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Asymmetric spillovers and resilience in physical and financial assets amid climate policy uncertainties: Evidence from China.

Authors :
Wu, Guo
Hu, Guoheng
Source :
Technological Forecasting & Social Change; Nov2024, Vol. 208, pN.PAG-N.PAG, 1p
Publication Year :
2024

Abstract

Climate policy is essential for fostering sustainable development and addressing climate-related issues, while climate policy uncertainty (CPU) introduces complex challenges in providing a consistent framework for action. In this study, we delve into the spillover dynamics among China's domestic CPU, foreign CPU, physical assets, and financial assets across various market scenarios, through a quantile-based connectedness method and evidence from China. The findings reveal: (1) The spillover dynamics are asymmetric across quantiles and time, and the COVID-19 pandemic influences the total connectedness. (2) The complexity of spillover patterns in physical assets is likely contingent upon market conditions, policy sources, asset types, and industrial-chain positions, while the spillovers of financial assets are quantile-dependent and time-varying, with the agricultural equity market showing relative resilience to the pandemic. (3) There is no significant Granger causality in quantiles between domestic CPU and foreign CPU under the entire sample period, and the rankings regarding the spillovers from CPUs to assets vary across market conditions. Implications for policymakers, investors, and firms are provided. • The spillovers of climate policy uncertainties (CPUs) and assets are asymmetric. • The pandemic influences the quantile-dependent total connectedness. • The spillover dynamics rely on market conditions and asset types. • Granger causality between China's domestic and foreign CPU is absent. • The agricultural sector shows relative resilience to the pandemic shock. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00401625
Volume :
208
Database :
Supplemental Index
Journal :
Technological Forecasting & Social Change
Publication Type :
Academic Journal
Accession number :
179633886
Full Text :
https://doi.org/10.1016/j.techfore.2024.123701