Introduction

Healthcare expenditure plays a crucial role in determining the quality and accessibility of healthcare services within a country. However, Healthcare must be a priority, which calls for either more spending and investment or a more proactive approach to boosting individual state economies so that more money can be allocated to healthcare sector development [1]. Public healthcare services significantly influence people's health status, and public healthcare infrastructure is one of the key factors affecting health outcomes in a nation [2]. To enhance India's ranking on the human development index, the Indian government must manage its public expenditures effectively [3]. In India, the healthcare sector is confronted with numerous challenges, including a vast and diverse population, inadequate infrastructure, and limited financial resources. The allocation of healthcare expenditure across different states can vary significantly, reflecting variations in economic development, healthcare infrastructure, and health outcomes [4]. Understanding the patterns of healthcare expenditure in Indian states is essential for formulating effective policies and interventions to improve healthcare delivery and ensure equitable access to healthcare services. Healthcare expenditure is a fundamental aspect of healthcare systems worldwide, serving as a key determinant of healthcare outcomes and access to quality care [5]. In the context of India, a country with a population of over 1.3 billion people and immense diversity, healthcare expenditure patterns are critical in addressing the healthcare needs of its states and population [6].

India's healthcare system is characterized by a complex mix of public and private sector participation, with varying degrees of resource allocation and service delivery. The Indian government has made efforts to improve healthcare infrastructure and services, notably through initiatives such as the National Health Mission and the Ayushman Bharat scheme. Investment in health expenditure has a positive degree of long-run correlation with life expectancy rate, while it is negatively associated with the infant mortality rate [7]. However, challenges persist, including disparities in healthcare expenditure across states, inadequate public healthcare infrastructure, and financial constraints. The allocation of public funds to the healthcare sector is a crucial determinant of healthcare expenditure. Governments at the state and central levels need to prioritize healthcare spending in the NER states to bridge the healthcare infrastructure gaps and improve access to quality healthcare services. Increased government spending on healthcare can lead to better healthcare outcomes and increased expenditure overall. To gain insights into the allocation of healthcare expenditure in Indian states, it is essential to examine comprehensive data that may, directly and indirectly, captures the healthcare spending patterns. Such data can include government budgetary allocations, total revenue collection, total social expenditure as well as debt and fiscal deficit accounts. Analyzing this data enables policymakers and researchers to assess the adequacy and efficiency of healthcare spending, identify areas of improvement, and develop evidence-based strategies to enhance healthcare delivery and access.

This study aims to explore the macroeconomic policy impact on healthcare expenditure patterns in northeast India. By examining the trends and variations in healthcare expenditure, we can gain valuable insights into the resource allocation dynamics and identify potential areas for policy interventions.

Materials and Methods

Utilizing the data from the Economic and Political Weekly Research Foundation, the present study included eight NER states of India, namely Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim and Tripura, for the period of 1990-91–2019-20. The chosen fiscal variables, including total social sector expenditure, per-capita gross state domestic product, total revenue receipts, and states’ own and non-tax revenue, are regarded as macroeconomic factors of an economy and may have a positive impact on healthcare spending. In contrast, variables like internal debt and the fiscal deficit may have a negative impact on healthcare spending.

Table 1 represents the description and summary statistics of the selected variables, which shows that the mean of PHE is 1.329 per cent while the mean of total revenue receipts is 29.947 per cent. There is a huge difference in the maximum and minimum value of total revenue receipts and PHE, respectively. It shows that most of the tax revenue across the states is derived from the low contribution of states’ own tax revenue. Huge differences have been also observed in maximum and minimum value of internal debt and gross fiscal deficit, indicating inter-state variation over time. Besides, positive correlation is found between PHE with other explanatory variables such as TSE, PCGSDP, TRR, SOTR, NTR, CGR, as well as IND and GFD (as described in Table 1). All the variables are taking the base year of 2011–2012 at constant prices.

