IQ and the Wealth of Nations

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 argues that differences in national income (in the form of per capita gross domestic product) correlate with differences in average national IQ. The authors interpret this correlation as showing that IQ is one important factor contributing to differences in national wealth and rates of economic growth, but that it is not the only determinant of these differences. The data, methodology, and conclusions have been criticized.

Outline
The book includes the authors' calculation of average IQ scores for 81 countries, based on their analysis of published reports. It reports their observation that national IQ correlates with gross domestic product per capita at 0.82, and with the rate of economic growth from 1950-1990 at 0.64.

The authors believe that average IQ difference between nations are due to both genetic and environmental factors. They also believe that low GDP can cause low IQ, just as low IQ can cause low GDP. (See: Positive feedback)

The authors write 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. It has also been severely criticized.

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 104 of the 185 nations, no studies were available. In those cases, the authors have used an estimated value by taking averages of the IQs of neighboring or comparable 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. Including those estimated IQs, the correlation of IQ and GDP is 0.62.

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). For the figure of Macau, the average IQ is 104 which is obtained from the score of the Programme for International Student Assessment (PISA) and in such a way transformed into an IQ score.

In some cases, the IQ of a country is estimated by averaging the IQs of 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 geographic neighbor, is not counted as such by Lynn and Vanhanen.

To account for the Flynn effect (an increase in IQ scores over time), the authors adjusted the results of older studies upward by a number of points.

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 and Vietnam seem to confirm this prediction, as China's GDP has grown rapidly since introducing market reforms. However, despite a supposedly higher average IQ and a market economy, South Korea still has a lower GDP/Capita than many Western nations.

Related studies
IQ and the Wealth of Nations' was not peer-reviewed before publication but was published by a publisher of academic literature. Peer reviewed articles have used the IQ scores presented in the book and some have also commented on the claims in the book.

Several negative reviews 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 questionably validity and are used in ways that cannot be justified." They also wrote that cross country comparisons are "virtually meaningless." Ken Richardson wrote "This is not so much science, then, as a social crusade. The Pioneer Fund of America, champion of many dubious causes in the past, will obtain little credit from having assisted this one." Thomas Nechyba wrote of "relatively weak statistical evidence and dubious presumptions." Astrid Ervik asked "are people in rich countries smarter than those in poorer countries?" and concluded that "the authors fail to present convincing evidence and appear to jump to conclusions."

Denny Borsboom (2006) finds that mainstream contemporary test analysis does not reflect substantial recent developments in the field and "bears an uncanny resemblance to the psychometric state of the art as it existed in the 1950s." For example, it notes that IQ and the Wealth of Nations, in order to show that the tests are unbiased, uses outdated methodology, if anything indicative of that test bias exist.

Thomas Volken wrote that the study is "neither methodologically nor theoretically convincing." Although critical of the IQ data, for the sake of argument Volken assumes that the data is correct but then criticizes the statistical methods used, finding no effect on growth or income. Using the same assumption, Garett Jones and W. Joel Schneider report a strong connection between intelligence and economic growth.

Erich Weede and Sebastian Kampf wrote that "there is one clear and robust result: average IQ does promote growth." Edward Miller wrote that "the theory helps significantly to explain why some countries are rich and some poor." Michael Palairet wrote that "Lynn and Vanhanen have launched a powerful challenge to economic historians and development economists who prefer not to use IQ as an analytical input." In a reanalysis of the Lynn and Vanhanen's hypothesis, Dickerson (2006) 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. 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. Other studies using different data sets find no correlation.

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.

Hunt and Wittmann (in press) use data from the Program for International Student Assessment (PISA) to conclude that "in spite of the weaknesses [in] several of their data points Lynn and Vanhanen's empirical conclusion was correct, but we question the simple explanation that national intelligence causes national wealth. We argue that the relationship is more complex".

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, and Lynn and Vanhanen's 2006 IQ and Global Inequality.

Jared Diamond's Guns, Germs and Steel instead argues that historical differences in economic and technological development for different areas can be explained by differences in geography (which affects factors like population density and spread of new technology) and differences in available crops and domesticatable animals. Richard Nisbett argues in his 2004 The Geography of Thought that some of these regional differences shaped lasting cultural traits, such as the collectivism required by East Asian rice irrigation, compared with the individualism of ancient Greek herding, maritime mercantilism, and money crops wine and olive oil (pp. 34-35).

Criticism of Research Funding Sources
Lynn has been frequently criticized as a Pioneer fund grantee.

Criticism of Dubious Data Sets
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. 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.

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.

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.

A test of 108 9-15-year olds in Barbados, of 50 13-16-year olds in Colombia, of 104 5-17-year olds in Ecuador, of 129 6-12-year olds in Egypt, of 48 10-14-year olds in Equatorial Guinea, and so on, all were taken as measures of 'national IQ'.

The notion that there is such a thing as a culturally neutral intelligence test is disputed. There are many difficulties when one is measuring IQ scores across cultures, and in multiple languages. Use of the same set of exams requires translation, with all its attendant difficulties and possible misunderstandings in other cultures. To adapt to this, some IQ test rely on non-verbal approaches, which involve pictures, diagrams, and conceptual relationships (such as in-out, big-small, and so on).

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.

Criticism of Data Set Sources and their Accuracy
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.

Criticism of Subjective Statistical Manipulation by Authors
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.

One critic writes: "Their scheme is to take the British Ravens IQ in 1979 as 100, and simply add or subtract 2 or 3 to the scores from other countries for each decade that the relevant date of test departs from that year. The assumptions of size, linearity and universal applicability of this correction across all countries are, of course, hugely questionable if not breathtaking. Flynn's original results were from only 14 (recently extended to twenty) industrialised nations, and even those gains varied substantially with test and country and were not linear. For example, recent studies report increases of eight points per decade among Danes; six points per decade in Spain; and 26 points over 14 years in Kenya (confirming the expectation that newly developing countries would show more rapid gains)."

There is controversy about the definition and usage of IQ and intelligence. See also race and intelligence.

It is generally agreed many factors, including environment, culture, demographics, wealth, pollution, and educational opportunities, affect measured IQ. See also Health 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, even assuming 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).