Citation
Nik Ahmad Sufian Burhan@Jaohari and Mohd Rosli Mohamad and Yohan Kurniawan and Abdul Halim Sidek (2015) Corrigendum to "The impact of low, average, and high IQ on economic growth and technological progress: do all individuals contribute equally? Intelligence Journal, 48. pp. 162-163. ISSN 0160-2896 |
Abstract
Individuals that reside in the highest social stratum of intelligence (i.e., those that have a high IQ) have been shown to generate relatively more national income and are more innovative, with those that have the lowest levels of IQ being less influential on economic development. However, the degree to which all levels of IQ influence economic growth and technological innovation remains unclear. By assuming that the IQ of a population is modeled based on a bell curve, we arrange IQ into three strata, namely intellectual class, average ability citizens, and non-intellectual class, which are represented by the 95th, 50th, and 5th percentiles of cognitive ability, respectively. Our multiple hierarchical regression analysis of a sample of over 60 countries shows that the intellectual class has the greatest impact on economic growth followed by average ability citizens and the non-intellectual class in that order. Moreover, we find evidence that the impact of the intellectual class on technological progress is exceptionally more significant than even the number of professional researchers engaged in R&D activities, with average ability citizens and the non-intellectual class not significant. These findings allow us to suggest that the government and private institutions should not only employ professionals with good experiences and high academic credentials, but also those who has excellent IQ levels to work in their R&D sectors. However, in order to foster economic growth, governments should invest into facilities that benefit all societal groups of intelligence level, with highest priority given to the intellectual class, followed by the average ability citizens and the non-intellectual class respectively. |
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Official URL: http://www.sciencedirect.com/science/journal/01602...
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Additional Metadata
Item Type: | Non-Indexed Article |
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Collection Type: | Institution |
Date: | 2015 |
Journal or Publication Title: | Intelligence Journal |
ISSN: | 0160-2896 |
Faculty/Centre/Office: | Faculty of Entrepreneurship and Business |
URI: | http://discol.umk.edu.my/id/eprint/8205 |
Statistic Details: | View Download Statistic |