This paper reconciles the debates on carbon return estimation by introducing the concept of equity duration. Our findings reveal that equity duration effectively captures the multifaceted effects of carbon transition risks. Regardless of whether carbon transition risks are measured by emission level or emission intensity, brown firms earn lower returns than green firms when the equity duration is long due to discount rate channel. This relationship reverses for short-duration firms conditional on the near-term cash flow. Our analysis underscores the pivotal role of carbon transitions' multifaceted effects on cash flow structures in understanding the pricing of carbon emissions.

Comprehensive evaluation and identification of the critical regulatory determinants of carbon emission efficiency (CEE) are very important for China’s low-carbon transition. Accordingly, this paper first employs an undesirable global super-hybrid measure approach to calculate the CEE of China’s iron and steel industry (ISI). We then further use spatial error and threshold regression models to examine the spatial and non-linear effects of heterogeneous environmental regulations on CEE, respectively. Our empirical results show that (1) CEE varies significantly across China’s regions, with the eastern region having the highest CEE score, followed by the western and central regions, with the northeast region ranking the lowest; (2) command-and-control and market-incentive regulations both promote CEE, whereas the public participation approach does not significantly contribute to performance gains; (3) all three types of environmental regulations exhibit a non-linear threshold effect on CEE; (4) openness level, technological progress, and industrial concentration enhance efficiency gains, while urbanization level exerts a negative impact on CEE. Our findings have important implications for the design of environmental regulations.

We (re)evaluate the general-equilibrium effects of (environmental) policies from the perspectives of input-output networks and firm dynamics and heterogeneity. Using China’s carbon emission trading system (ETS) as an example, we find that ETS leads to more patent applications, especially the ones associated with low-carbon technologies in the targeted sectors. The effects are muted at the firm level due to selection effects, whereby only larger firms are significantly and positively affected. Meanwhile, larger firms occupy a small share in number but a large share of aggregate outcomes, contributing to the discrepancy between the effects of ETS at the individual firm and aggregate sector levels. The effects also diffuse in input-output networks, leading to more patents in upstream/downstream sectors. We build and estimate the first firm dynamics model with input-output linkages and regulatory policies in the literature and conduct policy experiments. ETS’s effects are amplified given input-output networks.

This paper reconciles the debates on carbon return estimation by introducing the concept of equity duration. We demonstrate that emission level and emission intensity yield divergent results for green firms, driven by inherent data problems. Our findings reveal that equity duration effectively captures the multifaceted effects of carbon transition risks. Regardless of whether carbon transition risks are measured by emission level or emission intensity, brown firms earn lower returns than green firms when the equity duration is long. This relationship reverses for short-duration firms. Our analysis underscores the pivotal role of carbon transitions’ multifaceted effects on cash flow structures in understanding the pricing of carbon emissions.

Taking the national carbon market and seven local carbon markets in China, we use DEA model to measure market efficiency, and then classify them by hierarchical cluster method. Efficiency of the national carbon market and local carbon markets of Beijing, Shenzhen, Hubei and Shanghai are leading, while Guangdong is in the middle; Chongqing and Tianjin are left behind. Room for improvement and scale returns are further analyzed, and suggestions for each carbon market are proposed finally.

Fighting global warming has become a vital requirement for environmental sustainability. Green finance has gained popularity as a promising mechanism for transitioning to a lowcarbon economy. Thus, this paper investigates whether excess green financing increases renewable energy capacities and enhances environmental quality from 1992Q1 to 2020Q4 in China, one of the major CO2 emitters. We primarily used the method of moments-quantile regression with fixed-effect models. First, we found nonlinear U-shaped impacts of green finance on wind power capacities in all Chinese regions, thermal power capacities in the Western and Central areas, and hydropower capacities in Eastern China, respectively. Second, we confirmed an inverted U-shaped impact of green finance on CO2 emissions in the Eastern region but U-shaped effects in the Western and Central regions. The impacts of green finance were asymmetrical due to the heterogeneous distributions of renewable energy sources and environmental quality within and between regions. Green finance mostly improved environmental quality when certain conditions and thresholds were met. Third, green finance had substantial marginal effects on environmental quality in the least polluted provinces (Q.20) in Western China and the most polluted provinces (Q.80) in Eastern China. Finally, there were heterogeneous effects of oil prices, urbanization, foreign direct investments, and trade openness on renewable energy consumption and environmental quality across Chinese provinces. Accordingly, this study provides some policy recommendations for China’s sustainable development, a key example from which the international community can adjust its green policies.

