白塚　重典

In Japan, due to the prolonged period of ultra-low interest rate environments, we need to consider not just pure monetary policy effects from changes in the monetary policy stance but also information effects arising from the central bank’s communication of its private policy information. In this study, we examine the identification of monetary policy shocks using a functional shock approach based on estimated yield curve information.

Unlike central banks in major economies, the Bank of Japan does not set a predetermined time for announcing the results of its Monetary Policy Meeting. To identify monetary policy shocks using high-frequency data, we need to account for this institutional characteristic explicitly. In this study, we address this issue by incorporating news flow information into analyses using tick-by-tick and daily data.

Shadow short-term interest rate (SSR) models are expected to provide effective monetary policy indicators under the effective lower bound (ELB) constraint on nominal interest rates. This paper revisits the SSR models using yield curve data from the prolonged ultra-low interest rate environment in Japan. Specifically, this paper compares the various specifications of the SSR models based on the Nelson-Siegel model by focusing on a trade-off between estimation performance and theoretical consistency. This paper highlights the importance of evaluating monetary policy easing effects using the entire yield curve fluctuations, rather than relying solely on SSR estimates, especially in the ultra-low interest rate environment in Japan.