Women's political leadership and efficiency in reducing COVID-19 death rate: An application of technical inefficiency effects model across Indian states.

Evidence from earlier studies on COVID-19 suggests that the countries led by female leaders were more successful in handling the COVID-19. India being a patrilocal society evident that women's political autonomy in the Gram Panchayat does miracles concerning development. With this backdrop, the present paper aims to explore the role of women's political participation and leadership on the efficiency in reducing the COVID-19 death rate for Indian states. This predominantly empirical paper is entirely based on secondary data compiled from different sources. The empirical analysis of the paper is facilitated by the utilization of the Technical Inefficiency Effects model within the framework of Stochastic Production Frontier. The empirical results accredit us to conclude that the efficiency of the Indian states in reducing the COVID-19 death rate is highly influenced by female political participation and leadership, digitalization, urbanization, and literacy rate. The study ends with suitable policy prescriptions.

Interstate disparities in the performances in combatting COVID-19 in India: efficiency estimates across states.

BACKGROUND: Currently, the novel coronavirus or COVID-19 pandemic poses the greatest global health threat worldwide, and India is no exception. As an overpopulated developing country, it is very difficult to maintain social distancing to restrict the spread of the disease in India. Under these circumstances, it is necessary to examine India's interstate performances to combat COVID-19. This study aims to explore twin objectives: to investigate the comparative efficiency of Indian states to combat COVID-19 and to unfold the factors responsible for interstate disparities in the efficiency in combatting COVID-19. METHODS: The stochastic production frontier model was utilized for data analysis. The empirical analysis was facilitated by the inefficiency effects model, revealing the factors that influence interstate variability in disease management efficiency. Three types of variables, namely, output, inputs, and exogenous, were used to measure health system efficiency. The relevant variables were compiled from secondary sources. The recovery rate from COVID-19 was the output variable and health infrastructures were considered as the input variable. On the contrary, the non-health determinants considered to have a strong influence on the efficiency of states' disease management, but could not be considered as input variables, were recognised as exogenous variables. These exogenous variables were specifically used for the inefficiency analysis. RESULTS: The empirical results demonstrated the existence of disparities across Indian states in the level of efficiency in combatting COVID-19. A non-trivial outcome of this study was that Tamil Nadu was the best performer and Manipur was the worst performer of the investigated states. Variables such as elderly people, sex ratio, literacy rate, population density, influenced the efficiency of states, and thus, affected the recovery rate. CONCLUSION: This study argues for the efficient utilisation of the existing health infrastructures in India. Simultaneously, the study suggests improving the health infrastructure to achieve a long-run benefit.