Exploiting the Monthly Data Flow in Structural Forecasting
Federal Reserve Bank of New York Staff Reports
Reichlin, L., Giannone, D., Monti, F.
Date Published: December 2015
Abstract:
This paper develops a framework that allows us to combine the tools provided by structural
models for economic interpretation and policy analysis with those of reduced-form models
designed for nowcasting. We show how to map a quarterly dynamic stochastic general
equilibrium (DSGE) model into a higher frequency (monthly) version that maintains the same
economic restrictions. Moreover, we show how to augment the monthly DSGE with auxiliary
data that can enhance the analysis and the predictive accuracy in now-casting and forecasting.
Our empirical results show that both the monthly version of the DSGE and the auxiliary variables offer help in real time for identifying the drivers of the dynamics of the economy.
Citation:
Reichlin, L., Giannone, D. Monti, F. Exploiting the Monthly Data Flow in Structural Forecasting, Federal Reserve Bank of New York Staff Reports, Staff Report No. 751, December 2015
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