金融状况指数的FAVAR模型构建及效用检验

Construction and utility test of financial condition index based on FAVAR

目前多数研究均选用利率、汇率、房价和股价等指标构建金融状况指数,造成大量经济信息丢失,故通过建立FAVAR模型,选择利率类、汇率类、房价类及股价类等69个经济指标,采用广义脉冲响应函数构建金融状况指数,并分析金融状况指数对我国通货膨胀率的预测能力。结果表明：利用FAVAR模型编制的金融状况指数能有效预测未来5~8个月内的通货膨胀运行趋势,具有较强先导作用。建议政府机构定期编制金融状况指数,前瞻性地制定相关政策,为及时降低通胀水平提供帮助。

A general revision shows that the current study, most papers chose specific benchmark interest rate, exchange rate, house price and stock price to build FCI index, losing a lot of economic information. This paper establishes factors enhancing vector auto-regression model system, chooses interest rate categories, exchange rate categories, house price categories and stock price categories about 69 economic indicators, constructs the nation’s financial conditions index through the generalized impulse response function empowering, and empirical analyzes predictive ability of financial conditions index to Chinese inflation rate. The results show that financial conditions index compiled by employing of FAVAR model can predict the next 5~8 months inflation running trend of inflation rate, which has a leading role to inflation rate. Finally, it suggests the government agencies to compile financial condition index regularly and proactively develop policies so as to timely help reduce the level of inflation.