The distributional impacts of earmarked taxes and co‐payments in healthcare

Manjeet Kaur Harnek Singh et al.

Review of Financial Economics2026https://doi.org/10.1002/rfe.70043article
AJG 1ABDC B
Weight
0.50

What the paper says

Abstract This study analyses the distributional impact of healthcare reform policies using a computable general equilibrium model with disaggregated household groups. Two simulations are conducted using a static computable general equilibrium model for Malaysia based on a health‐focused Social Accounting Matrix to align with the government's aims in the Health White Paper: implementing an earmarked tax and a co‐payment system. The findings suggest that the earmarked tax scenario significantly benefits low‐income people if public health subsidies are expanded under the revenue neutrality policy. The welfare effect becomes more pronounced when the simultaneous health effect is present. Regarding expenditure, the household‐specific consumer price index demonstrates notable progressivity among urban households in the co‐payment simulation but not in the earmarked tax simulations. It is plausible to claim that raising the healthcare fund would boost welfare only if taxpayers received more benefits, as in the earmarked tax scenario. The findings provide insights for designing equitable and fiscally sustainable healthcare financing reforms in Malaysia, particularly in balancing revenue generation with distributional equity across income groups.

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https://doi.org/https://doi.org/10.1002/rfe.70043

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@article{manjeet2026,
  title        = {{The distributional impacts of earmarked taxes and co‐payments in healthcare}},
  author       = {Manjeet Kaur Harnek Singh et al.},
  journal      = {Review of Financial Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/rfe.70043},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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