IQ and the Wealth of Nations
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IQ and the Wealth of Nations is a controversial 2002 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. The book demonstrates that differences in national income (in the form of per capita gross domestic product) correlate with, and arguably attributes it to, differences in average national IQ.
The book was followed by Lynn's 2006 Race Differences in Intelligence, which expands the data by nearly four times and concludes the average human IQ is presently 90 when compared to a norm of 100 based on UK data, or two thirds of a standard deviation below the UK norm.
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[edit] Outline
The book includes the authors' estimates of average IQ scores for each country, based on their analysis of published reports; their observation that national gross domestic product per capita is correlated with IQ; and their conclusion that the IQ differences correlated with income differences by a factor of about 0.7, meaning that IQ explains more than half of the variation in per capita GDP.
The authors stated that they believe IQ is due to both genetic and environmental factors. They also stated that low GDP can cause low IQ, just as low IQ can cause low GDP. (See: Positive feedback)
The authors argued that it is the ethical responsibility of rich, high-IQ nations to financially assist poor, low-IQ nations, as it is the responsibility of rich citizens to assist the poor.
The book was cited several times in the popular press, notably the British conservative newspaper The Times. Because Tatu Vanhanen is the father of Matti Vanhanen, the Finnish Prime minister, his work has received wide publicity in Finland.
[edit] National IQ estimates
Central to the book's thesis is a tabulation of what Lynn and Vanhanen believe to be the average IQs of the world's nations. Rather than do their own IQ studies (a potentially massive project), the authors average and adjust existing studies.
For most of the 185 nations, no reliable studies are available. In those cases, the authors have used an estimated value by taking averages of the IQs of surrounding nations. For example, the authors arrived at a figure of 84 for El Salvador by averaging their calculations of 79 for Guatemala and 88 for Colombia. Those estimates are not included in the calculations of income differences and do not appear in the table below.
Several cases merit specific attention. To obtain a figure for South Africa, the authors averaged IQ studies done on different ethnic groups, resulting in a figure of 72. The figures for Colombia, Peru and Singapore were arrived at in a similar manner. For People's Republic of China, the authors used a figure of 109.4 for Shanghai and adjusted it down by an arbitrary 6 points because they believed the average across China's rural areas was probably less than that in Shanghai. Another figure from a study done in Beijing was not adjusted downwards. Those two studies formed the resultant score for China (PRC).
In many cases, the IQ of a country is estimated by averaging the IQs of "neighboring countries" that are not actually neighbors of the country in question. For example, Kyrgyzstan's IQ is estimated by averaging the IQs of Iran and Turkey, neither of which is close to Kyrgyzstan – China, which is a neighbor, is not counted as such by Lynn and Vanhanen. Such arbitrary selections of "neighbors" raise additional questions as to the objectivity of the IQ estimates.[citation needed]
To account for the Flynn effect (an increase in IQ scores over time), the authors sometimes adjusted the results of older studies upward by an arbitrary number of points. Because of these arbitrary adjustments and the fact that only limited data were available for most nations, the figures should be considered rough estimates.[citation needed]
[edit] Special cases
In several cases, actual GDP did not correspond with that predicted by IQ. In these cases, the authors argued that differences in GDP were caused by differences in natural resources and whether the nation used a "planned" or "market" economy.
One example of this was Qatar, whose IQ was estimated by Lynn and Vanhanen to be about 78, yet had a disproportionately high per capita GDP of roughly USD $17,000. The authors explain Qatar's disproportionately high GDP by its high petroleum resources. Similarly, the authors think that large resources of diamonds explain the economic growth of the African nation Botswana, the fastest in the world for several decades.
The authors argued that the People's Republic of China's per capita GDP of roughly USD $4,500 could be explained by its use of a communist economic system for much of its recent history. The authors also predicted that communist nations who they believe have comparatively higher IQs, including the PRC, Vietnam, and North Korea, can be expected to gain GDP by moving from centrally-planned to market economic systems, while predicting continued poverty for African nations. Recent trends in the economy of the People's Republic of China seem to confirm this prediction, as China's GDP has quadrupled since market reforms in 1978.
[edit] Peer-reviewed papers using IQ scores from the book
Like many books, IQatWoN's results were not peer-reviewed, but peer review has occurred in subsequent articles.
A review of the book in Contemporary Psychology (49 (4). pp389-395. Barnett, Susan M.; Williams, Wendy) stated: "In sum, 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 questionably validity and are used in ways that cannot be justified."
The book is sharply criticized in a peer-reviewed paper The Impact of National IQ on Income and Growth [1]. Although critical of the IQ data, for the sake of argument the paper assumes that the data is correct but then criticizes the statistical methods used, finding no effect on growth or income.