Prior to formulating the VECM model for the analysis, the following model has been used, covering the nine variables as mentioned in (Table 1):

PHE = β₀+ β₁TSE_it+ β₂PCGSDP_it + β₃TRR_it + β₄SOTR_it + β₅NTR_it + β₆IND_it + β₇GFD_it + β₈CGR_it + µ_it(1)

Sigma Convergence Analysis

To check the convergence tendency of the variables of public healthcare expenditure and the macroeconomic variables, such as total social sector expenditure, per capita GSDP, total revenue receipts, states’ own tax revenue and non-tax-revenue, internal debt, fiscal deficit and central grants to states, sigma convergence analysis has been applied. The sigma “σ”- convergence approach can be employed, through the help of the coefficient of variation (CV) over time. For the present case, all the eight North Eastern states were taken together to examine their tendency of convergence/divergence trend from 1990-91 to 2019-20. The following formula has been used for the analysis:

(2)

In this context, 'n' denotes the total number of objects, specifically referring to the eight states under consideration. 't' represents the specific year being discussed, while 'i' represents each individual member state being examined. Lastly, 'y' represents the cumulative fiscal pressure being analyzed.

Vector Error Correction Model (VECM) Approach

Further, the present paper uses the VECM approach for forecasting macroeconomic variables. The VECM is a widely used econometric model that allows for the analysis of long-run relationships and short-run dynamics among multiple time series variables. By incorporating both the cointegration and error correction mechanism, the VECM provides a powerful framework for modelling and forecasting macroeconomic variables. In this study, we apply the VECM methodology to a set of key macroeconomic indicators and evaluate its forecasting performance against alternative approaches. The VECM analysis shows the results of short as well as long-run impact, despite the stationarity properties of the series. The specification of the VECM model is as follows:

(3)

The symbol of ‘Δ’ denotes first-difference order, and is an error correction term with no correlation with the independent variables of the model. The long-run relationship of the variables can be achieved if b₀,_i= 0 is negative and it is rejected in the model. On the other hand, the short-term relationship among the variables can be observed, if b _1,i = 0 is rejected, through the Wald test.

Discussion

Macroeconomic Policies and the Public Health Expenditure: Indian States

The potential of a rise in India's public health expenditures is increased by the combination of improved growth prospects at least over the medium term and fiscal consolidation [8]. Since the 1990s there is changing trends of macroeconomic factors such as total social expenditure, per capita gross domestic product (GDP) as a proxy of economic growth, internal debt, fiscal deficit, central grants to respective states, and revenue account through total revenue receipts, states’ own and non-tax revenue and public health expenditure across the Indian states (Figure1). For the development of healthcare sector, the macroeconomic factors play a vital role in the contribution of fiscal space [9]. The growth trend of PHE to GDP has consistently increased and it increases from 0.2 in 1990-91 to 0.10 per cent in 2019-20. The trend of public health expenditure to GDP is increased with total social sector expenditure in the ratio of GDP. The increasing trend of total revenue receipts and central grants with increasing states’ own tax and non-tax revenue has been observed over time, which can be considered as the prospective source for financing the healthcare system. A similar study has found that Indian states being heterogeneous in nature and having low tax revenue, there is a positive impact of tax revenue on healthcare expenditure growth over time [10].

Figure 1: Public Health Expenditure and Macroeconomic Variables: Trends Analysis Source: Authors’ Calculation based on EPWRF data series (1990-91 to 2019-20).

However, with the increasing trend of the PHE-GDP ratio, the fiscal deficit and internal debt in ratio of GDP also increased, it may be considered that the debt and deficit amount is used in development expenditure purpose like public health and education. Despite of growth of revenue trend, the growth trend of PHE is slightly declined during 2001-02 to 2004-05 due to higher fiscal deficit but it increased after the reduction of fiscal deficit in 2007-08. Further, there is fluctuation in terms of per capita GDP of Indian states over time. Although, a positive bi-directional relationship has been found for developing countries. The effect of health expenditures on economic growth justifies the need for governments to implement policies that encourage health expenditures to create a healthier and more productive society in order to foster the development and expansion of the economy in developing nations [11].

