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Rational Error Correction

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  • Tinsley, P A

Abstract

Under general conditions, linear decision rules of agents with rational expectations are equivalent to restricted error corrections. However, empirical rejections of rational expectation restrictions are the rule, rather than the exception, in macroeconomics. Rejections often are conditioned on the assumption that agents aim to smooth only the levels of actions or are subject to geometric random delays. Generalizations of dynamic frictions on agent activities are suggested that yield closed-form, higher-order decision rules with improved statistical fits and infrequent rejections of rational expectations restrictions. Properties of these generalized "rational" error corrections are illustrated for producer pricing in manufacturing industries. Copyright 2002 by Kluwer Academic Publishers

Suggested Citation

  • Tinsley, P A, 2002. "Rational Error Correction," Computational Economics, Springer;Society for Computational Economics, vol. 19(2), pages 197-225, April.
    • Handle: RePEc:kap:compec:v:19:y:2002:i:2:p:197-225
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    1. Michael Arghyrou & Christopher Martin & Costas Milas, 2005. "Non-linear inflationary dynamics: evidence from the UK," Oxford Economic Papers, Oxford University Press, vol. 57(1), pages 51-69, January.
    2. Fanelli, Luca, 2006. "Multi-equational linear quadratic adjustment cost models with rational expectations and cointegration," Journal of Economic Dynamics and Control, Elsevier, vol. 30(3), pages 445-456, March.
    3. Angelini, Elena & Bokan, Nikola & Christoffel, Kai & Ciccarelli, Matteo & Zimic, Srečko, 2019. "Introducing ECB-BASE: The blueprint of the new ECB semi-structural model for the euro area," Working Paper Series 2315, European Central Bank.
    4. Sienknecht, Sebastian, 2016. "Reassessing price adjustment costs in DSGE models," MPRA Paper 73763, University Library of Munich, Germany.
    5. Pål Boug & Ådne Cappelen & Eilev S. Jansen & Anders Rygh Swensen, 2021. "The Consumption Euler Equation or the Keynesian Consumption Function?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(1), pages 252-272, February.
    6. Matthieu Lemoine & Harri Turunen & Mohammed Chahad & Antoine Lepetit & Anastasia Zhutova & Pierre Aldama & Pierrick Clerc & Jean-Pierre Laffargue, 2019. "The FR-BDF Model and an Assessment of Monetary Policy Transmission in France, Working Paper Series no. 736, Banque de France," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-02400611, HAL.
    7. Ireland, Peter N., 2001. "Sticky-price models of the business cycle: Specification and stability," Journal of Monetary Economics, Elsevier, vol. 47(1), pages 3-18, February.
    8. Jeanfils, Philippe & Burggraeve, Koen, 2008. ""NONAME": A new quarterly model for Belgium," Economic Modelling, Elsevier, vol. 25(1), pages 118-127, January.
    9. Kozicki, Sharon, 2012. "Macro has progressed," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 23-28.
    10. David Gbaguidi, 2012. "La courbe de Phillips : temps d’arbitrage et/ou arbitrage de temps," L'Actualité Economique, Société Canadienne de Science Economique, vol. 88(1), pages 87-119.
    11. Matthieu Lemoine & Harri Turunen & Mohammed Chahad & Antoine Lepetit & Anastasia Zhutova & Pierre Aldama & Pierrick Clerc & Jean-Pierre Laffargue, 2019. "The FR-BDF Model and an Assessment of Monetary Policy Transmission in France," Working papers 736, Banque de France.
    12. Christopher Martin & Michael Arghyrou & Costas Milas, 2004. "Nonlinear inflation dynamics: evidence from the UK," Money Macro and Finance (MMF) Research Group Conference 2003 59, Money Macro and Finance Research Group.

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