Empirical Analysis of Beneficial Equality of the Basic Medical Insurance for Migrants in China

Author:

Gao Jieying1ORCID,Chu Dongxiao1ORCID,Ye Tao2ORCID

Affiliation:

1. School of Finance, Capital University of Economics and Business, Beijing 100070, China

2. School of Banking and Finance, University of International Business and Economics, Beijing 100029, China

Abstract

The fairness of the benefits of basic medical insurance for the migrants is drawing increasing attention. This paper examined the beneficial equality of the basic medical insurance for the floating population in China using the “2014 National Internal Migrant Dynamic Monitoring Survey.” The Heckman model was employed due to selection bias among inpatients, and the random forest algorithm of machine learning was used to analyze the importance of factors affecting the hospitalization decision-making, hospitalization consumption, and reimbursement proportion of the floating population. The results show significant differences in the fairness of basic medical insurance benefits among different income groups, and the highest-income group benefits the most. In contrast, the higher-income group benefits the least. Further verification by introducing the commercial medical insurance indicated that the differences among different income groups did not disappear but reduced the degree of difference among the groups. Although China’s healthcare reform has progressed greatly, the study’s findings confirm that the government’s fair medical insurance can lead to unfair problems and the phenomena of low-income groups subsidizing high-income groups under the equalized basic medical insurance system. Adjusting the design of equalized medical insurance and allowing different income groups to pay different premium levels according to the payment level may be more conducive to the fairness of benefits based on achieving universal health coverage in China.

Funder

Great Wall Scholar Training Program for the Construction of High-level University Teachers

Publisher

Hindawi Limited

Subject

Modeling and Simulation

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