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A Note on Information Flows and Identification of News Shocks Models

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  • Marco M. Sorge

Abstract

This note points out a hitherto unrecognised identification issue in a class of rational expectations (RE) models with news shocks. We show that different degrees of anticipation (information flows) have strikingly different implications for the identifiability of the underlying structural model, irrespective of its non-fundamental time-series representation. In particular, under full shock anticipation equilibrium reduced forms behave as noisy perfect foresight state motions, which are non-identifiable. As a consequence, the underlying news shocks model fails to be (first-order) identified. The identification failure is illustrated with a New Keynesian model that can be solved analytically.

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  • Marco M. Sorge, 2013. "A Note on Information Flows and Identification of News Shocks Models," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 56(1), pages 28-38.
  • Handle: RePEc:eei:journl:v:56:y:2013:i:1:p:28-38
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    1. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    2. Broze, L. & Szafarz, A., 1984. "On linear models with rational expectations which admit a unique solution," European Economic Review, Elsevier, vol. 24(1), pages 103-111.
    3. Ippei Fujiwara & Yasuo Hirose & Mototsugu Shintani, 2011. "Can News Be a Major Source of Aggregate Fluctuations? A Bayesian DSGE Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(1), pages 1-29, February.
    4. Bennett T. McCallum & Edward Nelson, 2004. "Timeless perspective vs. discretionary monetary policy in forward-looking models," Review, Federal Reserve Bank of St. Louis, vol. 86(Mar), pages 43-56.
    5. 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.
    6. Eric M. Leeper & Todd B. Walker & Shu-Chun Susan Yang, 2008. "Fiscal Foresight: Analytics and Econometrics," NBER Working Papers 14028, National Bureau of Economic Research, Inc.
    7. Marco M. Sorge, 2013. "A Note on Information Flows and Identification of News Shocks Models," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 56(1), pages 28-38.
    8. Masanao Aoki & Matthew Canzoneri, 1979. "Reduced Forms of Rational Expectations Models," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 93(1), pages 59-71.
    9. Pesaran, M. H., 1981. "Identification of rational expectations models," Journal of Econometrics, Elsevier, vol. 16(3), pages 375-398, August.
    10. Beaudry, Paul & Portier, Franck, 2004. "An exploration into Pigou's theory of cycles," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1183-1216, September.
    11. Fève, Patrick & Matheron, Julien & Sahuc, Jean-Guillaume, 2009. "On the dynamic implications of news shocks," Economics Letters, Elsevier, vol. 102(2), pages 96-98, February.
    12. Taylor, John B, 1977. "Conditions for Unique Solutions in Stochastic Macroeconomic Models with Rational Expectations," Econometrica, Econometric Society, vol. 45(6), pages 1377-1385, September.
    13. Beaudry, Paul & Portier, Franck, 2007. "When can changes in expectations cause business cycle fluctuations in neo-classical settings?," Journal of Economic Theory, Elsevier, vol. 135(1), pages 458-477, July.
    14. Barsky, Robert B. & Sims, Eric R., 2011. "News shocks and business cycles," Journal of Monetary Economics, Elsevier, vol. 58(3), pages 273-289.
    15. Wegge, Leon L. & Feldman, Mark, 1983. "Identifiability criteria for Muth-rational expectations models," Journal of Econometrics, Elsevier, vol. 21(2), pages 245-254, February.
    16. George Evans & Seppo Honkapohja, 1986. "A Complete Characterization of ARMA Solutions to Linear Rational Expectations Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(2), pages 227-239.
    17. Eric M. Leeper & Todd B. Walker & Shu-Chun Susan Yang, 2008. "Fiscal Foresight: Analytics and Econometrics," NBER Working Papers 14028, National Bureau of Economic Research, Inc.
    18. Féve, Patrick & Jidoud, Ahmat, 2012. "Identifying News Shocks from SVARs," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 919-932.
    19. Sorge, Marco M., 2012. "News shocks or parametric indeterminacy? An observational equivalence result in linear rational expectations models," Economics Letters, Elsevier, vol. 114(2), pages 198-200.
    20. Laurence Broze & Ariane Szafarz, 1991. "The Econometric Analysis of Non-Uniqueness in Rational Expectations Models," ULB Institutional Repository 2013/649, ULB -- Universite Libre de Bruxelles.
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    Cited by:

    1. Paul Beaudry & Franck Portier, 2014. "News-Driven Business Cycles: Insights and Challenges," Journal of Economic Literature, American Economic Association, vol. 52(4), pages 993-1074, December.
    2. Marco M. Sorge, 2013. "A Note on Information Flows and Identification of News Shocks Models," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 56(1), pages 28-38.

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    More about this item

    Keywords

    Rational expectations; perfect foresight; news shocks; identification.;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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