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.
|Number of pages||41|
|Journal||Korean Economic Review|
|Publication status||Published - 2019|
Bibliographical noteFunding Information:
We thank the participants at the seminars of the Bank of Korea (BOK) and Korea Institute for International Economic Policy for their helpful comments and suggestions. The financial support of the BOK is greatly appreciated. The views expressed herein are those of the authors and do not necessarily reflect those of the BOK The usual disclaimers apply.
© 2019, Korean Economic Association. All rights reserved.
All Science Journal Classification (ASJC) codes
- Economics, Econometrics and Finance(all)