen's QHC index.
   11
   15
   20
   30
   40
   50
   60
   70
   80
   85
   89
   N/A

The quality of human conditions (QHC) index was computed from five variables.

  1. purchasing power parity Gross National Income (PPP-GNI) per capita 2002
  2. adult literacy rate 2002
  3. gross tertiary enrollment ratio
  4. life expectancy at birth 2002
  5. the level of democratization 2002 (Tatu Vanhanen's Index of Democratization)

Values of the index range from 10.7 (Burkina Faso) to 89 (Norway). Lynn and Vanhanen write that they would have preferred to include a sixth measure, an indicator of income inequality, but that statistical data for that variable was not available for all countries. They write that the QHC index differs significantly from other widely used indexes (such as the Human Development Index) in that QHC also measures democratization. Some of their claims have received support in a 2007 study by Rindermann.[18]

All countries Calculated IQ
(113 countries)
Estimated IQ
(79 countries)
Total
(192 countries)
QHC 0.805 0.725 0.791
PPP GNI per capita 2002 0.693 0.342 0.616
Adult literacy rate 2002 0.642 0.655 0.655
Tertiary enrollment ratio 0.746 0.699 0.745
Life expectancy at birth 2002 0.765 0.690 0.750
Index of Democratization 2002 0.569 0.322 0.530
Excluding smallest countries Calculated IQ
(98 countries)
Estimate IQ
(62 countries)
Total
(160 countries)
QHC 0.846 0.800 0.839
PPP GNI per capita 2002 0.739 0.266 0.649
Adult literacy rate 2002 0.710 0.746 0.733
Tertiary enrollment ratio 0.778 0.734 0.780
Life expectancy at birth 2002 0.833 0.753 0.817
Index of Democratization 2002 0.598 0.408 0.584

Other measures of global inequality

The relationship of national IQ to twelve other measures of global inequality were examined.

  1. Human Development Index (HDI)
  2. Gender-related Development Index (GDI)
  3. Economic growth rate (EGR)
  4. Gini index of inequality in income or consumption (Gini)
  5. Population below $2 a day international poverty line (Poverty)
  6. Measures of undernourishment (PUN)
  7. Maternal mortality ratio (MMR) and infant mortality rate (IMR)
  8. Corruption Perceptions Index (CPI)
  9. Economic freedom ratings (EFR)
  10. the Index of Economic Freedom (IEF)
  11. Population pyramids (MU-index)
  12. Human happiness and life-satisfaction.

All twelve measures of global inequality are significantly correlated with the QHC index. According to the book, eleven of the twelve measures are significantly correlated with national IQ. The measures of human happiness and life satisfaction are not significantly correlated with national IQ.

Correlations IQ QHC
HDI 0.776 0.940
GDI 0.849 0.951
EGR 3 0.747 0.840
EGR 4 0.709 0.871
Gini −0.538 −0.464
Poverty −0.653 −0.799
PUN 1 −0.500 −0.648
MMR −0.730 −0.759
IMR −0.771 −0.861
CPI 0.591 0.762
EFR 0.606 0.674
IEF 0.418 0.620
MU-index 0.806 0.902
Happiness 0.029 0.315
Life satisfaction 0.033 0.396

Latitude and temperature

Correlation Latitude Temperature
Degrees latitude 1 -0.885
Annual mean temperature -0.885 1
National IQ 0.677 -0.632
QHC 0.659 -0.562
PPP GNI per capita 2002 0.528 -0.407
Adult literacy rate 2002 0.482 -0.467
Tertiary enrollment ratio 0.718 -0.649
Life expectancy at birth 2002 0.505 -0.379
Index of Democratization 2002 0.512 -0.460

National IQ and QHC values

Lynn and Vanhanen base their analysis on data gathered from a literature review. They selected IQ data from studies which covered 113 nations. For another 79 nations, they estimated the mean IQs on the basis of the arithmetic means of the measured IQs of neighboring countries. They justify this method of estimation by pointing out that the correlation between the estimated national IQs they reported in IQ and the Wealth of Nations and the measured national IQs since obtained is very high (0.913). In the chart below, these estimates have been marked with an asterisk (*). The chart also includes the measured and estimated IQs from IQ and the Wealth of Nations.

