The effect of observables, functional specifications, model features and shocks on identification in linearized DSGE models
Sergey Ivashchenko and
Willi Mutschler ()
Economic Modelling, 2020, vol. 88, issue C, 280-292
The decisions a researcher makes at the model building stage are crucial for parameter identification. This paper contains a number of applied tips for solving identifiability problems and improving the strength of DSGE model parameter identification by fine-tuning the (1) choice of observables, (2) functional specifications, (3) model features and (4) choice of structural shocks. We offer a formal approach based on well-established diagnostics and indicators to uncover and address both theoretical (yes/no) identifiability issues and weak identification from a Bayesian perspective. The concepts are illustrated by two exemplary models that demonstrate the identification properties of different investment adjustment cost specifications and output-gap definitions. Our results provide theoretical support for the use of growth adjustment costs, investment-specific technology, and partial inflation indexation.
Keywords: DSGE models; Local identification; Weak identification; Investment adjustment costs; Output-gap; Observables (search for similar items in EconPapers)
JEL-codes: C18 C51 C68 E22 E52 (search for similar items in EconPapers)
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Working Paper: The effect of observables, functional specifications, model features and shocks on identification in linearized DSGE models (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:88:y:2020:i:c:p:280-292
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