Academic journal article Mankind Quarterly

Regional Differences in Intelligence and per Capita Incomes in Portugal

Academic journal article Mankind Quarterly

Regional Differences in Intelligence and per Capita Incomes in Portugal

Article excerpt

Regional differences in IQ and per capita income are presented for five regions of Portugal showing that both are highest in Central Lisbon.

Key Words: IQ; Income; Portugal; Regions.

Several studies have reported that average IQs differ in different geographical regions of a country, and that these different IQs are positively related to per capita incomes. Typically, although not invariably, the capital city has the highest average IQ and the highest per capita income. The objective of this paper is to examine whether this is the case in Portugal.

Previous studies reporting regional differences in average IQ and per capita income have been published for the British Isles, France, the United States and Italy. The first of these studies was concerned with IQ differences in 13 regions of the British Isles in the mid-twentieth century (Lynn, 1979). It found that IQ was highest (102.1) in London and South-East England, and lowest in Scotland (97.3), Northern Ireland (96.7), and the Republic of Ireland (96.0). These regional IQs were positively correlated with per capita income at r = .73. They were also positively correlated with intellectual achievement indexed by fellowship of the Royal Society (r = .94), and negatively with infant mortality (r = -.78) (Lynn, 1979). It has been shown subsequently that these regional differences in IQ are strongly associated negatively with differences in stature (Boldsen & Mascie-Taylor, 1985).

Similar results have been found in France, where regional differences in intelligence were reported for the mid-1950s by Montmollin (1958). IQs were obtained from 257, 000 18 year old male conscripts into the armed forces, and mean IQs were given for the 90 French departments. The highest IQs were obtained by conscripts from the Paris region and the lowest by conscripts from Corsica. As in the British Isles, it was shown that these departmental IQs were moderately well positively correlated with average per capita income (r = .61), with intellectual achievement indexed by membership of the Institut de France (r = .26), and negatively with infant mortality (r = -.30) (Lynn, 1980).

An association between regional IQ and per capita income has also been reported in the United States. It has long been known that in the United States the populations of the northern states have higher average IQs than those of the South-East (Kaufman et al, 1988). This has been confirmed by McDaniel (2006) who has calculated the IQs of the populations of the American states and found that these are highest in the north-eastern states of Massachusetts (104.3), New Hampshire (104.2) and Vermont (103.8), and lowest in the southern states of Mississippi (94.2) and Alabama (95.7), and in California (95.5). The McDaniel (2006) average state IQs are positively correlated with gross state product per capita (a measure of per capita income) at r = 0.28. Finally, the same positive relationship between regional IQs and per capita income has been reported for Italy, where average IQs for 12 Italian regions range from 103 the most northerly region of Friuli-Venezia to 89 in the most southerly region of Sicily, and there was a correlation of r = .94 between these regional IQs and per capita income (Lynn, 2010). There was also a strong negative correlation of r = -.86 between regional IQs and rates of infant mortality.

The explanation for the association between regional IQs and per capita income is that individuals with higher IQ tend on average to earn higher incomes. Regions are aggregates of individuals, so this association is also present at the population level. The classical study of the contribution of intelligence to income was made by Jencks (1972) who estimated a correlation of r = .31 (corrected for attenuation to .35) between IQ and income for a white male non-farm American sample aged 25-65. He concluded that this is a causal relationship such that IQ differences make a significant contribution to differences in incomes. …

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