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IQ AND SOCIOECONOMIC DEVELOPMENT ACROSS REGIONS OF THE UK

Published online by Cambridge University Press:  19 June 2015

Noah Carl
Noah Carl*
Affiliation:
Nuffield College, University of Oxford, Oxford, UK
*
1Email: noah.carl@nuffield.ox.ac.uk
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Summary

Cross-regional correlations between average IQ and socioeconomic development have been documented in many different countries. This paper presents new IQ estimates for the twelve regions of the UK. These are weakly correlated (r=0.24) with the regional IQs assembled by Lynn (1979). Assuming the two sets of estimates are accurate and comparable, this finding suggests that the relative IQs of different UK regions have changed since the 1950s, most likely due to differentials in the magnitude of the Flynn effect, the selectivity of external migration, the selectivity of internal migration or the strength of the relationship between IQ and fertility. The paper provides evidence for the validity of the regional IQs by showing that IQ estimates for UK nations (England, Scotland, Wales and Northern Ireland) derived from the same data are strongly correlated with national PISA scores (r=0.99). It finds that regional IQ is positively related to income, longevity and technological accomplishment; and is negatively related to poverty, deprivation and unemployment. A general factor of socioeconomic development is correlated with regional IQ at r=0.72.

Type
Research Article
Information
Journal of Biosocial Science , Volume 48 , Issue 3 , May 2016 , pp. 406 - 417
Copyright
Copyright © Cambridge University Press, 2015 