Lynn and Vanhanen calculated the national IQs in relation to a British mean of 100, with a standard deviation of 15. They adjusted all test results to account for the Flynn effect: adjustments were 2 points per decade for Raven's Progressive Matrices and 3 points per decade for all other types of tests. When two IQ studies were used from one country, their mean was calculated, whereas when three or more were available, the median was used.[1] Lynn and Vanhanen recommend the provision of iodine and other micronutrients as a way to increase cognitive functioning in the Third World. The book additionally states that part of the reason IQ's have shrunk since the prior book was published, is due to more immigration from the Third World. Sweden's IQ for example dropped from 101% to 99%, and Germany 101 to 99. Since national immigration has been active prior to the first book, ethnic IQ is most likely even higher.

Country/Region IQ (2002)[2] IQ (2006)[1] PPP-GNI per capita 2002[1] QHC[1]
 Hong Kong 107 108 27,490 60.8
 Singapore 103 108 23,730 60.7
 North Korea 105* 106* 1,000 38
 South Korea 106 106 16,960 75.4
 Japan 105 105 27,380 71.4
 Republic of China (Taiwan) 104 105 23,400 79.4
 People's Republic of China 100 105 4,520 39.7
 Italy 102 102 26,170 78.9
 Iceland 98* 101 29,240 80
 Mongolia 98* 101* 1,710 48.1
 Switzerland 101 101 31,840 82.2
 Austria 102 100 28,910 80.7
 Luxembourg 101* 100* 53,230 76.4
 Netherlands 102 100 28,350 82.8
 Norway 98 100 36,690 89
 United Kingdom 100 100 26,580 76.7
 Germany 102 99 26,980 78
 Belgium 100 99 28,130 84.1
 Canada 97 99 28,930 77.8
 Estonia 97* 99 11,630 64.5
 Finland 97 99 26,160 85.1
 New Zealand 100 99 20,550 76.2
 Poland 99 99 10,450 62.7
 Sweden 101 99 25,820 82.9
 Andorra N/A 98* 19,000 58.7
 Spain 99 98 21,910 75.8
 Australia 98 98 27,440 82.8
 Czech Republic 97 98 14,920 64.5
 Denmark 98 98 30,600 85.4
 France 98 98 27,040 78.1
 Hungary 99 98 13,070 64.1
 Latvia 97* 98* 9,190 65.5
 United States 98* 98* 36,120 86.6
 Belarus 96* 97* 5,500 57.2
 Malta 95* 97 17,710 66.4
 Russia 96 97 8,080 64.5
 Ukraine 96* 97* 4,800 61.8
 Moldova 95* 96* 1,600 46.2
 Slovakia 96 96 12,590 63.2
 Uruguay 96 96 7,710 64
 Israel 94 95 19,000 75.3
 Portugal 95 95 17,820 67
 Armenia 93* 94* 3,230 50.2
 Georgia 93* 94* 2,270 51.2
 Kazakhstan 93* 94* 5,630 49
 Romania 94 94 6,490 53
 Vietnam 96* 94* 2,300 39.6
 Argentina 96 93 10,190 64.7
 Bulgaria 93 93 7,030 59.1
 Greece 92 92 18,770 76.1
 Malaysia 92 92 8,500 78.5
 Ireland 93 92 29,570 52.1
 Brunei 92* 91* 19,210 50.8
 Cambodia 89* 91* 1,970 28.6
 Cyprus 92* 91* 18,650 67.6
 Lithuania 97* 91 10,190 65.4
 Republic of Macedonia 93* 91* 6,420 54.4
 Thailand 91 91 6,890 50.3
 Albania 70* 70* 4,960 51.2
 Bermuda N/A 90 36,000 75.8
 Bosnia and Herzegovina N/A 90* 5,800 51.4
 Chile 93* 90 9,420 59.5
 Croatia 90 90 10,000 61.7
 Kyrgyzstan 87* 90* 1,560 48.1
 Turkey 90 90 6,300 50.2
 Mexico 87 90 12,500 52.9
 Cook Islands N/A 89 5,000 45.7
 Costa Rica 91* 89* 8,650 53.7
 Laos 89* 89 1,660 24.9
 Mauritius 81* 89 10,820 52.2
 Suriname 89 89 6,590 50.6
 Ecuador 80 88 3,340 47.4
 Samoa 87 88 5,570 49.7
 Azerbaijan 87* 87* 3,010 47.2
 Bolivia 85* 87 2,390 49.7
 Brazil 87 87 7,450 51.1
 East Timor N/A 87* 3,940 46.7
 Guyana 84* 87* 3,070 40.2
 Indonesia 89 87 1,600 28.1
