Energy transition in China: Is there a role for climate policy uncertainty?

In exploring strategies to address global climate change and achieve carbon neutrality goals, climate policy uncertainty (CPU) has become a significant challenge that cannot be ignored. It is crucial to understand how regions can effectively respond to climate risks and achieve energy transition. In this context, we utilized panel data from 277 Chinese cities and employed fixed effects models to analyze the relationship and mechanism between Chinese climate policy uncertainty (CCPU) and energy transition (ET). Our study found that CCPU significantly hinders the progress of ET, and this impact exhibits asymmetric characteristics. Compared to regions with strong environmental regulations, limited fiscal decentralization, and higher administrative levels, CCPU has a more pronounced inhibitory effect on ET in regions with weak environmental regulations, significant fiscal decentralization, and lower administrative levels. Green finance and energy structure are identified as important channels through which CCPU reduces ET. Additionally, further analysis indicates that CCPU significantly suppresses regional high-quality economic development and innovation, and this impact is achieved through inhibiting ET. Therefore, in the face of external uncertainties, this research can provide insights for local climate policy formulation. Focusing on and striving to reduce CCPU will contribute to the development of ET in regions.

Climate policy uncertainty and its impact on the volatility, correlation, and hedging of sovereign and green bonds.

This study develops monthly climate policy uncertainty (CPU) indexes for 21 economies and three global CPU indexes to evaluate their effects on the long-term sovereign and green bond volatilities and the long-term sovereign-green bond correlation. Findings show significant increases in the CPU indexes during key climate policy events. Using the extended GARCH-MIDAS-CPU and DCC-MIDAS-CPU models, it finds that CPU significantly affects sovereign bond volatility following the Paris Agreement. Green bonds are more effective as hedging tools in the sovereign bond markets of emerging markets and developing economies than in developed ones, especially post-Paris Agreement. Diversified portfolios including green bonds offer superior hedging effectiveness. This study highlights the pivotal role of green bonds in managing CPU and promoting sustainable development goals.

Climate risk and green total factor productivity in agriculture: The moderating role of climate policy uncertainty.

In light of the escalating global warming and the escalating frequency of extreme weather events, the agricultural sector, being a fundamental and pivotal industry worldwide, is encountering substantial challenges due to climate change. Using Chinese provincial panel data for 2000-2021, this paper utilizes a two-way fixed-effect model to investigate the impact of Climate Risk (CR) on green total factor productivity in agriculture (AGTFP), with China's climate policy uncertainty (CPU) being introduced as a moderating variable within the research framework to scrutinize its influence in this context. The findings reveal a noteworthy adverse effect of CR on AGTFP, further exacerbated by CPU. Heterogeneity analysis results show that there is a clear regional variation in the effect of CR on AGTFP across different Chinese regions, with CR significantly inhibiting AGTFP development in the northern regions and provinces in major grain producing regions. Consequently, there is a pressing necessity to bolster the establishment of climate change monitoring infrastructures, devise tailored climate adaptation strategies at a regional level, and enhance the clarity and predictability of climate policies to fortify the resilience and sustainability of agricultural production systems.

Provincial-level analysis of electrification feasibility and climate policy interactions.

Improving electrification feasibility is essential for reducing emissions from non-electric energy sources, thereby enhancing air quality and public health. Concurrently, climate mitigation actions, such as carbon pricing policies, have significant potential to alleviate increasing carbon dioxide (CO2) and other co-emitted air pollutants. However, the interactions between climate policy and the improvement of electrification feasibility at the provincial level remain unclear, collectively impacting the net-zero transition of energy-intensive sectors. Here we combine a technologically rich economic-energy-environment model with air quality modeling across China to examine the health, climate, and economic implications of large-scale upgrades in electrification feasibility and climate policies from 2017 to 2030. The results indicate that advancing electrification feasibility, coupled with adopting carbon pricing policies, is likely to facilitate a transition towards electricity-dominant energy systems. Improved electrification feasibility is projected to yield a 7-25% increase in nationwide climate benefits and a 5-14% increase in health benefits by 2030. These incremental benefits, coupled with reduced economic costs, result in a 22-68% increase in net benefits. However, regionally, improvements in electrification feasibility will lead to heightened power demand and unintended emissions from electric energy production in certain provinces (e.g., Nei Mongol) due to the coal-dominated power system. Additionally, in major coal-producing provinces like Shanxi and Shaanxi, enhanced electrification feasibility exacerbates the negative economic impacts of climate policies. This study provides quantitative insights into how improving electrification feasibility reshapes energy evolution and the benefit-cost profile of climate policy at the provincial level. The findings underscore the necessity of a well-designed compensation scheme between affected and unaffected provinces and coordinated emission mitigation across the power and other end-use sectors.

