Unlike central banks in developed economies, the People's Bank of China (PBC) does not explicitly use forward guidance but rather provides explanatory information about monetary policy. The PBC has mainly used quarterly written reports and non-periodic oral channels to communication with the market, but there are significant differences in the institutional objectives and textual structures of these two types of communication. This paper investigates the real effects of the PBC's narrative on the macroeconomy. Our results show that the PBC's policy-related information can also guide inflation expectations and have a direct impact on the macroeconomy. The different macroeconomic effects between oral communication and written communication lies in their differences in timeliness, semantic complexity and ambiguity. Meanwhile, such explanatory communication can help the public understand policy stance, resist the negative impact of economic policy uncertainty, and thereby enhance monetary policy effectiveness. Finally, we find that oral communication has an increasingly significant impact on inflation expectations through variance decomposition.

This paper investigates the premium of ambiguous central bank communication with diversified policy stances on the cross-sectional asset prices. Distinguishing different inclinations (dovish, neutral and hawkish) in the communications of the People's Bank of China (PBC) governors through a field-specific lexicon approach, we construct the ambiguous communication index (ACI) based on the textual methodology. We find that ambiguous communication makes it difficult to predict policy stance and increases policy uncertainty, thus the ACI earns a significant negative premium in the cross-section of asset pricing. This paper contributes to the literature on policy uncertainty by proposing a new supplementary perspective, a feasible measure and empirical evidence of ambiguous communication. Furthermore, this contribution extends to the literature on policy communication by distinguishing the statistically and economically significant premium linked to ambiguous communication.

Summary Unlike the central banks of most developed economies, the People's Bank of China (PBC) does not release its macroeconomic forecasts to the public but instead carries out narrative communication. We apply a hurdle distributed multinomial regression to PBC communication texts in real time, addressing the ultrahigh dimensionality, sparsity, and look‐ahead biases. In addition, we embed text‐based indices into mixed‐data sampling (MIDAS)‐type models and conduct forecast combinations for prediction. Our results argue that the predictive information from communication texts improves the real‐time out‐of‐sample prediction performance. We connect textual analysis and real‐time macroeconomic projection, providing new insights into the value of central bank communication.

当前我国经济发展面临需求收缩、供给冲击、预期转弱三重压力.其中,供给冲击既有全球通胀带来的价格成本上涨和劳动力生产要素短缺,也有逆全球化导致的供应链断裂风险.这些冲击极大地限制企业生产能力,进而降低整体产出和消费,最终导致税收收入下降.基于此,文章构造包含农业部门、能源部门、工业部门和服务部门四部门的动态可计算一般均衡模型(DCGE),以 2022 年广东省经济状况为基础模拟分析供给冲击对税收收入的影响.模型测算表明,广东省税收收入在供给冲击下将减少3.447%.如果供给冲击持续,在其他条件不变的情况下,2027 年税收收入降幅将达到 15.548%.最后,从能源结构、产业链安全和制造业智能化改造等方面提出应对供给冲击的政策建议.

The People's Bank of China (PBC) now frequently uses communication as a policy tool. Whether its words are consistent with its deeds is important for the public to understand the PBC's complex behavior. In this paper, we employ a supervised learning model to construct monetary policy (MP) and economic outlook (EC) communication indices based on the outlook section of quarterly China Monetary Policy Reports (MPRs). We find that the PBC not only adjusts its interventions according to the corresponding economic situation, but also takes into account the information released in the previous outlook section, which indicates its consistency in words and deeds. Using a time-varying parameter model, we further find that the PBC's consistency of words and deeds has made progress over time. The PBC tends to be more consistent in words and deeds under higher uncertainty, and the improvement of such consistency can significantly decrease disagreement about inflation expectations. An additional analysis shows that the full text of MPRs can help predict future monetary policies on a longer time horizon.

Financial market is a key channel in the monetary policy transmission mechanism. Investigating the stock market effect of information communication, a new monetary policy tool, is of great significance for understanding the effectiveness of monetary policy and maintaining financial stability. Among various communication methods, the verbal communication of the governor of the central bank is the most timely and authoritative. This article uses a supervised dictionary analysis method to conduct all oral communication incidents of the governor of the People’s Bank of China from January 2003 to February 2019. The research results show that the stock market effect of central bank governors’ information communication is mainly reflected in the impact of intra-day price fluctuations and yield volatility, and this volatility effect has multiple levels of heterogeneity. From the perspective of communication content, compared with economic situation communication, monetary policy communication has a more significant impact on the volatility of stock market returns. From the perspective of communication, communication about monetary policy tightening tends to cause greater volatility than communication with loose tendencies. From the perspective of timeliness and pertinence, central bank communication has anticipatory management functions, but there is still obvious room for improvement, especially on the day of communication, when the volatility of stock prices is intensified and the impact is less than from actual intervention.

我国经济发展面临人口红利消失、老龄化趋势加快的现实问题,工业机器人等自动化技术能够应对由此带来的劳动力短缺,但也同时引发了公众对工业机器人冲击劳动力市场的广泛担忧.本文基于2019年800家广东企业调查数据,给出了工业机器人应用影响企业用工决策的微观层面证据.研究表明,相比没有应用工业机器人的企业,应用工业机器人的企业拥有更大的用人规模、具有更高的扩大用工意愿.这与工业机器人能扩大企业生产规模、提高企业生产效率、产生相关技术岗位需求等作用机制有关,同时也受到劳动替代效应阶段性特征的影响.异质性分析显示,非制造业企业、生产链上游企业和珠三角地区企业引入工业机器人的就业带动能力更强.本文研究结论表明,应该推动企业应用工业机器人进行智能化改造,从而促进就业水平,推动经济高质量发展.

