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Accès ouvert déclaré 2018 preprint

Monetary Policy Communication of the Bank of Japan: Computational Text Analysis

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In this study, we empirically examine the effects of the Bank of Japan (BOJ)'s communications through its meeting minutes on the financial markets, especially during Mr. Kuroda's administration from April 2013 to September 2017. Using computational linguistic models and the Latent Dirichlet Allocation, we quantify the contents of the BOJ minutes and extract topics form these minutes, including the bank's historical monetary policy and policymakers' views on current economic conditions. The empirical results suggest that a relationship exists between the estimated topics and the market reactions on the days on which the minutes are released. Although the market paid attention to the monetary policy description in the minutes in the early period of the introduction of quantitative and qualitative monetary easing (QQE), the significance of monetary policy information under the October 2014 expansion of the QQE on financial markets faded. In contrast, information on fund-provisioning measures to support Japanese companies' activities, including a negative interest rate policy, induced a decline in the stock market. We found that the market pays attention to meeting members' opinions on current economic conditions.

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Les sujets associés

Computational and Text Analysis MethodsAdvanced Text Analysis TechniquesTopic Modeling

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