Predicting Financial Distress Using a MIDAS Hazard Model: Evidence from Listed Companies in China

被引：0
|
作者：
Li, Xiangrong [1 ]
Zhang, Maojun [2 ,4 ]
Nan, Jiangxia [2 ,4 ]
Yang, Qingyuan [3 ]
机构：
[1] Guangxi Univ, Sch Econ, Nanning, Peoples R China
[2] Suzhou Univ Sci & Technol, Sch Business, Suzhou, Peoples R China
[3] Nanning Coll Vocat Technol, Sch Finance & Econ, Nanning, Peoples R China
[4] Suzhou Univ Sci & Technol, Sch Business, Xuefu Rd 99, Suzhou 215009, Peoples R China
来源：
EMERGING MARKETS FINANCE AND TRADE | 2023年
关键词：
Financial distress; Aalen model; mixed data sampling; special treatment; C52; G32; G33;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
This study aims to predict financial distress in an emerging country using data on ST listed companies in China from 2001 to 2021. A new Aalen hazard model with mixed data sampling (MIDAS) is adopted to investigate the impact of monthly macroeconomic variables and quarterly financial variables on financial distress. The empirical results show that the current ratio, operating profit ratio, current capital ratio, retention ratio, profit ratio and income ratio of listed companies have a significant impact on the time-varying intensity of financial distress. The consumer price index has a negative relation with the intensity of financial distress, while the production price index and credit spreads have a positive influence. Finally, the results of the robustness tests are consistent with those with different lag orders.
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页数：10
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