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 5, 1319-1347
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 â€œproblem of fundamentalness,â€ 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.
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Working Paper: Opening the Black Box: Structural Factor Models with Large Cross-Sections (2008)
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 (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:cup:etheor:v:25:y:2009:i:05:p:1319-1347_09
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