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Opening the Black Box: Structural Factor Models with Large Cross-Sections

  • Mario Forni
  • Domenico Giannone
  • Marco Lippi
  • Lucrezia Reichlin

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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File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/54099/1/RePEc_eca_wpaper_2008_036.pdf
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Paper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers ECARES with number 2008_036.

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Length: 40 p.
Date of creation: 2008
Date of revision:
Publication status: Published by:
Handle: RePEc:eca:wpaper:2008_036
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Web page: http://difusion.ulb.ac.be

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  3. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
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  15. Peter N. Ireland, 1999. "A Method for Taking Models to the Data," Boston College Working Papers in Economics 421, Boston College Department of Economics.
  16. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
  17. Forni, Mario & Lippi, Marco, 2000. "The Generalized Dynamic Factor Model: Representation Theory," CEPR Discussion Papers 2509, C.E.P.R. Discussion Papers.
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