This study aims to empirically investigate the short-term and long-term effects of healthcare expenditure, institutional quality and domestic and foreign investments on the economic growth of South Asian countries during the period 1996–2018. The pooled ordinary least squares (OLS) and random effects models, Johansen–Fisher cointegration test and Granger causality test have been employed to assess the short-term and long-term relationships and the direction of causality among the variables. The cointegration tests indicate the existence of a long-term equilibrium among the variables. The results reveal that there runs a bidirectional causality from health expenditure to economic growth in the concerned countries in the short run. Further, institutional quality is seen to have a unidirectional effect on health expenditure. Therefore, the authorities of the South Asian nations are required to strengthen the accessibility to and affordability and accountability of the healthcare services being provided to their population.

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This study aims to evaluate the impact of economic structure on the Environmental Kuznets Curve (EKC) in India. The present study deviates from the bulk of study in the literature with the incorporation of both aggregated and disaggregated measures of economic development on the environmental degradation function. For the empirical analysis, the study employed the Auto-Regressive Distributed Lag (ARDL) bounds testing approach of cointegration to analyse the long-run and short-run relationship during 1971–2014. Further, the direction of the causality is investigated through the Wald test approach. The results revealed that the conventional EKC hypothesis does not hold in India in both aggregated and disaggregated models since economic growth and its component have a U-shaped impact on the environmental quality in India. However, the effect of population on environmental quality is positive but not significant in the aggregated model. Whereas, in the disaggregated model, it is significantly affecting environmental quality. Hence, it is possible to infer that the population of the country increases, the demand for energy consumption increase tremendously, particularly consumption of fossil fuel like coal, oil, and natural gas, and is also evident from the energy structure coefficient from both models. This increase is due to the scarcity of renewable energy for meeting the needs of people. On the contrary, urbanization reduces environmental degradation, which may be due to improved living conditions in terms of efficient infrastructure and energy efficiency in the urban area leading to a negative relation between urbanization and environmental degradation.

PurposeThis paper empirically examines the relationship between foreign direct investment, financial development and other macroeconomic variables like trade openness, domestic investment and labour force and that of GDP per capita in select South Asian countries, i.e. India, Sri Lanka and Pakistan for the period 1990–2018.Design/methodology/approachThe study uses various econometrics tools such as Pedroni, Kao and Johansen–Fisher panel cointegration test, Panel FMOLS and DOLS and Granger causality in order to analyse the long-run and short-run dynamics among the variables under consideration.FindingsThe results of the panel data estimation techniques employed imply that there is a short-run causality running from GDP per capita to FDI and financial development, and results from FMOLS and DOLS indicate that FDI and financial development have positive impacts on GDP per capita in the countries under consideration.Originality/valueIn this paper, we use a dynamic macroeconomic modelling framework to examine the effect of FDI and financial development on per capita income in three major south Asian economies, which are categorized as three Non-Least Developed Contracting States under the South Asian Free Trade Area (SAFTA), 2006, established with an aim to facilitate free trade among them. Considering the diversity of the level of growth experienced by these economies, the study uses appropriate panel regression techniques. Therefore, in addition to proper formulation of policies directed towards scaling up of export and import levels, the respective authorities should also take care that the political stability and institutional quality are maintained.

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The rapid increases in ecological footprint and air pollution have followed the fast expansion of the global economy. Urbanization has aggravated environmental strain because of population surge, but the development in the degree of technological innovation would counter balance this negative effect. Hence, in this paper we examine the dynamic impact of urbanization, economic structure, technological innovation and population density on ecological footprint and air quality (PM2.5) in Newly Industrialized Countries (NICs) from 1990 to 2017. The study uses other variables like population density, energy consumption, and life expectancy to find out the long-run relationship among variables. We apply Westerlund co-integration, Mean Group (MG) and Pooled Mean Group (PMG) technique to ascertain the long-run and short-run associations among the variables. For robustness check, we use Augmented Mean Group (AMG) and Common Correlated Mean Group (CCEMG) approach. This study would be the first study in case 10 NICs considered the determinants of ecological footprint and PM2.5. The results reveal that economic growth increases ecological footprint in NICs in long run. Similarly, coefficient of industrialization is positive and significantly related to ecological footprint. However, the service sector shows a negative relation with ecological footprint in NICs. It means service sector helps to improve the environmental quality in long run. Population density, urbanization, energy consumption and life expectancy indicate a positive effect on ecological footprint. Further, in case of PM2.5, the results suggest that economic growth and industrial sectors have high magnitude effects on the PM2.5 than the other variables. The service sector reduces PM2.5, whereas the coefficient value is not significant, but agriculture sector positively influences PM2.5 in NICs. Similarly, population density and urbanization contribution to PM2.5 are positive and significant. Hence, these NICs countries should focus more on the investment in the renewable energy sector and make stringent environmental policy for protecting the nations from environmental issues.

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In this paper, we examined the relationship between renewable and non‐renewable energy consumption on CO2 emissions in India by taking disaggregated data from 1965 to 2018. In order to determine the effect of long‐run elasticity of independent variables on dependent variables, we have used ARDL bound testing approach. The directions of causality of the variables are investigated by Toda–Yamamoto Granger causality test. The long‐run results reveal that hydro energy consumption has a positive impact on CO2 emissions but not significant. However, nuclear energy consumption indicates that there is a negative effect on CO2 emissions. It reveals that all non‐renewable energy consumption sources have positive and significant effect on CO2 emissions.