Figure 5 - uploaded by Mesut Doğan
Content may be subject to copyright.
Net Total Directional Connectivity Notes: The outcomes stem from an analysis employing a TVP-VAR model with a lag length determined by the Bayesian Information Criterion (BIC) and a generalized prediction error variance decomposition extending up to 20 steps ahead. The shaded region depicted in black signifies the overall balanced interconnectedness, while the presence of green and red lines denotes positive and negative interconnectedness, respectively.
Source publication
This study examines the relationship between climate policy uncertainty (CPU), China's environmental impact, social responsibility and corporate governance practices (ESG) leader scores and logistics stocks. China Ocean Shipping Company (COSCO), one of the pioneers in global markets, was chosen to represent the logistics industry. The variables wer...
Contexts in source publication
Context 1
... Total Directional Connectivity provides a dynamic view of the net-receiving or net-transmitting role of a variable. The results are given in Figure 5. A positive value in Figure 5 indicates that the variable is a net transmitter in the network, and a negative value indicates that it is a net receiver. ...
Context 2
... results are given in Figure 5. A positive value in Figure 5 indicates that the variable is a net transmitter in the network, and a negative value indicates that it is a net receiver. It should be noted that the role of a variable in the network may change over time. ...
Citations
... The existing literature can be categorized into three primary areas. The first area examines how economic policy uncertainty (EPU) has a significant impact on China's carbon trading market (Wang et al. 2022;Tao Liu et al. 2023;Liu et al. 2023) The second area focuses on the effects of international climate policy uncertainty, particularly from the United States, on Chinese markets and various sectors (Xin et al., 2022;An et al., 2022;Niu et al., 2023;Zhu et al., 2023;Wang and Li, 2023;Altın et al., 2023;Chen, Zhang, and Weng, 2023;Alqaralleh, 2023;Lv and Li, 2023;Tian, Chen, and Dai, 2024;Iqbal et al., 2024;Zhao and Luo, 2024). Xin et al. (2022) find that high climate policy uncertainty (CPU) reduces current stock market returns and increases volatility in China, but decreases future volatility. ...
... Wang and Li (2023) studies show that CU and CEU can significantly affect the volatility of the CSI 300 ESG index. Altın et al. (2023) show that the volatility of China Ocean Shipping Company (COSCO) is transmitted to the China ESG index and CPU. Chen, Zhang, and Weng (2023) found that CPU has a significant impact on stock market price volatility. ...
This study aims to examine the relationship between CUM, CPU, CU, and UCT with the FTSE China Technology Index (FTXIN410) and SZSE Environmental Protection Index (SZEPI) using ARDL and NARDL methods. To test the robustness of the model, three additional parametric methods are employed: FMOLS, DOLS, and CCR. The technology and environmental protection sectors in China are crucial for the country's sustainable economic future. Understanding the impact of global and local uncertainties on these sectors is critical for predicting sectoral trends and future market dynamics. Climate uncertainties and global uncertainties can impact investors' returns and market behaviors. In critical sectors such as technology and environmental protection, uncertainties need to be closely monitored for their implications on investment decisions and market stability. The results of the study indicate a long-term relationship between China’s climate uncertainties and global uncertainties with technology and environmental protection indices.
