State comparative analysis of health expenditure of India

Introduction

Health is a crucial determinant for society as a whole. A healthy society contributes directly to productivity, human capital formation, and long-term economic growth. In India, health expenditure is important in determining access to universal health coverage, quality healthcare services, and financial protection for households. A critical aspect of India's health expenditure is significant, with inter-state variation in health financing. The paper highlights the disparities in public healthcare infrastructure, government contribution, and the prevalence of private providers, among the Indian states. This study focuses on five developed states of India selected in terms of NSDP -net state domestic product, which include West Bengal, Punjab, Gujarat, Maharashtra, and Tamil Nadu. Despite the states having high income, the ratio of Private Spending is higher than Government Spending in the health sector. Hence, the government of India has concerns about the persistently high share of Household Health Spending out of National Health Expenditure (NHE). Therefore, recently the government took policy initiatives such as Ayushman Bharat, National Health Mission, and increased government health spending, which have aimed to improve financial protection, although Household Health Spending (HHS) is still a burden on household of many states. In this context, understanding the trends of health expenditure at the state level is essential for designing effective health financing policies. This study was conducted on an analysis of health expenditure in five major Indian states-West Bengal, Punjab, Gujarat, Maharashtra, and Tamil Nadu for the period from 2014-15 to 2021-22. These states represent diverse economic, demographic, and institutional contexts across different regions of India. It examines trends in population, State Income [1] (SI), National Health Expenditure [2] (NHE), Per Head Healthcare Cost [3] (PHHC), Government Health Spending (GHS), and Household Health Spending [4] (HHS), and investigates how economic and demographic factors influence HHS payments.

Objectives

 To examine trends and to do a comparative study of the health expenditure across five Indian States, Zone-wise (West Bengal, Punjab, Gujarat, Maharashtra, and Tamil Nadu).  To identify determinants of Household Health Spending (HHS) using panel data analysis.

Literature review

The study reviewed more than 15 papers regarding the State Comparative Analysis of Health Expenditure of India. Most of the studies have included the objectives on the government contribution to the health sector, and examined the health outcomes by using various methodologies such as the panel unit root test, the Arellano-Bond Generalized Method of Moments, correlation matrix, and causality test.

On that basis, the relevant studies are enumerated below: Duggal et al. (1995) [1,2] conducted a study on Health Expenditure, highlighting the necessity of social investment for equitable access to health. They observed that the www.extensionjournal.com inefficient utilization of public health infrastructure and the unequal distribution of resources. For analysis, they used secondary data, descriptive and comparative statistical methods from the Central Statistical Organization and NSSO.

The study revealed that private expenditure on health (80 percent) is relatively high compared to public expenditure (20 percent). They found that health spending has been declining since 1970 and revealed significant regional disparities (rural and urban areas) in healthcare access. Hence, the study concluded that public investment is insufficient, with persistent disparities and a dominant private sector presence. Recommendations included increased public investment and improved regulatory mechanisms for health sector development.

Duggal et al. (1995) [1,2] examined regional disparities in health expenditure across Indian states, noting health as primarily a state responsibility. Their study used secondary data and longitudinal statistical analysis to compare various expenditure variables. The analysis revealed that despite an increase in family welfare programs since 1975, but still been a decline in total government spending since the mid-1980s, indicating inefficiency in resource allocation. Therefore, the study concluded that it found regional disparities, in which developed states spend more per capita on health, while poorer states remain underfunded. Bhat and Jain (2004) [3] studied state-level public health spending in India; they analysed that the government allocated around 0.5 percent of GSDP on health, excluding central initiatives like family welfare. Using secondary and panel data from 14 large states (1990-2002), they estimate an income elasticity of 0.68, highlighting diminishing PHCE as a percentage of GSDP amid economic challenges and showing that per capita health spending rises more slowly than income. This highlighted the difficulties in raising public spending to the suggested 2-3 percent of GDP, which is consistent with an increased quantity of studies on incomedriven yet inelastic health expenditures in emerging nations. Bokhari et al. (2006) [4] studied the relationship between government expenditures on health and health outcomes to examine whether an increase in health spending can improve mortality rates the UN Millennium Development Goals. They used an advanced econometric approach on cross-country data from 127 nations for the year 2000, and found that health spending has reduced child and maternal mortality rates. Their analysis revealed that a 1percent increase in government expenditure on health correlates with a 0.33 percent decrease in under-five mortality and a 0.50 percent decrease in maternal mortality. The study concluded that increased government health budgets are effective in improving health outcomes.