Comparative impacts of energy, climate, and economic policy uncertainties on renewable energy.

The ongoing adjustment and fluctuation of energy, climate, and economic policies leads to potential policy uncertainty. The potential uncertainty arising from these policies has a wide range of effects on renewable energy technology, leading to changes in investment decisions or consumption patterns. Hence, given the worldwide shift towards sustainable technologies, it is critical to assess how these policy uncertainties will affect renewable power. Given this backdrop, this study delves into the impact of energy policy uncertainty, climate policy uncertainty, economic policy uncertainty, and government effectiveness on renewable energy in the United States. The cross-quantilogram (CQ) methodology is employed by using monthly data from 2002 to 2022. The outcomes reveal that energy policy uncertainty effectively promotes renewable energy in the short run, whereas it serves as a barrier to the adoption of renewables in the long run. Economic policy uncertainty reduces renewable energy consumption in the short run, but it increases in the long run. Moreover, climate policy uncertainty accelerates the transition to low-carbon energy sources. Finally, government effectiveness is a significant supportive element of the energy transition towards renewables.

The dark side of climate policy uncertainty: Hindering energy transition by shaping environmental taxes effectiveness.

Climate policy uncertainty (CPU) may have an adverse impact on the environment by interfering with the effectiveness of environmental policies, but there is currently little evidence to support this indirect effect. By incorporating CPU into the transition function, this paper utilizes the panel smooth transition regression (PSTR) to dynamically analyze how CPU affects the relationship between environmental taxes (ETR) and energy transition. When CPU exceeds the threshold, the promoting effect of ETR on energy transition weakens or reverses. The robustness of the main conclusions is demonstrated by establishing a PSTR estimator with the instrumental variable. This paper also constructs a counterfactual scenario, showing that CPU reduces the positive impact of ETR on renewable energy consumption and generation by 7.6% and 3.5%, respectively. Further analysis indicates that this negative effect arises because CPU likely increases investment risk, particularly for long-term green projects, thereby inhibiting the clean energy market and energy-related green technological innovation. Heterogeneity analysis find that the weakening effect of CPU on the effectiveness of ETR is stronger in countries with low energy resource endowment, high energy intensity, and lower economic development levels, underscoring the need for tailored policy approaches. This research emphasizes that for countries with ambitious energy transition goals, climate policy stability is crucial for ensuring the healthy development of environmental taxes policy and renewable energy markets.

Asymmetric impacts of climate policy uncertainty, investor sentiment on energy prices and renewable energy consumption: Evidence from NARDL and wavelet coherence.

This paper seeks to look into the asymmetric impacts posed by climate policy uncertainty (CPU) and investor sentiment (IS) upon the price of non-renewable energy, specifically natural gas prices, and the consumption of renewable energy, embodied in geothermal energy, biofuels, and fuel ethanol. To this end, the analysis draws on a non-linear autoregressive distributed lag (NARDL) model and wavelet coherence (WTC) technique with monthly data from January 2000 to December 2021. The NARDL results establish an asymmetric association between the variables, where negative shocks to CPU exert a greater effect on each energy variable than positive shocks, while the reverse is true for IS. Furthermore, it has been noticed that CPU and IS exhibit primarily negative correlations with the target variables over the long term, with CPU having a more pronounced effect on natural gas prices than on other forms of renewable energy consumption. Wavelet analysis also reveals that CPU leads the energy variables over the medium to long run, while IS assumes a dominant role in the short to medium run. These momentous findings underscore the importance of this study in informing energy policy formulation and environmental management, as well as optimizing investor portfolios.

Will Hydrogen Be a New Natural Gas? Hydrogen Integration in Natural Gas Grids.

Hydrogen is similar to natural gas in terms of its physical and chemical properties but does not release carbon dioxide when burnt. This makes hydrogen an energy carrier of great importance in climate policy, especially as an enabler of increasing integration of volatile renewable energy, progressive electrification, and effective emission reductions in the hard-to-decarbonize sectors. Leaving aside the problems of transporting hydrogen as a liquid, technological challenges along the entire supply chain can be considered as solved in principle, as shown in the experimental findings of the Hydrogen Innovation Program of the German Technical and Scientific Association for Gas and Water. By scaling up production and end-use capacities and, most importantly, producing hydrogen in regions with abundant renewable energy, hydrogen and its applications can displace natural gas at affordable prices in the medium term. However, this substitution will take place at different rates in different regions and with different levels of added value, all of which must be understood for hydrogen uptake to be successful.

