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dc.contributor.authorMoench, Emanuelen_US
dc.contributor.authorNg, Serenaen_US
dc.contributor.authorPotter, Simonen_US
dc.date.accessioned2010-05-07en_US
dc.date.accessioned2012-08-17T14:35:05Z-
dc.date.available2012-08-17T14:35:05Z-
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/10419/60828-
dc.description.abstractThis paper uses multi-level factor models to characterize within- and between-block variations as well as idiosyncratic noise in large dynamic panels. Block-level shocks are distinguished from genuinely common shocks, and the estimated block-level factors are easy to interpret. The framework achieves dimension reduction and yet explicitly allows for heterogeneity between blocks. The model is estimated using a Markov chain Monte-Carlo algorithm that takes into account the hierarchical structure of the factors. We organize a panel of 447 series into blocks according to the timing of data releases and use a four-level model to study the dynamics of real activity at both the block and aggregate levels. While the effect of the economic downturn of 2007-09 is pervasive, growth cycles are synchronized only loosely across blocks. The state of the leading and the lagging sectors, as well as that of the overall economy, is monitored in a coherent framework.en_US
dc.language.isoengen_US
dc.publisherFederal Reserve Bank of New York New York, NYen_US
dc.relation.ispartofseriesStaff Report, Federal Reserve Bank of New York 412en_US
dc.subject.jelC10en_US
dc.subject.jelC20en_US
dc.subject.jelC30en_US
dc.subject.ddc330en_US
dc.subject.keywordForecastingen_US
dc.subject.keywordmonitoringen_US
dc.subject.keywordcomovementsen_US
dc.subject.keywordlarge dimensional panelen_US
dc.subject.keyworddiffusion indexen_US
dc.titleDynamic hierarchical factor modelsen_US
dc.typeWorking Paperen_US
dc.identifier.ppn622842811en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
Appears in Collections:Staff Reports, Federal Reserve Bank of New York

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