Short-Run and Long-Run Income Elasticity of Healthcare Expenditure in India: Role of Domestic Revenue and Public Debt

Existing literature argues that income growth is an important determinant for change in healthcare expenditure in developing economies. Most of them examine the elasticity of public health expenditure concerning per capita income while the role of scal policies – public revenue and public debt to determine the level of spending has never been studied. Therefore, this study examines the income elasticity of public health expenditure in both short-run and long-run by controlling domestic revenue, and public debt (i.e. borrowings) in India for the period from 1980-81 to 2015-16. The study follows three steps for empirical analysis. First, we test stationarity properties of variables using the Zivot and Andrews (ZA) unit root test assuming that the Indian economy might have experienced structural breaks at different time points. Second, we examine the cointegrating relationships among variables using the Auto-Regressive Distributed Lag (ARDL) bounds testing approach. Third, we estimate both short-run and long-run elasticity by controlling structural-breaks using the unrestricted Error-Correction Term (ECT). Our result nds that domestic revenue (i.e. tax and non-tax) shows a positive and statistically signicant effect while public debt (i.e. domestic and external) shows a negative and statistically signicant effect on health expenditure respectively. It implies that a 1 percent increase in revenue leads to a 0.78 percent increment in public health expenditure annually while a 1 percent increase in public debt leads to an -0.51 percent reduction in public health expenditure in the long-run. Our result suggests that conducive public nance policies and alternative revenue mobilization could be a potential strategy to increase the level of health spending in India. long-run The elasticity coecient that a percent 0.78 percent increment a a percent reduction


Introduction
The expansion of public nancing towards healthcare is one of the major strategies to reduce the burden The United Nations (UN) general assembly adopted SDGs to achieve the un nished agenda of Millennium Development Goals (MDGs) namely reduce child mortality, improve maternal health, and combat both communicable and non-communicable diseases (Boerma 2015). While India's progress on the MDGs achievement is below average than the other developing economies (Behera and Dash 2020; Duran et al. 2014; Marten et al. 2014) As per the WHO (2019) Global Health Expenditure (GHE) database, the share of public health expenditure to Gross Domestic Production (GDP) is around 1.37% in India which is comparatively lower than the countries such as Thailand, Bhutan, Sri Lanka, and Vietnam. The slower growth of public expenditure on healthcare has become a great concern for policymakers, therefore efforts have to be made to generate nance for healthcare through conducive macroeconomic policies such as sustained economic growth, revenue mobilization, and lower level of scal imbalance in resource-poor economies ( In the context of developing economies, few studies argue that higher revenue mobilization through conducive macro-scal policies and prioritization of health budget could be an alternative strategy to increase the allocation of public expenditure on healthcare (Reeves et al. 2015;Duran et al. 2014).
Existing studies have explored the income elasticity of public health expenditure using state-level data by controlling unobserved heterogeneity but they have not measured income elasticity of health expenditure by controlling scal components -revenue mobilization strategy and borrowing using aggregate data which subsumes both federal government and state government (Behera and Dash 2019, Meheus and Mclntyre 2017)). Additionally, there has no study in the Indian context has examined the elasticity of healthcare expenditure in both short-run and long-run by controlling structural breaks over the longer period from 1980-81 to 2015-16.
Very few studies namely Murthy and Okunade (2016); Chaabouni and Abednnadher (2014) have used a time series econometric model -Auto-Regressive Regression Lag (ARDL) model to examine the short-run and long-run income elasticity of health expenditure but in those studies, they have not taken into consideration scal policy components. The estimation procedure of the ARDL model involves three steps. First, it examines the stationarity properties of variables using Zivot and Andrew's (1991) unit-root tests and the advantage of this test is that it captures structural breaks in time series data. Second, examine the long-run associations among variables using the Auto-Regressive Distributed Lag (ARDL) bounds testing approach to cointegration. Third, it estimates both short-run and long-run elasticity of public health expenditure by controlling structural-break using the Unrestricted Error-Correction Model (ECM).
Our result implies that the accumulation of public debt is adverse while the effects of domestic revenue mobilization are positive towards public health expenditure in the long-run. Alternative revenue mobilization through conducive macroeconomic policies could be a suggestive alternative for nancing healthcare in India.
This study is organized as follows. Section 2 discusses data and methods. Section 3 contains results and discussion. Section 4 holds conclusions.

