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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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    Cited by:

    1. Ryo Horii & Yoshiyasu Ono, 2022. "Financial crisis and slow recovery with Bayesian learning agents," International Journal of Economic Theory, The International Society for Economic Theory, vol. 18(4), pages 578-606, December.
    2. 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.
    3. Miller, Marcus & Thampanishvong, Kannika, 2003. "Learning to Forget? Contagion and Political Risk in Brazil," CEPR Discussion Papers 3785, C.E.P.R. Discussion Papers.
    4. Ryo Horii & Yoshiyasu Ono, 2004. "Learning, Liquidity Preference, and Business Cycle," ISER Discussion Paper 0601, Institute of Social and Economic Research, Osaka University.
    5. Kobielarz, Michal, 2018. "The economics of monetary unions," Other publications TiSEM b0293536-68ec-4905-bffd-6, Tilburg University, School of Economics and Management.
    6. 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.
    7. Horii, Ryo & Ono, Yoshiyasu, 2009. "Information Cycles and Depression in a Stochastic Money-in-Utility Model," MPRA Paper 13485, University Library of Munich, Germany.
    8. Mason, Robin & Välimäki, Juuso, 2011. "Learning about the arrival of sales," Journal of Economic Theory, Elsevier, vol. 146(4), pages 1699-1711, July.
    9. 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.
    10. Ryo Horii & Yoshiyasu Ono, 2005. "Financial Crisis and Recovery: Learning-based Liquidity Preference Fluctuations," Macroeconomics 0504016, University Library of Munich, Germany.
    11. 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.

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