 Iraq 87 87 1,027 30.7
 Burma 86* 87* 930 42.4
 Tajikistan 87* 87* 1,640 27.5
 Turkmenistan 87* 87* 4,780 41.7
 Uzbekistan 87* 87* 1,640 39.4
 Kuwait 83* 86 17,780 49.9
 Philippines 86 86 4,450 51.6
 Seychelles 81* 86* 18,232 60.6
 Tonga 87 86 6,820 40.5
 Cuba 85 85 5,259 46.2
 Fiji 84 85 5,330 51.9
 Kiribati 84* 85* 800 37.1
 New Caledonia N/A 85 21,960 54.9
 Peru 90 85 4,880 49.2
 Trinidad and Tobago 80* 85* 9,000 52
 Yemen 83* 85 800 24.5
 Afghanistan 83* 84* 700 13.2
 Belize 83* 84* 15,960 56.1
 Colombia 88 84 5,490 44.2
 Federated States of Micronesia 84* 84* 6,150 48.4
 Iran 84 84 6,690 40.2
 Jordan 87* 84 4,180 43.4
 Marshall Islands 84 84 1,600 44.2
 Morocco 85 84 2,000 39.9
 Pakistan 81* 84 1,730 31.7
 Panama 84* 84* 1,960 26.2
 Paraguay 85* 84 6,060 56.6
 Puerto Rico 84 84 4,590 45.2
 Saudi Arabia 83* 84* 15,800 63.6
 Solomon Islands 84* 84* 12,660 44.1
 The Bahamas 78* 84* 1,590 41.5
 United Arab Emirates 83* 84* 24,030 48.8
 Vanuatu 84* 84* 2,850 31.4
 Venezuela 88* 84 5,220 47.4
 Algeria 84* 83* 5,530 39.9
 Bahrain 83* 83* 16,190 49.3
 Libya 84* 83* 7,570 49.3
 Oman 83* 83* 13,000 40.6
 Papua New Guinea 84* 83 2,180 38.4
 Syria 87* 83 5,348 38.9
 Tunisia 84* 83* 6,440 40.6
 Bangladesh 81* 82* 1,720 29.8
 Dominican Republic 84* 82 6,270 46.8
 India 81 82 2,650 36.3
 Lebanon 86 82 4,600 55.8
 Madagascar 79* 82 730 28.6
 Egypt 83 81 3,810 37.3
 Honduras 84* 81 2,540 41.9
 Maldives 81* 81* 4,798 38.5
 Nicaragua 84* 81* 2,350 41.3
 Northern Mariana Islands N/A 81 12,500 51.3
 Barbados 78 80 14,660 60.9
 Bhutan 78* 80* 1,969 24.1
 El Salvador 84* 80* 4,790 42.6
 Guatemala 79 79 4,040 34.6
 Sri Lanka 81* 79 3,510 47.7
 Nepal 78 78 1,370 26.9
 Qatar 78 78 19,844 45.6
 Comoros 79* 77* 1,640 24.6
 Cape Verde 78* 76* 4,920 40.5
 Mauritania 73* 76* 1,790 20.5
 Uganda 73 73 1,360 25.4
 Kenya 72 72 1,010 27.3
 South Africa 72 72 9,810 38.3
 Tanzania 72 72 580 23.2
 Ghana 71 71 2,080 33.7
 Grenada 75* 71* 6,600 45.3
 Jamaica 72 71 3,680 46.5
 Saint Vincent and the Grenadines 75* 71 5,190 48.4
 Sudan 72 71 1,740 24.6
 Zambia 77 71 800 21.8
 Antigua and Barbuda 75* 70* 10,390 53.2
 Benin 69* 70* 1,060 20.5
 Botswana 72* 70* 7,740 29.4
 Namibia 72* 70* 6,880 31.1
 Rwanda 70* 70* 1,260 18.5
 Togo 69* 70* 1,450 26
 Burundi 70* 69* 630 15.2
 Côte d'Ivoire 71* 69* 1,450 18.1
 Malawi 71* 69* 570 24.3
 Mali 68* 69* 840 13.4
 Niger 67* 69* 800 13.5
 Nigeria 67 69 800 27.3
 Angola 69* 68* 1,840 13.7
 Burkina Faso 66* 68* 1,090 10.7
 Chad 72* 68* 1,010 20.4
 Djibouti 68* 68* 2,040 22
 Eritrea 68* 68* 1,040 21.4
 Somalia 68* 68* 500 15.2
 Swaziland 72* 68* 4,730 22.2
 Dominica 75* 67 4,960 48.8
 Guinea 63 67 2,060 22.5
 Guinea-Bissau 63* 67* 680 20.3
 Haiti 72* 67* 1,610 20.4
 Lesotho 72* 67* 2,970 24.3
 Liberia 64* 67* 1,000 21.2
 Saint Kitts and Nevis 75* 67* 10,750 45.5
 São Tomé and Príncipe 59* 67* 1,317 37.9
 Senegal 64* 66* 1,660 20.7
 The Gambia 64* 66* 1,540 21.3
 Zimbabwe 66 66 2,180 25.2
 Republic of the Congo 73 65 630 17.9
 Cameroon 70* 64 1,910 23.1
 Central African Republic 68* 64 1,170 19.1
 Democratic Republic of the Congo 65 64 700 26.9
 Ethiopia 71 71 780 29.7
 Gabon 66* 64* 5,530 32.2
 Mozambique 72* 64 990 18
 Sierra Leone 64 64 500 13.8
 Saint Lucia 75* 62 4,950 51.1
 Equatorial Guinea 59 59 9,100 30.4

