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Time-Frequency connectedness of policy uncertainty, geopolitical risk and Chinese commodity markets: evidence from rolling window analysis

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  • Hao Wu
  • Huiming Zhu
  • Yiwen Chen
  • Fei Huang

Abstract

This article investigates the time-frequency connectedness of categorical policy uncertainty, geopolitical risk and Chinese commodity markets by applying the vector autoregression method for the period from August 2004 to March 2021. Specifically, our research employs rolling window analysis of wavelet decomposition series to uncover the dynamic properties of connectedness with a time-frequency framework. The results indicate that heterogeneity exists across time scales for policy-specific uncertainty, geopolitical risk and commodities throughout the study period. In particular, the directional connectedness shows that the commodity markets are most closely related to monetary policy uncertainty, followed by exchange rate policy uncertainty, fiscal policy uncertainty and trade policy uncertainty, and finally geopolitical risk. In addition, connectedness exhibits an obvious changing trend during the crisis period, and the spillover effects of policy uncertainty and geopolitical risk increase dramatically. Finally, the long-term connectedness between policy uncertainty, geopolitical risk and commodities are stronger than that in the short-term periods. Overall, our findings provide valuable implications that policymakers and investors should pay attention to dynamic and time-frequency features of connectedness when making decisions.

Suggested Citation

  • Hao Wu & Huiming Zhu & Yiwen Chen & Fei Huang, 2023. "Time-Frequency connectedness of policy uncertainty, geopolitical risk and Chinese commodity markets: evidence from rolling window analysis," Applied Economics, Taylor & Francis Journals, vol. 55(1), pages 90-112, January.
  • Handle: RePEc:taf:applec:v:55:y:2023:i:1:p:90-112
    DOI: 10.1080/00036846.2022.2056571
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    Cited by:

    1. Evrim Mandaci, Pınar & Azimli, Asil & Mandaci, Nazif, 2023. "The impact of geopolitical risks on connectedness among natural resource commodities: A quantile vector autoregressive approach," Resources Policy, Elsevier, vol. 85(PA).

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