A text mining application on monthly price developments reports

Artikel

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 significantly consistent with the annual CPI inflation figures from statistical point of view.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Central Bank Review (CBR) ; ISSN: 1303-0701 ; Volume: 18 ; Year: 2018 ; Issue: 2 ; Pages: 51-60 ; Amsterdam: Elsevier

Classification and Topics

• Classification: Wirtschaft
• Subject: Central bank ; Communication ; Reports ; Text mining ; Cluster analysis

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Eskici, Hatice Burcu ; Kocak, Necmettin Alpay
• Event: Veröffentlichung
• (who): Elsevier
• (where): Amsterdam
• (when): 2018

Further information

• DOI: doi:10.1016/j.cbrev.2018.05.001
• Handle: http://hdl.handle.net/10419/217320
• Last update: 10.03.2025, 11:43 AM CET