Tendency of Convergence: “σ” Analysis

As stated in the methodology section, the assessment of convergence/divergence through σ-convergence can be carried out using the coefficient of variation method. The results of the coefficient of variation over time for all the northeastern states together reveal that macroeconomic variables, including states' own tax revenue, internal debt, public health expenditure, and total social sector expenditure, tend to converge during the period of 2019-20. The variable of fiscal deficit has exhibited greater fluctuations compared to other variables. However, it is noteworthy that fiscal deficit has displayed a declining trend since the fiscal year 2016-17. Additionally, it is observed that variables such as per capita GSDP, non-tax revenue, and central grants to states have shown a tendency to diverge over time. Therefore, it is evident that the northeastern states reveal a similar pattern in terms of their performance in macroeconomic factors, as they are all economically, socially, and geographically underdeveloped.

Figure 2: Sigma Convergence Analysis from 1990-91 to 2019-20 Source: Authors’ Calculation based on EPWRF data series (1990-91 to 2019-20).

Macroeconomic Factors Response to PHE from 1990-91 to 2019-20

Prior to the empirical analysis of the model, the panel unit root test has been applied for all the nine variables of the study, by using Levin-Lin-Chu “LLC”, [12] and Im-Pesaran-Shin “IPS” [13] test. The LLC test is an extension of the Augmented Dicky Fuller (ADF) test for panel data. It assumes the presence of a common unit root across all individuals, while the IPS test allows for both a common unit root and individual-specific unit roots, considering cross-sectional dependence and heterogeneity. Afterwards, the long-term co-movement between the variables has checked through the Johansen cointegration test. The Johansen cointegration test enables the analysts to comprehend the interdependencies and dynamics between various economic variables and to make better decisions based on the discovered long-term relationships. Based on the results of unit root and cointegration test, further long-run and short-run impact of the macroeconomic variables on public health expenditure can be analyzed by utilizing the VECM approach.

Panel Unit-Root Tests

The result of panel unit root tests is presented in Table 2, where null shows non-stationarity and the alternative hypothesis indicates stationarity in the series. The variables, viz. public health expenditure, total social sector expenditure, per capita GSDP, states’ own tax revenue, internal debt, and central grants to states are panel non-stationary and total revenue receipts, states’ own non-tax revenue and fiscal deficit are stationary at the level in LLC test. Further, in case of the IPS test, except for states’ own non-tax revenue and fiscal deficit, all the other variables are panel non-stationary at level. Besides, all the variables are stationary at first difference level in case of both LLC and IPS tests.

Panel Cointegration Tests

The significance of cointegration test lies in its ability to facilitate the establishment of a meaningful and consistent association between variables, even in the absence of direct causal linkage. Table 3 demonstrates the results of the Johansen cointegration test [14], which indicates the long-term relationships between PHE and other macroeconomic variables (as eq.1). The results of the test show that there is significant long-run co-movement among public healthcare expenditure and the macroeconomic variables such as total social sector expenditure, per capita GSDP, total revenue receipts, states’ own tax and non-tax revenue, internal debt, fiscal deficit and central grants to states, implying that the public health expenditure would be sustained in the long-run with increase or decrease in total social sector expenditure, expansion of revenue generation, lower fiscal deficit and internal debt of the states.

