The effect of observables, functional specifications, model features and shocks on identification in linearized DSGE models
Ivashchenko Sergey, Mutschler Willi
Research article (journal) | Peer reviewedAbstract
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.
Details about the publication
Authors from the University of Münster
| Mutschler, Willi | Professur für VWL, Ökonometrie/Wirtschaftsstatistik (Prof. Trede) |
Promotionen, aus denen die Publikation resultiert
| Identification of DSGE models Candidate: Mutschler, Willi | Supervisors: Trede, Mark Period of time: 01/06/2012 - 31/12/2015 Doctoral examination procedure finished at: Doctoral examination procedure at University of Münster |