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http://hdl.handle.net/10419/60828
  
Title:Dynamic hierarchical factor models PDF Logo
Authors:Moench, Emanuel
Ng, Serena
Potter, Simon
Issue Date:2009
Series/Report no.:Staff Report, Federal Reserve Bank of New York 412
Abstract:This 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.
Subjects:Forecasting
monitoring
comovements
large dimensional panel
diffusion index
JEL:C10
C20
C30
Document Type:Working Paper
Appears in Collections:Staff Reports, Federal Reserve Bank of New York

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