The impact of climate policy uncertainty on China's green energy and non-ferrous metals market co-movement: Evidence from spillover perspectives.

The rapid development of green energy would render a profound impact on the non-ferrous metals markets in China. This paper adopts the quantile vector autoregression (QVAR) to investigate the spillover effects between China's green energy and non-ferrous metals markets as well as their dynamic pattern under normal and extreme conditions. Furthermore, GARCH-MIDAS model and quantile regression method are applied to examine the impact of China's climate policy uncertainty on the spillovers between the two markets. In doing so, we find that green energy markets mainly act as transmitters of return spillover effects to non-ferrous metals markets during normal market times and periods of downturns. However, in upturns, the non-ferrous metals markets would easily transit spillover effects to green energy ones. It is further indicated that China's climate policy uncertainty exacerbates the spillover effect, and the exacerbated effect of high uncertainty on the market relationship when the spillover effect is at high level is the most significant.

California dreaming: Why environmental justice is integral to the success of climate change policy.

In the realm of climate policy, issues of environmental justice (EJ) are often treated as second-order affairs compared to overarching sustainability goals. We argue that EJ is in fact critical to successfully addressing our national and global climate challenges; indeed, centering equity amplifies the voices of the diverse constituencies most impacted by climate change and that are needed to build successful coalitions that shape and advance climate change policy. We illustrate this perspective by highlighting the experience of California and the contentious processes by which EJ became integrated into the state's climate action efforts. We examine the achievements and shortcomings of California's commitment to climate justice and discuss how lessons from the Golden State are influencing the evolution of current federal climate change policy.

Impact of Climate Policy Uncertainty (CPU) and global Energy Uncertainty (EU) news on U.S. sectors: The moderating role of CPU on the EU and U.S. sectoral stock nexus.

This article accounts for the impact of positive and negative shocks of the news-related Climate Policy Uncertainty (CPU) and the novel Economist Intelligence Unit's report-based global Energy Uncertainty (EU) on the U.S. sectoral stock returns by using the ARDL and NARDL approaches with dynamic multiplier simulations. We also utilize both the DCC-GARCH and ADCC-GARCH approaches to extract the symmetric and asymmetric dynamic conditional correlations between the EU and the U.S. sectoral stock returns and then regress these conditional correlation series on the CPU through series of quantile regressions. Overall, the findings suggest that only the positive CPU shocks negatively impact the U.S. sectoral stock returns of Consumer Services, Financials, Industries, Telecommunication and Utilities in the long-term, whereas the negative CPU shocks insignificantly predict the U.S. sectoral returns. The findings also report that only the negative EU shocks increase the U.S. sectoral stock returns of Consumer Services, Financials, Health Care, Industries, Moreover, the positive (negative) EU shocks cause the U.S. sectoral returns of Materials and Technology to decrease (increase) in the long-term. Portfolio managers may consider diversifying their portfolios to include sectors least susceptible to negative impacts from the CPU and EU shocks such as Health Care and Oil & Gas. Our findings also show that CPU shocks moderate the dynamic conditional correlations between the EU and the U.S. sectoral returns of Consumer Services, Materials, Health Care, Telecommunication, Oil and Gas and Utility. Fund managers should contemplate augmenting the allocations to the Financials, Industrials, and Technology sectors owing to their diminished interconnectivity with the EU during periods of heightened CPU.

Does climate policy uncertainty drive the extreme spillovers of carbon-energy-shipping markets?

In addressing the ramifications of climate change, the shipping industry, reliant on energy, has been integrated into the Emissions Trading System (ETS). This study utilizes the quantile connectedness model to investigate the information spillover mechanisms and extreme time-varying interconnections among carbon, energy, and shipping markets. Whether climate policy uncertainty drives the extreme interconnections is also discussed during both pre- and post-Paris Agreement periods, by using GARCH-MIDAS model. The empirical findings underscore the following key points: (i) the systemic connectedness is highly sensitive to market conditions and major events, increasing significantly under extreme market conditions; (ii) following the implementation of the Paris Agreement, an elevated level of informational interdependence has manifested between the carbon market and the energy and shipping sectors; (iii) the information transfer mechanism between carbon and shipping sectors creates direct and indirect spillover paths, with crude oil market mediating the indirect path; (iv) climate policy uncertainty greatly affects the extreme time-varying interconnections, and this impact has decreased after the Paris Agreement came into effect. These results offer valuable insights for market policymakers and shipping companies in achieving a balance between carbon emission reduction and shipping business, particularly amidst heightened climate policy uncertainty.

