This article empirically examines the impact of globalization on the health status of countries by using panel data. Unlike previous studies, it has attempted to use three different dimensions of globalization and estimate their impact on health status measured by infant mortality rate and life expectancy. It also introduces an initial level of development status as an explanatory variable and found that it has an important role. The fixed effects panel data analysis shows that globalization has a positive impact on the health indicators. Out of the three dimensions of globalization, namely, economic, social and political, the first one has the highest influence on health for the less developed countries. However, as one moves up the ladder of development, social dimension becomes more important. Moreover, the pace of improvement in health indicators is faster in developed countries, indicating a divergence between the developed and the underdeveloped world.

The purpose of this paper is to study the volatility comparison and volatility spillover effects in India and major global indices. The study uses a vector autoregression model with various GARCH models in order to measure conditional volatility (GARCH), asymmetric effect in the conditional volatility (T-GARCH), volatility persistence in conditional volatility (E-GARCH), the impact of conditional volatility on conditional returns (M-GARCH) and volatility spillover (GARCH (1, 1) with exogenous variable) for the period of 2005 to 2020. The estimates show that the Indian stock market had a strong impact on selected global indices. Volatility spillover was found to be in existence from the Indian stock market to global indices and vice-versa. The T-GARCH estimates show the existence of a significant asymmetric effect in conditional volatility. The results of the E-GARCH estimates show the existence of volatility persistence in conditional volatility and the M-GARCH estimates indicated that there was no significant impact of conditional volatility on conditional returns of the sample indices. These findings have substantial insinuations and outcomes for portfolio managers, analysts, and investors for investment assessments and decisions regarding asset allocations. Higher volatility will lead to a higher level of fretfulness among market participants and investors, which will push them to be more risk-averse. The results of the study are also relevant for policymakers with respect to the Indian as well as global markets. This study will try to add a new dimension to the existing literature by studying how the Indian index has an impact on global indices like Brazil, USA, Russia, China, Japan, Hong Kong, and South Korea.

Background: COVID-19 pandemic has affected all countries across the globe in varying intensity resulting in varied numbers for total cases and deaths. Objectives: The paper aims to understand if different socioeconomic factors have a role to play in determining the intensity of COVID-19 impact. Methods: The study uses a country-wise number of corona cases and deaths and analyse them in a cross-country multivariate regression framework. It uses gross domestic product per capita, average temperature, population density, and median age as independent variables. The study uses testing data as a control variable. Results: In absence of the testing variable, higher-income countries have experienced a higher number of COVID cases. The population density, median age, climate do not have significant impact. The countries with higher population density have lower deaths. Each region shows different patterns of correlation between socioeconomic factors and COVID intensity. Conclusion: The majority of the cross-country variation can be attributed to the number of tests done by a country. The countries with high population density would have applied strict lockdowns and proactive testing to curb the deaths. The study essentially refutes claims around corona being a high-income group disease, cold-climate disease, or a disease impacting old-age patients more.

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There has been an ongoing debate about the impact of trade openness on the health. This study aims to inform this debate by comparing health impacts of trade in services vis-à-vis trade in goods. Prima facie, the former, due to association with the higher human capital requirement and less pollution, may have a higher positive health impact. The main finding is that the trade in services has a higher positive impact on the health status compared to that of the trade in goods. However, for the least developed countries trade in goods is the dominant factor impacting the health status.