Deciphering Monetary Policy Board Minutes with Text Mining: The Case of South Korea

Young Joon Lee, Soohyon Kim and Ki Young Park
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Young Joon Lee: Yonsei University
Soohyon Kim: Yonsei University
Ki Young Park: Yonsei University

Korean Economic Review, 2019, vol. 35, 471-511

Abstract: 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.

Keywords: Monetary Policy; Text Mining; Taylor Rule; Machine Learning; Bank of Korea (search for similar items in EconPapers)
JEL-codes: E43 E52 E58 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (9)

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