This study examines the impact of climate-transition risks on trade credits for Chinese listed companies from 2007-2017. We develop an index of county-level climate-transition risks faced by Chinese-listed companies using data on local carbon emissions and carbon sequestration when moving towards net zero carbon emissions. Our two-way fixed effects OLS regression results find that local firms facing greater climate-transition risks significantly reduce their trade credit financing. Specifically, a one standard deviation of increase in Risk leads to a 0.73% decrease in trade credit. This reduction is more pronounced for state-owned enterprises (SOEs), firms operating in less competitive industries, and those headquartered in regions without carbon trading markets. Our main finding is robust to a battery of sensitivity tests including the use of alternative measures and lagged independent variables. Results on an Instrumental Variable (IV) method and a differences-in-difference (DiD) analysis suggest a causal relationship between climate-transition risks on trade credit. Further analyses reveal two plausible channels for the effect: increased financial distress risk and enhanced access to bank credit.

China’s energy stocks are confronted with significant climate-related challenges. This paper aims to measure the daily climate transition risk in China by assessing the intensity of climate policies. The daily climate physical risk encountered by China’s renewable energy stocks is also measured based on the perspective of temperature change. Then, the partial linear function coefficient model is adopted to empirically investigate the non-linear impacts of climate transition risk and climate physical risk on the return and volatility of renewable energy stocks. The nonlinear moderating effect of climate transition risk is also involved. It is found that: (1) Between 2017 and 2022, the climate transition risk in China exhibited a persistent upward trend, while the climate policies during this period particularly emphasized energy conservation, atmospheric improvements, and carbon emissions reduction. Additionally, the climate physical risk level demonstrated a pattern consistent with a normal distribution. (2) There is a U-shaped nonlinear impact of climate physical risk on the return and volatility of renewable energy stocks. High climate physical risk could not only increase the return of renewable energy stocks but also lead to stock market volatility. (3) Climate transition risk exhibits a U-shaped effect on the return of renewable energy stocks, alongside an inverted U-shaped effect on their volatility. Notably, a high level of climate transition risk not only increases the return of renewable energy stocks but also serves to stabilize the renewable energy stock market. Moreover, the heightened risk associated with climate transition enhances the negative impact of oil price volatility on the yield of renewable energy stocks and, concurrently, leads to an increase in volatility.The strength of this moderating effect is directly correlated with the level of climate risk.

As the problem of global climate change becomes more severe, countries have proposed the goals of carbon capping and carbon neutrality. Green finance is an essential capacity support for achieving carbon peaking and carbon neutrality, and it can guide and stimulate social capital to invest in low-carbon industries and initiatives via marketbased mechanisms. Based on the panel data of Chinese prefecture-level cities from 2006 to 2020, this paper empirically examines the impact of green finance on carbon emission efficiency using a two-way fixed-effects model, conducts a regional heterogeneity analysis, and examines the threshold effect of economic development level and the mediating role of regional innovation. The results indicate that, first, green finance contributes significantly to the improvement of carbon emission efficiency, and second, the level of regional economic development has a double threshold effect on the contribution of green finance to the improvement of carbon emission efficiency. Third, regional innovation is an important green finance channel for influencing carbon emission efficacy. The sensitivity of carbon emission efficiency to the green finance index demonstrates an inverted U-shaped trend. Fifth, the importance of green finance sub-dimensions in relation to carbon emission efficacy is as follows: green support, green credit, green insurance, green investment, green equity, green bond, and green fund. These findings provide theoretical support for green finance's role in promoting co-carbon efficiency and are valuable for policy formulation.

This paper examines the impact of the carbon emissions trading scheme (ETS) on directed technological change in the context of Chinese pilot schemes. We focus on firms’ heterogeneity in driving innovation and explore policy variations across pilots. Using a matched difference-in-differences design with a zero-inflated Poisson model, we find that the low-carbon innovation is driven by firms at the intensive margin. On average, a firm files 0.16 additional low-carbon patents annually at the intensive margin. In addition, when looking across pilots, the effect on low-carbon innovation is significant in two pilots, Beijing and Shanghai. We further find that, when looking at firms with different productivity levels measured by output per worker, the pilot ETS encourages low-carbon innovation at the intensive margin but reduces entry into low-carbon innovation at the extensive margin for the more productive firms. Our results suggest that innovation inertia matters, and future policies should encourage smaller firms covered by ETS to start innovation in low-carbon technologies.