Abstract
ABSTRACTA factor augmented vector autoregressive models with time-varying coefficients and stochastic volatility is used to constructing financial conditions index to explore the link between composite index of financial indicators and future inflation. Time variation in the models’ parameters allows for the weights attached to each financial variable in the index to evolve over time. A monthly data of Chinese CPI and a wide range of macroeconomic variables are adopted to construct FCI and the experiment result shows its good forecasting performance to inflation.
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