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Health Financing, Out-of-Pocket Payments and Income Inequality: Evidence from an International Panel (2000–2020)

Author

Listed:
  • Balladares Ponguillo, Karen Andrea

  • Morales Vergara, José Roberto

  • Trinidad Segovia, Juan Evangelista

  • Arevalo Avecillas, Danny Xavier

Abstract

This study examines the relationship between health financing mechanisms and income inequality using an international panel of 135 countries over the period 2000–2020. From a macro-comparative perspective, the analysis focuses on total health expenditure as a percentage of GDP and the share of out-of-pocket payments within total health spending, while controlling for key macroeconomic and social variables including GDP per capita, unemployment, inflation, education, and health outcomes. Methodologically, the study estimates a country fixed-effects model to capture contemporaneous within-country associations and, as a robustness exercise, a dynamic panel specification using the Arellano–Bond difference GMM estimator to account for the temporal persistence of income inequality. The static results suggest that higher overall health expenditure is associated with moderate reductions in income inequality, whereas a greater reliance on out-of-pocket payments is linked to increases in the Gini coefficient, consistent with their regressive nature. However, once dynamic persistence is incorporated, these effects lose statistical significance, while income inequality exhibits strong structural inertia. Unemployment and infant mortality emerge as relevant determinants of inequality across specifications. Overall, the findings indicate that health financing structures matter for distributive outcomes, but their effects are neither immediate nor independent of entrenched inequality trajectories. Health reforms should therefore be conceived as part of broader, long-term redistributive strategies integrated with labor market and fiscal policies.

Suggested Citation

  • Balladares Ponguillo, Karen Andrea & Morales Vergara, José Roberto & Trinidad Segovia, Juan Evangelista & Arevalo Avecillas, Danny Xavier, 2026. "Health Financing, Out-of-Pocket Payments and Income Inequality: Evidence from an International Panel (2000–2020)," Revista Galega de Economía, University of Santiago de Compostela. Faculty of Economics and Business., vol. 35(2), pages 1-29.
  • Handle: RePEc:sdo:regaec:v:35:y:2026:i:2_6
    DOI: 10.15304/rge.35.2.11193
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    References listed on IDEAS

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    1. Sen, Amartya, 1973. "On Economic Inequality," OUP Catalogue, Oxford University Press, number 9780198281931.
    2. Mr. David Coady & Mr. Sanjeev Gupta, 2012. "Income Inequality and Fiscal Policy," IMF Staff Discussion Notes 2012/008, International Monetary Fund.
    3. Persson, Torsten & Tabellini, Guido, 1994. "Is Inequality Harmful for Growth?," American Economic Review, American Economic Association, vol. 84(3), pages 600-621, June.
    4. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    5. Francesca Bastagli & David Coady & Sanjeev Gupta, 2012. "Income Inequality and Fiscal Policy (2nd Edition)," IMF Staff Discussion Notes 12/08R, International Monetary Fund.
    6. Ms. Francesca Bastagli & Mr. David Coady & Mr. Sanjeev Gupta, 2012. "Income Inequality and Fiscal Policy (2nd Edition)," IMF Staff Discussion Notes 2012/009, International Monetary Fund.
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    More about this item

    Keywords

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    JEL classification:

    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I15 - Health, Education, and Welfare - - Health - - - Health and Economic Development
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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