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References

Almeida, L. S., Lemos, G. C. & Lynn, R. (2011) Regional differences in intelligence and per capita incomes in Portugal. Mankind Quarterly 52, 213–221.Google Scholar
Barnes, J. C., Beaver, K. M. & Boutwell, B. B. (2013) Average county-level IQ predicts county-level disadvantage and several county-level mortality risk rates. Intelligence 41, 59–66.Google Scholar
Beraldo, S. (2010) Do differences in IQ predict Italian north–south differences in income? A methodological critique to Lynn. Intelligence 38, 456–461.CrossRefGoogle Scholar
Boutwell, B. B., Franklin, T. W., Barnes, J. C., Beaver, K. M., Deaton, R., Lewis, R. H., Tamplin, A. K. & Petkovsek, M. A. (2013) County-level IQ and fertility rates: a partial test of Differential-K theory. Personality and Individual Differences 55, 547–552.Google Scholar
Carl, N. (2014) Does intelligence explain the association between generalized trust and economic development? Intelligence 47, 83–92.Google Scholar
Chen, H., Chen, Y., Liao, Y. & Chen, H. (2013) Relationship of fertility with intelligence and education in Taiwan: a brief report. Journal of Biosocial Science 45, 567–571.Google Scholar
Cornoldi, C., Belacchi, C., Giofrè, D., Martini, A. & Tressoldi, P. (2010) The mean southern Italian children IQ is not particularly low: a reply to R. Lynn (2010) Intelligence 38, 462–470.Google Scholar
Cornoldi, C., Giofrè, D. & Martini, A. (2013) Problems in deriving Italian regional differences in intelligence from 2009 PISA data. Intelligence 41, 25–33.Google Scholar
D’Amico, A., Cardaci, M., Di Nuovo, S. & Naglieri, J. A. (2012) Differences in achievement not in intelligence in the north and south of Italy: comments on Lynn (2010a) and Lynn (2010b). Learning and Individual Differences 22, 128–132.Google Scholar
Daniele, V. (2013) Does the intelligence of populations determine the wealth of nations? Journal of Socio-Economics 46, 27–37.Google Scholar
Daniele, V. (2015) Two Italies? Genes, intelligence and the Italian North–South economic divide. Intelligence 49, 44–56.Google Scholar
Daniele, V. & Malanima, P. (2011) Are people in the South less intelligent than in the North? IQ and the North–South disparity in Italy. Journal of Socio-Economics 40, 844–852.Google Scholar
Dutton, E. & Lynn, R. (2014) Regional differences in intelligence and their social and economic correlates in Finland. Mankind Quarterly 54, 447–456.Google Scholar
Eppig, C., Fincher, C. L. & Thornhill, R. (2010) Parasite prevalence and the worldwide distribution of cognitive ability. Proceedings of the Royal Society B 277, 3801–3808.CrossRefGoogle ScholarPubMed
Eppig, C., Fincher, C. L. & Thornhill, R. (2011) Parasite prevalence and the distribution of intelligence among the states of the USA. Intelligence 39, 155–160.CrossRefGoogle Scholar
Eurostat (2014) Regional statistics. Regions and Cities: Main Tables. URL: http://ec.europa.eu/eurostat/data/database Google Scholar
Felice, E. & Giugliano, F. (2011) Myth and reality: a response to Lynn on the determinants of Italy's north–south imbalances. Intelligence 39, 1–6.CrossRefGoogle Scholar
Flynn, J. R. (2012) Are We Getting Smarter?. Cambridge University Press, Cambridge, UK.Google Scholar
Hopcraft, R. L. (2014) Sex differences in the relationship between status and number of offspring in the contemporary U.S. Evolution and Human Behavior 36, 146–151.Google Scholar
Jokela, M. (2014) Flow of cognitive capital across rural and urban United States. Intelligence 46, 47–53.CrossRefGoogle Scholar
Jones, G. & Schneider, W. J. (2006) Intelligence, human capital, and economic growth: a Bayesian averaging of classical estimates (BACE) approach. Journal of Economic Growth 11, 71–93.Google Scholar
Kanazawa, S. (2014) Intelligence and childlessness. Social Science Research 48, 157–170.Google Scholar
Knies, G. (2014) Understanding Society: the UK Household Longitudinal Study, Waves 1–4, 2009–2013, User Manual. UK Data Service.Google Scholar
Kura, K. (2013) Japanese north–south gradient in IQ predicts differences in stature, skin color, income, and homicide rate. Intelligence 41, 512–516.Google Scholar
Lynn, R. (1979) The social ecology of intelligence in the British Isles. British Journal of Social and Clinical Psychology 18, 1–12.Google Scholar
Lynn, R. (1980) The social ecology of intelligence in France. British Journal of Social and Clinical Psychology 19, 325–331.Google Scholar
Lynn, R. (2010) In Italy, north–south differences in IQ predict differences in income, education, infant mortality, stature, and literacy. Intelligence 38, 93–100.Google Scholar
Lynn, R. (2011) Dysgenics: Genetic Deterioration in Modern Populations. Ulster Institute for Social Research, London, UK.Google Scholar
Lynn, R. (2012) North–south differences in Spain in IQ, educational attainment, per capita income, literacy, life expectancy and employment. Mankind Quarterly 52, 265–291.Google Scholar
Lynn, R. (2013) Who discovered the Flynn effect? A review of early studies of the secular increase in intelligence. Intelligence 41, 765–769.Google Scholar
Lynn, R. & Cheng, H. (2013) Differences in intelligence across thirty-one regions of China and their economic and demographic correlates. Intelligence 41, 553–559.Google Scholar
