Abstract
“Skills, Occupation Inequality and Development” is a theoretical study. There is no general agreement about how income inequality will affect development in the long run. Classic growth models show that income inequality is beneficial to development due to agent’s heterogeneity and marginal propensity to save increasing with wealth. Neoclassical growth models present that income distribution plays no significant role on development assuming representative agents and decreasing marginal returns in investment. New classical growth theory demonstrates that income inequality impedes growth due to credit constraints and indivisibility of investment in human capital. This paper studies income inequality through the channel of complementary skills and occupations in aggregate production. In a new classical model economy with two complementary occupations, CES production technology, skills in utility, and uncertainty of completing high-skilled occupations, we find a continuum of equilibria denoted by a correspondence between aggregate capital stock and the low-skilled population share regardless of the distribution in initial endowments. Aggregate capital stock and aggregate income per capita are non-monotonically related to the low-skilled population share. Aggregate income per capita will be maximized at a certain distribution of occupations on the continuum of equilibria. Therefore, the correlation between development and inequality of occupation distribution can be both positive and negative which depends on the position of occupation division on the continuum of equilibria. The correlation between low skills and occupation inequality is monotonic within a country, but the correlation is opposite between developed and developing economies. The low skills will move up on the continuum of equilibria if the occupation inequality is smaller (larger) in developed (developing) economies. The study also shows that inequality of the occupation distribution plays different effects in developed economies from those in developing economies due to the assumption that skills affect the completion of occupations. Developing economies also present two patterns of equilibria, in which one has higher optimum inequality of occupations, another one has lower optimum inequality of occupations. The cause of two patterns of equilibria for developing economies comes from the assumption of Cobb-Douglas production function. Shifts of equilibrium lead to new levels of development due to a change of inequality in other characteristics of the economy. “Fair Division of Income Distribution, Development and Growth: Evidence from a Panel of Countries” is an empirical exercise. I use an unbalanced panel data to explore the correlation between aggregate income per capita and income inequality. A lot of studies document controversial results using the Gini index or other summary measurements of income inequality. I measure income inequality by the two dimensions of a point on the Lorenz Curve, where the Lorenz curve has unit slope. It is called fair division point, which involves the fair population share and the fair income share. The difference between the fair population share and the fair income share approximates the Gini index of an income distribution. My analysis shows that a country’s low income population relatively decreases (the fair population share drops slightly) as the economy grows; and at the same time, those low income households are relatively worse off (the fair income share falls even though the GDP per capita increases). Inversely, as an economy becomes rich, there are more low income households (the fair population share increases), but those low income households are better off (the fair income share goes up and GDP per capita increases as well). Overall, both the Gini index and the difference between the fair population share and the fair income share have been increasing during the last half century in the panel of countries. Therefore, income inequality increases as an economy is getting richer. The analysis presents strong evidence for optimum income inequality regarding both the aggregate productivity and the growth rate of GDP, where income inequality is measured by either the Gini index or the fair division shares. But no evidence has been found for the Kuznets’ hypothesis. Both high and low inequality of income distribution could harm an economy as we compare with its potential optimum inequality. Also developed economies show different optimum inequality from that in developing economies, and there is the growth-worst fair population share that results in the lowest growth in developed economies. Measurement of income inequality matters on its economic effects for the subsamples of the panel data.