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Identifying Interest Rate Transmission Mechanism under a Bayesian Network

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  • Byoung Jo Chun

    (School of Business, Sejong University, Seoul 05006, Republic of Korea)

Abstract

This study examines causal relationships among various short- and long-term interest rates in the Korean financial market to identify transmission channels. Monthly time series data from January 2015 to February 2024 were used, covering nine interest rates, including call rates, commercial paper (CP) rates, bank lending rates, and Treasury bond yields of different maturities. The study employs a Bayesian network to identify an acyclic causal structure between interest rates alongside a vector error correction model (VECM) to capture long-term equilibrium relationships and short-term dynamics. The findings reconfirm the traditional call rate transmission mechanism, aligning with conventional monetary policy views, demonstrating the call rate’s significant influence on bank lending rates, which affects corporate bond spreads and CP rates. Additionally, it reveals that 10-year Treasury bond yields form an independent interest rate transmission pathway, a finding not previously identified in the literature. These results underscore the need for coordinated monetary and fiscal policies due to the distinct transmission pathways of Treasury yields for sustainable macroeconomic management and growth.

Suggested Citation

  • Byoung Jo Chun, 2024. "Identifying Interest Rate Transmission Mechanism under a Bayesian Network," Sustainability, MDPI, vol. 16(14), pages 1-15, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:5840-:d:1431624
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    References listed on IDEAS

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