Author
Abstract
Purpose - The burgeoning literature on climate-related finance suggests that climate change influences financial markets. Building on this foundation, the present study aims to investigate the time-varying predictive power of news related to physical and transition climate risks for financial instability across the financial systems of the US, EU, and the ASEAN+3 countries (comprising the Association of Southeast Asian Nations plus China, Japan, and South Korea), from January 2003 to August 2022, on a monthly basis. Design/methodology/approach - In this study, we use the VAR-based Granger-causality test in the presence of instabilities introduced by Rossi and Wang (2019), and combine it with the innovative rolling and recursive bootstrap time-varying Granger-causality approach of Shiet al. (2020). These methods were chosen for their capacity to effectively capture the dynamic influence of climate risk-related news on financial instability over time, offering an advantage over traditional constant parameter regressions and standard Granger causality methods. Additionally, we make use of the Media Climate Change Concerns indices recently developed by Ardiaet al. (2022), coupled with regional financial stress indices. Findings - Our findings indicate that the predictive power of climate change news for financial instability is substantial but varies over time. This influence becomes especially pronounced during periods that align with specific local and global events. In the US and EU, the predictive power is influenced by a combination of global and local macroeconomic, political, health, and climate-related factors. In contrast, ASEAN+3 financial systems show a stronger response to regional and local events, with comparatively less sensitivity to global events. Practical implications - The results of this study are noteworthy for investors, highlighting increased market instability during periods with prevalent climate change news. Investors can adjust their strategies to mitigate risks and respond to macro-events that trigger climate news-related market instability, while considering regional sensitivities. Similarly, these findings are significant for policymakers, emphasizing the need to consider the influence of climate news on financial markets when designing regulatory frameworks. This could involve enacting measures to stabilize the financial system during periods of significant climate news. Policymakers might consider developing macroprudential regulations to bolster financial institutions’ resilience against climate change news effects. Originality/value - This study pioneers the exploration of how climate change news affects financial system stability at the macro level. It extends beyond traditional research, typically focusing on direct effects of climate change in banking and asset markets, by examining broader implications of climate risk-related news for financial system instability. Furthermore, this study enhances our understanding of the predictors of global financial stability by examining the financial systems of the US, the EU, and ASEAN+3. It specifically investigates the impact of climate change news, a topic not extensively explored in previous research focusing mainly on macro-factors such as financial liberalization and business cycles.
Suggested Citation
Brahim Gaies, 2024.
"Exploring the time-varying predictability of global financial instability over the last two decades: the influence of climate change news,"
Journal of Economic Studies, Emerald Group Publishing Limited, vol. 52(5), pages 904-918, August.
Handle:
RePEc:eme:jespps:jes-01-2024-0031
DOI: 10.1108/JES-01-2024-0031
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Keywords
Financial instability;
Climate risks;
Time-varying granger-causality approach;
Macro-events;
G01;
Q54;
C32;
E32;
All these keywords.
JEL classification:
- G01 - Financial Economics - - General - - - Financial Crises
- Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
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