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Currency crisis: Evolution of beliefs and policy experiments

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  • Arifovic, Jasmina
  • Maschek, Michael K.

Abstract

We study a model of currency crisis where agents’ beliefs are the only source of volatility containing the potential for currency devaluation. Using the basic framework of Arifovic and Masson (2003), we simulate the model for a large number of parameter specifications. The learning dynamics of our agent-based computational model, based on imitation of successful expectational rules and occasional experimentation, result in recurrent currency crises. Recurrent crises are a robust feature of the dynamics regardless of the model's parameter specifications. We discuss both the impact of imitation and experimentation on the model's dynamics, as well as the impact of the parameter values on the duration of episodes of devaluation and periods of no-devaluation. In addition, we compare the first difference in interest rate spread statistics of the data generated in our simulations and real world data. Finally, we conduct policy experiments in our agent-based type environment designed to examine the power of the interest rate policy changes in decreasing the number as well as the duration of the episodes of currency crisis. Our results indicate that the policy of decreasing, rather than increasing, the emerging market interest rate proves more effective at reducing the likelihood of devaluation.

Suggested Citation

  • Arifovic, Jasmina & Maschek, Michael K., 2012. "Currency crisis: Evolution of beliefs and policy experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 82(1), pages 131-150.
  • Handle: RePEc:eee:jeborg:v:82:y:2012:i:1:p:131-150
    DOI: 10.1016/j.jebo.2012.01.001
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    References listed on IDEAS

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    1. Jeanne, Olivier & Masson, Paul, 2000. "Currency crises, sunspots and Markov-switching regimes," Journal of International Economics, Elsevier, vol. 50(2), pages 327-350, April.
    2. Corsetti, Giancarlo & Pesenti, Paolo & Roubini, Nouriel, 1999. "What caused the Asian currency and financial crisis?," Japan and the World Economy, Elsevier, vol. 11(3), pages 305-373, October.
    3. Arifovic, Jasmina, 1996. "The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 510-541, June.
    4. Krugman, Paul, 1979. "A Model of Balance-of-Payments Crises," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 11(3), pages 311-325, August.
    5. Lux, Thomas & Schornstein, Sascha, 2005. "Genetic learning as an explanation of stylized facts of foreign exchange markets," Journal of Mathematical Economics, Elsevier, vol. 41(1-2), pages 169-196, February.
    6. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
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    Cited by:

    1. Giorgio Fagiolo & Andrea Roventini, 2017. "Macroeconomic Policy in DSGE and Agent-Based Models Redux: New Developments and Challenges Ahead," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 20(1), pages 1-1.
    2. Olga Shurchkov, 2013. "Coordination and learning in dynamic global games: experimental evidence," Experimental Economics, Springer;Economic Science Association, vol. 16(3), pages 313-334, September.
    3. Kato, Mika & Proaño, Christian R. & Semmler, Willi, 2018. "Does international-reserves targeting decrease the vulnerability to capital flights?," Research in International Business and Finance, Elsevier, vol. 44(C), pages 64-75.
    4. Bogna Gawronska-Nowak & Wojciech Grabowski, 2016. "Using Genetic Algorithm In Dynamic Model Of Speculative Attack," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(2), pages 287-306, June.
    5. repec:hal:spmain:info:hdl:2441/dcditnq6282sbu1u151qe5p7f is not listed on IDEAS

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    More about this item

    Keywords

    Currency crisis; Evolution of beliefs; Policy implications;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods

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