Data And Methods
This study has formulated the following simple regression model to examine the effects of income growth, domestic revenue, and public debt on public health expenditure in India for the period from 1980-81 to 2015-16.
We have taken Public health expenditure (PHE) as our dependent variables which include both medical & public health and family welfare expenditure in both current and capital accounts of the general government (i.e. central and state) in India. We have taken Economic growth (EG), Total Revenue (REV), Total Debt (DEBT) as our independent variables. EG is calculated as the annual percentage change in Gross Domestic Product (GDP). REV includes the revenue generated from both tax and non-tax sources.
Tax revenue includes both direct taxes and indirect taxes. Direct taxes include taxes on personal income, property, and capital transactions whereas indirect taxes include taxes on sales of goods & services. Nontax revenue includes revenue generated from fees & nes, interest receipts from commercial enterprises, royalties from natural resources. Total debt (DEBT) includes both domestic and external liabilities. In Eq.
(1) PHE is measured as a percentage of GDP; REV is measured as a percentage of GDP; DEBT is measured as a percentage of GDP; is a disturbance error term; is time; ln is the natural log. The data has been collected from the Handbook of Statistics on the Indian Economy published by RBI (2019). All the data are from combined government nance [1] which includes aggregate public health expenditure, aggregate revenue, and aggregate debt. All variables are in constant (real) prices at base 2004-05 and converted into a natural logarithm except EG for the empirical analysis. Table 1 represents the descriptive statistics and pairwise correlation results of variables. We have found that the mean percentage of revenue (i.e. as a ratio of GDP) and the mean percentage of public debt (i.e. as a ratio of GDP) is 21% and 68% respectively in India. Similarly, the mean annual growth of GDP and mean percentage of PHE (i.e. a ratio of GDP) is 6% and 1.27% respectively. The gap between minimum and maximum range values of variables -DEBT and REV is larger but there is a very little gap between minimum and maximum values in PHE. The pair-wise correlation result shows that there is a positive association between PHE and REV while a negative association between PHE and DEBT. The simple correlation analysis could not be produced the strength of the association between variables. Therefore, we have employed advanced econometric methods to examine the short-run and long-run relationships between PHE and other macro-scal factors -EG, REV, and DEBT for the last 36 years of the Indian economy. Eq. (2), ∆ denotes the rst difference operator of the respective variables and non-stochastic drift parameter. To nd out whether there is a long-run cointegrating relationship among variables -PHE, EG, REV, and DEBT, we test the null that: H 0 : β 1 = β 2 = β 3 = β 4 = 0 and the alternative hypothesis, H a : β 1 ≠ β 2 ≠ β 3 ≠ β 4 ≠ 0 by following a non-standard F-test statistics. If it rejects the null hypothesis of no cointegration in Eq. (2) statistically, we can say that there is a long-run association exists among the variables.
After getting a long-run association among variables using the ARDL bounds testing approach to cointegration, we can estimate the short-run and long-run elasticity of public health expenditure using the following unrestricted Error-Correction Model (ECM): where λ is the speed of adjustment parameter and ECT (Error Correction Term) is the residuals from the estimated model in Eq. (3).   Figure 2 also shows the graphical representation of structural breaks of all adopted variables. We have found that the structural break in REV is observed in the year 1993, which is closely associated with the tax system reform initiated by the tax reform committee in 1991. As a result, the direct tax-GDP ratio was improved from 2 percent in 1991-92 to 4.     Fig. 3). Notes: *, ** and *** denote the signi cance at 1%, 5% and 10% level.

