Risk or resilience? Assessing the impact of climate policy uncertainty on MENA stock markets: A ST-VECM analysis

Quantile connectedness between the climate policy and economic uncertainty: Evidence from the G7 countries

Climate and economic policy uncertainties undermine carbon trading supply-demand dynamics, triggering price volatility. To explore how the carbon price will change, we develop a unified price forecasting model based on multi-frequency data. Based on this, carbon trading markets in Hubei and Shanghai are chosen as research cases to explore the different price volatility of markets across market activity under climate and economic policy uncertainties, respectively. This paper presents a novel study optimizing the accuracy of existing price forecasting models by considering dual policy uncertainties. Results revealed that in the short term, the Shanghai carbon trading pilot exhibits asymmetry in short-term asset price volatility, whereas such a characteristic is not observed in the Hubei carbon trading market. In the long term, climate policy uncertainties cause more significant price volatility under both markets, while economic policy uncertainties only have an impact on the Hubei carbon market. Additional study indicates that including macroeconomic factors, especially economic policy uncertainty, can enhance the predictive prowess of carbon trading price forecasting models.

Energy consumption within policy uncertainty: Considering the climate and economic factors

How does the time-varying dynamics of spillover between clean and brown energy ETFs change with the intervention of climate risk and climate policy uncertainty?

Climate policy uncertainty influences carbon emissions in the semiconductor industry

Global warming is pressuring policymakers to change climate policies in shifting the global economy onto a net-zero pathway. While financial assets are responsive to policy changes and development, climate change policies are becoming increasingly unpredictable, making policy decision less certain. This study investigates connectedness and spillover effects of US climate policy uncertainty on energy stocks, alternative energy stocks, and carbon emissions futures. We analyzed spillover and connectedness before and after the Paris Agreement. We employed monthly frequency data from August 2005 to March 2021 and applied DY (2012) method and MGARCH approach. We found that world energy stocks and carbon emissions futures are connected to US climate policy uncertainty. Uncertainty in climate policy and world energy stocks act as information transmitters in return spillover, while global alternative energy and carbon market are shock receivers. On volatility spillover, climate policy uncertainty, energy stocks, and carbon emissions future are shocks transmitters, while alternative energy stocks are receivers. We observe increase in connectedness following the Paris Agreement suggesting strengthened global efforts in tackling climate change. DCC and ADCC estimations revealed spillover effects of climate policy on futures returns and volatilities of world energy stocks and carbon emissions futures and the shocks could be transmitted through to the energy sector. During period of uncertainty in US climate policy, carbon allowances can potentially serve as a safe haven for energy stocks and provide downside protection for alternative energy stocks, hence hedging against climate transition risks.

ABSTRACTWith the serious ecological damage and frequent climate risks, stakeholders are increasingly concerned about corporate sustainability capability. Government agencies are also actively formulating climate policies to guide corporates to carry out ESG behaviors and promote economic and social sustainability. However, frequent climate policies may bring significant policy uncertainty, inhibiting firms' capability to improve sustainability. Based on the sample data of 742 listed firms in China from 2011 to 2022, we examine the impact of climate policy uncertainty (CPU) on corporate sustainability capability. The study finds that CPU significantly inhibits corporate sustainability capability, and this conclusion remains valid after a series of robustness tests. The mechanism tests show that CPU significantly inhibits corporate sustainability capability by reducing climate perception capability, triggering investor pessimism, and increasing bank risk. Further research found that government digital transformation can directly reduce CPU, thereby reducing the negative impact on corporate sustainability capability. The moderation analysis reveals that corporate digital transformation can significantly positively moderate the impact of CPU on corporate sustainability capability. The findings from the heterogeneity test indicate that corporates with high policy and risk sensitivity are more significantly affected by CPU in terms of their sustainability capability. Overall, this paper adds to the micro‐level analytical framework and empirical evidence of climate policy shocks. Policymakers should pay attention to the issue of climate policy uncertainty and mitigate its negative shock on the sustainable development capacity of enterprises by creating more stable climate policy expectations.

