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Learning Hyperinflations

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  • Atanas Christev

    (Heriot-Watt University, Edinburgh)

Abstract

Emprical studies of hyperinflations reveal that the rational expectations hypothesis fails to hold. To address this issue, we study a model of hyperinflation and learning in an attempt to better understand the volatility in movements of expectations, money, and prices. The findings surprisingly imply that the dynamics under neural network learning appear to support the outcome achieved under least squares learning reported in the earlier literature. Relaxing the assumption that inflationary expectations are rational, however, is essential since it improves the fit of the model to actual data from episodes of severe hyperinflation. Simulations provide ample evidence that if equilibrium in the model exists, then the inflation rate converges to the low inflation rational expectations equilibrium. This suggests a classical result: a permanent increase in the government deficit raises the stationary inflation rate (Marcet and Sargent, 1989)

Suggested Citation

  • Atanas Christev, 2007. "Learning Hyperinflations," Money Macro and Finance (MMF) Research Group Conference 2006 126, Money Macro and Finance Research Group.
  • Handle: RePEc:mmf:mmfc06:126
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    References listed on IDEAS

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    Keywords

    Hyperinflation; Learning; Rational Expectations Equlibria; Neural Networks;

    JEL classification:

    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • E63 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Comparative or Joint Analysis of Fiscal and Monetary Policy; Stabilization; Treasury Policy
    • E65 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Studies of Particular Policy Episodes

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