Another peer-reviewed paper with the same assumption, Intelligence, Human Capital, and Economic Growth: An Extreme-Bounds Analysis [2], finds a strong connection between intelligence and economic growth, although the paper makes no explicit claim that IQ explains most of the difference in growth between nations.
In a reanalysis of the Lynn and Vanhanen's hypothesis, Dickerson (in press) finds that IQ and GDP data is best fitted by an exponential function, with IQ explaining approximately 70% of the variation in GDP. Dickerson concludes that as a rough approximation "an increase of 10 points in mean IQ results in a doubling of the per capita GDP."
Whetzel and McDaniel (2006) conclude that the book's "results regarding the relationship between IQ, democracy and economic freedom are robust". Moreover, they address "criticisms concerning the measurement of IQ in purportedly low IQ countries", finding that by setting "all IQ scores below 90 to equal 90, the relationship between IQ and wealth of nations remained strong and actually increased in magnitude." On this question they conclude that their findings "argue against claims made by some that inaccuracies in IQ estimation of low IQ countries invalidate conclusions about the relationship between IQ and national wealth."
Voracek (2004) used the national IQ data to examine the relationship between intelligence and suicide, finding national IQ was positively correlated with national male and female suicide rates. The effect was not attenuated by controlling for GDP.
Barber (2005) found that national IQ was associated with rates of secondary education enrollment, illiteracy, and agricultural employment. The effect on illiteracy and agricultural employment remained with national wealth, infant mortality, and geographic continent controlled.
Both Lynn and Rushton have suggested that high IQ is associated with colder climates. To test this hypothesis, Templer and Arikawa 2006 compare the national IQ data from Lynn and Vanhanen with data sets that describe national average skin color and average winter and summer temperatures (see also discussion [3]). They find that the strongest correlations to national IQ were −0.92 for skin color and −0.76 for average high winter temperature. They interpret this finding as strong support for IQ-climate association. Templer and Arikawa 2006 is currently listed as the most downloaded article in Intelligence at ScienceDirect (Jan. - March 2006).[4] Other studies using different data sets find no correlation [5][6].
Kanazawa (2006), "IQ and the wealth of states" (in press in Intelligence), replicates across U.S. states Lynn and Vanhanen's demonstration that national IQs strongly correlate with macroeconomic performance. Kanazawa finds that state cognitive ability scores, based on the SAT data, correlate moderately with state economic performance, explaining about a quarter of the variance in gross state product per capita.[7]
[edit] Critique
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Please see the discussion on the talk page. |
The figures were obtained by taking unweighted averages of different IQ tests. The number of studies is very limited; the IQ figure is based on one study in 34 nations, two studies in 30 nations. There were actual tests for IQ in 81 nations. In 104 of the world's nations there were no IQ studies at all and IQ was estimated based on IQ in surrounding nations.[8] The number of participants in each study was usually limited, often numbering under a few hundred. The exceptions to this were the United States and Japan, for which studies using more than several thousand participants are available.
Studies that were averaged together often used different methods of IQ testing, different scales for IQ values and/or were done decades apart. IQ in children is different although correlated with IQ later in life and many of the studies tested only young children.
Many nations are very heterogeneous ethnically. This is true for many developing countries. It is very doubtful that an often limited number of participants from one or a few areas are representative for the population as whole.
There are also errors in the raw data presented by authors. The results from Vinko Buj's 1981 study of 21 European cities and the Ghanaian capital Accra used different scaling from Lynn and Vanhanen's. A comparison of the reported to actual data from only a single study found 5 errors in 19 reported IQ scores [9][10].
As noted earlier, in many cases arbitrary adjustments were made by authors to account for the Flynn effect or when the authors thought that the studies were not representative of the ethnic or social composition of the nation.
There is controversy about whether IQ is a valid measurement of intelligence, especially among third-world populations. (See the article at IQ for details, as well as the article race and intelligence.) It is generally agreed many factors, including environment, culture, demographics, wealth, pollution, and educational opportunities, affect measured IQ. However, the origin of differences in IQ is disputed; according to those positing a partly genetic origin, non-hereditary factors account for anywher from 20-60% of the disparity [11]. Others posit an exclusively non-hereditary origin.
One common criticism is that many of the countries with the best average scores are those where testing (e.g. American SATs, baccalaureate examinations) is a crucial aspect of the educational process, and that many of these tests (esp. the SATs) have been shown to be very similar to IQ tests. In these nations, because students study extensively for the high-stakes examinations, it is quite possible that IQ scores are higher because people are subjected to frequent examinations for which they prepare extensively.
There are many difficulties when one is measuring IQ scores across cultures, and in multiple languages. First of all, use of the same set of exams requires translation, with all its attendant difficulties. To adapt to this, many IQ testers rely on both verbal tests, involving word analogies and the like, and non-verbal tests, which involve pictures, diagrams, and conceptual relationships (such as in-out, big-small, and so on). Roughly the same results tend to be gained with either approach.
