Determinants of Poverty: A Dynamic Panel Data Analysis with Controls for Income Level and Inequality
This paper assesses the relationship between poverty on the one hand and economic growth and income inequality on the other hand by utilising a panel data set of 145 economies spanning the period, 1982 to 2017. The Arellano-Bond GMM estimation technique is employed to address the potential endogeneity problem in the regression exercise. In the course of the assessment, controls are effected for different country characteristics namely, income level and the degree of income inequality. Generally, it is found that economic growth and income inequality have a stronger bearing, negatively and positively respectively, on the incidence of poverty in middleincome than in low-income economies. The two variables also appear to have a larger impact in low-income inequality than in high-income inequality economies.