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All Journal Economic Journal of Emerging Markets
Emin Efecan Aktas
Department of Accounting and Tax Practices, Kirsehir Ahi Evran University, Kirşehir, Turkey
Economics, Econometrics & Finance

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Nonlinear effects of ıncome ınequality on economic growth: A comparative analysis of selected countries Emin Efecan Aktas; Pelin Varol Iyidogan
Economic Journal of Emerging Markets Volume 14 Issue 1, 2022
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/ejem.vol14.iss1.art6

Abstract

Purpose ― The paper queries the impacts of income inequality on economic growth in selected advanced and emerging market economies by adopting nonlinearity and endogeneity. Methods ― This research analysis is based on a balanced panel from 1996 to 2018 and employs the dynamic panel threshold analysis after baseline estimations with the fixed-effect, system Generalized Method of Moments, and difference Generalized Method of Moments. Findings ― This study finds a nonlinearity between income inequality and economic growth. Income inequality has a significant threshold effect on the growth of both panels. Besides, the threshold effect of emerging market countries is higher than the level for advanced countries. This means emerging market economies are negatively affected above the estimated threshold value according to the advanced economies. Implication ― This paper supports that inequality may harm much more economic growth above a specific level. On the other hand, these distorting effects are related to the other economic issues of countries, such as government spending, inflation, export of goods and services, gross fixed capital formation, and foreign direct investment. Originality ― This paper contributes to the literature by focusing on the nonlinear effects of income inequality and different aspects of economic growth above or below the estimated threshold value, thereby providing cross-country comparability and endogeneity.
Co-Authors Pelin Varol Iyidogan