This article examines the relationships between technological innovation and environmental quality in India relying on the availability of annual data from 1980 to 2018. Both inward remittances and economic growth are also considered as key determinants in CO2 emissions and technological innovation functions. The result from utilizing autoregressive distributed lag (ARDL) bounds testing cointegration approach indicates the existence of long‐run relationship between the series. The combined cointegration test is also used as a result robust checking and validating the long‐run relationship. While considering the carbon dioxide emissions function, the findings document that technological innovation and economic growth degrade environmental quality in India via promoting atmospheric emissions in the long‐run, whereas U‐shaped relationship between inward remittances and carbon dioxide emissions is established. Further considering the technological innovation function, findings clearly indicate that both carbon dioxide emissions and economic growth promote the new technological innovation in the long‐run and also fails to confirm the inverted U‐shaped relationship between remittances inflows and technological innovation. On the policy front, we suggest that technological innovation should be made eco‐friendly and heavy utilization of inward remittances on pollution‐driving households’ appliances need to be discouraged in India for mitigating both climate change and global warming in the long‐run.

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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.

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PurposeThe eco-innovation is considered one of the possible ways to tackle climate change. However, the conflicting empirical evidence related to the role of eco-innovation on environmental quality becomes a motivation to explore the effect of eco-innovation on environmental degradation proxied by ecological footprint. Besides, it controls economic growth, remittance inflows, trade openness and total energy consumption in the environmental degradation function.Design/methodology/approachUses the Augmented Auto Regressive Distributed Lag (AARDL) approach to examine the cointegration relation among the series during the period ranging from 1975 to 2017 for India within the environmental Kuznets curve (EKC) framework.FindingsThe result suggests that eco-innovation can mitigate climate change by reducing the ecological footprint. Similarly, economic growth reduces the ecological footprint in the short- and long-run. However, the square of economic growth is positive and significant. Thus, it shows evidence against the conventional EKC hypothesis. The results also reveal that remittance inflows have an insignificant negative role on the ecological footprint, while total energy consumption and trade openness harm the environment by enhancing the ecological footprint.Practical implicationsThis study provides important implications for climate change mitigation. Thus, the government should promote eco-innovation to mitigate climate change by offering a favorable legal environment to the firms to adopt the same in their production and consumption activities. It also suggests that initiatives like green strategies should give serious attention while incurring research expenditure.Originality/valueNo prior studies assess the impact of eco-innovation on the ecological footprint for the period of 1975–2017 in India.

This paper explores the relationship between renewable energy consumption, urbanization, human capital, trade, natural resources, and material footprint for BRICS countries from 1990 to 2016. We apply the cross-sectional dependency test to check the correlation among the crosssection. Then, we use the second-generation panel test like CADF and CIPS to check the stationary in the series. After that, we go for the panel cointegration test, i.e., Pedroni and Westerlund panel cointegration, to know the long-run relationship of the variable. The test results reject the null hypothesis of no cointegration among the variables and accept cointegration. The long-run results indicate that economic growth, natural resources, renewable energy, and urbanization have reduced the environmental quality for BRICS countries in case of material footprint employed to measure environmental degradation. However, foreign trade, human capital improves environmental quality. Based on the empirical results, the study recommended some important policy suggestions to achieve sustainable development in BRICS countries.

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