Anticipatory management is a critical tool in macroeconomic regulation, with central bank communication serving as the primary policy instrument for such management. This study examines the micro-level effects of central bank communication, focusing on its impact on corporate risk levels.
By constructing a theoretical model, this paper analyzes the underlying mechanisms through which central bank communication influences corporate risk-taking levels. Building upon this foundation, an empirical examination is conducted using quarterly unbalanced panel data from listed companies spanning 2003 to 2020. The findings reveal a significant U-shaped relationship between the optimistic signals in central bank communication and corporate risk-taking levels.
Furthermore, this U-shaped relationship is weakened when there is inconsistency between the central bank's words and actions, whereas it's enhanced by a high degree of policy transparency. In addition, when comparing normal periods with crisis periods, the analysis finds that during public health events, the relationship between the sentiment expressed in central bank communication and corporate risk-taking levels transitions from a U-shaped pattern to a significant positive correlation. This suggests that central bank communication during crisis periods may yield more effective anticipatory management outcomes.
Based on the research findings, this paper proposes four policy suggestions. Firstly, to maintain an appropriate level of corporate risk-taking, the central bank should adjust the tone and wording of its communication. Secondly, attention should be paid to the coordination of regulatory measures with unconventional monetary policies. Thirdly, after issuing signals, the central bank should ensure that its subsequent policy actions align with its verbal communications. Fourthly, in the aftermath of economic disruptions caused by public health events, greater emphasis should be placed on leveraging anticipatory management policies.
Key words
Central Bank Communication /
Risk-Taking /
Signal Effect /
Text Mining
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