Dynamic Hierarchical Factor Model

Emanuel Moench, Serena Ng () and Simon Potter

The Review of Economics and Statistics, 2013, vol. 95, issue 5, 1811-1817

Abstract: This paper uses multilevel 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 an MCMC algorithm that takes into account the hierarchical structure of the factors. The importance of block-level variations is illustrated in a four-level model estimated on a panel of 445 series related to different categories of real activity in the United States. © 2013 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

Keywords: diffusion index forecasting; monitoring; large dimensional panel (search for similar items in EconPapers)
JEL-codes: C10 C20 C30 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (7)

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Working Paper: Dynamic hierarchical factor models (2009)
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