Economic Growth and Income Inequality: Evidence from Dynamic Panel Investigation
Dong Jin Lee, Jong Chil Son
Abstract
Dong Jin Lee, Jong Chil Son
Abstract
This paper empirically investigates the effect of income inequality on economic growth using extended panel data covering a broad range of developing and developed countries. We use system generalized method of moments (GMM) techniques in a dynamic panel analysis, which alleviates the possible positive bias in difference GMM due to the persistence of lagged dependent variables as instruments. We find strong evidence of a negative effect on growth from income inequality, which contradicts the findings of Forbes [2000, September. A reassessment of the relationship between inequality and growth, American Economic Review, 90(4), pp. 869–887] and Li and Zou [1998, October. Income inequality is not harmful for growth: Theory and evidence, Review of Development Economics, 2(3), pp. 318–34]. Further analyses using combined Gini coefficients show that the difference can be overall attributed to the problem of omitted control variables and the differences in how the variations in inequality across countries are reflected. We also find that the negative effects of inequality on economic growth can be of great significance when using a sample of less developed countries or more recent inequality data set.
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This paper empirically investigates the effect of income inequality on economic growth using extended panel data covering a broad range of developing and developed countries. We use system generalized method of moments (GMM) techniques in a dynamic panel analysis, which alleviates the possible positive bias in difference GMM due to the persistence of lagged dependent variables as instruments. We find strong evidence of a negative effect on growth from income inequality, which contradicts the findings of Forbes [2000, September. A reassessment of the relationship between inequality and growth, American Economic Review, 90(4), pp. 869–887] and Li and Zou [1998, October. Income inequality is not harmful for growth: Theory and evidence, Review of Development Economics, 2(3), pp. 318–34]. Further analyses using combined Gini coefficients show that the difference can be overall attributed to the problem of omitted control variables and the differences in how the variations in inequality across countries are reflected. We also find that the negative effects of inequality on economic growth can be of great significance when using a sample of less developed countries or more recent inequality data set.
Key concepts: Inequality, Economic inequality, Panel data, Economics, Gini coefficient, Income inequality metrics, Generalized method of moments, Econometrics