Recent events, such as the financial crisis, oil price shocks or fluctuations, Brexit, the US–China trade war, the COVID-19 pandemic, the Russia–Ukraine conflict and the subsequent energy crisis, have surged global economic policy uncertainty. As climate change has recently been more pronounced around the globe, discussions about climate policies and related uncertainties have also become a major concern. This study investigates the role of economic policy uncertainty (EPU) and climate policy uncertainty (CPU) on climate change (environmental degradation) for selected emerging and developed economies, expanding the IPAT framework and merging it with the Environmental Kuznets Curve (EKC) hypothesis. The IPAT framework examines the impact (I) of population (P), affluence (A), and technology (T) on the environment, whereas the EKC hypothesis proposes an inverted U-shaped curve between affluence and environmental degradation. Two models were created and tested for emerging and developed countries, namely Model 1 with EPU and Model 2 with CPU. A Pooled Mean Group (PMG) estimator is employed to investigate the interrelation between carbon dioxide (CO2) emissions and selected variables; namely the real Gross Domestic Product (GDP) per capita, squared real GDP per capita, renewable share in consumption, the EPU, the CPU and population. Test results indicate that the EKC hypothesis is verified only in Model 1 and for emerging countries, whereas population escalates climate change in both country groups. Furthermore, in line with the consumption effect theorized earlier in the literature, EPU is negatively related to carbon emissions in emerging countries. Thus, the EPU leads to a decrease in the use of energy and pollution-intensive commodities and mitigates climate change in EMEs. Compatible with our ex-ante expectations, renewable energy consumption alleviates climate change in both country groups in the short term. In Model 2, with CPU, we find no evidence supporting the EKC hypothesis for any country groups. However, we reaffirm that renewable energy consumption decreases CO2 emissions in developed countries, which is in support of the argument that energy transition holds the key to tackling climate change. Finally, CPU is associated with a decrease in CO2 emissions in emerging countries in the short term, potentially leading to a reduction in overall economic activity and alleviating climate change. This might also be attributable to the fact that the decisions of economic agents substantially rely on current and future policy (both economic and climate) expectations. Overall, verifying the EKC hypothesis for emerging countries in Model 1, we might argue that there is good potential for emerging countries to save money and time on environmental costs via the adoption of clean technologies and related policies. Last but not least, on a global scale, energy transition with better utilization of renewable sources holds the key to tackling climate change and reducing emissions.

With rising climate policy uncertainty (CPU) and economic policy uncertainty (EPU), it is crucial to analyze the factors influencing the renewable energy stock market (RE) from a comprehensive perspective. Using data from January 2009 to May 2022, we use a time‐varying parameter vector autoregressive model with stochastic volatility (TVP‐VAR‐SV) to examine CPU, EPU, macroeconomic factors, and RE in a unified framework. We analyze the various responses of RE to CPU and EPU. Furthermore, we test for differences in the impact of the four classifications of EPU on RE. The findings are as follows. The time‐varying impact of CPU on RE is centered on the short term and is positive during non‐crisis periods. In contrast, the impact of EPU on RE is negative in the short term. In addition, causal identification at the micro level reveals that RE can increase by 0.932% on average after being affected by CPU. Further comparing the four classifications of EPU, we find that exchange rate policy uncertainty has the largest negative impact. Our study enriches the investment theory on RE. It avoids biased interpretations of various policy uncertainties and has a significant implication for policymakers, renewable energy firms, and investors.

Can green bond hedges climate policy uncertainty in the United States: New insights from novel time-varying causality and quantile-on-quantile methods?

