Exploiting the Monthly Data Flow in Structural Forecasting

45 Pages Posted: 10 Dec 2015 Last revised: 30 Aug 2017

See all articles by Domenico Giannone

Domenico Giannone

Federal Reserve Banks - Federal Reserve Bank of New York; Centre for Economic Policy Research (CEPR)

Multiple version iconThere are 2 versions of this paper

Date Written: 2015-12-01

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.

Keywords: DSGE models, forecasting, temporal aggregation, mixed-frequency data, large data sets

JEL Classification: C33, C53, E30

Suggested Citation

Giannone, Domenico, Exploiting the Monthly Data Flow in Structural Forecasting (2015-12-01). FRB of NY Staff Report No. 751. Available at SSRN: https://ssrn.com/abstract=2701190

Domenico Giannone (Contact Author)

Federal Reserve Banks - Federal Reserve Bank of New York ( email )

33 Liberty Street
New York, NY 10045
United States

Centre for Economic Policy Research (CEPR)

London
United Kingdom

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