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金融研究  2025, Vol. 538 Issue (4): 1-20    
  本期目录 | 过刊浏览 | 高级检索 |
中央银行通货膨胀预期管理有效性评估——基于文本通货膨胀预期指数的研究
郭豫媚, 王航, 郭田勇, 郭俊杰
中央财经大学金融学院,北京 102206
The Assessment of Central Bank's Inflation Expectation Management Effectiveness: A Study Based on Textual Inflation Expectation Indexes
GUO Yumei, WANG Hang, GUO Tianyong, GUO Junjie
School of Finance, Central University of Finance and Economics
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摘要 全面系统地评估通货膨胀预期管理的有效性,对于健全预期管理机制、实施科学的预期管理,具有重要的理论与现实意义。已有研究对于中国央行通货膨胀预期管理有效性的评估主要是整体性评估,对预期管理效果影响因素的讨论仍有待深入。本文首先构建了一个包含央行预期引导的理论模型,从理论上分析了政策空间、不确定性和市场预测能力对央行预期管理效果的影响。在此基础上,本文使用中国宏观经济研究报告文本,采用机器学习和文本分析方法构建了周度频率的市场通货膨胀预期指数开展实证分析。研究发现,中国央行通货膨胀预期能够起到引导市场通货膨胀预期的作用,并且在政策空间缩小、不确定性上升和市场预测能力不足的情况下中央银行通货膨胀预期管理能够发挥更大的作用。本文研究为系统评估中国通货膨胀预期管理有效性提供了基础指标、理论支撑和经验证据,并为健全预期管理机制提供了政策建议。
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郭豫媚
王航
郭田勇
郭俊杰
关键词:  预期管理  通货膨胀预期  央行沟通  机器学习    
Summary:  Enhancing expectation management is key to refining the modern monetary policy framework with Chinese characteristics. The Third Plenary Session of the 20th CPC Central Committee explicitly emphasized the need to “improve the expectation management mechanism”. Inflation expectations exert a profound influence on the decision-making of economic agents and the dynamics of inflation, playing a pivotal role in the central bank's efforts to guide market expectations through policy communication. Enhancing the central bank's ability to manage inflation expectations is of great significance for achieving price stability and economic growth. However, existing indexes of inflation expectations often suffer from low frequency and limited sample sizes, restricting their ability to provide granular assessments or facilitate heterogeneous analysis. These limitations hinder the identification of critical areas for improving expectation management effectiveness.
This paper employs theoretical modeling, text analysis, and empirical analysis to investigate the effectiveness of the People's Bank of China (PBC) in guiding market inflation expectations and the factors influencing this process. First, this paper constructs a theoretical model incorporating central bank inflation expectations and the formation of market inflation expectations, demonstrating the guiding role of the central bank in the formation of market inflation expectations and the factors influencing the effectiveness of the central bank's inflation expectation management. Next, based on over 60,000 Chinese macroeconomic research reports, this paper employs a combination of machine learning and text analysis to construct a weekly market inflation expectation index. Similarly, it uses central bank communication texts to construct a central bank inflation expectation index. Finally, this paper conducts empirical analysis using central bank inflation expectation indexes and market inflation expectation indexes to explore the guiding effect of central bank inflation expectations on market inflation expectations and tests whether the factors identified in the theoretical model influence the effectiveness of the People's Bank of China's inflation expectation management.
The main findings of this paper are as follows. First, the People's Bank of China's inflation expectation management can guide market inflation expectations, and this conclusion holds under various endogeneity tests and robustness tests. Second, policy space, uncertainty, and market forecasting ability all significantly influence the effectiveness of the People's Bank of China's inflation expectation management, and this conclusion is supported by both the theoretical model and empirical analysis. Specifically, the effectiveness of the central bank's inflation expectation management is better when policy space is limited, uncertainty is high, and market forecasting ability is weak. This is because, under such circumstances, the market has a higher demand for central bank information and relies more heavily on the central bank's inflation expectations.
This study provides important policy implications for the central bank to establish a sound expectation management mechanism and implement effective expectation management. First, fully leverage the coordinated role of expectation management and traditional monetary policy to enhance policy effectiveness. Second, closely align expectation management with macroeconomic and market conditions, implementing appropriate discretionary measures. Third, improve market expectation monitoring and feedback mechanisms to enhance the effectiveness of expectation management.
This paper contributes to the literature in two ways. First, by utilizing textual data and machine learning techniques, it constructs a novel index for measuring inflation expectations in China. This index, derived from macroeconomic research reports, provides a high-frequency, information-rich, and continuously updated measure, addressing the limitations of existing low-frequency and small-sample indexes. As one of the first attempts to develop a market inflation expectation index through textual big data, this study offers a crucial foundation for comprehensive and systematic assessments of the central bank's expectation management. Second, this paper extends the understanding of inflation expectation management by identifying key factors that influence its effectiveness, both theoretically and empirically. While previous studies have often been constrained by limited data availability, making it difficult to explore the drivers of effective expectation management, this research overcomes these challenges through high-frequency indexes and extensive heterogeneous analysis. The findings highlight the significant role of policy space, uncertainty, and market forecasting capabilities, offering valuable insights for enhancing the design and implementation of expectation management strategies within the broader monetary policy framework.
Keywords:  Expectation Management    Inflation Expectations    Central Bank Communication    Machine Learning
JEL分类号:  E58   E50   E31  
基金资助: * 本文感谢国家自然科学基金项目(72273159,72103216,72342033)、中央高校基本科研业务费专项资金和中央财经大学科研创新团队支持计划的资助。感谢匿名审稿人的宝贵意见,文责自负。
通讯作者:  郭俊杰,经济学博士,副教授,中央财经大学金融学院,E-mail: junjguo@cufe.edu.cn.   
作者简介:  郭豫媚,经济学博士,副教授,中央财经大学金融学院,E-mail: guoyumei@cufe.edu.cn.
王 航,博士研究生,中央财经大学金融学院,E-mail: wanghang@email.cufe.edu.cn.
郭田勇,经济学博士,教授,中央财经大学金融学院,E-mail: gtyong@263.net.
引用本文:    
郭豫媚, 王航, 郭田勇, 郭俊杰. 中央银行通货膨胀预期管理有效性评估——基于文本通货膨胀预期指数的研究[J]. 金融研究, 2025, 538(4): 1-20.
GUO Yumei, WANG Hang, GUO Tianyong, GUO Junjie. The Assessment of Central Bank's Inflation Expectation Management Effectiveness: A Study Based on Textual Inflation Expectation Indexes. Journal of Financial Research, 2025, 538(4): 1-20.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2025/V538/I4/1
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