Intelligence and the Wealth of Nations: Genetics Matter but there is Still Much Room to Reduce Inequalities preliminary

This paper first sets an equation for the average intelligence of a country or a human group, which is determined by genetic factors and other variables where education is one of them. Another equation representing a production function of education depends upon intelligence and different elements that improve the quality of education. These two equations solve for the average level of intelligence and the level of education simultaneously. A third equation is a production function, where the GDP of the country is determined by human capital, physical capital and labor. Human capital is approached by the level of education obtained in the first two equations. The previous system is estimated in a cross section for 42 countries. Intelligence is approached by the IQ level by countries shown by Lynn and Vanhanen (2002); the genetic factors explaining intelligence are taken from the haplogroups maps of the Y DNA chromosome of McDonald (2005) (haplogroups being groups of distinct genes). Other factors explaining intelligence are nutrition?approached by the per capita ingestion of calories presented by FAO? and education. The elements that improve the quality of education are supposed to be the per primary pupil expenditure in education and the per capita expenditure on health of the Human Development Report. Real economic variables are taken from different sources, mainly from the Penn World Table. Results show that in the determination of the IQ genetics matter. However, other factors much less related to genetics are equally important. The per primary pupil expenditure on education may boost both the level of the IQ and the level of education, which also can explain the so called Flynn effect (a situation where the IQ is increasing in time. Flynn (1984)). At the same time, human capital is approximated better for education than for the IQ itself. The paper performs a simulation. Here, the levels of the majority of the non genetic factors of the model are equated among countries. Main results of the simulation are that the inequality of the IQ and education among countries falls sharply, while the inequality on the per capita GDP falls only slightly due to the already observed differences in the per capita physical capital. Results suggest that policies aimed at improving the quality of education in poor countries with low levels of IQ and education should be welcome.