Constructing a Coincident Index of Business Cycles Without Assuming a One-Factor Model

Yasutomo Murasawa and Roberto Mariano

No 710, Econometric Society 2004 Far Eastern Meetings from Econometric Society

Abstract: The Stock--Watson coincident index and its subsequent extensions assume a static linear one-factor model for the component indicators. Such assumption is restrictive in practice, however, with as few as four indicators. In fact, such assumption is unnecessary if one poses the index construction problem as optimal prediction of latent monthly real GDP. This paper estimates a VAR model for latent monthly real GDP and other indicators using the observable mixed-frequency series. The EM algorithm is useful for overcoming the computational difficulty, especially in model selection. The smoothed estimate of latent monthly real GDP is the proposed index

Keywords: state-space model; mixed-frequency; EM algorithm; monthly real GDP (search for similar items in EconPapers)
JEL-codes: C32 C43 C53 (search for similar items in EconPapers)
Date: 2004-08-11
References: Add references at CitEc
Citations: View citations in EconPapers (3)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: Constructing a Coincident Index of Business Cycles without Assuming a One-factor Model (2004)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ecm:feam04:710

Access Statistics for this paper

More papers in Econometric Society 2004 Far Eastern Meetings from Econometric Society Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum (baum@bc.edu).