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| Title: | | Dynamic hierarchical factor models  |
| 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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