The impact of climate policy uncertainty on corporate pollution Emissions--Evidence from China.

Climate change is considered one of the major systemic risks facing the world in the 21st century. To address climate change, China has adopted a series of climate policies, but the uncertainty brought about by frequent climate policy issuance has increased pressure on enterprises, which may not be conducive to enterprises reducing emissions. This paper uses data on 1211 listed companies on the A-share market in China from 2012 to 2022 to study the impact of climate policy uncertainty on enterprise pollutant emissions. The research findings show that climate policy uncertainty increases corporate pollution emissions; climate policy uncertainty mainly generates negative impacts on enterprise environmental regulation, social responsibility, and R&D investment, thereby negatively affecting enterprise emissions reduction. Further heterogeneity analysis shows that climate policy uncertainty in China has a more significant impact on non-state-owned enterprises, technology-intensive enterprises, lightly polluting enterprises, and enterprises in western regions. These findings emphasize the importance of enterprise social responsibility, environmental regulation, and R&D investment in enterprise emissions reduction and provide policy implications for Chinese enterprises to optimize their energy-saving and emission reduction strategies in the face of climate policy uncertainty.

Inaction in Urban Climate Policy Undermines Health.

This paper investigates the critical intersection of urban climate policy and public health, emphasizing the pressing need for integrated strategies to address the intertwined challenges of climate change and health in urban settings. Despite cities being central to global emissions and energy consumption, a significant gap exists in the incorporation of health considerations into urban climate strategies, as evidenced by the analysis of urban content in Nationally Determined Contributions (NDCs). The paper highlights the Coalition for High Ambition Multilevel Partnerships (CHAMP) initiative and the forthcoming Intergovernmental Panel on Climate Change (IPCC) Special Report as pivotal moments for integrating climate and health agendas. However, it also points out the underwhelming response from cities in adopting comprehensive climate strategies, which undermines potential public health benefits. With substantial investments required to bridge the gap in health-focused climate resilience, the paper calls for a redefined approach to urban climate policy. This approach should prioritize health outcomes, leverage opportunities like the 15-Minute City concept, and foster the development of infrastructures that support both climate resilience and public health. The upcoming NDC revision cycle is identified as a critical opportunity for embedding health imperatives into urban climate strategies, emphasizing the need for a holistic perspective that views urban areas as ecosystems where climate and health are intricately connected. This comprehensive view aims to promote policies that are mutually reinforcing, thus contributing to healthier, more livable cities.

The essential role of climate policy uncertainty in carbon emissions: a fresh insight.

This study assesses the influence of climate policy uncertainty (CPU) on carbon emissions (CE) against the backdrop of economic policy uncertainty (EPU) in the US. The wavelet analysis provides a comprehensive understanding of correlations in the time and frequency domains. The results demonstrate a significant correlation between CPU and CE, which varies across different time periods and frequencies. In the time domain, the results indicate that the CPU and CE move together during certain subperiods. Moreover, there are observable comovements in the frequency domain, particularly in the short to medium range. However, the correlation becomes stronger in the short term when there is no EPU, suggesting a closer interaction between CPU and CE. Therefore, it is crucial for governments to prioritize improving the clarity, credibility, and consistency of climate policies. They should also consider potential economic shocks when designing these policies.

The risk paradox: Exploring asymmetric nexus between climate policy uncertainty and renewable energy technology budgets.

The ups and downs of climate policy uncertainty (CPU) cast a captivating shadow over the budgets allocated to renewable energy (RE) technologies, where strategic choices and risk assessment will determine the course of our green environmental revolution. The main intention of this investigation is to scrutinize the effect of CPU on the RE technology budgets (RETBs) in the top 10 countries with the highest RE research and development budgets (the USA, China, South Korea, India, Germany, the United Kingdom, France, Japan, Australia, and Italy). Although former researchers have typically employed panel data tools to contemplate the connection between CPU and RE technology, they repeatedly ignored variations in this connection throughout different economies. In contrast, our research adopts a unique approach, "quantile-on-quantile," to check this association at the country-to-country level. This approach offers a comprehensive worldwide perspective while procuring tailor-made perceptions for individual economies. The outcomes suggest that CPU significantly decreases RETBs across several data quantiles in our sample nations. In addition, the outcomes underscore that the connections between our variables differ among nations. These outcomes highlight the significance of policymakers implementing thorough appraisals and skillfully governing plans relevant to CPU and RETBs.

