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

Qifa Xu, Mengnan Xu, Cuixia Jiang and Weizhong Fu

Economic Systems, 2023, vol. 47, issue 4

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.

Keywords: Growth-at-Risk; MIDAS-QR; Skewed t-distribution; Conditional density (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosys:v:47:y:2023:i:4:s0939362523000651

DOI: 10.1016/j.ecosys.2023.101131

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