We investigate the cross-sectional factors of Chinese corporate bond returns via the reducedrank regression analysis (RRA) proposed by He et al. (2022). We collect 37 individual bond characteristics in the extant literature using a new dataset and construct 40 factor portfolios. Empirically, we find that the four-factor models created by RRA outperform the traditional factor models, PCA, and PLS factor models, both in-sample and out-of-sample. Among the 40 factors, the bond market factor is the most substantial predictor of future bond returns. In contrast, other factors provide limited incremental information for the cross-sectional pricing. Therefore, it is necessary to find more new bond factors. We further find that stock market anomalies do not improve the explanatory power of the RRA factor models. In particular, stock market anomalies can only partially explain the systematic part of bond returns in the RRA framework and have almost no explanatory power for the idiosyncratic component.

We investigate the relationship between ESG rating divergence and stock returns from an investor’s perspective, to explore the impact of inconsistency among ESG rating agencies on the capital market. We construct ESG rating divergence data using ratings from three prominent ESG rating agencies in China. Our study is based on 54,679 company-quarter observations from 2018 to 2022, which covers 4,377 Chinese listed companies. Our findings demonstrate a significant negative impact of ESG rating divergence on stock returns, which we validate through a series of robustness tests and endogenous analyses. Notably, we find that investors’ expectations mediate the relationship between ESG rating divergence and stock returns. Further analyses show that only the divergence in social ratings have a significant inhibitory effect on stock returns. In addition, ESG rating divergence significantly impedes subsequent average ESG ratings. The adverse relationship between ESG rating divergence and stock returns is particularly pronounced in non-heavy pollution companies, non-state-owned companies, and companies with lower external attention.

This paper explores the relationship between ESG rating disagreement and the stock price crash risk. Using 2011-2020 Chinese A-share listed companies in Shanghai and Shenzhen as research sample, the empirical test results show that ESG rating disagreement significantly increases the stock price crash risk. The mechanism tests find that ESG rating disagreement influences the stock price crash risk by undermining corporate information transparency and increasing the level of investor sentiment. The findings of this paper reveal the potential negative economic consequences of ESG rating disagreement and enrich the research on the influencing factors of stock price crash risk, which contribute to the prevention of possible financial risk and the sustainable development.

Using the firm-level data of the Chinese industrial sector from 1998 to 2010, this study investigates the impact of the previous environmental protection experience of prefecture-level Communist Party secretaries on the COD regulation within the secretaries’ respective jurisdictions. The study finds that the secretaries’ previous environmental protection experience has reduced the COD discharge intensity. The duration of the previous environmental protection experience is selected as an instrumental variable and the endogeneity is further addressed; the research conclusion remains unchanged. However, this negative impact only lasts for two years and presents an unclear long-term impact. The negative effect on COD discharge intensity caused by the previous environmental protection experience is affected by the mandatory regulation pressure from the central government and the overall polluting density of the sub-sectors. Secretaries with previous environmental protection experience do not reduce the COD discharge intensity by using the punishment mechanism of increasing sewage charges. The secretaries, instead, encourage enterprises to use clean production technology, save water resources, and reduce the produced COD level. Also, the secretaries place an emphasis on the treatment of wastewater pollutants, thus reducing the COD discharge intensity. The conclusions of this study can provide decisionmaking reference for the selection and training of local officials, with the goal of environmental regulation.

政府补贴是国家进行宏观调控的重要手段,具有克服市场失灵、激励企业创新及引导产业升级转型等作用。然而,由于政府补贴政策制定及其执行过程中普遍存在重国企轻民企的现象,导致我国政府补贴呈现出非竞争中性的特点。鉴于此,文章以公平竞争审查制度在我国的落地推进为契机,研究了公平竞争审查这一“事前规制”形式的竞争政策是否能够有效缓解政府补贴的非竞争中性问题。研究发现,在政府实施公平竞争审查后,国有企业与民营企业在政府补贴获取上 的差异显著缩小,政府补贴的竞争中性原则更好地得到了实现。同时,文章从政策制定机关推进公平竞争审查的内在驱动力强度以及企业自身对政府补贴的竞争意愿强弱两个角度,进一步探究了公平竞争审查对政府补贴竞争中性影响的差异,发现小微企业在地区经济中的重要性程度、政府资金在企业研发经费中占比高低、行业垄断性与儒家文化等因素会影响公平竞争审查制度在缓解政府补贴非竞争中性问题上的实施效果。文章的研究对优化我国政府补贴政策向竞争中性转型具有重要的借鉴意义。

