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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. [ABSTRACT FROM AUTHOR]

The aim of this study is to examine the causal relationship between corruption, political stability and Foreign Direct Investment (FDI) in India. The study is based on annual time series data spanning from 1996 to 2017. In order to find out the exact relationship between the variables, the Johansen cointegration test has been applied. For checking the long-run causality, Vector Error Correction Model (VECM), and for short-run relationship, the Wald test have been utilized. The study also applied the Granger causality test for testing the causal link among the variables. This study also used the Impulse Response Function (IRF) to understand the impact of one standard deviation change in one variable on the other variables. It is found that there is cointegration among the variables. The Granger causality test shows that there is a unidirectional relationship between control of corruption and FDI and there is a bidirectional relationship between political stability and FDI. It can also be seen that the Cholesky response function supports the results of the Granger causality test. The Wald test shows that there is a short-run relationship between the variables. These results can be used in policy formations and helpful for decision makers in devising pro-FDI inflow strategies. [ABSTRACT FROM AUTHOR]