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Medical expenditure in urban China: a quantile regression analysis

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International Journal of Health Economics and Management Aims and scope Submit manuscript

Abstract

Many countries have been trying to expand their public health insurance coverage in recent years. To achieve two fundamental policy goals—equity in health care utilization and control of health care costs—policymakers need a better understanding of the underlying determinants of individual health care expenditure beyond the results of mean regressions. In this paper, we apply a quantile regression method to investigate the heterogeneous effects of various determinants of medical expenditure in China. Comparing with the average effects, we find that health care expenditures at the upper end of the distribution are under stronger influences of need factors such as poor health status, and weaker influences of socioeconomic factors and insurance status. On the other hand, health care expenditures at the lower end of the distribution are under stronger influences of socioeconomic factors and insurance status, and weaker influences of need factors. Our study may provide useful information to policymakers for the optimal design of their health care systems, and it may be of particular interests to the health policymakers in China, where is currently still in a period of reshaping its health-care system.

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Notes

  1. One exception is Kowalski (2010), in which the author adopts a quantile regression approach.

  2. For both surveys, the questionnaire was designed by Chinese and foreign researchers and implemented by China’s National Bureau of Statistics (NBS). Although most survey contents in 2009 survey are similar to the CHIP 2002 data, some questions or answer options in 2009 RUMiCI (also called CHIP 2008) data are different from those from the CHIP 2002 data.

  3. For detailed sampling information, please refer http://rumici.anu.edu.au.

  4. Among them, inability to work group includes formally retired people or individuals who are unable to work. Unemployed group is composed of lay-off workers and purely unemployed individuals. Finally, the group named not ready for job contains full-time homemakers, students, and other idle persons.

  5. To control the potential city-specific effect and heteroscedasticity problem (errors clustered at city level), we have tried to add a group of city dummies instead of the provincial dummies, and reached similar results. To save more degrees of freedom, we run the regressions with provincial dummies.

  6. From Tables 7 and 8, an interesting finding is that the marginal effects of age for GIS holders are relatively stable across health care expenditure distribution, and much stronger than that for UEBMI holders. Rising health expenditures on the elderly is a major concern for policymakers in the developed world. Our results indicate that it might be closely related to features of health insurance plans.

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Acknowledgments

This research is sponsored by “Humanities and Social Sciences Planning Fund, No: 10YJC790393 ” from Chinese Ministry of Education.

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  1. China Academy of Public Finance & Public Policy, Central University of Finance & Economics, 39 South College Road, Haidian District, Beijing, 100081, People’s Republic of China

    Jianmei Zhao & Hai Zhong

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  1. Jianmei Zhao
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  2. Hai Zhong
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Correspondence to Jianmei Zhao.

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Zhao, J., Zhong, H. Medical expenditure in urban China: a quantile regression analysis. Int J Health Econ Manag. 15, 387–406 (2015). https://doi.org/10.1007/s10754-015-9174-0

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