A text mining application on monthly price developments reports

Text mining analysis provides big opportunities for economic research. Underlying natural language processing techniques allow us to read the monthly price developments reports (MPDR) of the Central Bank of the Republic of Turkey (CBRT) and to analyse the words, to explore topics and clusters inside. Previous literature on CBRT documents has focused on making word clouds, measuring the sentiments and therefore it is limited with text documents. This study sets out to close this gap and extends the text mining analysis to measure the statistical consistency of the MPRDs with the annual consumer price index (CPI) inflation figures for Turkey. In this study, we showed that MPDRs contain intensifying references to core-groups/sectors in evaluation of inflation as well as they are interested in the tendency of inflation rather than its level. We also showed that how the clusters of MPDRs are significantlyconsistent with the annual CPI inflation figures from statistical point of view.

Kaynakça

Acosta, Miguel, 2015. FOMC Responses to Calls for Transparency. Finance and Economics Discussion Series 2015-60. Board of Governors of the Federal Reserve System (U.S.). https://ideas.repec.org/p/fip/fedgfe/2015-60.html.

Blinder, Alan S., Ehrmann, Michael, Fratzscher, Marcel, Haan, Jakob de, Jansen, David-Jan, 2008. Central Bank Communication and Monetary Policy: a Survey of Theory and Evidence. Working Paper Series 898. European Central Bank. https://ideas.repec.org/p/ecb/ecbwps/2008898.html.

CBRT, 2016. Annual Report. Annual Report Series. Central Bank of Republic of Turkey. http://www3.tcmb.gov.tr/yillikrapor/2016/files/en-tcmb2016.pdf.

Chambers, J.M., Hastie, T.J., 1992. Statistical Models in S. Wadsworth & Brooks/Cole. Christiano, Lawrence J., Eichenbaum, Martin, 1992. Liquidity effects and the mon-etary transmission mechanism. Am. Econ. Rev. 82 (2), 346e353. American Economic Association. http://www.jstor.org/stable/2117426.

Feldman, Ronen, Sanger, James, 2006. The Text Mining Handbook: Advanced Ap-proaches in Analyzing Unstructured Data.

Fellows, Ian, 2014. Wordcloud: Word Clouds. https://CRAN.R-project.org/ package¼wordcloud.

Hansen, Stephen, McMahon, Michael, 2015. Shocking Language: Understanding the Macroeconomic Effects of Central Bank Communication. Discussion Papers1537. Centre for Macroeconomics (CFM). https://ideas.repec.org/p/cfm/wpaper/ 1537.html.

Hofmann, Thomas, 2001. Unsupervised learning by probabilistic latent semantic analysis. Mach. Learn. 42 (1), 177e196. https://doi.org/10.1023/A: 1007617005950.

Hotho, A., Nurnberg, A., Paas, G., 2005. A brief survey of text mining. J. Comput. Ling. Lang. Technol. 20 (1). http://media.dwds.de/jlcl/2005_Heft1/19-62_ HothoNuernbergerPaass.pdf.

Iglesias, Joaquin, Ortiz, Alvaro, Rodrigo, Tomasa, 2017. How Do the EM Central Bank Talk? a Big Data Approach to the Central Bank of Turkey. Working Papers 17/24. BBVA Bank, Economic Research Department. https://ideas.repec.org/p/bbv/ wpaper/1724.html.

Jansen, David-Jan, Haan, Jakob de, 2010. An Assessment of the Consistency of ECB Communication Using Wordscores. DNB Working Papers 259. Netherlands Central Bank, Research Department. https://ideas.repec.org/p/dnb/dnbwpp/ 259.html.

Kahveci, Eyup, Odabas, Aysun, 2016. Central banks' communication strategy and content analysis of monetary policy statements: the case of fed, ECB and CBRT. Procedia Soc. Behav. Sci. 235. http://www.sciencedirect.com/science/article/pii/ S1877042816315737.

Kara, A.Hakan, 2008. Turkish experience with implicit inflation targeting. Cent. Bank Rev. 8 (1), 1e16. https://ideas.repec.org/a/tcb/cebare/v8y2008i1p1-16.html.

Kumar, Anil, Chandrasekhar, S., 2012. Text data pre-processing and dimensionality reduction techniques for document clustering. Int. J. Eng. Res. Technol. 1 (5). In: https://www.ijert.org/download/475/text-data-pre-processing-and-dimensionality-reduction-techniques-for-document-clustering.

Lucca, David O., Trebbi, Francesco, 2009. Measuring Central Bank Communication: an Automated Approach with Application to FOMC Statements. NBER Working Papers 15367. National Bureau of Economic Research, Inc. https://ideas.repec. org/p/nbr/nberwo/15367.html.

R Core Team, 2017. R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project. org/.

Ranaldo, Angelo, Rossi, Enzo, 2010. The reaction of asset markets to Swiss National Bank communication. J. Int. Money Finance 29 (3), 486e503. https://ideas. repec.org/a/eee/jimfin/v29y2010i3p486-503.html.

Weiss, Sholom, Indurkhya, N., Zhang, T., Damerau, F.J., 2004. Text Mining: Predictive Methods for Analyzing Unstructured Information. Springer.

Kaynak Göster