The book reports a correlation between IQ and GDP. The book does not explicitly point out other factors which may directly cause the correlation. The Copenhagen Consensus points out that "iodine-deficient individuals score an average of 13.5 points lower in IQ tests." Countries with individuals plagued by iodine deficiency may have other factors depressing IQ, so this finding in isolation does not suggest that such a deficiency alone accounts for 13.5 IQ points. In this case, barring intervention, a nation's poverty may be self-sustaining in cases where successive generations cannot meet basic nutrition requirements.
Other factors may serve to heighten poverty while simultaneously decreasing IQ. For example, it is common for teenage children in sub-Saharan Africa to be the primary earners for their family. This is due to AIDS-related deaths of older caregivers. As children leave school to begin subsistence farming, their education ends and IQs will be markedly lower. The book does not adequately address the casual relationship of these outside factors to both poverty and intelligence.
Finally, the Flynn effect may well reduce or eliminate differences in IQ between nations in the future. One estimate is that the average IQ of the US was below 75 before factors like improved nutrition started to increase IQ scores. Some predict that considering that the Flynn effect started first in more affluent nations, it will also disappear first in these nations. Then the IQ gap between nations will diminish. However, to take a reductio ad absurdum, that the IQ difference will disappear among the babies born today, the differences will remain for decades simply because of the composition of the current workforce. Steve Sailer noted as much when discussing the workforce in both India and China (see second diagram) [12].
[edit] U.S. states and political party hoax
Some sources, such as The Economist, 15th-21st May 2004 (p.44 in the UK edition), have reported a list of average IQs of U.S. states, supposedly from IQ and the Wealth of Nations. In fact, such data do not appear in the book. At about the same time, conservative American commentator Steve Sailer exposed the table as a hoax that had already circulated among hundreds of liberal-leaning blogs and other Internet sites [13]. In the following week's edition of The Economist, the editors admitted their error and stated in the column On the trail that they "were the victim of a hoax." The hoax recurred after the 2004 U.S. election, and it was again falsely attributed to IQ and the Wealth of Nations [14], but the incident prompted yet another hoax—a claim that a computer scientist had compiled a genuine state-by-state chart using SAT and ACT scores [15]. This was allegedly compiled by Psychology "Professor Mark Jones, from Virginia Tech," who does not exist. While there is a faculty member by that name, he is an Assistant Professor in the computer science department [16]. Furthermore, no link to such a study, or evidence that he did such a study, has ever been provided.
Sailer and anthropologist Henry Harpending provide a list of mean IQs of U.S. states from 1960, arguing that the scores correlate reasonably with public school 8th graders' achievement test scores on the 2003 National Assessment of Education, and thus may be one of the closest data sets to a national sample of IQ scores (table here; discussion here, also see [17]).
[edit] End material
[edit] References
- IQ and the Wealth of Nations Richard Lynn, Tatu Vanhanen Praeger, ISBN 0-275-97510-X
- See [18]
- International Monetary Fund reported 2004 per capita GDP (PPP). [19]
- Barber, N. (2005). "Educational and ecological correlates of IQ: A cross-national investigation". Intelligence 33 (3): 273-284.
- Dickerson, R. E.. "Exponential correlation of IQ and the wealth of nations". Intelligence In Press, Corrected Proof.
- Hunt, E. & Wittmann, W. (in press) Relations Between National Intelligence and Indicators of National Prosperity. Sixth Annual Conference of International Society for Intelligence Research, Albuquerque, NM. [20]
- Templer, D. I. and Arikawa, H. (2006). "Temperature, skin color, per capita income, and IQ: An international perspective". Intelligence 34 (2): 121-139.
- Voracek, M. (2004). "National intelligence and suicide rate: an ecological study of 85 countries". Personality and Individual Differences 37 (3): 543-553.
- McDaniel, M.A. & Whetzel, D.L. (2005). IQ and the Wealth of Nations: Prediction of National Wealth. Sixth Annual Conference of International Society for Intelligence Research, Albuquerque, NM. [21]
- Whetzel, D. L. & McDaniel, M. A.. "Prediction of national wealth". Intelligence 34: 449-458.
[edit] See also
[edit] External links
- "Intelligence and the Wealth and Poverty of Nations" - article by Lynn and Vanhanen
- PISA scores transformed into IQ values in comparison with IQ estimated by Lynn and Vanhanen
- Smart Fraction Theory of IQ and the Wealth of Nations
- Exponential correlation of IQ and the wealth of nations - Peer reviewed article to be published in an upcoming edition of Intelligence (journal)
- "The Bigger Bell Curve: Intelligence, National Achievement, and The Global Economy", review by J. Philippe Rushton
- "A Reader's statistical update of IQ & The Wealth of Nations"
- A Few Thoughts on IQ and the Wealth of Nations, Steve Sailer, VDARE, April 2002.
