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A review of nonfundamentalness and identification in structural VAR models

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  • Alessi, Lucia
  • Barigozzi, Matteo
  • Capasso, Marco

Abstract

We review, under a historical perspective, the development of the problem of nonfundamentalness of Moving Average (MA) representations of economic models. Nonfundamentalness typically arises when agents’ information space is larger than the econometrician’s one. Therefore it is impossible for the latter to use standard econometric techniques, as Vector AutoRegression (VAR), to estimate economic models. We restate the conditions under which it is possible to invert an MA representation in order to get an ordinary VAR and identify the shocks, which in a VAR are fundamental by construction. By reviewing the work by Lippi and Reichlin [1993] we show that nonfundamental shocks may be very different from fundamental shocks. Therefore, nonfundamental representations should not be ruled out by assumption and indeed methods to detect nonfundamentalness have been recently proposed in the literature. Moreover, Structural VAR (SVAR) can be legitimately used for assessing the validity of Dynamic Stochastic General Equilibrium models only if the representation associated with the economic model is fundamental. Factor models can be an alternative to SVAR for validation purposes as they do not have to deal with the problem of nonfundamentalness. JEL Classification: C32, C51, C52

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 0922.

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Date of creation: Jul 2008
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Handle: RePEc:ecb:ecbwps:20080922

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Keywords: dynamic stochastic general equilibrium models; Factor models; Nonfundamentalness; Structural VAR;

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Cited by:
  1. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(5), pages 67-116.
  2. Valter Di Giacinto & Giacinto Micucci & Pasqualino Montanaro, 2010. "Dynamic Macroeconomic Effects of Public Capital: Evidence from Regional Italian Data," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 69(1), pages 29-66, April.
  3. Fève, Patrick & Jidoud, Ahmat, 2012. "Identifying News Shocks from SVARs," TSE Working Papers 12-287, Toulouse School of Economics (TSE).
  4. Lanne, Markku & Saikkonen, Pentti, 2013. "Noncausal Vector Autoregression," Econometric Theory, Cambridge University Press, vol. 29(03), pages 447-481, June.
  5. Giorgio Fagiolo & Andrea Roventini, 2008. "On the Scientific Status of Economic Policy: A Tale of Alternative Paradigms," Working Papers 47/2008, University of Verona, Department of Economics.
  6. Beaudry, Paul & Portier, Franck, 2013. "News Driven Business Cycles: Insights and Challenges," CEPR Discussion Papers 9624, C.E.P.R. Discussion Papers.
  7. Helmut Lütkepohl, 2012. "Fundamental Problems with Nonfundamental Shocks," Discussion Papers of DIW Berlin 1230, DIW Berlin, German Institute for Economic Research.

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