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

Yihua Yu (), Li Zhang and Xinye Zheng

Economic and Political Studies, 2016, vol. 4, issue 3, 319-331

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.

Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/20954816.2016.1218670 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:repsxx:v:4:y:2016:i:3:p:319-331

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/reps20

DOI: 10.1080/20954816.2016.1218670

Access Statistics for this article

Economic and Political Studies is currently edited by Qing He and Cunna Li

More articles in Economic and Political Studies from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().