Source
Author's estimation

Result of Short-Run and Long-Run Elasticity of Public Health Expenditure
The existence of long-run association among variables using the ARDL bounds testing approach to cointegration leads us to examine the short-run and long-run effects of domestic revenue and public debt on public health expenditure by controlling economic growth and structural break − 1998 dummy. Using structural break − 1998 dummy as one of the explanatory variables while the measuring elasticity of PHE would provide the signi cance of the particular reform during that period. Table 4 presents the long-run ARDL model which estimates the long-run elasticity of public health expenditure. It shows that the effects of EG and REV on PHE are positive, while the effects of DEBT on PHE are negative in the long-run. The estimated coe cient of EG and REV implies that a 1 percent increase in GDP growth annually leads to a 0.04 percent increment in PHE on average, while a 1 percent rise in revenue productivity leads to a 0.78 percent increment in PHE. Earlier studies found similar positive relationships between per capita public health expenditure and per capita tax revenue in selected Indian states, nd that a 1 percent rise in tax revenue leads to a 0.73 percent increment in per capita public health expenditure in the long-run (Behera and Dash, 2019b). Similarly, we have found that DEBT shows a negative and statistically signi cant relationship with PHE. The estimated coe cient implies that a 1 percent increase in total debt annually, leads to a 0.51 percent reduction in PHE in the long-run. Notes: *, ** and *** denote the signi cance at 1%, 5% and 10% level.

Source
Author's estimation Table 4 also presents the results of the structural dummy. We have added the structural break dummy in our ADDL estimated equation to examine the effects of scal reform in the year 1998 on the growth of PHE in India. We nd that there is a positive association between PHE and scal reform which took place during the period 1991 to 2000. The study has argued that from 1993 to 1998 was a period of initial economic reforms in the country and scal restructuring arrangements were undertaken at the state level.
So, the policies adopted in 1998 for scal consolidation show a positive effect on PHE but not a statistically signi cant impact on the rise of health expenditure in the long-run. Notes: *, ** and *** denote the signi cance at 1%, 5% and 10% level.

Source
Author's estimation  (2007) nd that higher debt ratios reduce public health expenditure in the long-run using cross-country samples.
The result of the error-correction term, (ECT t−1 ) presents in Table 5 and which is signi cant at the 1 percent level and exhibits the expected negative sign. It implies that 1.56 percentage of short-run disequilibrium in healthcare demand and supply originating from the past macroeconomic shocks adjusted in the current period, and the speed of adjustment towards long-run equilibrium is relatively faster. Table 4 presents the diagnostic test results of the selected ARDL long-run model. The diagnostic tests in our analysis suggest that error terms of short-run models are normally distributed; free from serial correlation, heteroscedasticity (ARCH), and multicollinearity (RESET).

Conclusions
Measuring income elasticity of healthcare expenditure in both short-run and long-run by controlling scal policies and structural breaks have been overlooked by the health nancing literature. Using a time-series econometric framework, this study examines the effects of domestic revenue and public debt on healthcare expenditure in India for the period from 1980-81 to 2015-16. The empirical results have found the following insights. First, the ARDL bounds testing approach to cointegration con rms that healthcare expenditure shows a long-run comovement with other macroeconomic factors -domestic revenue; public debt, and economic growth. Second, domestic revenue (tax and non-tax) shows an important factor to rise in healthcare expenditure while public debt (domestic and external) shows a detrimental impact on health expenditure in the long-run respectively. The elasticity coe cient shows that a 1 percent increase in domestic revenue leads to a 0.78 percent increment in healthcare expenditure annually while a 1 percent increase in public debt leads to a -0.51 percent reduction in health expenditure. Third, 1.56 percentage of short-run disequilibrium originating from the past shocks (i.e. structural breaks) adjusted in the current period, and the speed of adjustment towards long-run equilibrium in healthcare demand and