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Learning and Inflation Convergence in the ERM

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  • Driffill, John
  • Miller, Marcus

Abstract

This paper develops a model where agents learn about the probability of devaluations in a fixed exchange rate regim e. The true probability of devaluation is assumed to be low (or zero) b ut agents are initially unsure about the government's intentions and st art with a high prior belief. Bayesian updating dictates that private sector expectations are revised down during periods when no devaluat ion occurs, but are sharply increased when a devaluation does occur. Thi s model of learning is embedded in a model of overlapping contracts to study the process of inflation convergence after ERM entry. The main results are that agents over-estimate the authorities' desired realignment rate, so inflation will be high in anticipation; but as the authorities do not actually devalue, there is a terms of trade loss leading to recession. Before long-run equilibrium in which agents correctly estimate realignment rates can be attained, competitivenes s losses actually have to be regained by a sustained deflation. Copyright 1993 by Royal Economic Society.

Suggested Citation

  • Driffill, John & Miller, Marcus, 1993. "Learning and Inflation Convergence in the ERM," Economic Journal, Royal Economic Society, vol. 103(417), pages 369-378, March.
  • Handle: RePEc:ecj:econjl:v:103:y:1993:i:417:p:369-78
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    References listed on IDEAS

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    Cited by:

    1. Miller, Marcus & Thampanishvong, Kannika & Zhang, Lei, 2003. "Learning to Forget? Contagion and Political Risk in Brazil," CEPR Discussion Papers 3785, C.E.P.R. Discussion Papers.
    2. Fabrizio Carmignani & Emilio Colombo & Patrizio Tirelli, 2004. "Consistency versus credibility: how do countries choose their exchange rate regime?," Working Papers 85, University of Milano-Bicocca, Department of Economics, revised Feb 2005.
    3. Ascari, Guido & Rankin, Neil, 2002. "Staggered wages and output dynamics under disinflation," Journal of Economic Dynamics and Control, Elsevier, vol. 26(4), pages 653-680, April.
    4. Horii, Ryo & Ono, Yoshiyasu, 2009. "Information Cycles and Depression in a Stochastic Money-in-Utility Model," MPRA Paper 13485, University Library of Munich, Germany.
    5. Mason, Robin & Välimäki, Juuso, 2011. "Learning about the arrival of sales," Journal of Economic Theory, Elsevier, vol. 146(4), pages 1699-1711, July.
    6. Christodoulakis, Nicos M. & Kalyvitis, Sarantis C., 1997. "Efficiency testing revisited: a foreign exchange market with Bayesian learning," Journal of International Money and Finance, Elsevier, vol. 16(3), pages 367-385, June.
    7. Ryo Horii & Yoshiyasu Ono, 2005. "Financial Crisis and Recovery: Learning-based Liquidity Preference Fluctuations," Macroeconomics 0504016, EconWPA.
    8. Carmignani, Fabrizio & Colombo, Emilio & Tirelli, Patrizio, 2008. "Exploring different views of exchange rate regime choice," Journal of International Money and Finance, Elsevier, vol. 27(7), pages 1177-1197, November.
    9. Ryo Horii & Yoshiyasu Ono, 2004. "Learning, Liquidity Preference, and Business Cycle," ISER Discussion Paper 0601, Institute of Social and Economic Research, Osaka University.

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