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On the nexus of environmental quality and public spending on health care in China: a panel cointegration analysis

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  • Yihua Yu
  • Li Zhang
  • Xinye Zheng

Abstract

Does pollution drive up public spending on health care? This paper aims to answer such a crucial question empirically using a panel data set of 31 Chinese provinces during the period 1997–2014. In particular, this paper explores the non-stationarity and cointegration properties between health care expenditure and environmental indicators in a panel cointegration framework; in doing so, it examines both the long-run and the short-run impacts of the per capita provincial GDP, waste gas emissions, dust and smog emissions, and waste water emissions on the per capita public health expenditure. We apply panel unit root tests, heterogeneous panel cointegration tests, FMOLS techniques, and a panel-based error-correction model. The conclusion is that, both in the long run and in the short run, public health care expenditure is positively affected not only by the provincial economy but also by the environmental quality.

Suggested Citation

  • Yihua Yu & Li Zhang & Xinye Zheng, 2016. "On the nexus of environmental quality and public spending on health care in China: a panel cointegration analysis," Economic and Political Studies, Taylor & Francis Journals, vol. 4(3), pages 319-331, July.
  • Handle: RePEc:taf:repsxx:v:4:y:2016:i:3:p:319-331
    DOI: 10.1080/20954816.2016.1218670
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    Cited by:

    1. Ramesh Chandra Das & Enrico Ivaldi, 2021. "Is Pollution a Cost to Health? Theoretical and Empirical Inquiry for the World’s Leading Polluting Economies," IJERPH, MDPI, vol. 18(12), pages 1-17, June.
    2. Muhammad Haroon Shah & Nianyong Wang & Irfan Ullah & Ahsan Akbar & Karamat Khan & Kebba Bah, 2021. "Does environment quality and public spending on environment promote life expectancy in China? Evidence from a nonlinear autoregressive distributed lag approach," International Journal of Health Planning and Management, Wiley Blackwell, vol. 36(2), pages 545-560, March.

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