Misplaced Pages

Revision as of 09:56, 10 October 2010

This article needs to be updated. Please help update this article to reflect recent events or newly available information. (September 2010)

It has been suggested that this article be merged into IQ and the Wealth of Nations. (Discuss) Proposed since September 2010.

IQ and Global Inequality is a controversial 2006 book by Dr. Richard Lynn, Professor Emeritus of Psychology at the University of Ulster, Northern Ireland, and Dr. Tatu Vanhanen, Professor Emeritus of Political Science at the University of Tampere, Tampere, Finland. IQ and Global Inequality is follow-up to their 2002 book IQ and the Wealth of Nations, 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. Unlike IQ and the Wealth of Nations, the book was not published by an academic publisher but by Washington Summit Publishers.

Lynn and Vanhanen's research on IQ and economic development has attracted academic attention from several fields, with mixed reception. There has also been criticisms.

Summary

• 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.

Correlations between 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.

J. Philippe Rushton in a review writes that 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 was very high, 0.91. Rushton thus conclude that this method is remarkably accurate.

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 tests done 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.

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.

One 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."

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 quire low.

Richard Lynna 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 "an IQ of 68 as the best reading of the IQ in sub-Saharan Africa".

Studies using the national IQ scores from the book

A number of studies have accepted and used the national IQ scores from the book. Higher national education levels and IQ had a strong positive impact on democracy, rule of law and political liberty independent from GDP. Lower national IQ is associated with more violent crime. Higher national IQ is associated with more atheism. Higher national IQ is associated with more patents per person. Lower national IQs associated with higher HIV-infection rates, which is stronger effect than the association with low gross domestic product and low modernization. Both higher GDP and IQ independently reduce fertility. The study argues that "at present rates of fertility and mortality and in the absence of changes within countries, the average IQ of the young world population would decline by 1.34 points per decade and the average per capita income would decline by 0.79% per year."

Associations between national IQ and other factors

Quality of human conditions index

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 been received support in a 2007 study by Rindermann.

Other measures of global inequality

Latitude and temperature

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. Lynn and Vanhanen recommend the provision of iodine and other micronutrients as a way to increase cognitive functioning in the Third World.

Country/Region	IQ (2002)	IQ (2006)	PPP-GNI per capita 2002	QHC
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
Taiwan	104	105	23,400	79.4
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	90*	90*	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
Myanmar	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	3,730	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	63	64	780	16.7
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

• "*" Denotes estimated National IQ
• PPP-GNI = purchasing power parity gross national income.
• QHC = is a composite index called quality of human conditions.

See also

Book's Publisher

• Washington Summit Publishers

Theories of Race and Intelligence:

• Cattell Culture Fair III
• Evolution of human intelligence
• Flynn effect
• Fluid and crystallized intelligence
• General intelligence factor
• Gini coefficient
• Hominid intelligence
• Intelligence and public policy
• Race and intelligence

Publications of Race and Intelligence:

• IQ and the Wealth of Nations
• IQ and Global Inequality
• The Mismeasure of Man
• Race Differences in Intelligence
• The global bell curve

Theories of other Intelligence links:

• Brain to body mass ratio
• Height and intelligence
• Neuroscience and intelligence
• Sex and intelligence

External links

• Lynns posting of a favorable review that characterizes the 2006 work as a reply to criticisms of their earlier results
• A site critical of Lynn's claims
• National IQ means, calibrated on the basis of PISA scores and transformed from educational attainment

References

1. ^ Richard Lynn and Tatu Vanhanen (2006). IQ and Global Inequality. Washington Summit Publishers: Augusta, GA. ISBN 1593680252
2. ^ 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). Paper by Heiner Rindermann.
4. "Intelligence, Human Capital, and Economic Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach". Paper by Garett Jones and W. Joel Schneider.
5. Älykkyyden tabu murtuu? Review by J.P. Roos in Sosiologia 3/2007.
6. ^ 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
7. ^ 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
8. ^ Nisbett, Richard. 2009. Intelligence and how to get it. pp. 215.
9. "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
10. Relevance of education and intelligence for the political development of nations: Democracy, rule of law and political liberty, Heiner Rindermann, Intelligence, Volume 36, Issue 4, July-August 2008, Pages 306-322, http://dx.doi.org/10.1016/j.intell.2007.09.003
11. National differences in intelligence, crime, income, and skin color, J. Philippe Rushton and Donald I. Templer, Intelligence, Volume 37, Issue 4, July-August 2009, Pages 341-346, http://dx.doi.org/10.1016/j.intell.2009.04.003
12. Average intelligence predicts atheism rates across 137 nations, Richard Lynn, John Harvey, and Helmuth Nyborg, Intelligence, Volume 37, Issue 1, January-February 2009, Pages 11-15, http://dx.doi.org/10.1016/j.intell.2008.03.004
13. IQ, cultural values, and the technological achievement of nations, Garry A. Gelade, Intelligence, Volume 36, Issue 6, November-December 2008, Pages 711-718, http://dx.doi.org/10.1016/j.intell.2008.04.003
14. Relevance of education and intelligence at the national level for health: The case of HIV and AIDS, Heiner Rindermann and Gerhard Meisenbergb, Intelligence, Volume 37, Issue 4, July-August 2009, Pages 383-395, http://dx.doi.org/10.1016/j.intell.2009.03.005
15. Journal of Biosocial Science (2009), 41:519-535 Cambridge University Press, Wealth, Intelligence, Politics and Global Fertility Differentials, http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=5794948
16. 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

• Articles to be merged from September 2010
• Race and intelligence controversy