Lynn, R. & Van Court, M. (2004) New evidence of dysgenic fertility for intelligence in the United States. Intelligence 32, 193–201.Google Scholar
Lynn, R. & Vanhanen, T. (2012a) National IQs: a review of their educational, cognitive, economic, political, demographic, sociological, epidemiological, geographic and climatic correlates. Intelligence 40, 226–234.Google Scholar
Lynn, R. & Vanhanen, T. (2012b) Intelligence: A Unifying Construct for the Social Sciences. Ulster Institute for Social Research, London, UK.Google Scholar
Lynn, R. & Yadav, P. (2015) Differences in cognitive ability, per capita income, infant mortality, fertility and latitude across the states of India. Intelligence 49, 179–185.CrossRefGoogle Scholar
McDaniel, M. A. (2006) Estimating state IQ: measurement challenges and preliminary correlates. Intelligence 34, 607–619.Google Scholar
McFall, S. (2013) Understanding Society: UK Household Longitudinal Study: Cognitive Ability Measures. UK Data Archive Study Number 6614.Google Scholar
Meisenberg, G. (2010) The reproduction of intelligence. Intelligence 38, 220–230.CrossRefGoogle Scholar
Meisenberg, G. & Lynn, R. (2011) Intelligence: a measure of human capital in nations. Journal of Social, Political & Economic Studies 36, 421–454.Google Scholar
OECD (2014) Pisa 2012 Results: What Students Know and Can Do – Student Performance in Reading, Mathematics and Science. PISA, OECD Publishing, Volume 1.Google Scholar
ONS (2013) Region and Country Profiles – Key Statistics Tables. Reference Tables, Office for National Statistics.Google Scholar
Pesta, B., McDaniel, M. A. & Bertsch, S. (2010) Toward an index of well-being for the fifty U.S. states. Intelligence 38, 160–168.Google Scholar
Piffer, D. & Lynn, R. (2014) New evidence for differences in fluid intelligence between north and south Italy and against school resources as an explanation for the north–south IQ differential. Intelligence 46, 246–249.Google Scholar
Pollet, T. V. (2013) Much ado about p. What does a p-value mean when testing hypotheses with aggregated cross-cultural data in the field of evolution and human behavior? Frontiers in Psychology 4, 734.Google Scholar
Quillien, T. (2015) Population finiteness is not a concern for null hypothesis significance testing when studying human behaviour. A reply to Pollet (2013). Frontiers in Neuroscience 9, 81.Google Scholar
Reeve, C. L., Lyerly, J. E. & Peach, H. (2013) Adolescent intelligence and socio-economic wealth independently predict adult marital and reproductive behaviour. Intelligence 41, 358–365.Google Scholar
Richwine, J. (2009) IQ and immigration policy. Doctoral Dissertation, Harvard University.Google Scholar
Rindermann, H. (2012) Intellectual classes, technological progress and economic development: the rise of cognitive capitalism. Personality and Individual Differences 53, 108–113.Google Scholar
Rindermann, H. & Thompson, J. (2011) Cognitive capitalism: the effect of cognitive ability on wealth, as mediated through scientific achievement and economic freedom. Psychological Science 22, 754–763.CrossRefGoogle ScholarPubMed
Rindermann, H. & Thompson, J. (2014) The cognitive competences of immigrant and native students across the world: an analysis of gaps, possible causes and impact. Journal of Biosocial Science doi: 10.1017/S0021932014000480.Google Scholar
Rindermann, H., Woodley, M. A. & Stratford, J. (2012) Haplogroups as evolutionary markers of cognitive ability. Intelligence 40, 362–375.Google Scholar
Roivaninen, E. (2012) Economic, educational, and IQ gains in eastern Germany 1990–2006. Intelligence 40, 571–575.Google Scholar
Spearman, C. (1904) “General intelligence”, objectively determined and measured. American Journal of Psychology 15, 201–292.CrossRefGoogle Scholar
Sternberg, R. J. (2013) “The intelligence of nations”: Smart but not wise – A comment on Hunt (2012). Perspectives on Psychological Science 8, 187–189.Google Scholar
Templer, D. I. (2012) Biological correlates of northern–southern Italy differences in IQ. Intelligence 40, 511–517.CrossRefGoogle Scholar
Trahan, L. H., Stuebing, K. K., Fletcher, J. M. & Hiscock, M. (2014) The Flynn effect: a meta-analysis. Psychological Bulletin 140, 1332–1360.CrossRefGoogle ScholarPubMed
University of Essex (2013) Institute for Social and Economic Research and NatCen Social Research, Understanding Society: Waves 1–3, 2009–2012, 5th Edn. UK Data Archive, Colchester, Essex.Google Scholar
Wicherts, J. M., Borsboom, D. & Dolan, C. V. (2010a) Why national IQs do not support evolutionary theories of intelligence. Personality and Individual Differences 48, 91–96.Google Scholar
Wicherts, J. M., Borsboom, D. & Dolan, C. V. (2010b) Evolution, brain size, and the national IQ of peoples around 3000 years B.C. Personality and Individual Differences 48, 104–106.Google Scholar
Woodley, M. A. (2015) How fragile is our intellect? Estimating losses in general intelligence due to both selection and mutation accumulation. Personality and Individual Differences 75, 80–84.Google Scholar
Woodley, M. A., Rindermann, H., Bell, E., Stratford, J. & Piffer, D. (2014) The relationship between Microcephalin, ASPM and intelligence: a reconsideration. Intelligence 44, 51–63.Google Scholar