Least-cost decarbonization pathways for electricity generation in Finland: A convex quantile regression approach.

This study investigates the least-cost decarbonization pathways in the Finnish electricity generation industry in order to achieve the national carbon neutrality goal by 2035. Various abatement measures, such as downscaling production, capital investment, and increasing labor and intermediate inputs, are considered. The marginal abatement costs (MACs) of greenhouse gas emissions are estimated using the convex quantile regression method and applied to unique register-based firm-level greenhouse gas emission data merged with financial statement data. We adjust the MAC estimates for the sample selection bias caused by zero-emission firms by applying the two-stage Heckman correction. Our empirical findings reveal that the median MAC ranges from 0.1 to 3.5 euros per tonne of CO2 equivalent. The projected economic cost of a 90% reduction in emissions is 62 million euros, while the estimated cost of achieving zero emissions is 83 million euros.

Financial regulations and sustainability: The role of energy price and climate policy uncertainty.

Russia ranks among the top five countries worldwide in terms of carbon emissions, with the energy, transportation, and manufacturing sectors as the major contributors. This poses a significant threat to both current and future generations. Russia faces challenges in achieving Sustainable Development Goal 13, necessitating the implementation of more innovative policies to promote environmental sustainability. Considering this alarming situation, this study investigates the role of financial regulations, energy price uncertainty, and climate policy uncertainty in reshaping sectoral CO2 emissions in Russia. This study utilizes a time-varying bootstrap rolling-window causality (BRW) approach using quarterly data from 1990 to 2021. The stability test for parameters indicates instability, suggesting that the full sample causality test may yield incorrect inferences. Thus, the BRW approach is employed for valid inferences. Our findings confirm the time-varying negative impact of financial regulations on CO2 emissions from energy, manufacturing, and transportation sectors. Additionally, findings confirm time-varying positive impact of energy prices and climate policy uncertainty on CO2 emissions from the energy, manufacturing, and transportation sectors. Strong financial regulations and stable energy and climate policies are crucial for achieving sustainability, highlighting significant policy implications for policymakers and stakeholders.

Intergenerational altruism and climate policy preferences.

Climate mitigation constitutes an intergenerational moral dilemma; the decisions we make today will inevitably shape the prospects for generations to come. Yet, we still know little about the relationship between intergenerational altruism (IGA)-our concerns for the well-being of future generations-and support for costly climate mitigation policies. In this study, we present an approach to measuring IGA through an intergenerational dilemma, where participants allocate resources across generations. First, we describe how IGA depends on the temporal (social) distance between generations and demonstrate robust correlations between IGA and support for several climate policies. Then, we leverage randomized participation in the intergenerational dilemma to show that it causally increases climate policy support, an effect we attribute to higher worries about human-induced climate change among treated subjects. An exploratory heterogeneity analysis suggests that the impact of the intergenerational dilemma is primarily driven by female and nonbinary participants. In sum, this study presents both a novel measurement strategy and robust evidence of a malleable moral basis of climate policy preferences.

China's anthropogenic N2O emissions with analysis of economic costs and social benefits from reductions in 2022.

We assess China's overall anthropogenic N2O emissions via the official guidebook published by Chinese government. Results show that China's overall anthropogenic N2O emissions in 2022 were around 1593.1 (1508.7-1680.7) GgN, about 47.0 %, 27.0 %, 13.4 %, 4.9 %, and 7.7 % of which were caused by agriculture, industry, energy utilization, wastewater, and indirect sources, respectively. Maximum reduction rate for N2O emissions from agriculture, industry, energy utilization, wastewater, and indirect sources can achieve 69 %, 99 %, 79 %, 86 %, and 48 %, respectively, in 2022. However, given current global scenarios with a rapidly changing population and geopolitical and energy tension, the emission reduction may not be fully fulfilled. Without compromising yields, China's theoretical minimum anthropogenic N2O emissions would be 600.6 (568.8-633.6) GgN. In terms of the economic costs for reducing one kg of N2O-N emissions, the price ranged from €12.9 to €81.1 for agriculture, from €0.08 to €0.16 for industry, and from €104.8 to €1571.5 for energy utilization. We acknowledge the emission reduction rates may not be completely realistic for large-scale application in China. The social benefits gained from reducing one kg of N2O-N emissions in China was about €5.2, indicating anthropogenic N2O emissions caused a loss 0.03 % of China's GDP, but only justifying reduction in industrial N2O emissions from the economic perspective. We perceive that the present monetized values will be trustworthy for at least three to five years, but later the numerical monetized values need to be considered in inflation and other currency-dependent conditions.