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?

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

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.

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.

PurposeThis study aims to examine the ability of clean energy stocks to provide cover for investors against market risks related to climate change and disturbances in the oil market.Design/methodology/approachThe study adopts the feasible quasi generalized least squares technique to estimate a predictive model based on Westerlund and Narayan’s (2015) approach to evaluating the hedging effectiveness of clean energy stocks. The out-of-sample forecast evaluations of the oil risk-based and climate risk-based clean energy predictive models are explored using Clark and West’s model (2007) and a modified Diebold & Mariano forecast evaluation test for nested and non-nested models, respectively.FindingsThe study finds ample evidence that clean energy stocks may hedge against oil market risks. This result is robust to alternative measures of oil risk and holds when applied to data from the COVID-19 pandemic. In contrast, the hedging effectiveness of clean energy against climate risks is limited to 4 of the 6 clean energy indices and restricted to climate risk measured with climate policy uncertainty.Originality/valueThe study contributes to the literature by providing extensive analysis of hedging effectiveness of several clean energy indices (global, the United States (US), Europe and Asia) and sectoral clean energy indices (solar and wind) against oil market and climate risks using various measures of oil risk (WTI (West Texas intermediate) and Brent volatility) and climate risk (climate policy uncertainty and energy and environmental regulation) as predictors. It also conducts forecast evaluations of the clean energy predictive models for nested and non-nested models.

Climate policy uncertainty influences carbon emissions in the semiconductor industry

With 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.

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

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

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.

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.

Purpose Amid escalating global climate change challenges, this paper explores strategies for promoting a low-carbon economy and achieving sustainable growth through the lens of corporate strategy. Grounded in the dynamic capabilities theory and real options theory, it examines whether climate policy uncertainty acts as a catalyst or a deterrent for enterprise digital transformation (DT). Furthermore, it aims to investigate how environmental regulations (ERs) and market competition moderate the relationship between climate policy uncertainty and enterprise DT. Design/methodology/approach This study draws on a comprehensive panel data set comprising 37,637 firm-year observations from A-share listed companies in Shanghai and Shenzhen Stock Exchange spanning the period 2009–2023. The dependent variables are constructed using text analysis techniques. To address unobserved heterogeneity, the study uses firm fixed-effects models, while endogeneity concerns are mitigated through instrumental variable (IV) approaches and dynamic panel estimations. In addition, moderating effect analyses are conducted to assess the impact of regional and industry factors. Findings The results indicate that climate policy uncertainty significantly promotes corporate DT. This effect remains robust after addressing endogeneity concerns and conducting extensive robustness checks. Further analysis reveals that the positive impact of climate policy uncertainty on DT is more pronounced in regions with stricter ERs and in industries characterized by intense competition. Practical implications Both governments and enterprises should recognize that climate policy uncertainty presents a long-term challenge. Policymakers should implement targeted measures – such as subsidies, tax incentives and enhanced access to external financing – to accelerate DT, especially in regions with stringent ERs and sectors marked by intense market competition. For businesses, strategic responses to policy uncertainty should center on enhancing long-term competitiveness through increased investment in digital technologies, talent acquisition and continuous upgrading of digital infrastructure. These measures will better equip firms to navigate the complexities arising from climate policy changes. Originality/value This study contributes to the literature on enterprise DT by examining its drivers from the perspective of climate policy uncertainty. It addresses a critical question: whether firms actively embrace digitalization or scale back their efforts in response to uncertainty? Furthermore, it strengthens the causal link between climate policy uncertainty and DT by using IV techniques and dynamic panel models. Lastly, it explores the moderating effects of external factors, revealing the extent to which climate policy uncertainty “pushes” enterprises toward DT under varying levels of ER across regions and competitive intensity within industries.

How to improve global environmental governance? Lessons learned from climate risk and climate policy uncertainty

This study explores the impact of climate policy uncertainty (CPU) on corporate cash holdings in the United Arab Emirates (UAE). The UAE Sustainable Finance Working Group has set principles for effectively managing climate-related risks in the UAE market. Using a panel data analysis for a sample of 46 non-financial firms listed on UAE stock markets during the period from 2013Q1 to 2022Q4, we find that CPU reduces corporate cash holdings. This result confirms the prediction of agency theory and the transaction motive theory. Furthermore, we find that the cash held by corporations responds to high CPU events differently from low CPU events, supporting the asymmetric effect phenomenon. We also find that firm size plays a significant role in reducing the link between CPU and cash holdings. Cash held by large firms responds to CPU differently from cash held by small firms. An increase in CPU produces a greater cash crunch for small firms and very low cash saving for large firms, meaning that liquidity in small firms is greatly harmed by CPU compared to that in large firms. This study serves as a guide for policymakers, managers, stakeholders, and climate policy risk regulators. Public authorities should pursue climate policy risk plans to mitigate the negative effect of CPU. Managers should improve corporate governance to mitigate the negative impact of CPU on corporate cash holdings by effectively managing short-term liquidity and disclosing appropriate information to pursue controlling for climate policy risk.

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.

Climate policy uncertainty and the price dynamics of green and brown energy stocks