Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/53764
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dc.contributor.authorMaier, Philippen_US
dc.date.accessioned2011-04-05en_US
dc.date.accessioned2011-12-15T12:55:30Z-
dc.date.available2011-12-15T12:55:30Z-
dc.date.issued2011en_US
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_US
dc.language.isoengen_US
dc.publisher|aBank of Canada |cOttawaen_US
dc.relation.ispartofseries|aBank of Canada Working Paper |x2011,11en_US
dc.subject.jelC50en_US
dc.subject.jelC53en_US
dc.subject.jelE37en_US
dc.subject.jelE47en_US
dc.subject.ddc330en_US
dc.subject.keywordEconometric and statistical methodsen_US
dc.subject.keywordInternational topicsen_US
dc.subject.stwSozialprodukten_US
dc.subject.stwPrognoseen_US
dc.subject.stwPrognoseverfahrenen_US
dc.subject.stwBewertungen_US
dc.subject.stwChinaen_US
dc.titleMixed frequency forecasts for Chinese GDPen_US
dc.typeWorking Paperen_US
dc.identifier.ppn655708588en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US

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