ZHANG Jinfan, GANG Jianhua, QIAN Zongxin, ZHANG Lingyan
School of Management and Economics, Chinese University of Hong Kong (Shenzhen)/ Shenzhen Finance Institute/ International Monetary Institute, Renmin University of China; China Financial Policy Research Center, School of Finance, Renmin University of China; Department of Industrial Engineering and Operations Research, Columbia University
Abstract:
This paper constructs a Bayesian mixed frequency VAR (MF-BVAR) model to study the dynamics of China’s macro-economy and to forecast the key macro variables. The MF-BVAR model can nest high frequency macro information (e.g. capital market price) without compromising to the low frequency information (e.g GDP, investment) in economic projection. Empirical evidence shows that the MF-BVAR model dominates other classic models on forecasting key macro indicators such as CPI, RPI and GDP growth. The study further demonstrates that the real estate investment plays a significant role in forecasting China’s economic dynamics, while the stock market is insignificant in macro projection.
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