Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/130633 
Year of Publication: 
2015
Series/Report no.: 
Staff Report No. 751
Publisher: 
Federal Reserve Bank of New York, New York, NY
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.
Subjects: 
DSGE models
forecasting
temporal aggregation
mixed-frequency data
large data sets
JEL: 
C33
C53
E30
Document Type: 
Working Paper

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