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dc.contributor.authorQu, Zhongjunen_US
dc.date.accessioned2019-06-05T14:39:53Z
dc.date.available2019-06-05T14:39:53Z
dc.date.issued2018-12-02
dc.identifier.citationZhongjun Qu. 2018. "A composite likelihood framework for analyzing singular dsge models." The Review of Economics and Statistics, Volume 100, Issue 5, pp. 916 - 932 (17).
dc.identifier.issn0034-6535
dc.identifier.urihttps://hdl.handle.net/2144/35943
dc.description.abstractThis paper builds upon the composite likelihood concept of Lindsay (1988) to develop a framework for parameter identification, estimation, inference, and forecasting in DSGE models allowing for stochastic singularity. The framework consists of the following four components. First, it provides a necessary and sufficient condition for parameter identification, where the identifying information is provided by the first and second order properties of nonsingular submodels. Second, it provides an MCMC based procedure for parameter estimation. Third, it delivers confidence sets for structural parameters and impulse responses that allow for model misspecification. Fourth, it gen- erates forecasts for all the observed endogenous variables, irrespective of the number of shocks in the model. The framework encompasses the conventional likelihood analysis as a special case when the model is nonsingular. It enables the researcher to start with a basic model and then gradually incorporate more shocks and other features, meanwhile confronting all the models with the data to assess their implications. The methodology is illustrated using both small and medium scale DSGE models. These models have numbers of shocks ranging between one and seven.en_US
dc.format.extentp. 916 - 932en_US
dc.language.isoen_US
dc.publisherMassachusetts Institute of Technology Press (MIT Press)en_US
dc.relation.ispartofThe Review of Economics and Statistics
dc.subjectEconomicsen_US
dc.subjectApplied economicsen_US
dc.subjectEconometricsen_US
dc.subjectBusiness cycleen_US
dc.subjectDynamic stochastic general equilibrium modelsen_US
dc.subjectIdentificationen_US
dc.subjectImpulse responseen_US
dc.subjectMCMCen_US
dc.subjectStochastic singularityen_US
dc.titleA composite likelihood framework for analyzing singular DSGE modelsen_US
dc.typeArticleen_US
dc.description.versionAccepted manuscripten_US
pubs.elements-sourcemanual-entryen_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Economicsen_US
pubs.publication-statusPublisheden_US
dc.identifier.mycv427681


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