This paper shows how large-dimensional dynamic factor models are suitable for structural analysis. We argue that all identification schemes employed in SVAR analysis can be easily adapted in dynamic factor models. Moreover, the ``problem of fundamentalness'', which is intractable in structural VARs, can be solved, provided that the impulse-response functions are sufficiently heterogeneous. We provide consistent estimators for the impulse-response functions, as well as (n,T) rates of convergence. An exercise with US macroeconomic data shows that our solution of the fundamentalness problem may have important empirical consequences.
Opening the Black Box: Structural Factor Models with large cross-sections / Forni, Mario; Giannone, D; Lippi, M. AND REICHLIN L.. - In: ECONOMETRIC THEORY. - ISSN 0266-4666. - STAMPA. - 25:5(2009), pp. 1319-1347. [10.1017/S026646660809052X]
Opening the Black Box: Structural Factor Models with large cross-sections
FORNI, Mario;
2009
Abstract
This paper shows how large-dimensional dynamic factor models are suitable for structural analysis. We argue that all identification schemes employed in SVAR analysis can be easily adapted in dynamic factor models. Moreover, the ``problem of fundamentalness'', which is intractable in structural VARs, can be solved, provided that the impulse-response functions are sufficiently heterogeneous. We provide consistent estimators for the impulse-response functions, as well as (n,T) rates of convergence. An exercise with US macroeconomic data shows that our solution of the fundamentalness problem may have important empirical consequences.
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