The loose monetary policy has not translated into actual credit increments, and the real investment rate has declined. This paper extracts the level of policy uncertainty perception from enterprise management analysis and discussion based on text analysis methods to identify the investment intention of enterprises. It is found that enterprise uncertainty perception can weaken corporate investment intention, thus hindering the promotion of loose monetary policy on investment. On the one hand, this paper verifies that uncertainty perception can weaken the effectiveness of monetary policy implementation at the micro level of enterprises; On the other hand, this paper finds that merely being based on the financing constraint theory may not be able to explain the capital investment behavior of Chinese companies. It also requires examining the investment intentions of enterprises themselves, enriching the research conclusions of enterprise investment theory.

This paper uses machine learning method to construct quantitative investment strategy based on news.First,we use iterative estimation to improve the SESTM（sentiment extraction via screening and topic modeling）,and Monte Carlo simulation verifies its advantages in the accuracy of sentiment extraction.Second,we apply it on over 1 million news articles related to the CSI 300 index stocks from 2013 to 2020,and then construct a stock investment strategy.Our results show that,the trading strategy based on the sentiment can obtain net excess returns that is far exceeding the market return,and the iterative estimation can improve its performance with timely training set in the period with higher market volatility.Even in the face of emergencies such as COVID-19,our strategy can still obtain benefits after including more timely news.This paper demonstrates that the economic intuition behind the strategy premium is that news sentiment can predict stock returns,and that there are differences in the speed of information absorption for different assets.The strategy in this paper performs better in stocks with small market capitalization,low turnover,and low beta.It is because of the slow absorption of news in these stocks,which provides arbitrage space for our machine learning strategies based on news sentiment.

China's stock market is a policy-driven market, which is eager to get any signals about the monetary policy. Due to its limited independence, the People’s Bank of China (PBC) prefer to release ambiguous information with multiple sentiments at the single communication to the public. This paper explores the cross-sectional asset pricing implications of the ambiguity of central bank communication in China. By distinguishing different sentiments for each communication event with a field-specific lexicon, we obtain the time series of the probabilities that the policy stance of the PBC is dovish, neutral, or hawkish. Using these three probabilities, we develop a measurement for the ambiguity of PBC communication. The main findings indicate that our ambiguity index earns a significant negative risk premium, even after controlling other textual policy uncertainty indexes. This paper contributes to the literature by investigating the ambiguity of central bank communication with novel empirical evidence that ambiguity is an economically important factor in the cross-section of asset returns.

宏观经济预测是宏观调控精准施策的重要前提,一直以来是方法论研究的前沿议题.随着央行沟通在预期管理中的频繁使用,其传达的信息受到普遍关注,本文致力于利用央行沟通文本进行宏观经济预测.首先生成符合央行沟通表达习惯的专用词典用于构建完整语料库,继而利用栅栏分布式多项回归模型从高维和稀疏的语料库中提取有效信息,得到央行沟通测度.基于152个指标构建基准动态因子模型,进一步引入央行沟通测度作为新的预测因子,结果显示央行沟通测度有助于提升模型样本内拟合效果.考察样本外预测效果,在不包括预测变量历史信息时,央行沟通测度能够使得不同期限的预测精度提高6.80％-16.65％;包含预测变量历史信息时则出现分化,在期限较短时,央行沟通未能提升预测精度,这是因为主要沟通信息与预测变量历史信息重叠;当期限较长时,预测精度有所提升,表明沟通中少量的前瞻性指引具有持续的预测能力.本文研究从预测角度验证了中国央行沟通在预期管理中的作用,并为进一步利用非结构化的文本大数据提升中国宏观经济实时预测能力提供了新思路.

信息沟通有助于公众理解和预测货币政策的实际干预,进而提高货币政策有效性.研究中国人民银行的信息沟通对实际政策干预的预测能力需要解决沟通文本的测度问题,同时考虑实际政策干预多工具并用的复杂性.基于此,本文通过文本分析方法提取《货币政策执行报告》的信息,进而考察央行沟通对于货币政策实际干预的预测能力.研究表明,整体而言,市场对中国人民银行"听其言"有助于"观其行".具体来看,央行沟通对于直接可控的基准利率和存款准备金率具有持续的预测能力,但对于市场利率的预测能力较差,对于M2增长率的预测甚至存在方向不一致的情况.

在商事制度改革的推动下,我国市场主体数量呈现快速增长态势,加之各种新模式、新业态的持续涌现,使得市场监管面临着前所未有的挑战.党的十九届四中全会提出坚持和完善共建共治共享的社会治理制度,"政府监管、企业自治、行业自律、社会监督"的多元共治市场监管模式成为这一理论的重要实践.文章首先从基本逻辑、关键主体和边界性三个方面阐述市场监管多元共治的理论基础;其次,总结市场监管多元共治的中国实践,尤其是东莞的先行探索经验;最后,从实施机制、"互联网+"、大数据以及人工智能等角度探讨了多元共治的深化改革方向.

本文以2003年1月至2018年8月中国央行行长所有口头沟通内容为文本基础,生成央行行长沟通这一特定领域的专用词典,进而使用短语数量加权的方法分别构造货币政策沟通指数和经济形势沟通指数.其中,货币政策沟通指数与实际基准利率和存款准备金率的变动具有高度相关性,而经济形势沟通指数可以作为经济基本面的信号器.进一步,本文基于监督学习方法,通过训练子样本词典得到具有倾向的短语及其概率分布,利用文本分类器对新的沟通文本进行自动分类,最终对新样本进行指数计算.子样本的监督学习与全样本信息具有一致的结果,表明本文的央行行长口头沟通测度具有可复制性和可延展性.