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This study investigates the effects of corruption on health indicators and main cause of corruption by using structural equation modeling. Based on the heterogeneous dataset of 126 countries, structural equation model was estimated by using partial least square method where different development levels of countries were included. Findings indicate that GDP per capita, democracy levels and education level of women are three prominent variables that explain corruption in highly developed and developed countries. Corruption decreases as the regime becomes more democratic and GDP per capita increases. Furthermore, corruption has significantly displayed the effect it has on health indicators. As to middle and low-developed countries, the education level of women and health expenditure affect health indicators regardless of corruption and GDP per capita. And as the regime becomes more autocratic, corruption rises.

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The Relationship between Socio-Economic Development, Corruption and Health Indicators: Application of Partial Least Squares Structural Equation Modeling