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On the transmission mechanism of Asia‐Pacific yield curve characteristics

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  • David Gabauer
  • Sowmya Subramaniam
  • Rangan Gupta

Abstract

This study investigates the transmission mechanism of Asia‐Pacific sovereign bond yields using a monthly data set, which reaches over the period from January 2003 until December 2017. Sovereign bond yields are decomposed into three latent factors – level, curvature and slope – using the dynamic Nelson–Siegel procedure proposed by Diebold and Li, Journal of Econometrics, 2006, 130(2), 337–364. The yield curve propagation mechanism is examined using the dynamic connectedness framework of Diebold and Yılmaz, Journal of Econometrics, 2012, 182(1), 119–134 and Diebold and Yılmaz, Journal of Econometrics, 2014, 182(1), 119–134 which is based on a time‐varying parameter vector auto‐regression (TVP‐VAR). The results suggest that the net transmitters of shocks are Australia, Hong Kong, Korea and Singapore whereas China, India, Indonesia, Japan and Malaysia have been net receivers of shocks. Across factors, those results are consistent except for the Korean curvature factor. In addition, findings revealed that the highest market interconnectedness can be found in the level factor followed by the slope and the curvature factor. Notably, all dynamic connectedness indices strongly increased during the Global Financial Crisis (2009), which illustrates that the Asia‐Pacific monetary policy is interconnected with each other especially during periods of economic unrest.

Suggested Citation

  • David Gabauer & Sowmya Subramaniam & Rangan Gupta, 2022. "On the transmission mechanism of Asia‐Pacific yield curve characteristics," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 473-488, January.
    • Handle: RePEc:wly:ijfiec:v:27:y:2022:i:1:p:473-488
    DOI: 10.1002/ijfe.2163
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    3. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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