See also

Theories of Race and Intelligence:

Publications of Race and Intelligence:

External links

References

  1. ^ a b c d e Richard Lynn and Tatu Vanhanen (2006). IQ and Global Inequality. Washington Summit Publishers: Augusta, GA. ISBN 1593680252
  2. ^ a b Lynn, R. and Vanhanen, T. (2002). IQ and the wealth of nations. Westport, CT: Praeger. ISBN 0-275-97510-X
  3. ^ "Relevance of education and intelligence at the national level for politics: Democracy, rule of law and political liberty" (PDF). http://groups.uni-paderborn.de/rindermann/materialien/PublikationsPDFs/ISIRSF.pdf.  Paper by Heiner Rindermann.
  4. ^ Älykkyyden tabu murtuu? Review by J.P. Roos in Sosiologia 3/2007.
  5. ^ a b c d Review by J. Philippe Rushton in Personality and Individual Differences, 2006, 41, 983-5. http://www.rlynn.co.uk/index.php?page=richard-lynn-and-tatu-vanhanen-iq-and-global-inequality-2006
  6. ^ a b c Wicherts, J. M., et al., A systematic literature review of the average IQ of Sub-Saharan Africans, Intelligence (2009), http://dx.doi.org/10.1016/j.intell.2009.05.002
  7. ^ a b Nisbett, Richard. 2009. Intelligence and how to get it. pp. 215.
  8. ^ a b 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
  9. ^ http://www.pioneerfund.org/Grantees.html
  10. ^ Lynn & Vanhanen 2002 p.2
  11. ^ 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
  12. ^ "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
  13. ^ 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
  14. ^ 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/
  15. ^ 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
  16. ^ IQ IN THE PRODUCTION FUNCTION: EVIDENCE FROM IMMIGRANT EARNINGS, GARETT JONES1, W. JOEL SCHNEIDER2, conomic Inquiry, Volume 48, Issue 3, pages 743–755, July 2010 http://onlinelibrary.wiley.com/doi/10.1111/j.1465-7295.2008.00206.x/full
  17. ^ 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
  18. ^ Rindermann, Heiner: 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 (2007) 667-706 [1]

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