Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62843 
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dc.contributor.authorClements, Michael P.en
dc.contributor.authorGalvão, Ana Beatrizen
dc.contributor.authorMarcellino, Massimilianoen
dc.date.accessioned2012-09-20T13:00:10Z-
dc.date.available2012-09-20T13:00:10Z-
dc.date.issued2007-
dc.identifier.urihttp://hdl.handle.net/10419/62843-
dc.description.abstractMany macroeconomic series such as US real output growth are sampled quarterly, although potentially useful predictors are often observed at a higher frequency. We look at whether a mixed data-frequency sampling (MIDAS) approach can improve forecasts of output growth. The MIDAS approach is compared to other ways of making use of monthly data to predict quarterly output growth. The MIDAS specification used in the comparison employs a novel way of including an autoregressive term. We find that the use of monthly data on the current quarter leads to significant improvement in forecasting current and next quarter output growth, and that MIDAS is an effective way of exploiting monthly data compared to alternative methods. We also exploit the best method to use the monthly vintages of the indicators for real-time forecasting.en
dc.language.isoengen
dc.publisher|aQueen Mary University of London, Department of Economics |cLondonen
dc.relation.ispartofseries|aWorking Paper |x616en
dc.subject.jelC51en
dc.subject.jelC53en
dc.subject.ddc330en
dc.subject.keywordMixed data frequencyen
dc.subject.keywordCoincident indicatorsen
dc.subject.keywordReal-time forecastingen
dc.subject.keywordUS output growthen
dc.subject.stwWirtschaftsprognoseen
dc.subject.stwGesamtwirtschaftliche Produktionen
dc.subject.stwStatistische Methodeen
dc.subject.stwAutokorrelationen
dc.subject.stwUSAen
dc.titleMacroeconomic forecasting with mixed frequency data: Forecasting US output growth-
dc.typeWorking Paperen
dc.identifier.ppn548435383en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen

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