Abstract: In this paper, we transform words from China Monetary Policy Report into quantitative indicators based on the decoding algorithm. We provide a detailed description of the judgment of the monetary policy phases, the identification of significant signal words, the determination of the weights of the signal words and the calculation of the indicator to make our algorithm comprehensive, robust and replicable. The sensitivity analysis shows that: (1) the indicator becomes smoother when we include the signal words describing the foreign economic situations; (2) changing the weights of the signal words doesn’t have much influence upon the final indicator; (3) changing the number of signal words will not change the direction of the monetary policy but will influence the intensity significantly; (4) changing the judgment of controversial monetary policy phases influences the chosen signal words but has little influence upon the final result. The further spectral analysis upon the monetary instruments shows that the spectral density of central bank communication is distributed more uniformly among different frequency domains compared with quantitative and pricing instruments, which reflects its characteristic of reacting fast and emphasizing the long-term continuity of policies.

Key words: Central Bank Communication, Measurement, Wording, Spectral Analysis