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dc.contributor.authorEspasa Terrades, Antoni
dc.contributor.authorSenra Díaz, Eva 
dc.date.accessioned2017-11-24T18:38:06Z
dc.date.available2017-11-24T18:38:06Z
dc.date.issued2017-10-06
dc.identifier.bibliographicCitationEconometrics, 2017, 5, 4; doi:10.3390/econometrics5040044
dc.identifier.issn2225-1146
dc.identifier.urihttp://hdl.handle.net/10017/31124
dc.description.abstractThe Bulletin of EU and US Inflation and Macroeconomic Analysis (BIAM) is a monthly publication that has been reporting real time analysis and forecasts for inflation and other macroeconomic aggregates for the Euro Area, the US and Spain since 1994. The BIAM inflation forecasting methodology stands on working with useful disaggregation schemes, using leading indicators when possible and applying outlier correction. The paper relates this methodology to corresponding topics in the literature and discusses the design of disaggregation schemes. It concludes that those schemes would be useful if they were formulated according to economic, institutional and statistical criteria aiming to end up with a set of components with very different statistical properties for which valid single-equation models could be built. The BIAM assessment, which derives from a new observation, is based on (a) an evaluation of the forecasting errors (innovations) at the components' level. It provides information on which sectors they come from and allows, when required, for the appropriate correction in the specific models. (b) In updating the path forecast with its corresponding fan chart. Finally, we show that BIAM real time Euro Area inflation forecasts compare successfully with the consensus from the ECB Survey of Professional Forecasters, one and two years aheaden
dc.description.sponsorshipMinisterio de Economía y Competitividades_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.rightsAttribution 4.0 International (CC BY 4.0)en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectDisaggregationen
dc.subjectIndirect forecasten
dc.subjectOutliersen
dc.subject.jelC13
dc.titleTwenty-two years of inflation assessment and forecasting experience at the Bulletin of EU and US Inflation and Macroeconomic Analysisen
dc.typeinfo:eu-repo/semantics/articleen
dc.subject.ecienciaEconomíaes_ES
dc.subject.ecienciaEconomicsen
dc.contributor.affiliationUniversidad de Alcalá. Departamento de Economíaes_ES
dc.date.updated2017-11-24T18:36:35Z
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.3390/econometrics5040044
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//ECO2015-70331-C2-2-R/ES/INDICADORES ECONÓMICOS: PREDICCIÓN CON INCERTIDUMBRE E INESTABILIDADes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//ECO2015-66593-P/ES/ Big data y datos complejos en empresa y finanzases_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//ECO2016-76818-C3-3-P/ES/TECNOLOGÍA, CAPITAL HUMANO, INNOVACIÓN Y COMERCIO 2es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.identifier.uxxiAR/0000026818
dc.identifier.publicationtitleEconometricsen
dc.identifier.publicationvolume5
dc.identifier.publicationlastpage28
dc.identifier.publicationissue4
dc.identifier.publicationfirstpage1


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Attribution 4.0 International (CC BY 4.0)
Este ítem está sujeto a una licencia Creative Commons.