The transition to renewable energy (REN) is indispensable for achieving long-term environmental sustainability, but its advancement necessitates substantial input of critical minerals such as cobalt, graphite, rare elements, and lithium. While the importance of these minerals for the transition to clean energy is increasingly recognized in the literature, the role of policy -induced uncertainties—particularly energy policy uncertainty (ENPU) and climate policy uncertainty (CPU) — in shaping mineral production remains underexplored, especially in China. This study addresses this gap by empirically investigating the impact of ENPU, CPU, and energy transition (ENT) on the production of REN-related minerals in China from October 2002 to October 2022. To capture the heterogeneous and nonlinear relationships among the variables, the analysis utilizes advanced econometric techniques, namely the multivariate quantile-on-quantile regression (M-QQR) and the Fourier-based quantile causality test (FQCT). The findings reveal three major insights: (i) ENPU exerts a statistically significant negative influence solely on graphite production, with negligible effects on other minerals; (ii) CPU has a positive and robust influence on the output of graphite, rare elements, and lithium across multiple quantiles; and (iii) ENT consistently drives an increase in the production of all examined REN minerals. These results underscore the differential sensitivity of mineral production to various policy uncertainties and the structural changes associated with the energy transition. The study concludes that reducing energy policy uncertainty and promoting investment in clean energy technologies are essential for securing a stable and sustainable mineral supply chain to support China’s low-carbon transition.

Against the backdrop of worsening global climate change, countries worldwide have implemented climate policies to reduce corporate pollution emissions and promote corporate social responsibility. However, regional differences in climatic conditions have intensified the uncertainty of climate policies during implementation, creating a critical research gap: the influence of climate policy uncertainty (CPU) on corporate pollution behavior remains underexplored, despite its theoretical value for enriching environmental policy and corporate behavior research and practical significance for guiding policy optimization. To address this gap, this study takes 3,702 listed enterprises across 31 provinces in China (2010–2022) as the research sample. It empirically examines the impact of CPU on enterprises' “pollution migration” behavior, with a focus on testing underlying mechanisms (e.g., financing constraints) and heterogeneous effects (e.g., by artificial intelligence [AI] adoption level, enterprise pollution intensity, and ownership type). The key findings are as follows: (1) CPU significantly exacerbates enterprises' pollution migration; (2) the mechanism test confirms that CPU increases enterprises' financing constraints, which in turn aggravates pollution transfer; (3) enterprises with higher AI adoption levels experience a weaker impact of CPU on pollution migration; and (4) heterogeneity analysis shows that CPU exerts a more pronounced effect on pollution migration among highly polluting enterprises and non-state-owned enterprises (NSOEs). This study validates the “pollution haven” hypothesis in the context of climate policy uncertainty, providing important references for both policymakers and enterprises. For governments, it is recommended to stabilize climate policy expectations, improve the green financial system, and support enterprises in AI application. For enterprises, proactive monitoring of policy trends and enhancement of AI application capabilities are essential to mitigate the adverse effects of CPU and achieve sustainable development.

This study explores the role of corporate social responsibility in bolstering firm resilience amid the escalating threats of climate change and climate policy uncertainties. Specifically, it assesses whether corporate social responsibility initiatives can act as strategic buffers enhancing corporate sustainability. The research utilizes a panel dataset comprising annual observations from 451 US‐based firms over the period 2012 to 2023, yielding a total of 5412 firm‐year observations. Our findings indicate that corporate social responsibility potentially reduces the detrimental effects of climate change and policy uncertainty. Furthermore, the study examines the interaction effects between sustainability committees and green audits on the efficacy of corporate social responsibility. Our results reveal that sustainability committees significantly strengthen the nexus between corporate social responsibility investments and effective climate change mitigation strategies, while green audits enhance firm capabilities to navigate climate policy uncertainties. Collectively, these findings suggest that robust corporate social responsibility practices contribute to corporate value creation in the face of climate‐related challenges.

This study investigates how uncertainty in climate and global economic policies affects private investment in sub‐Saharan Africa (SSA). Using panel data from 41 countries over the period 2000–2022, the study employs a dynamic panel model to estimate the effects of these two types of uncertainty on the private investment‐to‐gross domestic product ratio. The study finds that both global economic policy uncertainty (EPU) and climate policy uncertainty have a negative and significant influence on private investment, implying that higher levels of uncertainty discourage private investors from undertaking long‐term projects in the sub‐region. The study also finds that the effect of uncertainty on climate policy is stronger than that of EPU, suggesting that private investors are more sensitive to the lack of clarity and coherence in the global climate policy framework. The findings are robust to different estimation techniques. The study concludes that reducing policy uncertainty, especially in the area of climate change, is crucial for enhancing private investment and promoting sustainable development in SSA.

Green bond and green stock in China: The role of economic and climate policy uncertainty