Impact of GDP and tax revenue on health care financing: An empirical investigation from Indian states
Deepak Behera () and
Additional contact information
Umakant Dash: Indian Institute of Technology Madras, India
Theoretical and Applied Economics, 2017, vol. XXIV, issue 2(611), Summer, 249-262
This paper investigates the long run impact of GDP and tax revenue on public health care expenditure using panel FMOLS and DOLS models for sixteen major states of India over the period 1980-2013. This study is more relevant in order to measure the progress in universal health care financing across the states of India because states are heterogeneous in terms of health care spending, associated with low tax bases and low level of GDP growth. The empirical result shows that health expenditure, GDP and tax revenue are cointegrated in the long run. There is a positive and significant impact of income and revenue generation on growth of health care expenditure while the elasticity of health care expenditure is less than one. The result implies that there is state level heterogeneity in the share of medical and public health care expenditure to income in India. These research findings would serve as effective policy instruments to measure the progress towards universal health coverage among the states of India.
Keywords: public health care expenditure; Indian states; GDP; tax revenue. (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:agr:journl:v:xxiv:y:2017:i:2(611):p:249-262
Access Statistics for this article
Theoretical and Applied Economics is currently edited by Marin Dinu
More articles in Theoretical and Applied Economics from Asociatia Generala a Economistilor din Romania - AGER Contact information at EDIRC.
Series data maintained by Marin Dinu ().