The Evolutionary Trend of Global Inequality: Analyzing the Impacts of Economic Structure - Ma, Ning; Li, Victor Jing; Cheong, Tsun Se; Zhuang, Delin (Frontiers in Psychology, 2021)
The aim of this study is to examine the evolution of inequality by focusing on the impacts of the economic structure. The technique of decomposition by income sources is employed to evaluate the contribution of the three major sectors, namely the agricultural, industrial, and service sectors to overall inequality. The data cover almost all the countries in the world from 2001 to 2017 for a total of 18 years. There are four stages of analysis in this study. The first stage of study is to provide an overall view of the evolutionary trend of global inequality, the second stage focuses on the North-South divide, the third stage determines the impacts of income groups, and the fourth stage investigates the impacts for each region. There are several salient findings: First, global inequality had declined in the study period. Second, the service sector is identified as the largest contributor to global inequality, followed by the industrial sector, while the contribution of the agricultural sector is negligible. For the North-South divide, disparity in the service sector was more marked in the North than in the South. The industrial sector played a major role in the South and contributed more than 40% to overall inequality. For the comparison amongst the income groups, our findings show that the higher the income, the higher the percentage contribution of the service sector (except for the low-income group). Finally, for the comparison across regions, although the contribution of the agricultural sector in most regions are below 1.5%; however the contribution of the agricultural sector in both Sub-Saharan Africa and South Asia is more than 8%. It implies that a lot of people in these regions still rely on the agricultural sector for a living, and the development in the industrial and service sectors in these two regions lagged behind those of the other regions. Our analysis show that the evolution pattern is very different for each region, therefore, it is necessary to take the effects of income and geographical location into consideration in formulating development policies.