Analyzing the nexus between financial risk and economic risk in India: Evidence through the lens of wavelet coherence and non-parametric approaches.

The gravest challenge for economic sustainability is the undetermined growth in the financial and economic risks of the nation, which need to be overcome with adequate measures without compromising economic growth. The uncertainty of economic factors produces fluctuations in the financial sector and makes them more vulnerable. However, the existing literature has not significantly focused on the economic and financial risk challenge for sustainable economic growth.

Appraisal of CO emission in Tunisia's industrial sector: a dynamic vector autoregression method.

The world is confronted with a slew of environmental issues, one of which is attenuating the detrimental impacts of carbon dioxide (CO) emission-induced climate change. The ever-increasing use of energy is eroding natural resources to the point that our economic future may be jeopardized. The Tunisian economic growth indicates the excellent performance in the industrial sector as the minimum required input for these developments which necessitate additional energy consumption, resulting in increased CO emissions and environmental degradation.

Environmental pollution and agricultural productivity in Pakistan: new insights from ARDL and wavelet coherence approaches.

The most serious challenge to the global facade is figuring out how to mitigate pollution levels without compromising agricultural productivity. The spillover effect of environmental change is predicted to be very high, although it will differ by region and crop. Considering this view, this study tries to address this issue by adopting comprehensive methodologies to assess the influence of carbon dioxide (CO) emissions, agricultural labor, land, feeds, and fertilizers on agricultural productivity in Pakistan from 1961 to 2018.

The environmental sustainability effects of financial development and urbanization in Latin American countries.

The present study assesses the impact of urbanization, economic growth, energy consumption, and financial development on CO emissions in Latin American countries using a dataset spanning between 1980 and 2017. The current paper employs utilized panel econometric techniques such as CIDF, panel unit test, the Westerlund panel cointegration, fully modified ordinary least squares (FMOLS), dynamic ordinary least squares (DOLS), and Dumitrescu Hurlin panel causality test to assess these associations. The outcomes from the FMOLS and DOLS estimation reveal that (i) economic growth impacts CO emissions positively, (ii) energy consumption exerts a positive impact on CO emissions, and (iii) urbanization impacts CO emissions positively.