Sunday, August 22, 2010

GDP and IQ

This is not new, the study on a country's average IQ and how that correlates to GDP growth and/or per capita income. In any study that implies intelligence with citizenship or race - it is bound to be controversial. I think there is some merit to the study, but seriously, you do not need the entire population IQ to be high to be successful. We have to take into consideration how some populous countries have a large rural population (which may not get ready access to education).


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. This is presumably because the ethnic groups of the area speak Iranian and Turkic languages, but do not include Chinese.

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.

Rank↓ Country↓ IQ estimate[3]↓
1 Hong Kong 107
2 South Korea 106
3 Japan 105
4 Republic of China (Taiwan) 104
5 Singapore 103
6 Austria 102
6 Germany 102
6 Italy 102
6 Netherlands 102
10 Sweden 101
10 Switzerland 101
12 Belgium 100
12 China 100
12 New Zealand 100
12 United Kingdom 100
16 Hungary 99
16 Poland 99
16 Spain 99
19 Australia 98
19 Denmark 98
19 France 98
19 Mongolia 98
19 Norway 98
19 United States 98
25 Canada 97
25 Czech Republic 97
25 Finland 97
28 Argentina 96
28 Russia 96
28 Slovakia 96
28 Uruguay 96
32 Portugal 95
32 Slovenia 95
34 Israel 94
34 Romania 94
36 Bulgaria 93
36 Ireland 93
36 Greece 93
39 Malaysia 92
40 Thailand 91
41 Croatia 90
41 Peru 90
41 Turkey 90

Rank↓ Country↓ IQ estimate[3]↓
44 Colombia 89
44 Indonesia 89
44 Suriname 89
47 Brazil 87
47 Iraq 87
47 Mexico 87
47 Samoa 87
47 Tonga 87
52 Lebanon 86
52 Philippines 86
54 Cuba 85
54 Morocco 85
56 Fiji 84
56 Iran 84
56 Marshall Islands 84
56 Puerto Rico 84
60 Egypt 83
60 Saudi Arabia 83
60 United Arab Emirates 83
61 India 81
62 Ecuador 80
63 Guatemala 79
64 Barbados 78
64 Nepal 78
64 Qatar 78
67 Zambia 77
68 Congo 73
68 Uganda 73
70 Jamaica 72
70 Kenya 72
70 South Africa 72
70 Sudan 72
70 Tanzania 72
75 Ghana 71
76 Nigeria 67
77 Guinea 66
77 Zimbabwe 66
79 Democratic Republic of the Congo 65
80 Sierra Leone 64
81 Ethiopia 63
82 Equatorial Guinea 59

In several cases the 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 whom 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. South Korea has a higher average IQ and a market economy. However, South Korea still has a lower GDP/Capita than many Western nations (but relatively high overall), but South Korean economic reform started in 1970s and it is one of the fastest growing economies in the world. Contrary to the theory of correlation between IQ and economy type many planned economies had higher literacy rates than most market economies. Still, South Korea went from amongst the poorest nations in the world to advanced economy by recording among fastest growth rate in the world. Despite a supposedly higher average IQ and a market economy since the Meiji Restoration in 1867, Japan still has a lower GDP/Capita than many Western nations.

The two most striking exceptions, however, may be Ireland and the United States. Ireland, whose average I.Q. is listed at 93, had the fourth highest per capita GDP (PPP adjusted) of any country in the world (after tiny Luxembourg, Norway and the United States). The United States, with an average I.Q. of 98, has the third-highest per capita GDP (PPP adjusted), and is by far the most populous of the richest 10 countries. Both of these countries have I.Q. averages considerably below those of countries such as South Korea, Taiwan, and Germany, but have per capita GDPs about 1.5 times higher.

In the case of The United States, there is a striking contrast existing within its cultural sectors of the population. Several aspects must be hold into account. The African American population scored on average 87 while the Latino population scored 88, leaving the Asian and Caucasian population with an average IQ of 106. Although it is undeniable that some of this is due to cultural, educational and historical factors, there is also strong evidence that there is a genetic component to these observed differences

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 Programme 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.

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