DYNAMIC HIERARCHICAL FACTOR MODELS
成果类型：
Article
署名作者：
Moench, Emanuel; Ng, Serena; Potter, Simon
署名单位：
Federal Reserve System - USA; Federal Reserve Bank - New York; Columbia University
刊物名称：
REVIEW OF ECONOMICS AND STATISTICS
ISSN/ISSBN：
0034-6535
DOI：
10.1162/REST_a_00359
发表日期：
2013-12
页码：
1811-1817
关键词：
摘要：
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.
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