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dc.contributor.authorMaier, Philippen
dc.date.accessioned2011-04-05-
dc.date.accessioned2011-12-15T12:55:30Z-
dc.date.available2011-12-15T12:55:30Z-
dc.date.issued2011-
dc.identifier.pidoi:10.34989/swp-2011-11en
dc.identifier.urihttp://hdl.handle.net/10419/53764-
dc.description.abstractWe evaluate different approaches for using monthly indicators to predict Chinese GDP for the current and the next quarter ('nowcasts' and 'forecasts' respectively). We use three types of mixed-frequency models, one based on an economic activity indicator (Liu et al., 2007), one based on averaging over indicator models (Stock and Watson, 2004), and a static factor model (Stock and Watson, 2002). Evaluating all models' out-of-sample projections, we find that all the approaches can yield considerable improvements over naive AR benchmarks. We also analyze pooling across forecasting methodologies. We find that the most accurate nowcast is given by a combination of a factor model and an indicator model. The most accurate forecast is given by a factor model. Overall, we conclude that these models, or combinations of these models, can yield improvements in terms of RMSE's of up to 60 per cent over simple AR benchmarks.en
dc.language.isoengen
dc.publisher|aBank of Canada |cOttawaen
dc.relation.ispartofseries|aBank of Canada Working Paper |x2011-11en
dc.subject.jelC50en
dc.subject.jelC53en
dc.subject.jelE37en
dc.subject.jelE47en
dc.subject.ddc330en
dc.subject.keywordEconometric and statistical methodsen
dc.subject.keywordInternational topicsen
dc.subject.stwSozialprodukten
dc.subject.stwPrognoseen
dc.subject.stwPrognoseverfahrenen
dc.subject.stwBewertungen
dc.subject.stwChinaen
dc.titleMixed frequency forecasts for Chinese GDP-
dc.typeWorking Paperen
dc.identifier.ppn655708588en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:bca:bocawp:11-11en

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