Macroeconomic Factors on Public Health Expenditure Growth: Long-run Impact

This section summarizes the key findings of the study and emphasizes the value of the VECM approach in forecasting macroeconomic variables. We highlight its advantages over traditional models and its potential to capture both short-run dynamics and long-run equilibrium relationships. The long-run impact of macroeconomic factors on public health expenditure growth is presented in Table 4. The coefficient of total social sector expenditure is positive and significant at one per cent level, indicating that an increase in TSE leads to 5 per cent increase in PHE. Surprisingly, the per capita GSDP is negative with -1.49 points at one per cent significant level. A similar study found that the northeastern states namely, Nagaland, Manipur and Meghalaya exhibit a regressive trend in the change of public healthcare financing. This is attributed to the moderate increase in the states' domestic product, which is accompanied by a decline in government health expenditure [15]. Further, total revenue receipts and states’ own tax revenue are positively significant, implying an increase in both the indicators leads to 3.8 and 11.9 per cent increase in PHE, respectively. The coefficients of states’ own non-tax revenue and central grants to states have negative and significant impact on the growth of PHE in the long run. Although, all the eight northeastern states are getting higher central grants, being in the list of Special Category States, due to various disadvantageous features [16]. The northeastern states might fail to increase healthcare expenditure due to their lack of physical and social infrastructure facilities. Besides, the coefficient of internal debt is negative, while the fiscal deficit has positive impact on PHE at ten per cent level. Thus, it is clear that an increase in total social sector expenditure and revenue receipts have favourable impact on the growth of PHE for the North Eastern states in the long run.

Macroeconomic Factors on Public Health Expenditure Growth: Short-run Impact

Due to lack of resources and lack of proper utilization of the existing resources, low-income category states of India were lagging behind in public sector efficiency [17]. The short-run impact of macroeconomic variables on PHE has been analysed through the VECM approach. Table 5 explains that the model that has short-run impact and the error correction term value is -0.052 at one per cent significant level. The coefficients of total social sector expenditure and states’ own tax revenue have positive short run impacts on the growth of public health expenditure. Additionally, PHE has been negatively affected, through central grants. Further, fiscal deficit has negatively and significant effect on PHE in the short-run. The other variables such as total revenue receipts, per capita GSDP, states’ own non-tax revenue and internal debt have no short-run impact on PHE. Thus, it is clear that an increase in total social sector expenditure and revenue receipts also has favourable impact on the growth of PHE for the northeastern states in the short run.

Conclusion

The relationship between macroeconomic factors and healthcare expenditure can be complex and can vary across countries depending on their healthcare systems, policies, and socio-economic factors, which need to carefully balance these factors to ensure sustainable and equitable healthcare spending. The present study examines the impact of macroeconomic factors i.e. economic growth, revenue account, internal debt, fiscal deficit, and central grants on the public health expenditure in evaluating financial space for health in the northeastern states of India from 1990-91 to 2019-20. The study observed that the trend of public health expenditure to GDP is increased with total social sector expenditure, total revenue receipts and central grants with increasing states’ own tax and non-tax revenue in ratio of GDP, which can be considered as the prospective source for financing healthcare system of Indian states. Besides, the macroeconomic factors of the northeastern states, such as states' own tax revenue, internal debt, public health expenditure, and total social sector expenditure tend to converge during 2019-20. Fiscal deficit fluctuates more than other indicators but tends to converge since 2015-16. Further, per capita GSDP, non-tax revenue, and central transfers to states are diverging over time. The study results based on the VECM approach highlight that with the increase in total social sector expenditure and all the revenue receipts heads viz. total receipts and states’ own and non-tax revenue have favourable impact on the growth of PHE for the northeastern states in both long-run and short-run. The central grants to the northeastern states have both short-run and long-run impacts on PHE. Thus, it can be said that being key indicators of economic development, the macroeconomic factors lead to a significant impact on healthcare expenditure. The variables like fiscal deficit and internal debt have no short-run impact but they have long-run significant impact on the growth of healthcare expenditure. Thus, the findings of the study suggest that the government of northeast India should develop such schemes for healthcare development with higher infrastructure facilities, including hospitals, clinics, and healthcare training institutes. Increased investment in infrastructure can contribute to higher healthcare expenditure.

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