This paper examines the Urban Construction Investment Bond (UCIB) as a tradable product in the financial market and a financial tool for local government in China. The development of this financial product is contextualised in infrastructure finance and local government debt. The creation of UCIB helps finance infrastructure investment and potentially reveal the relative risks through the secondary market. The spatial distribution of UCIB demonstrates different relative risks of this financial instrument in local conditions. The government uses this financial tool to bridge the emerging capital market and infrastructure finance, and the Chinese financial market now treats UCIB as an emerging asset class. The development of UCIB has sped up the pace of financialisation in China. Although relative risks help investors choose different UCIBs, the overall risk of UCIB cannot be ignored.

当前，绿色金融备受关注，然而该领域的基础理论非常薄弱。根据经济学的一般原理，由于污染的外部性问题，环保的主要力量应当是公共部门而非金融系统。然而为什么越来越多的国家选择发展绿色金融？其背后的经济学原理是什么？深入探讨这些问题，是有效制定政策、构建绿色金融理论体系的基础。基于跨国面板数据的分析表明，绿色金融对经济增长具有显著的促进效应，表现出与公共部门环保投入的显著差异。在此基础上，本文构建基于经济增长框架的绿色金融理论模型，对经验事实给出了理论解释。模型指出，绿色金融的风险分担功能使其具有独特的长期增长效应，是经济发展高级阶段的必然选择；而绿色金融政策与绿色财政政策的协调配合是实现高质量发展的有效手段。本文从理论层面回答了“我们为什么需要绿色金融？”的问题，为绿色金融的经济学理论发展和政策分析提供了可借鉴的框架

发展绿色金融已经成为新时代中国一项重要的国家战略，但这一领域的理论研究并不深入，研究“多而不精”、理论基础模糊、理论框架欠缺。本文通过系统性地梳理绿色金融的理论渊源、学说脉络和前沿趋势，提出绿色金融的核心议题是以金融手段促进经济的绿色发展。这一核心议题在宏观层面直接关系到经济的高质量发展，而在微观领域涉及金融机构和投资者的社会责任理论。在此基础上，本文提出金融的“绿色功能”假说，并给出了一个基于一般均衡理论的“绿色金融的经济学基准模型”。这一基准模型有效地连接了绿色金融的微观运行机制和宏观经济效应，不仅能够实现多种扩展、用于政策分析，而且从理论层面指明了未来研究的方向、为绿色金融理论体系的构建提供了一种思路。

This paper examines whether a government can play an important role in determining a firm’s related party transactions associated with tunnelling. Through the lens of political turnover in 31 Chinese provinces for 2000-2018, we show that political turnover is negatively associated with state-owned enterprises’ (SOEs’) related party transactions (RPTs) but has no impact on non-SOEs’. Political turnover engenders uncertainty to SOEs, which curtail tunnelling-related RPTs. We identify two channels – corruption and policy-induced RPTs – leading political turnover to reduce RPTs. Corruption RPTs fall more significantly in highly corrupt provinces and before the 2012 anti-corruption campaign. Policy RPTs of SOEs with delisting risk and in high public debt provinces decrease considerably. Financially constrained firms, older officials and within-province appointments diminish the impact of political turnover on RPTs. On average, the fall in RPTs starts a year before a political turnover and ends a year after.

Whether responsible investing reduces portfolio risk remains open to discussion. We study the relationship between ESG performance and downside risk at fund level in the Chinese equity mutual fund market. We find that fund ESG performance is positively associated with fund downside risk during the period between July 2018 and March 2021, and that the positive relationship weakens during the COVID-19 pandemic. We propose three channels through which fund ESG performance could affect fund downside risk: (i) the firm channel in which the risk-mitigation effect of portfolio firms’ good ESG practices could be manifested at fund level, (ii) the diversification channel in which the portfolio concentration of high ESG-rated funds could amplify fund downside risk, and (iii) the flow channel in which fund ESG performance may attract greater investor flows that could reduce fund downside risk. We show evidence that the observed time-varying relationship between fund ESG performance and downside risk is driven by the relative force of the three channels.

We study how professional fund managers’ growth expectations affect the actions they take with respect to equity investment and in turn the effects on prices. Using novel data on China’s mutual fund managers’growth expectations, we show that pessimistic managers decrease equity allocations and shift away from more-cyclical stocks. We identify a strong short-run causal effect of growth expectations on stock returns, despite statistically significant delays in price discovery from short-sale constraints. Finally, we find that an earnings-based measure of price informativeness is increasing in fund investment.

Over the last decade, China’s P2P lending industry has been seen as an important credit source but it has recently suffered from a wave of bankruptcies. Using 126,090 P2P loan deals from RenRen Dai, one of the biggest online P2P websites in China, this paper attempts to predict credit default probabilities for P2P lending by implementing machine-learning techniques. More specifically, thisstudy proposes a stacking ensemble machine-learning model to assess credit default risk for P2P lending platforms. A Max-Relevance and Min-Redundancy (MRMR) method is used for feature selection and then irrelevant features are eliminated by using k-means clustering method. Finally, the stacking ensemble model is performed to produce accurate and stable predictions in the feature subset. Experimental results show that stacking ensemble model yields high performance, not only in prediction accuracy but also in precision and recall. In comparison to single classifiers, the stacking ensemble machine-learning model has a minimum error rate and provides more accurate credit default risk prediction. The results also confirm the efficiency of the proposed stacking ensemble model through the area under the ROC curve.

Can bank competition help attenuate the prevalence of zombie firms? Motivated by a stylized model, this paper studies the effect of bank competition on the formation of zombie firms in two stages: the formation of distressed firms and distressed firms obtaining zombie lending. Using China’s 2009 bank entry deregulation as a quasi-natural experiment, the paper finds that bank competition lowers the probability of the formation of distressed firms, while it increases the probability of distressed firms obtaining zombie lending. Overall, bank competition decreases the formation of zombie firms. In addition, the findings show that a higher ex ante proportion of bad loans and higher probability of bad loan recovery will lead to a higher probability of distressed firms receiving zombie lending. Both factors encourage banks to sustain lending to distressed firms to keep them alive and to gamble that those firms may recover in the future.

In this paper, we leverage the bank governance reform in China as a laboratory to explore the impact of the banking governance system on lending activities. Specifically, a well-functioning governance system does not improve the bank’s selection abilities due to the regulation constraints. However, a good governance system enhances the bank’s monitoring abilities. Finally, a well-governance bank needs more independent directors on the board, lower shareholdings of the top 1 shareholder, the government as the top 1 shareholder, and fewer risk management committee meetings. Therefore, this paper sheds light on banking governance and has important policy implications for bank sectors in the transition economy.

Research into asset pricing anomalies in the China A-share market is hampered given the short time series of available returns. Even when average excess returns on candidate factor portfolios are economically sizeable, conventional portfolio sorting methods lack statistical power. We apply an efficient sorting procedure that combines firm characteristics with the covariance matrix. For the China A-share market, we find that the efficient sorting procedure doubles the t-statistics compared to conventional portfolio sorts, leading to nine instead of three significant anomalies over the postreform period from 2008 to 2020. We find significant size, value, low-risk, and returns-based anomalies. While portfolio characteristics differ between sorting methods, we find that efficient sorting portfolios highly correlate with equally weighted portfolios and capture the same underlying anomaly.