Health Disparity in India: An Enquiry into Convergence and Divergence

Abstract

Population health is vital to a nation’s overall well-being and development. Reducing health inequalities and increasing interstate convergence in health indicators are necessary for sustainable human development. Evaluation of the convergence patterns can aid the government in monitoring the health progress across the Indian states. Since 1990s, India has witnessed remarkable economic growth, resulting in significant improvements in population health. However, alongside these advancements in the health system, the country also faces challenges in the form of widening health disparities among its states. In this context, the study has examined four primary objectives: first, to investigate the convergence hypothesis in the health status of individuals among Indian states from 1990 to 2020; second, to examine whether health inequalities have widened or converged during this period and explore the impact of economic development on health outcomes; third, to assess the potential regional convergence in healthcare spending among Indian states and also examine the relationship between healthcare spending and fiscal space; lastly, to explore the potential convergence of human development indices across the Indian states. The data used in the thesis are extracted from various rounds of the Global Data Lab (GDL) and the Reserve Bank of India (RBI). The Gini and Theil index are used to measure the absolute and relative health inequality across Indian states. The study tests the convergence hypothesis using the standard parametric (Catching plots, Absolute and conditional beta-convergence, sigma-convergence, and log t-test), and non-parametric model (kernel density estimators) to detect the presence of convergence, divergence, and club convergence among Indian states. Furthermore, the study employs the System-Generalized Method of Moments (S-GMM) model, cross-sectional dependence test, second Generation Cointegration test, fully modified ordinary least square (FMOLS), and Dumitrescu-Hurlin Panel Granger Causality test to examine the above-mentioned objectives. The study findings indicate both convergence and divergence in health outcomes, healthcare expenditure, and human development index. The log t-test results support club convergence, heterogeneity, and divergence in the overall health indicator analysis. The result also highlights inter-state inequality across the health indicators in India. Improvements in economic development, including increased healthcare expenditure, education, and per capita income, have a substantial positive impact on health outcomes. Conversely, income inequality has a detrimental effect on health outcomes, reducing overall well-being. Health improvement and income equality policies are crucial to reduce health disparities and promote economic growth. The findings further emphasize the importance of fiscal space and economic growth in healthcare expenditure. A bidirectional causality between healthcare spending, fiscal space, and economic growth. Tax revenue, non-tax revenue, fiscal transfers, and per capita income positively impact per capita health expenditure, while borrowing negatively affects it in the long run. Enhancing fiscal capacity is essential to ensure balanced healthcare expenditure among the states. This thesis provides a methodological toolkit for empirical analyses of health transition and convergence, specifically emphasizing inequalities in population and health indicators. It sheds new light on the analysis of health inequalities by linking it to health progress and convergence while promoting economic growth.