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Fundamental Problems with Nonfundamental Shocks

  • Helmut Lütkepohl

Economic agents using information that is not incorporated in the econometric model is seen as a possible reason for why nonfundamental shocks are important in econometric models. Allowing for nonfundamental shocks in structural vector autoregressive (SVAR) analysis by considering moving average (MA) representations with roots in the complex unit circle is a possible response to the problem. A case is made for viewing nonfundamentalness as an omitted variables problem rather than a problem of MA roots in the unit circle. The omitted variables problem will always lurk in the background of SVAR analysis as well as other econometric studies and cannot be avoided. In SVAR analysis it is even more problematic than what the literature on nonfundamental shocks suggests. Still, SVARs can be useful tools for empirical analysis.

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File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.406511.de/dp1230.pdf
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Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 1230.

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Length: 18 p.
Date of creation: 2012
Date of revision:
Handle: RePEc:diw:diwwpp:dp1230
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  1. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
  2. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez & Thomas J. Sargent & Mark Watson, 2006. "A,B,C's (and D's)'s for Understanding VARS," Levine's Bibliography 321307000000000646, UCLA Department of Economics.
  3. PESARAN M. Hashem & SCHUERMANN Til & WEINER Scott, . "Modelling Regional Interdependencies using a Global Error-Correcting Macroeconometric Model," EcoMod2003 330700121, EcoMod.
  4. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
  5. Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2007. "A Review of Nonfundamentalness and Identification in Structural VAR Models," LEM Papers Series 2007/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  6. Bańbura, Marta & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Large Bayesian VARs," Working Paper Series 0966, European Central Bank.
  7. Forni, Mario & Lippi, Marco, 2000. "The Generalized Dynamic Factor Model: Representation Theory," CEPR Discussion Papers 2509, C.E.P.R. Discussion Papers.
  8. Jörg Breitung & Sandra Eickmeier, 2006. "Dynamic factor models," AStA Advances in Statistical Analysis, Springer, vol. 90(1), pages 27-42, March.
  9. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
  10. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?," Discussion Paper Series 1: Economic Studies 2006,32, Deutsche Bundesbank, Research Centre.
  11. Binswanger, Mathias, 2004. "How important are fundamentals?--Evidence from a structural VAR model for the stock markets in the US, Japan and Europe," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 14(2), pages 185-201, April.
  12. Marco Lippi & Lucrezia Reichlin, 1994. "VAR analysis, non-fundamental representations, Blashke matrices," ULB Institutional Repository 2013/10151, ULB -- Universite Libre de Bruxelles.
  13. Jesús Fernández-Villaverde & Juan F. Rubio-Ramíre & Thomas J. Sargent, 2006. "Economic and VAR Shocks: What Can Go Wrong?," Levine's Bibliography 122247000000000990, UCLA Department of Economics.
  14. Lanne, Markku & Lütkepohl, Helmut, 2010. "Structural Vector Autoregressions With Nonnormal Residuals," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 159-168.
  15. Giannone, Domenico & Reichlin, Lucrezia, 2006. "Does Information Help Recovering Structural Shocks from Past Observations?," CEPR Discussion Papers 5725, C.E.P.R. Discussion Papers.
  16. Lars Peter Hansen & Thomas J. Sargent, 1979. "Formulating and estimating dynamic linear rational expectations models," Working Papers 127, Federal Reserve Bank of Minneapolis.
  17. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  18. Braun, Phillip A. & Mittnik, Stefan, 1993. "Misspecifications in vector autoregressions and their effects on impulse responses and variance decompositions," Journal of Econometrics, Elsevier, vol. 59(3), pages 319-341, October.
  19. SBRANA, Giacomo & SILVESTRINI, Andrea, 2009. "What do we know about comparing aggregate and disaggregate forecasts?," CORE Discussion Papers 2009020, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  20. Cooley, Thomas F. & Leroy, Stephen F., 1985. "Atheoretical macroeconometrics: A critique," Journal of Monetary Economics, Elsevier, vol. 16(3), pages 283-308, November.
  21. Cooley, Thomas F. & Dwyer, Mark, 1998. "Business cycle analysis without much theory A look at structural VARs," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 57-88.
  22. repec:hal:journl:hal-00287137 is not listed on IDEAS
  23. Mario Forni & Domenico Giannone & Marco Lippi & Lucrezia Reichlin, 2007. "Opening the Black Box: Structural Factor Models with Large Cross-Sections," Center for Economic Research (RECent) 008, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
  24. Terasvirta, Timo & Tjostheim, Dag & Granger, Clive W. J., 2010. "Modelling Nonlinear Economic Time Series," OUP Catalogue, Oxford University Press, number 9780199587155, March.
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