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Forecasting in nonstationary environments: What works and what doesn't in reduced-form and structural models

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dc.contributor.author Giacomini, Raffaella
dc.contributor.author Rossi, Barbara
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
dc.date.accessioned 2020-05-25T09:26:58Z
dc.date.available 2020-05-25T09:26:58Z
dc.date.issued 2014-12-01
dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=1476
dc.identifier.citation Annual Review of Economics, 7, 207-229, 2015
dc.identifier.uri http://hdl.handle.net/10230/23388
dc.description.abstract This review provides an overview of forecasting methods that can help researchers forecast in the presence of non-stationarities caused by instabilities. The emphasis of the review is both theoretical and applied, and provides several examples of interest to economists. We show that modeling instabilities can help, but it depends on how they are modeled. We also show how to robustify a model against instabilities.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries Economics and Business Working Papers Series; 1476
dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.title Forecasting in nonstationary environments: What works and what doesn't in reduced-form and structural models
dc.type info:eu-repo/semantics/workingPaper
dc.date.modified 2020-05-25T09:24:37Z
dc.subject.keyword forecasting
dc.subject.keyword instabilities
dc.subject.keyword structural breaks.
dc.subject.keyword Macroeconomics and International Economics
dc.subject.keyword Statistics, Econometrics and Quantitative Methods
dc.rights.accessRights info:eu-repo/semantics/openAccess


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