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Application Of An Adaptive Step-Size Algorithm In Models Of Hyperinflation

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  • Kostyshyna, Olena

Abstract

An adaptive step-size algorithm [Kushner and Yin, Stochastic Approximation and Recursive Algorithms and Applications, 2nd ed., New York: Springer-Verlag (2003)] is used to model time-varying learning, and its performance is illustrated in the environment of Marcet and Nicolini [American Economic Review 93 (2003), 1476–1498]. The resulting model gives qualitatively similar results to those of Marcet and Nicolini, and performs quantitatively somewhat better, based on the criterion of mean squared error. The model generates increasing gain during hyperinflations and decreasing gain after hyperinflations end, which matches findings in the data. An agent using this model behaves cautiously when faced with sudden changes in policy, and is able to recognize a regime change after acquiring sufficient information.

Suggested Citation

  • Kostyshyna, Olena, 2012. "Application Of An Adaptive Step-Size Algorithm In Models Of Hyperinflation," Macroeconomic Dynamics, Cambridge University Press, vol. 16(S3), pages 355-375, November.
    • Handle: RePEc:cup:macdyn:v:16:y:2012:i:s3:p:355-375_00
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    Cited by:

    1. Jaqueson K. Galimberti, 2020. "Information weighting under least squares learning," CAMA Working Papers 2020-46, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    2. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
    3. Takuro Uehara & Yoko Nagase & Wayne Wakeland, 2016. "Integrating Economics and System Dynamics Approaches for Modelling an Ecological–Economic System," Systems Research and Behavioral Science, Wiley Blackwell, vol. 33(4), pages 515-531, July.
    4. Gáti, Laura, 2023. "Monetary policy & anchored expectations—An endogenous gain learning model," Journal of Monetary Economics, Elsevier, vol. 140(S), pages 37-47.
    5. Hartwell, Christopher A & Szybisz, Martin Andres, 2021. "Corralling Expectations: The Role of Institutions in (Hyper)Inflation," MPRA Paper 105612, University Library of Munich, Germany.
    6. Mauersberger, Felix, 2021. "Monetary policy rules in a non-rational world: A macroeconomic experiment," Journal of Economic Theory, Elsevier, vol. 197(C).
    7. Carlos Carvalho & Stefano Eusepi & Emanuel Moench & Bruce Preston, 2023. "Anchored Inflation Expectations," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(1), pages 1-47, January.
    8. Cone, Thomas E., 2022. "Learning with unobserved regimes," Journal of Macroeconomics, Elsevier, vol. 73(C).
    9. Milani, Fabio, 2014. "Learning and time-varying macroeconomic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 47(C), pages 94-114.

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