OPENING THE BLACK BOX: STRUCTURAL FACTOR MODELS WITH LARGE CROSS SECTIONS

Mario Forni (), Domenico Giannone (), Marco Lippi () and Lucrezia Reichlin ()

Econometric Theory, 2009, vol. 25, issue 05, pages 1319-1347

Abstract: This paper shows how large-dimensional dynamic factor models are suitable for structural analysis. We argue that all identification schemes employed in structural vector autoregression (SVAR) analysis can be easily adapted in dynamic factor models. Moreover, the which is intractable in SVARs, can be solved, provided that the impulse-response functions are sufficiently heterogeneous. We provide consistent estimators for the impulse-response functions and for (n, T) rates of convergence. An exercise with U.S. macroeconomic data shows that our solution of the fundamentalness problem may have important empirical consequences.

Date: 2009

Downloads: (external link)
http://journals.cambridge.org/abstract_S026646660809052X link to article abstract page (text/html)

Related works:
Working Paper: Opening the black box - structural factor models with large gross-sections (2007)
Working Paper: Opening the Black Box: Structural Factor Models with Large Cross-Sections (2007)
Working Paper: Opening the Black Box: Structural Factor Models with Large Cross-Sections (2008)
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: http://EconPapers.repec.org/RePEc:cup:etheor:v:25:y:2009:i:05:p:1319-1347_09

Access Statistics for this article

More articles in Econometric Theory from Cambridge University Press
Address: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Series data maintained by Mike Eden ().