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El trimestre económico
versão On-line ISSN 2448-718Xversão impressa ISSN 0041-3011
Resumo
QUITO, Byron; OCHOA-MORENO, Wilman-Santiago; ALVAREZ-GARCIA, José e RIO-RAMA, María de la Cruz del. Economic development and income inequality: Accessing evidence from lens of Kuznets’ hypothesis for a global sample. El trimestre econ [online]. 2025, vol.92, n.366, pp.477-514. Epub 02-Jul-2025. ISSN 2448-718X. https://doi.org/10.20430/ete.v92i366.2388.
This research examines the non-linear relationship between economic development and income inequality by using a balanced panel of 113 countries during 1985-2017. The countries are grouped into four subsamples: 45 high-income countries (HIC), 32 upper-middle-income countries (UMIC), 26 lower-middle-income countries (LMIC), and 10 low-income economies (LIC). The Gini indexes before and after taxes and transfers are used as proxies for income inequality, while economic development is represented by the level of real production per capita (GDP). Several panel data estimation techniques are applied, in addition to using second-generation cointegration techniques. Cross-sectional dependence (CD) is considered to examine the long-term non-linear relationship, and, finally, causality tests are applied to developing policy implications. We find there are long-term relationships between economic development and income inequality, before and after taxes and transfers. Interestingly, when considering the subgroups for the analysis, economic development generates different effects for each group. In particular, there seems to be an inverted U-shaped relationship in the HIC, UMIC, and LMIC groups. However, the second inequality measure, after taxes and transfers, is valid throughout the panel and for all groups of countries. This study proposes potential political implications, which require a deeper understanding of the distribution mechanisms between countries. By considering subsamples, we show that income inequality could distort economic growth.
Palavras-chave : Inequality income; Kuznets; global sample; panel data; cointegration.












