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Mixed-frequency Growth-at-Risk with the MIDAS-QR method: Evidence from China

Author

Listed:
  • Xu, Qifa
  • Xu, Mengnan
  • Jiang, Cuixia
  • Fu, Weizhong
Abstract
High-frequency financial indicators provide more useful information and are efficient at forecasting low-frequency GDP. To this end, we extend the traditional Growth-at-Risk (GaR) framework for mixed frequency data. In this extension, monthly financial indicators are used to forecast quarterly GDP with the mixed data sampling-quantile regression (MIDAS-QR) method. Its ability for high-frequency monitoring of GaR is investigated using Chinese evidence. The evidence shows that our mixed-frequency GaR is promising in terms of good forecasting and nowcasting results, and can offer early warning of GDP downturns.

Suggested Citation

  • Xu, Qifa & Xu, Mengnan & Jiang, Cuixia & Fu, Weizhong, 2023. "Mixed-frequency Growth-at-Risk with the MIDAS-QR method: Evidence from China," Economic Systems, Elsevier, vol. 47(4).
    • Handle: RePEc:eee:ecosys:v:47:y:2023:i:4:s0939362523000651
    DOI: 10.1016/j.ecosys.2023.101131
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    References listed on IDEAS

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    Cited by:

    1. Tibor Szendrei & Arnab Bhattacharjee & Mark E. Schaffer, 2024. "MIDAS-QR with 2-Dimensional Structure," Papers 2406.15157, arXiv.org.

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