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Testing for Sufficient Information in Structural VARs

  • Mario Forni
  • Luca Gambetti

We derive necessary and sufficient conditions under which a set of variables is informationally sufficient, i.e. it contains enough information to estimate the structural shocks with a VAR model. Based on such conditions, we suggest a procedure to test for informational sufficiency. Moreover, we show how to amend the VAR if informational sufficiency is rejected. We apply our procedure to a VAR including TFP, unemployment and per-capita hours worked. We find that the three variables are not informationally sufficient. When adding missing information, the effects of technology shocks change dramatically.

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File URL: http://research.barcelonagse.eu/tmp/working_papers/536.pdf
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Paper provided by Barcelona Graduate School of Economics in its series Working Papers with number 536.

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Date of creation: Feb 2011
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Handle: RePEc:bge:wpaper:536
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  1. Eric M. Leeper & Todd B. Walker & Shu-Chun Susan Yang, 2008. "Fiscal Foresight: Analytics and Econometrics," Caepr Working Papers 2008-013, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
  2. Domenico Giannone & Lucrezia Reichlin, 2006. "Does information help recovering structural shocks from past observations?," ULB Institutional Repository 2013/166169, ULB -- Universite Libre de Bruxelles.
  3. Jesús Fernández-Villaverde & Juan Francisco Rubio-Ramírez & Thomas Sargent, 2005. "A, B, C’s, (and D’s) for understanding VARs," Working Paper 2005-09, Federal Reserve Bank of Atlanta.
  4. Mario Forni & Luca Gambetti, 2010. "Fiscal Foresight and the Effects of Government Spending," UFAE and IAE Working Papers 851.10, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
  5. Chari, V.V. & Kehoe, Patrick J. & McGrattan, Ellen R., 2008. "Are structural VARs with long-run restrictions useful in developing business cycle theory?," Journal of Monetary Economics, Elsevier, vol. 55(8), pages 1337-1352, November.
  6. repec:ulb:ulbeco:2013/10125 is not listed on IDEAS
  7. Forni, Mario & Giannone, Domenico & Lippi, Marco & Reichlin, Lucrezia, 2007. "Opening the black box: structural factor models with large cross-sections," Working Paper Series 0712, European Central Bank.
  8. Ben S. Bernanke & Jean Boivin & Piotr Eliasz, 2004. "Measuring the effects of monetary policy: a factor-augmented vector autoregressive (FAVAR) approach," Finance and Economics Discussion Series 2004-03, Board of Governors of the Federal Reserve System (U.S.).
  9. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
  10. Alexei Onatski, 2005. "Determining the number of factors from empirical distribution of eigenvalues," Discussion Papers 0405-19, Columbia University, Department of Economics.
  11. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  12. Luca Gambetti, 2010. "Fiscal Policy, Foresight and the Trade Balance in the U.S," Working Papers 505, Barcelona Graduate School of Economics.
  13. Lawrence J. Christiano & Martin Eichenbaum & Robert Vigfusson, 2003. "What Happens After a Technology Shock?," NBER Working Papers 9819, National Bureau of Economic Research, Inc.
  14. Eric Leeper & Todd Walker, 2011. "Information Flows and News Driven Business Cycles," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 14(1), pages 55-71, January.
  15. Gelper, Sarah & Croux, Christophe, 2007. "Multivariate out-of-sample tests for Granger causality," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3319-3329, April.
  16. Marco Lippi & Lucrezia Reichlin, 1994. "VAR analysis, non-fundamental representations, Blashke matrices," ULB Institutional Repository 2013/10151, ULB -- Universite Libre de Bruxelles.
  17. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
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