Strategic central bank communication: Discourse analysis of the Bank of Japan’s Monthly Report

We conduct a discourse analysis of the Bank of Japan’s Monthly Report and examine its characteristics in relation to business cycles. We find that ambiguous expressions tend to appear more frequently with negative expressions, and this tendency is more pronounced in recessions. This suggests that the central bank communicates strategically by obfuscating the reports when their private information is unfavorable.

[1]  N. Bloom The Impact of Uncertainty Shocks , 2007 .

[2]  S. Eijffinger,et al.  How Transparent are Central Banks? , 2002 .

[3]  Sven Ove Hansson,et al.  Measuring Uncertainty , 2009, Stud Logica.

[4]  Tatevik Sekhposyan,et al.  Macroeconomic uncertainty indices based on nowcast and forecast error distributions , 2015 .

[5]  J. Sobel,et al.  STRATEGIC INFORMATION TRANSMISSION , 1982 .

[6]  Ellyn R. Boukus,et al.  The Information Content of FOMC Minutes , 2006 .

[7]  Tim Loughran,et al.  When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks , 2010 .

[8]  Scott Hendry,et al.  Central bank communication or the media's interpretation: What moves markets? , 2012 .

[9]  Geoffrey Nowell‐Smith,et al.  Selections from the prison notebooks of Antonio Gramsci , 2015 .

[10]  John Morgan,et al.  Shrouded Attributes and Information Suppression: Evidence from the Field , 2010 .

[11]  J. Toomasian The Case for the Case , 2016, Perfusion.

[12]  Philip N. Johnson-Laird,et al.  The Meaning of Modality , 1978, Cogn. Sci..

[13]  Eve Sweetser,et al.  From Etymology to Pragmatics: Preface , 1990 .

[14]  Miguel Acosta FOMC Responses to Calls for Transparency , 2015 .

[15]  Marvin Goodfriend,et al.  Monetary Mystique: Secrecy and Central Banking , 1985 .

[16]  Giuseppe Bruno,et al.  Text mining and sentiment extraction in central bank documents , 2016, 2016 IEEE International Conference on Big Data (Big Data).

[17]  H. Narrog Modality in Japanese: The Layered Structure of the Clause and Hierarchies of Functional Categories , 2009 .

[18]  Andrew McCallum,et al.  Rethinking LDA: Why Priors Matter , 2009, NIPS.

[19]  Hamza Bennani,et al.  The (home) bias of European central bankers: new evidence based on speeches , 2015 .

[20]  Yuji Matsumoto,et al.  Collecting Evaluative Expressions for Opinion Extraction , 2004, IJCNLP.

[21]  Michael Woodford,et al.  Interest and Prices , 2011 .

[22]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[23]  David M. Blei,et al.  Probabilistic topic models , 2012, Commun. ACM.

[24]  M. Grimaldi,et al.  The Information Content of Central Bank Minutes , 2012 .

[25]  J. Stein Cheap Talk and the Fed: A Theory of Imprecise Policy Announcements , 1989 .

[26]  J. Barlow The Age of Turbulence. Adventures in a New World , 2007 .

[27]  S. Morris,et al.  Social Value of Public Information , 2002 .

[28]  Scott Hendry,et al.  Text Mining and the Information Content of Bank of Canada Communications , 2010 .

[29]  Feng Li Annual Report Readability, Current Earnings, and Earnings Persistence , 2008 .

[30]  Feng Li Textual Analysis of Corporate Disclosures: A Survey of the Literature , 2011 .

[31]  R. Dye DISCLOSURE OF NONPROPRIETARY INFORMATION , 1985 .

[32]  Michael Tomz,et al.  The Electoral Implications of Candidate Ambiguity , 2009, American Political Science Review.

[33]  Takashi Inui,et al.  Extracting Semantic Orientations of Words using Spin Model , 2005, ACL.

[34]  Franciska de Jong,et al.  Predicting the impact of central bank communications on financial market investors' interest rate expectations , 2014, WaSABi-FEOSW@ESWC.

[35]  E. Kahveci,et al.  Central Banks’ Communication Strategy and Content Analysis of Monetary Policy Statements: The Case of Fed, ECB and CBRT , 2016 .

[36]  S. Morris,et al.  Central Bank Forward Guidance and the Signal Value of Market Prices , 2018 .

[37]  T. Landauer,et al.  Indexing by Latent Semantic Analysis , 1990 .

[38]  S. Davis,et al.  Measuring Economic Policy Uncertainty , 2013 .

[39]  Michael McMahon,et al.  Shocking Language: Understanding the Macroeconomic Effects of Central Bank Communication , 2015 .

[40]  David Bholat,et al.  Text Mining for Central Banks , 2015 .

[41]  G. Montes,et al.  Does clarity of central bank communication affect credibility? Evidences considering governor-specific effects , 2017 .

[42]  Ippei Fujiwara Is the central bank's publication of economic forecasts influential? , 2005 .

[43]  Stephen Morris,et al.  Central Bank Transparency and the Signal Value of Prices , 2006 .

[44]  Hal R. Varian,et al.  Big Data: New Tricks for Econometrics , 2014 .

[45]  C. Green,et al.  Monetary theory and policy , 1991 .

[46]  Masaru Kitsuregawa,et al.  Building Lexicon for Sentiment Analysis from Massive Collection of HTML Documents , 2007, EMNLP.

[47]  D. Jansen Does the Clarity of Central Bank Communication Affect Volatility in Financial Markets? Evidence from Humphrey‐Hawkins Testimonies , 2011 .

[48]  Lillian Lee,et al.  Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..

[49]  D. Romer,et al.  Federal Reserve Information and the Behavior of Interest Rates , 2000 .

[50]  Paul R. Milgrom,et al.  Good News and Bad News: Representation Theorems and Applications , 1981 .

[51]  Michael Ehrmann,et al.  Central Bank Communication on Financial Stability , 2011, SSRN Electronic Journal.

[52]  Michael McMahon,et al.  Transparency and deliberation within the FOMC: a computational linguistics approach , 2014 .

[53]  A. Blinder The Quiet Revolution , 2004 .

[54]  Michael Ehrmann,et al.  Starting from a Blank Page? Semantic Similarity in Central Bank Communication and Market Volatility , 2017, Journal of Monetary Economics.

[55]  Janyce Wiebe,et al.  Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis , 2005, HLT.