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Swiss Journal of Economics and Statistics

, Volume 146, Issue 1, pp 107–120 | Cite as

Indeterminacy, causality, and the foundations of monetary policy analysis

  • Bennett T. McCallum
Open Access
Article
  • 22 Downloads

Summary

To be useful as a guide to behavior, a model that includes a relationship between x t and zt+1 must specify whether x t is influenced by the expectation at t of zt+1 or, that zt+1 is inertially influenced by x t . We show that, for a broad class of linear RE models, distinct causal specifications will be uniquely associated with distinct solutions. Alternatively, a solution refinement requiring continuity of solution coefficients with respect to basic parameters implies this same solution. For a given structure there is only one RE solution that is fully consistent with the model’s specification.

Keywords

Causality Indetermacy Relational Expectations Equilibria 

JEL-Classification

C61 C62 E37 

References

  1. Blanchard, Olivier J. (1979), “Backward and Forward Solutions for Economies with Rational Expectations”, American Economic Review, 69, pp. 114–118.Google Scholar
  2. Blanchard, Olivier J., and Charles M. Kahn (1980), “The Solution of Linear Difference Models Under Rational Expectations”, Econometrica, 48, pp. 1305–1311.CrossRefGoogle Scholar
  3. Calvo, Guillermo (1978), “On the Indeterminacy of Interest Rates and Wages with Perfect Foresight”, Journal of Economic Theory, 19, pp. 321–337.CrossRefGoogle Scholar
  4. Cho, Seonghoon, and Bennett T. McCallum (2009), “Another Weakness of ‘Determinacy’ as a Selection Criterion for Rational Expectations Models”, Economics Letters, 104, pp. 17–19.CrossRefGoogle Scholar
  5. Cochrane, John H. (2007), “Inflation Determination with Taylor Rules: A Critical Review”, NBER Working Paper 13409.Google Scholar
  6. Evans, George W., and Seppo Honkapohja (2001), Learning and Expectations in Macroeconomics, Princeton.Google Scholar
  7. Golub, Gene H., and Charles F. Van Loan (1996), Matrix Computations, 3rd ed. Baltimore.Google Scholar
  8. Horn, Roger A., and Charles R. Johnson (1985), Matrix Analysis, New York.Google Scholar
  9. Horn, Roger A., and Charles R. Johnson (1991), Topics in Matrix Analysis, Cambridge University Press.Google Scholar
  10. King, Robert G., and Mark W. Watson (1998), “The Solution of Singular Linear Difference Systems Under Rational Expectations”, International Economic Review, 39, pp. 1015–1026.CrossRefGoogle Scholar
  11. Klein, Paul (2000), “Using the Generalized Schur Form to Solve a Multivariate Linear Rational Expectations Model”, Journal of Economic Dynamics and Control, 24, pp. 1405–1423.CrossRefGoogle Scholar
  12. Lubik, Thomas A., and Frank Schorfheide (2003), “Computing Sunspot Equilibria in Linear Rational Expectations Models”, Journal of Economic Dynamics and Control, 28, pp. 273–285.CrossRefGoogle Scholar
  13. McCallum, Bennett T. (1983), “On Nonuniqueness in Linear Rational Expectations Models: An Attempt at Perspective”, Journal of Monetary Economics, 11, pp. 139–168.CrossRefGoogle Scholar
  14. McCallum, Bennett T. (2003), “Multiple-Solution Indeterminacies in Monetary Policy Analysis”, Journal of Monetary Economics, 50, pp. 1153–1175.CrossRefGoogle Scholar
  15. McCallum, Bennett T. (2009a), “Causality, Structure, and the Uniqueness of Rational Expectations Equilibria”, NBER Working Paper 15234.Google Scholar
  16. McCallum, Bennett T. (2009b), “A Continuity Refinement for Rational Expectations Solutions”, Working Paper, Carnegie Mellon University.Google Scholar
  17. McCallum, Bennett T. (2009c), “Inflation Determination with Taylor Rules: Is New-Keynesian Analysis Critically Flawed?”, Journal of Monetary Economics, 56, pp. 1101–1108 and 1114–1115.CrossRefGoogle Scholar
  18. Sargent, Thomas J. (1979) Macroeconomic Theory, Academic Press (2nd edition 1987).Google Scholar
  19. Simon, Herbert A. (1953) “Causal Ordering and Identifiability”, in W.C. Hood and T.C. Koopmans (eds), Studies in Econometric Method, Cowles Commission Monograph No. 14, New York.Google Scholar
  20. Sims, Christopher A. (2002), “Solving Linear Rational Expectations Models”, Computational Economics, 20, pp. 1–20.CrossRefGoogle Scholar
  21. Uhlig, Harald (1999), “A Toolkit for Analyzing Nonlinear Dynamic Stochastic Models Easily”, in Ramon Marimon and Andrew Scott (eds), Computational Methods for the Study of Dynamic Economies, Oxford.Google Scholar
  22. Zellner, Arnold (1979) “Causality and Econometrics”, Carnegie-Rochester Conference Series on Public Policy 10, pp. 9–54.CrossRefGoogle Scholar

Copyright information

© Swiss Society of Economics and Statistics 2010

Authors and Affiliations

  • Bennett T. McCallum
    • 1
  1. 1.Swiss Re Centre for Global DialogueRüschlikonSwitzerland

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