Unraveling uncertainty spillovers: Climate policy's role in global economic, energy and geopolitical landscapes

This paper discusses the uncertainty spillover among climate policy, economic policy, energy market and geopolitics, using time-varying parameter vector autoregression (TVP-VAR) connectedness approach. The major results show that the total connectedness index (TCI) is dominated by long-term connectedness in static analysis. The main spillover transmitters are climate policy uncertainty in China (CPUC) and economic policy uncertainty (EPU) while the receivers are the USA (CPUS) and energy-related uncertainty (ERU) when considering time and frequency. Next, in the dynamic analysis, the TCI exhibits a downward trend, and the net total directional connectedness indicates that CPUC is still a pure transmitter, while CPUS plays a completely opposite role. Finally, dynamic net pairwise analysis shows that CPUC exerts spillovers on EPU, ERU and geopolitical risk. Conversely, CPUS is more likely to accept the shock of other uncertainties. The major contribution is that the different uncertainties are incorporated into a unified research framework, and explain the detailed influencing channels. More importantly, this paper recognizes the different roles of CPUC and CPUS in the entire uncertainty connectedness with considering time and frequency, and argue that China is reshaping global economy, energy market and geopolitical situation. Some policies, including prudent and firm climate policy, international climate cooperation, and depoliticization in climate-related decisions, are provided for promoting economic development, stabilizing energy market and geopolitical tensions.

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Publication Details

Journal
Energy & Environment
Published
2025-02-18
DOI
https://doi.org/10.1177/0958305x251319370
Citations
3
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
9.39
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article

Unraveling uncertainty spillovers: Climate policy's role in global economic, energy and geopolitical landscapes

Hong-Wen Liu, Kai‐Hua Wang, Lu Liu
3 citations
Energy & Environment
Market Dynamics and Volatility
9.39
article

Unraveling uncertainty spillovers: Climate policy's role in global economic, energy and geopolitical landscapes

Hong-Wen Liu, Kai‐Hua Wang, Lu Liu
article en
3 citations

Abstract

This paper discusses the uncertainty spillover among climate policy, economic policy, energy market and geopolitics, using time-varying parameter vector autoregression (TVP-VAR) connectedness approach. The major results show that the total connectedness index (TCI) is dominated by long-term connectedness in static analysis. The main spillover transmitters are climate policy uncertainty in China (CPUC) and economic policy uncertainty (EPU) while the receivers are the USA (CPUS) and energy-related uncertainty (ERU) when considering time and frequency. Next, in the dynamic analysis, the TCI exhibits a downward trend, and the net total directional connectedness indicates that CPUC is still a pure transmitter, while CPUS plays a completely opposite role. Finally, dynamic net pairwise analysis shows that CPUC exerts spillovers on EPU, ERU and geopolitical risk. Conversely, CPUS is more likely to accept the shock of other uncertainties. The major contribution is that the different uncertainties are incorporated into a unified research framework, and explain the detailed influencing channels. More importantly, this paper recognizes the different roles of CPUC and CPUS in the entire uncertainty connectedness with considering time and frequency, and argue that China is reshaping global economy, energy market and geopolitical situation. Some policies, including prudent and firm climate policy, international climate cooperation, and depoliticization in climate-related decisions, are provided for promoting economic development, stabilizing energy market and geopolitical tensions.

Energy & Environment
Qingdao University (CN), People’s Hospital of Rizhao (CN), City University of Macau (MO)
Openalex Percentile: Top 3%
Market Dynamics and Volatility
9.39
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