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dc.contributor.authorDufour, Jean-Marieen_US
dc.contributor.authorKhalaf, Lyndaen_US
dc.contributor.authorKichian, Maralen_US
dc.date.accessioned2011-12-15T12:55:45Z-
dc.date.available2011-12-15T12:55:45Z-
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/10419/53781-
dc.description.abstractWeak identification is likely to be prevalent in multi-equation macroeconomic models such as in dynamic stochastic general equilibrium setups. Identification difficulties cause the breakdown of standard asymptotic procedures, making inference unreliable. While the extensive econometric literature now includes a number of identification-robust methods that are valid regardless of the identification status of models, these are mostly limited-information-based approaches, and applications have accordingly been made on single-equation models such as the New Keynesian Phillips Curve. In this paper, we develop a set of identification-robust econometric tools that, regardless of the model's identification status, are useful for estimating and assessing the fit of a system of structural equations. In particular, we propose a vector auto-regression (VAR) based estimation and testing procedure that relies on inverting identification-robust multivariate statistics. The procedure is valid in the presence of endogeneity, structural constraints, identification difficulties, or any combination of these, and also provides summary measures of fit. Furthermore, it has the additional desirable features that it is robust to missing instruments, errors-in-variables, the specification of the data generating process, and the presence of contemporaneous correlation in the disturbances. We apply our methodology, using U.S. data, to the standard New Keynesian model such as the one studied in Clarida, Gali, and Gertler (1999). We find that, despite the presence of identification difficulties, our proposed method is able to shed some light on the fit of the considered model and, particularly, on the nature of the NKPC. Notably our results show that (i) confidence intervals obtained using our system-based approach are generally tighter than their single-equation counterparts, and thus are more informative, (ii) most model coefficients are significant at conventional levels, and (iii) the NKPC is preponderantly forward-looking, though not purely so.en_US
dc.language.isoengen_US
dc.publisherBank of Canada Ottawaen_US
dc.relation.ispartofseriesBank of Canada Working Paper 2009,19en_US
dc.subject.jelC52en_US
dc.subject.jelC53en_US
dc.subject.jelE37en_US
dc.subject.ddc330en_US
dc.subject.keywordInflation and pricesen_US
dc.subject.keywordEconometric and statistical methodsen_US
dc.subject.stwMakroökonomiken_US
dc.subject.stwÖkonometrieen_US
dc.subject.stwVAR-Modellen_US
dc.subject.stwNew-Keynesian Phillips Curveen_US
dc.titleStructural multi-equation macroeconomic models: Identification-robust estimation and fiten_US
dc.typeWorking Paperen_US
dc.identifier.ppn60400138Xen_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
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