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Economic growth and the geographic maldistribution of health care resources: Evidence from China, 1949-2010

Xuezheng Qin () and Chee-Ruey Hsieh

China Economic Review, 2014, vol. 31, issue C, 228-246

Abstract: The geographic maldistribution of health care resources is one of the most persistent characteristics of health care systems around the world. Based on China’s provincial-level panel data in 1949-2010, this paper empirically investigates whether the geographic distribution of health care resources is convergent or divergent in the long run and whether the rapid economic growth contributes to reducing the regional disparity in health care resources in China. Using a dynamic convergence model that controls unobserved provincial heterogeneity and spatial dependence, the empirical results provide much support for β-convergence in that the provinces with lower initial values of health care resources, including the densities of physicians and hospital beds, are seen to grow faster and to catch up with the provinces with higher initial stocks. In addition, we find that GDP per capita has a significant and non-linear impact on the convergence rate of health care resources, providing support for a Kuznets curve in China’s health sector. That is, the inequality in the distribution of health care resources follows an inverted “U” shape as income increases over time. An important implication of our study is that economic growth per se provides a built-in stabilizer to mitigate health inequality through the convergence of health care resources across regions in the long run.

Keywords: Health Care Resources; Economic Growth; Geographic Maldistribution; Dynamic Convergence Model; Kuznets Curve (search for similar items in EconPapers)
JEL-codes: I14 I15 O18 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chieco:v:31:y:2014:i:c:p:228-246

DOI: 10.1016/j.chieco.2014.09.010

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China Economic Review is currently edited by B.M. Fleisher, K. X. D. Huang, M.E. Lovely, Y. Wen, X. Zhang and X. Zhu

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