Dynamic Hierarchical Factor Models

Emanuel Moench; Serena Ng; Simon Potter

doi:10.1162/rest_a_00359

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Dynamic Hierarchical Factor Models

Emanuel Moench¹; Serena Ng²; Simon Potter¹

¹ Federal Reserve Bank of New York · ² Columbia University

The Review of Economics and Statistics 2013

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.

DOI: 10.1162/rest_a_00359
Volume: 95 (5)
Pages: 1811-1817
Language: en
Export: BibTeX
Sources: crossref openalex