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Prioritization of government expenditure on health in India: A fiscal space perspective

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  • Behera, Deepak Kumar
  • Dash, Umakant

Abstract

Unequal distribution of fiscal resources and lower prioritization of budget towards healthcare are the most important challenges in achieving universal health coverage in India. This study has examined relationships between government health expenditure and fiscal space (i.e. tax revenue, non-tax revenue, fiscal transfer, and borrowings) in twenty-one states of India for the period of 1980–2014. Our panel regression results imply that mobilization of tax revenue has a positive impact, while borrowings have a negative impact on the allocation of government expenditure on healthcare in the long-run. The panel quantile regression results show that states associated with the low and middle level of revenue growth have been mobilizing finance through central government transfer and borrowings in short-run. Further, the panel vector error correction models show that sum of the lagged coefficients of borrowings have a greater impact on health financing process as compared to other sources of fiscal space at short-run, and the speed of adjustment towards long-run equilibrium is relatively slower. The overall analysis concludes that less domestic revenue mobilization and higher dependency of borrowings for healthcare financing may create fiscal stress on state finances in the long-run, and thereby it could possibly reduce the prioritization of spending. Therefore, improvement in revenue growth and proper utilization of fiscal transfer would be appropriate policy implications from this study.

Suggested Citation

  • Behera, Deepak Kumar & Dash, Umakant, 2019. "Prioritization of government expenditure on health in India: A fiscal space perspective," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:soceps:v:68:y:2019:i:c:s0038012118300041
    DOI: 10.1016/j.seps.2018.11.004
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    2. Biswajit Nag & Willem van der Geest, 2020. "Economic Impact Analysis of Covid-19 Implication on India’s GDP, Employment and Inequality," Working Papers 2041, Indian Institute of Foreign Trade.
    3. Behera, Deepak, 2020. "Does the Higher Level of Health System Spending Speed Up the COVID-19 Detection Rate?: Evidence from South-East Asia Region," MPRA Paper 100554, University Library of Munich, Germany, revised 31 Apr 2020.
    4. Chakrabarty, Himadri Shekhar & Roy, Rudra Prosad, 2021. "Pandemic uncertainties and fiscal procyclicality: A dynamic non-linear approach," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 664-671.
    5. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data: a comment on the Canay (2011) fixed effects estimator," Working Papers w0249, Center for Economic and Financial Research (CEFIR).
    6. Galina Besstremyannaya & Sergei Golovan, 2019. "Reconsideration of a simple approach to quantile regression for panel data: a comment on the Canay (2011) fixed effects estimator," Working Papers w0249, New Economic School (NES).

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    More about this item

    Keywords

    Government health expenditure; Fiscal space; Universal health coverage; Panel data; Quantile regression; India;
    All these keywords.

    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • H61 - Public Economics - - National Budget, Deficit, and Debt - - - Budget; Budget Systems
    • H70 - Public Economics - - State and Local Government; Intergovernmental Relations - - - General
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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