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.

The economic institutionalist literature often suggests that sub-optimal institutional arrangements impart unique distortions in China, and excessive corporate debt is a symptom of this condition. However, lax monetary policies after the global financial crisis, and specifically, quantitative easing have led to concerns about debt bubbles under a wide range of institutional regimes. This study draws on data from Chinese listed firms, supplemented by numerous macroeconomic control variables, to isolate the effect of international capital flows from other drivers of firm leverage. We conclude that the rise in, and distribution of, Chinese corporate debt can partly be as-cribed to the effects of monetary policy outside of China and that Chinese institutional features amplify these effects. Whilst Chinese firms are affected by developments in the global financial ecosystem, domestic institutional realities and distortions may unevenly add their own particular effects, providing further support for and extending the variegated capitalism literature.

A unique natural experiment in China – the city-level staggered introduction of admin-istrative approval centers (AAC) – reduces bank loan processing times by substantially speeding up the process of registering collateral without affecting credit decisions. Fol-lowing the establishment of an AAC, firms significantly reduce their cash holdings. State-owned enterprises are less affected. Cash flow sensitivity of cash holdings de-creases, as does the cash flow sensitivity of investment. The share of short-term debt increases, while inventory holdings and reliance on trade credit decrease. Defaults also decrease. These results suggest that timely access to credit has important implications on firms’ financial management.

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.

This paper investigates the price overreaction during the initial continuous trading period of the Chinese corn futures market. Using a dynamic modeling algorithm, we identify the overreaction behavior of intraday high-frequency (1 min and 3 min) prices during the first session of daytime trading. The results indicate that the overreaction hypothesis is confirmed for the daytime prices of the Chinese corn futures market. We also find a noticeable reduction in overreaction following the introduction of night trading and this decline appears to diminish over time. Furthermore, this paper conducts an overreaction trading strategy to assess traders’ returns, revealing a slight decline in average return after the introduction of night trading. This study provides valuable insights and recommendations for exchanges and regulators in monitoring overreaction and formulating effective policies to address it.

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.

This paper revisits the default-crash risk relation in the context of China. We find that firms with higher default risk have lower stock price crash risk both in monthly and yearly frequencies. To identify the causal effect, we use the first-ever default event in China’s onshore bond market in 2014 as an exogenous shock to the strength of implicit guarantees. The negative relation arises from the active involvement of the government before 2014 and creditors after 2014 in corporate governance. Consistent with the external scrutiny mechanism, the impact of default risk on stock price crashes is stronger in situations in which creditors are more likely to engage in active monitoring (i.e., firms with higher liquidation costs, lower liquidation value, and higher levels of information asymmetry), with these effects primarily observed in the post-2014 period. Overall, our study highlights the role of the “invisible hand” in the absence of the “visible hand.”

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。

The aging population is intensifying, and solving the problem of elderly care is urgent. This article is based on CHFS (2019) survey data, and empirical research has found that commercial pension insurance significantly promotes households' allocation of risky financial assets. The mechanism is tested using household risk perception and investment risk preference as mediating variables. In addition, through heterogeneity testing, it was found that the positive effect of commercial pension insurance on the allocation of risky financial assets is more significant in rural households with household registration, two sets of housing, and households in the northeast.