텍스트 마이닝에 기반한 통화정책 기조가 한국 주식시장 및 부동산시장에 미치는 영향에 대한 분석

During the period of the zero lower bound (ZLB) on interest rates after the financial crisis of 2008, unconventional monetary policies were extensively implemented by central banks of major economies. However, previous studies that investigated the effectiveness of monetary policies have exceedingly relied on interest rates such as the base rate or call rate due to the lack of the analytical proxy. This study first constructs monetary policy stance (MPS) from the minutes of monetary policy meetings based on text mining following the methodology of Lee et al. (2019) and then investigates the effects of MPS on equity and real estates markets in Korea. The estimation results suggest that in response to a contractionary monetary policy shock, which is denoted as “hawkish”, equity prices fall and its impact persists over 4 months. In addition, real estate sales prices decline to a much lesser extent and its effect persists over 10 months. Finally, our findings suggest that MPS constructed through an analysis of the communication of the central bank based on text mining can be a new analytical measure in quantifying the effectivess of monetary policies, given that it is possible to analyze the response of the real estates market, which is not significant when interest rates are employed.