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Climate policy uncertainty through production networks: Evidence from the stock market

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  • Yao, Xiaoyang
  • He, Wenjing
  • Li, Jianfeng
  • Le, Wei

Abstract

This thesis provides a deeper insight into quantifying the part of the production network in explaining spillovers of climate policy uncertainty (CPU) shocks to stock returns. By introducing world input–output data into the spatial vector autoregression (SAR) model, we distinguish the direct impact of CPU and the indirect impact occurring through the production network. The results show that more than 60 % of CPU’ effect on the stock market can be explained by the spillovers induced by the production network. In addition, the indirect effect is more obvious in the long term than in the short term.

Suggested Citation

  • Yao, Xiaoyang & He, Wenjing & Li, Jianfeng & Le, Wei, 2023. "Climate policy uncertainty through production networks: Evidence from the stock market," Economics Letters, Elsevier, vol. 233(C).
    • Handle: RePEc:eee:ecolet:v:233:y:2023:i:c:s0165176523004317
    DOI: 10.1016/j.econlet.2023.111405
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    References listed on IDEAS

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    Cited by:

    1. Li, Jianfeng & Yao, Xiaoyang & Wang, Hui & Le, Wei, 2024. "Hedging the climate change risks of China's brown assets: Green assets or precious metals?," International Review of Economics & Finance, Elsevier, vol. 94(C).
    2. Ruge-Murcia, Francisco, 2024. "Asset prices in a production network," European Economic Review, Elsevier, vol. 166(C).
    3. Niu, Hongli & Hu, Wenwen, 2024. "Static and dynamic interdependencies among natural gas, stocks of global major economies and uncertainty," Resources Policy, Elsevier, vol. 94(C).

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