Identification and Frequency Domain QML Estimation of Linearized DSGE Models
Zhongjun Qu and
No WP2010-053, Boston University - Department of Economics - Working Papers Series from Boston University - Department of Economics
This paper considers issues related to identification, inference and computation in linearized Dynamic Stochastic General Equilibrium (DSGE) models. We first provide a necessary and su¢ cient condition for the local identification of the structural parameters based on the (first and) second order properties of the process. The condition allows for arbitrary relations be- tween the number of observed endogenous variables and structural shocks and is simple to verify. The extensions, including identification through a subset of frequencies, partial iden- tification, conditional identification and identification under general nonlinear constraints, are also studied. When lack of identification is detected, the method can be further used to trace out non-identification curves. For estimation, restricting our attention to nonsingular systems, we consider a frequency domain quasi-maximum likelihood (FQML) estimator and present its asymptotic properties. The limiting distribution of the estimator can be di¤erent from results in the related literature due to the structure of the DSGE model. Finally, we discuss a quasi- Bayesian procedure for estimation and inference. The procedure can be used to incorporate relevant prior distributions and is computationally attractive.
Keywords: Infinite dimensional mapping; Local identification; MCMC; Non-identification curve; Rank condition; Spectral domain (search for similar items in EconPapers)
JEL-codes: C10 C13 C30 E1 (search for similar items in EconPapers)
Pages: 55 pages
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Persistent link: https://EconPapers.repec.org/RePEc:bos:wpaper:wp2010-053
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