统计研究 ›› 2020, Vol. 37 ›› Issue (6): 79-92.doi: 10.19343/j.cnki.11-1302/c.2020.06.007

• • 上一篇    下一篇

中国金融风险周期监测与央行货币政策非对称性效果识别

陈创练 单敬群 林玉婷   

  • 出版日期:2020-06-25 发布日期:2020-06-23

Monitoring on China’s Financial Risk Cycle and the Identification of Asymmetric Effects of the Central Bank’s Monetary Policy

Chen Chuanglian Shan Jingqun Lin Yuting   

  • Online:2020-06-25 Published:2020-06-23

摘要: 本文采用时变参数因子增广向量自回归模型(TVP-FAVAR),并基于动态模型平均法测度了金融子系统变量的时变权重,通过加权计算得到我国金融风险周期指数(FRI)。然后改进构建了分区制货币政策模型系统,并采用逻辑平滑转换向量自回归模型(LST-VAR)研究了高低区制下,价格型和数量型货币政策对金融风险的传导效应,在此基础上,设计并测度了我国货币政策的时滞效应。研究发现,我国金融风险具有明显的两区制特征,样本区间内FRI大多时期处于低风险区制,而高风险区制的时间段与国内外重大金融风险事件相吻合。两种紧缩的货币政策均有利于抑制金融风险及其波动,且在高风险区制的抑制效应更为显著。对于货币政策时滞效应,数量型货币政策对金融风险的抑制作用大于价格型货币政策,但2008、2012和2015年三个高金融风险期的时滞效应均较小。最后,根据研究结果提出相应政策建议。

关键词: 金融风险周期, 货币政策, 逻辑平滑转换向量自回归模型

Abstract: In this paper, the time-varying parameters factor augmented vector autoregressive model (TVPFAVAR) is adopted,and the time-varying weights of financial subsystems variables are measured based on the average method of the dynamic model, and the financial risk syde index (FRI) of China is obtained through weighted calculation. then the regime-based system of monetary policy model is improved and constructed.Finally, based on the logical smooth transition vector autoregressive model, we study the transmission effect of price or quantitative monetary policy on financial risks under both high and low regimes, and propose and measure the time lag effect of China’s monetary policy. The estimated results show that China’s financial risk has an obvious characteristic of two regimes, and mostly FRI is in the low financial risk regime, while the time periods in the high financial risk regime are consistent with the occurrence of some major domestic and foreign financial risk events. Furthermore, both types of tightening monetary policy can reduce the financial risk and its fluctuations, which is more significant in the high financial risk regime. In the study of the lag effect of monetary policy, we find quantitative monetary policy has a greater effect on reducing financial risk than price monetary policy, whereas the lag effect is relatively small in 2008, 2012 and 2015. Finally, this paper puts forward some corresponding policy suggestions.

Key words: Financial Risk Cycle, Monetary Policy, Logical Smooth Transition Vector Autoregressive Model