Deciphering monetary policy board minutes with text mining: The case of South Korea

Young Joon Lee, Soohyon Kim, Ki Young Park

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


We quantify the Monetary Policy Board minutes of the Bank of Korea (BOK) by using text mining. We propose a novel approach that uses a field-specific Korean dictionary and contiguous sequences of words (n-grams) to capture the subtlety of central bank communications. Our text-based indicator helps explain the current and future BOK monetary policy decisions when considering an augmented Taylor rule, suggesting that it contains additional information beyond the currently available macroeconomic variables. In explaining the current and future monetary policy decisions, our indicator remarkably outperforms English-based textual classifications, a media-based measure of economic policy uncertainty, and a data-based measure of macroeconomic uncertainty. Our empirical results also emphasize the importance of using a field-specific dictionary and the original Korean text.

Original languageEnglish
Pages (from-to)471-511
Number of pages41
JournalKorean Economic Review
Issue number2
Publication statusPublished - 2019

Bibliographical note

Funding Information:
Acknowledgments We thank the DARPA TransTac program for funding and the anonymous reviewers for their constructive suggestions.

Publisher Copyright:
© 2019, Korean Economic Association. All rights reserved.

All Science Journal Classification (ASJC) codes

  • Economics, Econometrics and Finance(all)


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