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This study aims to investigate the impact of foreign direct investment (FDI) on environmental quality in China over the period 1984-2014. Specifically, the research focuses on the possibility of the effects of FDI on the quality of the environment in China. We employ the bound test approach and found a significant cointegration among environmental quality and other variables, the autoregressive distributed lag model (ARDL) model used after finding a cointegration connection between environmental quality and other independent variables to explore the short and long-run relationships among the variables. The coefficient of the long-run (ARDL) model indicates that the impact of FDI on the quality of the environment is positive, and it implies that better FDI inflows in China, resulting in higher energy consumption and thus leading in the direction of higher release of CO 2 emission. Moreover, in the short run the coefficient obtained by the error correction mechanism shows that FDI does not improve the environmental quality, and it leads to more environmental degradation in China. The causality approach specifies that FDI and environmental quality have a unidirectional relationship. Therefore, the finding suggests that China should foray balance between FDI inflows and environmental quality, and encourage more FDI inflows, particularly in technology-intensive and environment-friendly industries, to improve environmental quality.

The efficient planning, execution, and management of institutional frameworks for climate change adaptation are essential to sustainable development. India, in particular, is known to be disproportionately vulnerable to the consequences of climate change. This study examines the effects of environmental taxes, corruption, urbanization, economic growth, ecological risks, and renewable energy sources on CO2 emissions in India from 1978 to 2018. Therefore, the ARDL model is used to draw inferences, and Pairwise Granger causality is also applied to demonstrate a cause-and-effect relationship. The empirical results show that corruption, environmental dangers, GDP, and urbanization positively influence India’s carbon emissions. However, the results of short-run elasticities show that carbon emissions reduce ecological sustainability. Environmental hazards and costs, like other countries, impact India’s carbon emissions. Therefore, decision-makers in India should set up strict environmental regulations and anti-corruption measures to combat unfair practice that distorts competition laws and policies. In addition, the government concentrates more on energy efficiency policies that diminish carbon emissions without hampering economic growth in the country.

The present study tries to understand the association among Foreign Direct Investment (FDI) and Economic growth in India. This paper applies the causality test of Granger (1969) based on the VECM and non-linear causality test of Dike and Panchenko over the period 1993-2016. This study gives a proof about the continuation of a long-run equilibrium association between FDI and Gross Domestic Product (GDP) or Economic Growth for the period being investigated. Unidirectional causality runs from FDI to GDP in the long run. The apparent non-linear causality running from FDI to GDP means that FDI is a policy instrument in stimulating Indian economic growth and provides support for the bi-directional non-linear causal connection between FDI and economic growth with 1, 2 and 4 lags. There has been no definitive investigation as of recently to