Abstract
In this paper, we will analyze monetary policy of the Bank of Japan, the central bank of Japan, just after the sales tax hike held in April 2014, through November 2014. The period matches the Japan’s turning point to the recession owing to the sales tax hike in April 2014. With the Abe second Cabinet which started in December 2012, the Bank set the “price stability target” at 2 percent. We analyzed the Monetary Policy Meeting minutes by text mining technologies. Especially we conducted a topic extraction using the Latent Dirichlet Allocation model from the Meeting minutes. The extracted topics clearly showed the impact of the sale tax hike. The biggest topic was the economic conditions related topic and its ratio peaks corresponded to the time of Japan’s GDP data released. In addition, we found that the money easing policy topic ratio increased after the tax hike and that the economic growth related topic ratio showed the decline after the tax hike.
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Notes
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CRAN web page: http://cran.r-project.org/.
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Cabinet Office, Government of Japan: Composite Indexes (2010 = 100) Coincident Index, CENT'CIDX10C, Indexes of Business Conditions November 2014 Preliminary Release (January 9, 2015).
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Acknowledgment
We thank Hirohiko Okumura, an emeritus professor of Gakushuin University for thoughtful comments that improved this paper. We thank Prof Tetsuji Kuboyama for his wide range of knowledge about machine learning that helps our research. This research was partly supported by funds from Gakushuin University Computing Centre as its special research project in 2014.
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Shirota, Y., Hashimoto, T., Sakura, T. (2015). Topic Extraction Analysis for Monetary Policy Minutes of Japan in 2014. In: Perner, P. (eds) Advances in Data Mining: Applications and Theoretical Aspects. ICDM 2015. Lecture Notes in Computer Science(), vol 9165. Springer, Cham. https://doi.org/10.1007/978-3-319-20910-4_11
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DOI: https://doi.org/10.1007/978-3-319-20910-4_11
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