Each country designs its own scheme to achieve green financing and, in general, credit is considered to be a fundamental source of greening financial systems. The novelty of this study resides in that we examined green financing initiatives in USA, Canada and Brazil by focusing on major components of the financial systems before, during and after the 2008 world financial crisis. By means of panel data analysis conducted on observations ranging across the period 1970–2018, we investigated variables such as domestic credit from banks, domestic credit from the financial sector, GDP, N2O emissions, CO2 emissions and the value added from agriculture, forest and fishing activities. According to our findings, domestic credit from banks was insufficient to achieve green financing. Namely, in order to increase economic growth while reducing global warming and climate change, the financial sector should assume a bigger role in funding green investments. Moreover, our results showed that domestic credit from the financial sector contributed to green financing, while CO2 emissions remained a challenge in capping global warming at the 1.5 °C level. Our empirical study supports the idea that economic growth together with policies targeting climate change and global warming can contribute to green financing. Over and above that, governments should strive to design sustainable fiscal and monetary policies that promote green financing.

The article investigates the contribution of adjusted net savings to sustainable economic growth for 10 Central and Eastern European and Baltic nations, which are former Soviet bloc nations known as transition economies, using panel data analysis for the period 2005–2016. Our results indicated that adjusted net savings impacted on the GDP across the 10 countries analyzed. Nevertheless, national authorities are called on to implement policy changes in these countries to achieve sustainable economic growth and make an efficient transition from a brown economy towards a green economy.

The study investigated the impact of factors such as non-performing loans, CO2 emissions, bank credit, and inflation on the variable sustainable economic growth for India, Brazil, and Romania during the period 2005–2017, through a panel data analysis. Specifically, we investigated the timeline before, during, and after economic turmoil, with a special focus on the global financial crisis. Our empirical results are valuable for both developing and developed nations. As a first result, we showed that CO2 emissions increased the level of economic growth, but in this context, authorities should design suitable policies to limit its impact on the overall society. In addition, a single supervision mechanism increased the level of sustainable economic growth. Last but not the least, the period during and after the global financial crisis, sustainable economic growth decreased under the influence of bank credit, inflation, and non-performing loans. Within this framework, public authorities are called to design efficient economic, fiscal, and monetary policies.

The study focuses on the effects of imports, exports, financial direct investment inflow and financial direct investment outflow on sustainable economic growth expressed by various macroeconomic indicators (gross domestic product, gross domestic savings, gross domestic capital) using the least squares panel method. Sample data were selected for ten Central and Eastern European (CEE) countries and the time frame considered was 2005–2016. Generally, transitional economies have to incorporate strong savings and a steady capital formation in order to achieve higher economic growth via foreign direct investment. Results showed that the analyzed factors played a major role in the sustainable economic growth of CEE countries. Another important and valuable insight of this study is that the financial sector steers the process of achieving sustainable economic growth across CEE countries.

This article addresses the challenging problem of fixed-time output-constrained synchronization for master–slave chaotic financial systems with unknown parameters and perturbations. A fixed-time neural adaptive control approach is originally proposed with the aid of the barrier Lyapunov function (BLF) and neural network (NN) identification. The BLF is introduced to preserve the synchronization errors always within the predefined output constraints. The NN is adopted to identify the compound unknown item in the synchronization error system. Unlike the conventional NN identification, the concept of indirect NN identification is employed, and only a single adaptive learning parameter is required to be adjusted online. According to the stability argument, the proposed controller can ensure that all error variables in the closed-loop system regulate to the minor residual sets around zero in fixed time. Finally, simulations and comparisons are conducted to verify the efficiency and benefits of the proposed control strategy. It can be concluded from the simulation results that the proposed fixed-time neural adaptive controller is capable of achieving better synchronization performance than the compared linear feedback controller.