Structural estimation

Multiple filtering devices for the estimation of cyclical DSGE

JEL code(s)	E32 Business Fluctuations; Cycles
Keywords	Business Cycles., factor models, Filters, Structural estimation
Series Number:	Universitat Pompeu Fabra Economics Working Papers 1135/2009
Authors:	Fabio Canova Filippo Ferroni
Date published:	March 1, 2009
Abstract:	We propose a method to estimate time invariant cyclical DSGE models using the information provided by a variety of filtering approaches. We treat data filtered with alternative procedures as contaminated proxy of the relevant model-based quantities and estimate structural and non-structural parameters jointly using an unobservable component structure. We employ simulated data to illustrate the properties of the procedure and compare our estimates with those obtained when just one filter is used. We revisit the role of money in the transmission of monetary business cycles.
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JEL code(s)	E32 Business Fluctuations; Cycles
Keywords	Business Cycles., DSGE models, Filters, Structural estimation
Authors:	Filippo Ferroni
Date published:	April 1, 2009
Abstract:	DSGE models are currently estimated with a two step approach: data is first filtered and then DSGE structural parameters are estimated. Two step procedures have problems, ranging from trend misspecification to wrong assumption about the correlation between trend and cycles. In this paper, I present a one step method, where DSGE structural parameters are jointly estimated with filtering parameters. I show that different data transformations imply different structural estimates; the two step approach lacks a statistical-based criterion to select among them. The one step approach allows to test hypothesis about the most likely trend specification for individual series and/or use the resulting information to construct robust estimates by Bayesian averaging. The role of investment shock as source of GDP volatility is reconsidered.
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