This study explores the price drivers of Chinese Emissions Allowances (CEAs) in the early stage of China’s national carbon market. Using daily time series data from July 2021 to July 2023, we find limited influence from conventional drivers, including energy prices and economic factors. Instead, national power generation emerges as a significant driver. These are primarily due to the distinct institutional features of China’s national carbon market, notably its rate-based system and sectoral coverage. Moreover, the study uncovers cumulative abnormal volatility in CEA prices ranging from 12% to 20% around the end of the first compliance cycle, reflecting sentiments about the policy design and participants’ limited understanding about carbon trading. Our results extend previous literature regarding carbon pricing determinants by highlighting China’s unique carbon market design, comparing it with the traditional cap-and-trade programs, and offering valuable insights for tailored market-based policies in developing countries.

This paper investigates the contribution of futures market information to enhancing the predictive accuracy of macroeconomic forecasts, using data from China. We employ three cat-egories of predictors: monthly macroeconomic factors, daily commodity futures factors, and daily financial futures variables. Principal component analysis is applied to extract key fac-tors from large data sets of monthly macroeconomic indicators and daily commodity futures contracts. To address the challenge of mixed sampling frequencies, these predictors are incor-porated into factor-MIDAS models for both nowcasting and long-term forecasting of critical macroeconomic variables. The empirical results indicate that financial futures data provide modest improvements in forecasting secondary and tertiary GDP, whereas commodity futures factors significantly improve the accuracy of PPI forecasts. Interestingly, for PMI forecast-ing, models relying exclusively on futures market data, without incorporating macroeconomic factors, achieve superior predictive performance. Our findings underscore the significance of futures market information as a valuable input to macroeconomic forecasting.

It is diffffcult to understand the risk-return trade-off in option market with observable factormodels. In this paper, we employ a latent factor model for delta-hedge option returns over a varietyof important exchange traded options in China, based on the instrumented principal componentanalysis (IPCA). This model incorporates conditional betas instrumented by option characteristics,to tackle the diffffculty caused by short lifespans and rapidly migrating characteristics of options. Ourresults show that a three-factor IPCA model can explain 19.30% variance in returns of individualoptions and 99.23% for managed portfolios. An asset pricing test with bootstrap shows that there isno unexplained alpha term with such a model. Comparison with observable factor model indicatesthe necessity of including characteristics. We also provide subsample analysis and characteristicimportance.

This paper examines the influence of gambling culture on household investment decisions concerning risky financial assets. To estimate these effects, the study utilizes data from the 2019 China Household Finance Survey. The empirical findings reveal that gambling culture significantly enhances household preferences for risky financial assets and raises the proportion of household allocations to these assets. Furthermore, both subjective financial literacy and objective financial literacy amplify these positive effects. The heterogeneity analysis revealed that the effects of gambling culture on household preference for and allocation of risky financial assets varied across regions, income levels, and household types.

人工智能技术正以前所未有的速度重塑人类社会的基本结构，其影响广度从 日常生活延伸至全球治理体系。2025年，全球人工智能核心产业规模已突破6000 亿元人民币，用户规模接近 2.5 亿，技术渗透率高达 17.7%。这一指数级增长态 势既孕育着社会效率革命的曙光，又潜伏着深刻的伦理危机。当深度伪造技术能 够以几可乱真的方式模拟人类生物特征，当算法偏见在招聘、信贷领域悄然固化 社会不平等，人类不得不面对一个核心命题：如何在享受 AI 技术红利的同时， 构建牢不可破的伦理防护网？本文从 AI 技术的社会影响全景出发，系统分析其 作为效率引擎与犯罪工具的双重面相，并探索符合技术伦理与现实需求的治理路 径，为构建安全可信的人工智能未来提供理论支撑与实践指南。

Using data from Chinese A-share listed firms from 2015 to 2022, we employ a difference-in-differences model to empirically examine the impact of bankruptcy regimes, marked by the establishment of bankruptcy courts, on firms’ total factor productivity (TFP). The results show a significant decline in TFP among firms in regions following the establishment of bankruptcy courts. This finding remains valid after a series of robustness tests. Mechanism tests reveal that establishing bankruptcy courts increases firms’ risk aversion incentives by endowing creditors with excessive rights. Consequently, firms tend to reduce liabilities, curtail R&D investment, and accumulate liquid assets as coping measures, ultimately contributing to a decline in TFP. Furthermore, this effect is more pronounced for firms with high financial risk. However, the improvement of the market mechanism can alleviate the negative impact of bankruptcy courts excessively strengthening creditor protection. Specifically, when firms are located in regions with weak government intervention and strong financial development, as well as in market environments with low uncertainty and strong competition, this negative impact can be mitigated. These findings provide fresh insights into the dual nature of creditor protection and offer valuable references for governments to improve the bankruptcy legal system.

This study examines how localized carbon reduction policies affect corporate environmental productivity. Leveraging a quasi-experiment from China’s low-carbon pilot policy rollout across cities, we implement a difference-in-differences approach to estimate the causal impact of these interventions. Pilot policies significantly increased regulated polluting corporate environmental productivity by around 3 percentage points. The productivity gains persisted over time and were greater for financially constrained firms, firms facing less market competition and with lower capital intensity. Additional analysis reveals the pilots enhanced executive environmental awareness. Overall, our results demonstrate appropriately designed local regulations can improve environmental productivity.

Exploiting a unique market-oriented media reform initiated in 1996 in China, we investigate the role of media environment in affecting firm behaviour. We find robust evidence that market-oriented media environment is conductive to firm innovation, with the reform promoting patent quantity and quality substantially. The effect is more pronounced for firms with higher information asymmetry. Matching firm data with 1.3 million news reports, we find the market-oriented media reform significantly improves the criticalness and unbiasedness of news coverage and shapes an innovation-friendly environment. Our findings highlight economic outcomes of relaxing media control and underline substantial gains from deepening the reform.

Do firms adjust their hiring decisions after receiving environmental punishments? Using data on over 4.3 million job postings for Chinese listed firms from 2015 to 2021, we find that firms subjected to environmental punishments will subsequently increase their corporate green hiring (i.e., employees with green skills). Pressure from local environmental concerns and regulatory efforts incentivizes firms to increase their demand for employees with green skills. Environmental punishments have a more pronounced effect on corporate green hiring for non-state-owned enterprises and firms with lower financial constraints. Moreover, green hiring can have a remediation effect on firms' environmental performance and stimulate their green innovation activities and spillover effects on other firms within the industry. Overall, our findings shed light on corporate hiring decisions under environmental regulations.

The aging population is expanding globally, and addressing the challenges of elderly care is urgent. Using the 2019 China Household Finance Survey data, this study finds that commercial pension insurance significantly promotes households’ allocation of risky financial assets. We test the mechanisms using household risk perception and investment risk preference as mediating variables. Heterogeneity analysis reveals that the positive effect of commercial pension insurance on risky financial asset allocation is more significant in rural households with household registration, those with two sets of housing, and households in the northeast. The research findings of this article aim to promote the continuous improvement of China’s elderly care system and provide important empirical evidence for the formulation of relevant policies.