Samuel Asante Gyamerah, Henry Ofoe Agbi-Kaiser, Clement Asare, Nelson Dzupire
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引用次数: 0
Abstract
Investing in green bonds has been recognized as a strategy that not only promotes environmental performance but also offers attractive investment returns. However, macroeconomic factors, such as geopolitical risk (GPR), climate policy uncertainty (CPU), and global economic policy uncertainty (GEPU), play a substantial role in shaping green bond returns. Using the returns of US green bonds as a proxy for the returns of green bonds, we argue in this paper that these heterogenous uncertainty measures might have asymmetric impacts on the returns of green bonds (GB). By employing monthly data from January 2016 to August 2022, we apply the nonlinear autoregressive distributed lags model (NARDL) to examine the asymmetric impact of these heterogenous uncertainty measures on the returns of GB. The NARDL findings reveal evidence of short-run asymmetric impacts of GPR, GEPU, and CPU on the returns of green bonds. In the long run, there is an asymmetric impact of GPR and CPU on the returns of GB. However, there is a symmetric impact of CPU on the returns of GB in the long run. Specifically, in the short run, we found that a positive CPU shock causes a decline in the returns of green bonds. A similar magnitude of negative CPU shock causes an increase in the returns of green bonds. Moreover, a positive shock to GPR increases the return of green bonds, while a comparable negative shock to GPR reduces the return of GB. Furthermore, only negative shocks to GEPU have an impact on GB returns in the short run. Specifically, a negative GEPU shock reduces GB returns. In the long term, the returns of GB are positively impacted by negative shocks in GPR and both positive and negative shocks in GEPU, whereas positive shocks in GPR affect the returns of GB negatively.
期刊介绍:
The main objective of Discrete Dynamics in Nature and Society is to foster links between basic and applied research relating to discrete dynamics of complex systems encountered in the natural and social sciences. The journal intends to stimulate publications directed to the analyses of computer generated solutions and chaotic in particular, correctness of numerical procedures, chaos synchronization and control, discrete optimization methods among other related topics. The journal provides a channel of communication between scientists and practitioners working in the field of complex systems analysis and will stimulate the development and use of discrete dynamical approach.