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A SOLUTION METHOD FOR LINEAR RATIONAL EXPECTATION MODELS UNDER IMPERFECT INFORMATION

Published online by Cambridge University Press:  11 May 2011

Katsuyuki Shibayama
Katsuyuki Shibayama*
Affiliation:
University of Kent at Canterbury
*
Address correspondence to: Katsuyuki Shibayama, School of Economics, University of Kent, Canterbury, Kent CT2 7NP, UK; e-mail: k.shibayama@kent.ac.uk.
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Abstract

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This article presents a solution algorithm for linear rational expectation models under imperfect information, in which some decisions are made based on smaller information sets than others. In our solution representation, imperfect information does not affect the coefficients on crawling variables, which implies that, if a perfect-information model exhibits saddle-path stability, for example, the corresponding imperfect-information models also exhibit saddle-path stability. However, imperfect information can significantly alter the quantitative properties of a model. Indeed, this article demonstrates that, with a predetermined wage contract, the standard RBC model remarkably improves the correlation between labor productivity and output.

Keywords

Linear Rational Expectation ModelsImperfect Information

Information

Type
Articles
Information
Macroeconomic Dynamics , Volume 15 , Issue 4 , September 2011 , pp. 465 - 494
Copyright
Copyright © Cambridge University Press 2011

References

REFERENCES

Blanchard, Olivier Jean and Kahn, Charles M. (1980) The solution of linear difference models under rational expectations. Econometrica 48, 1305–1312.CrossRefGoogle Scholar
Boyd, John H. and Dotsey, Michael (1990) Interest Rate Rues and Nominal Determinacy. Working paper, Federal Reserve Bank of Richmond.Google Scholar
Christiano, Lawrence J. (1998) Solving Dynamic Equilibrium Models by a Method of Undetermined Coefficients. NBER technical working papers 225.Google Scholar
Cooley, Thomas F. and Prescott, Edward C. (1995) Economic growth and business cycles. In Cooley, Thomas F. (ed.), Frontiers of Business Cycle Research, pp. 1–38. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Dupor, Bill and Tsuruga, Takayuki (2005) Sticky information: The impact of different information updating assumptions. Journal of Money, Credit and Banking 37, 1143–1152.CrossRefGoogle Scholar
King, Robert G. and Watson, Mark W. (1998) The solution of singular linear difference systems under rational expectations. International Economic Review 39, 1015–1026.CrossRefGoogle Scholar
King, Robert G. and Watson, Mark W. (2002) System reduction and solution algorithms for singular linear difference systems under rational expectations. Computational Economics 20, 57–86.CrossRefGoogle Scholar
Klein, Paul (2000) Using the generalized Schur form to solve a multivariate linear rational expectations model. Journal of Economic Dynamics and Control 10, 1405–1423.CrossRefGoogle Scholar
Mankiw, Gregory N. and Reis, Ricardo (2001) Sticky Information Versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve. NBER working papers 8290.CrossRefGoogle Scholar
Sims, Christopher A. (2002) Solving linear rational expectations models. Computational Economics 20, 1–20.CrossRefGoogle Scholar
Uhlig, Harald (1999) A toolkit for analyzing nonlinear dynamic stochastic models easily. In Marimon, Ramon and Scott, Andrew (eds.), Computational Methods for the Study of Dynamic Economics, pp. 30–61. Oxford, UK: Oxford University Press.Google Scholar
Wang, Pengfei and Wen, Yi (2006) Solving Linear Difference Systems with Lagged Expectations by a Method of Undetermined Coefficients. Working paper 2006-003C, Federal Reserve Bank of St. Louis.CrossRefGoogle Scholar
Woodford, Michael (undated) Reds-Solds User's Guide. Mimeo, Princeton University.Google Scholar