Hooda (2016) [5] studied the determinants of public health expenditure in India using an empirical panel model. The study used the data on 16 selected major states of India for the time period 1987 to 2012. They used various methodologies, including Fixed Effects Panel and the Arellano-Bond Method, to explore the impact of factors such as income, political participation, and fiscal capacity on health expenditure per capita. The outcome shows a significant positive correlation between political participation and health spending, highlighting that states generating higher revenue can better fund healthcare. The conclusion emphasized that health is a fundamental need, and many Indian states are inadequately prioritized in their health expenditure. Balani et al. (2023) [6] analysed the correlation between public expenditure on health and income across Indian states. For state-wise analysis, the study used an advanced Granger causality test on data from 1981 to 2017, classified into two categories: the special states and non-special states based on demographic and economic factors. They found a short-run non-linear bi-directional relationship influenced by regime changes and institutional factors. special states (EAG) exhibited higher income elasticity in health spending compared to non-special states (non-EAG), although their expenditure levels were less consistent. The study revealed that the link between health expenditure and income is influenced by government factors, and recommended to use fund in an efficient manner that is output-based, based on budget implications, especially in developing EAG states. Sofi and Yasmin (2024) [7] studied the effect of OOP health expenditure on the economic growth of Indian states. They emphasised how OOPHE affects the households. They used secondary data from the NHA and panel analysis of 19 states for the time period 2013-2014 to 2019-2020. They found that population growth and government health expenditure had no significant effect, and on the other hand, GSDP significantly reduces OOPHE. They concluded that reducing OOP health expenditure is essential for economic growth and recommended improving public health investment efficiency through health insurance coverage and strengthening primary healthcare infrastructure.

Conclusion

In short, the study indicates that reducing Household Health Spending, improving public health spending, and enhancing the effectiveness and targeting of universal health coverage will contribute to growth in India. Key policies that have been highlighted are strengthening primary healthcare, increasing insurance coverage, and improving state-level development. Therefore, all of the analysed research provides credibility to the idea that long-term economic growth and social development depend on fair access to healthcare and sustainable health financing.

Research gap

The study examines trends and conducts a comparative analysis of health expenditure in five Indian States (Punjab, Gujarat, Maharashtra, West Bengal, and Tamil Nadu), zonewise, using panel data and Household Health Spending determinants.

Research methodology

B. To identify determinants of PHE expenditure using panel data analysis.

Section two examines the effectiveness of health financing policies of these five states. The study analyses the economic and demographic determinants of Household Health Spending. Using panel data analysis in specific Indian states, focusing on the role of State Income (SI), Per Head Healthcare Cost (PHHC), and Population (POP). The result will be empirical evidence for reducing HHS burden and strengthening financial protection in India's health system. This panel data Fixed Effects (FE) model was selected through a rigorous specification testing process to robustly estimate the HHS determinants across Indian states, accounting for unobserved state-specific heterogeneity. Panel data methods were employed due to the balanced dataset (5 states × 8 years = 40 observations), which captures both cross-sectional (inter-state) and time-series (temporal) variations in HHS drivers like SI, PHHC, and POP. This approach mitigates omitted variable bias common in crosssectional analysis and controls for endogeneity better than time-series alone, aligning with prior health economics studies on Indian states (e.g., Hooda, 2016; Sofi & Yasmin, 2024) [5,7] . ). Larger population sizes tend to increase Household Health Spending (HHS), reflecting pressure on public health systems and greater reliance on private healthcare.  Overall, the pooled model suggests that economic growth reduces HHS burden, while population pressure and increased per-capita health spending raise it.  It also explains that if the P-value is above 0.05, we accept the panel least squares pooled OLS result, if the P-value is below 0.05, indicating rejection of the null hypothesis, we run a fixed or random effects model.  Hence, the P-value is below 0.05, we reject the null hypothesis, and further, we run a fixed or a random effects model. 3.933218 0.359863 10.92975 0 Source: Author's Estimation R-square = 0.81, F-statistic = 54.11, Prob = 0, Durbin-Watson stat = 0.39 A period random effects model was estimated to capture unobserved time-specific factors such as policy changes, macroeconomic shocks, and structural reforms affecting public health expenditure.  All three independent variables remain statistically www.extensionjournal.com significant: SI -Negative and Significant, and PHHC and Population -Positive and Significant.  The R-square remains the same to pooled model (0.818), and the F-statistic is also significant, indicating good model fit.  The RE model assumes that state-specific effects are random and uncorrelated with regressors. It suggests that higher income reduces HHS, while population growth and Per Head Healthcare Cost increase the HHS burden.  However, whether RE is appropriate must be confirmed using the Hausman test.

For Panel Data Analysis

References

1. Duggal R, Nandraj S, Vadair A. Health expenditure across states -Part I. Economic and Political Weekly. 1995;30(15):834-844.
2. Duggal R, Nandraj S, Vadair A. Health expenditure across states -Part II: Regional disparity in expenditure. Economic and Political Weekly. 1995;30(17):982-990.
3. Bhat R, Jain N. Analysis of public expenditure on health using state-level data. Ahmedabad: Indian Institute of Management Ahmedabad; 2004. www.extensionjournal.com
4. Bokhari FAS, Gai Y, Gottret P. Government health expenditures and health outcomes. Health Economics. 2006;16(3):257-273.
5. Hooda SK. Determinants of public expenditure on health in India: A panel data analysis at sub-national level. Journal of Quantitative Economics. 2016;14(2):257-282.
6. Balani K, Gaurav S, Jana A. Spending to grow or growing to spend? Relationship between public health expenditure and income of Indian states. SSM - Population Health. 2023;21:101310.
7. Sofi SA, Yasmin E. Out-of-pocket health expenditure and associated factors: Insights from National Health Accounts using panel data analysis. INQUIRY: The Journal of Health Care Organization, Provision, and Financing. 2024;61:1-19.
8. National Health Systems Resource Centre. National Health Accounts report (2014-2015 to 2021-2022). Available from: https://nhsrcindia.org/national-healthaccounts-records