我国人口老龄化的加速带来劳动年龄人口持续减少,就业者与岗位匹配的结构性问题更加突出。就业匹配质量低意味着个人和社会的人力资本不能被充分利用,会给个人和社会带来生产力损失。提升就业匹配质量是缓解我国劳动力市场结构性矛盾,提高就业质量的重要途径,社会网络是劳动者求职过程中的重要资源。文章首先通过理论模型分析社会网络对就业匹配质量的影响机制,然后使用中国家庭追踪调查（CFPS）2018 年数据对农村背景人群进行实证研究,发现社会网络有助于降低过度教育概率,提高人力资本配置效率,这一结论在以是否有家谱或族谱和春节期间来拜访的亲友家数作为工具变量的估计结果中仍然稳健。机制分析表明,社会网络主要通过信息传递和提升人际信任度作用于就业匹配质量。文章认为,减少职业搜寻过程中的信息不对称,降低搜寻摩擦对于提高就业匹配质量和缓解结构性矛盾都具有重要作用。

We investigate the dynamic extremal connectedness of sectors within the Chinese stock market conditional on exogenous extreme risk through multivariate extreme value regression. To proxy the exogenous extreme risk, we independently consider market volatility-based measures and policy uncertainty-based measures. We discover that market volatility-based measures have a stronger influence than policy uncertainty-based measures on the extremal connectedness of sectors. The oil volatility index is the most influential on extremal connectedness, and the energy sector plays a direct role in transmitting exogenous extreme risk. Our findings provide new insights into understanding the drivers of systematic and idiosyncratic contagion.

Combining daily personnel records of an unlisted manufacturer with stock market data, we find that market overnight returns negatively predicts same-day worker output. The effect is greater on Mondays and extreme overnights. Analysis suggests that the stock market attracts (discourages) public attention when the overnight returns are extremely positive (negative), consistent with humans’ natural tendency of incorporating good news while discounting bad news. As a result, employees at work are disproportionally distracted by positive overnight returns, leading to reduced output. Additional evidence suggests that our results can hardly be explained with alternative distraction events or workers’ stock wealth concerns. This study reveals a novel channel through which the financial market shapes labor supply.

This paper examines the effects of digital finance and corporate stock price crash risk, and the underlying mechanisms, using panel data from Chinese A-share listed companies between 2012 and 2021. Specifically, we focus on whether digital transformation and environmental, social, and governance (ESG) performance are intermediary channels through which digital finance mitigates corporate stock price crash risk. By employing panel regression and mediation effect models, we demonstrate that digital finance significantly reduces corporate stock price crash risk. This conclusion remains robust after a series of robustness tests, including the replacement of core explanatory variables, lagging digital finance by one period, using alternative dependent variables, applying the instrumental variables method, and system GMM estimation. More importantly, we find that digital finance curbs stock price crash risk by enhancing digital transformation and ESG performance. In addition, we reveal that digital finance has heterogeneous effects on corporate stock price crash risk. The inhibitory effect of digital finance on stock price crash risk is more pronounced in the central and western regions of China and for companies with lower internal control levels, higher information transparency, and higher financing constraints.

Despite the dominance of retail investors in the Chinese stock market, there’s a conspicuous absence of price momentum in weekly and monthly returns. This study uncovers the presence of price momentum in daily returns and, through a systematic analysis of trading heterogeneity among investors, links daily momentum to the attention and trading activities of new investors—a phenomenon particularly signiffcant in emerging stock markets. Furthermore, our ffndings indicate the existence of daily price momentum in various other emerging markets, contrasting with its relative scarcity in developed ones.