Purpose: The main purpose of the present research is to analyze the relationship between technological development, financial development and economic growth in India in a non-linear and asymmetric framework. Design/methodology/approach: The study employs the nonlinear autoregressive distributed lags model (NARDL) and Hetemi J asymmetric causality tests to explore nonlinearities in the dynamic interaction among the variables. The stationarity properties of data are checked by using Ng–Perron and ADF structural break unit root tests. The unit root test confirms that the variables are non-stationarity in level and are differenced stationary. Findings: The study finds that there is a cointegrating relationship between technological development, financial development and economic growth in the long run. The findings suggest that a positive shock in technological development increases economic growth (coefficient value 1.497 at 1% significance level) and a negative shock will harm economic performance (coefficient value −0.519 at 1% significance level). A long-term positives shock in financial development boosts the economy (coefficient value 1.08 at 5% significance level) and negative shock hampers the economic performance (coefficient value −1.09 at 5% significance level). The asymmetric causality test result confirms bi-directional causality between technological development and economic growth and unidirectional causality from negative economic growth to negative technological development and bi-directional causality between economic growth and financial development, unidirectional negative financial development to economic growth. Research limitations/implications: The results of this research can significantly facilitate stakeholders and policymakers in devising short-term as well as long-term policies for financial development and technological innovation to achieve sustainable long-run economic growth in India. Originality/value: This paper is the first of its kind to empirically examine the cointegrating and causal relationship between technology, financial development and economic growth in India using non-linear asymmetric cointegration and causality tests.

Purpose: The present study aims to construct and compare Composite Environmental Sustainability Index (CESI) for 20 emerging countries for the period 1990–2020.Design/methodology/approach: The study constructs CESI using the principal component analysis (PCA). Furthermore, for the preparation of index weights, varimax rotation is used to get component loadings.Findings: The study finds that the overall CESI values lies between 2 and 4.8 for the 20 emerging countries considered in the study. This study depicts a diverse picture of environmental sustainability among emerging countries. The study also shows the trend of CESI values from 1990 to 2020. The bottom three countries whose CESI is very low compared to others are Iran, South Africa and Saudi Arabia. However, Brazil, Columbia and Chile are top three highest scorers in 2020.Originality/value: The study contributes to the literature by constructing a composite index comprising of three sub-indices to measure the environmental sustainability of an economy. These sub-indices include seven indicators that are more inclusive and comprehensive. To the authors' knowledge, this is a pioneering attempt in the construction of the index for emerging countries.

This article examines the empirical relationship between electricity consumption, economic growth, energy prices and technology development for India by taking annual time series data from 1981 to 2017. By using the ARDL bounds testing approach to co-integration, the study found long-run equilibrium relationship does exist among the variables. The article reports the existence of positive and significant impact of economic growth on electricity consumption, whereas technological development negatively affects electricity consumption in both the long run and short run. The Granger causality results reveal the presence of unidirectional causality from economic growth and technological development to electricity consumption in India. Therefore, the present study suggests policy makers in India to increase investment in electricity infrastructure to support high economic growth in the country. Further, the policy makers and the government should encourage more technological innovation to minimise usage of fossil fuels and support the use of green energy. This action could help the economy achieve a sustainable economic growth with better environmental quality. JEL Codes: C22, O4, O13, Q43, Q48

Purpose: The main purpose of this paper is to examine the role of population aging in determining the health care expenditure (HCE) in India over the period 1981 to 2018.Design/methodology/approach: While establishing the linkage between population aging and HCE, the study has used economic growth, urbanization and CO2 emissions as control variables and used the autoregressive distributed lag (ARDL) approach to cointegration and VECM based Granger causality approach to estimate both the long-run and short-run relationships among the variables.Findings: The results of the ARDL bounds test showed that there is a stable and long-run relationship among the variables. The long-run and short-run coefficients reveal that population aging and income per capita exert a statistically significant and positive effect on per capita HCE in India. The VECM causality evidence shows that there is a presence of short-run causality from economic growth and population aging to per capita HCE, urbanization to environmental degradation and further from aging to urbanization. However, the long-run causality evidence confirms unidirectional causality from population aging to the per capita HCE.Research limitations/implications: The research findings could be improved by considering the changes in mortality rate over time because of other environmental factors such as air pollution, among others as control variables. Various other variables affecting the health of an aged person could be considered for better research outcome which is not included in the present study because of the paucity of data. However, the present research findings would certainly serve effective policy instrument aiming at maximizing health gains that are highly associated with the elderly population and economic growth towards achieving sustainable development in India.Originality/value: The uniqueness of the present study lies in its estimation where the relationship between population aging and HCE is looked at while considering the impact of other environmental factors separately. The causal relationship is shown among the variables using updated econometrics time-series techniques. The study tried to resolve the ambiguity associated with the relationship between aging and HCE at a macro level.