Arbeitspapier
Dynamic hierarchical factor models
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: Staff Report ; No. 412
- Klassifikation
-
Wirtschaft
Econometric and Statistical Methods and Methodology: General
Single Equation Models; Single Variables: General
Multiple or Simultaneous Equation Models; Multiple Variables: General
- Thema
-
Forecasting
monitoring
comovements
large dimensional panel
diffusion index
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Moench, Emanuel
Ng, Serena
Potter, Simon
- Ereignis
-
Veröffentlichung
- (wer)
-
Federal Reserve Bank of New York
- (wo)
-
New York, NY
- (wann)
-
2009
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Moench, Emanuel
- Ng, Serena
- Potter, Simon
- Federal Reserve Bank of New York
Entstanden
- 2009
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