Networking the Yield Curve: Implications for Monetary Policy

Connectedness in the Brazilian yield curve

“…This means that there is a low level of transmission of shocks between the short-end and the long-end parts of the curve. This is consistent with Dalhaus et al (2021) who also find that short-and long-term interest rate surprises are not directedly connected, while medium-term maturities are well connected to both the short and long end of the yield curve. All in all, the results for Brazil show that the belly of the curve acts as focal point, transmitting shocks for the other segments of the curve.…”

“…Moreover, Stenfors et al (2022a) found that short-term Japanese Government Bonds (JGBs) act as net receivers of shocks, which is consistent with the interpretation of this paper. Finally, Dalhaus et al (2021) also find that the future path of interest rates (which they associate to forward guidance) drives the yield curve network intensity in their models.…”

“…Relatedly, Dalhaus et al (2021) introduced a Dynamic Spatial Lag model to study the interconnectedness of the U.S. yield curve, aiming to understand how different dimensions of monetary policy (short-term rates, forward guidance and quantitative easing) interact. They found that forward guidance drives the dynamics of network intensity in a negative way, i.e., lower interest rates in the future are associated with higher spillover intensity, and also that uncertainty (proxied by the VIX) and lower economic growth increase the estimated network intensity.…”