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Price level targeting with evolving credibility

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  • Honkapohja, Seppo
  • Mitra, Kaushik

Abstract

Global learning dynamics for price-level targeting (PLT) monetary policy are analyzed and compared to inflation targeting in a nonlinear New Keynesian model. Domain of attraction of target steady state is a new robustness criterion for policy regimes. Robustness of PLT depends on whether a known target path is incorporated into learning. Credibility is measured by accuracy of this forecasting method relative to simple statistical forecasts evolving through reinforcement learning. Initial credibility and target price are key factors influencing performance. Model results are in line with the Swedish experience of price stabilization in1930’s.

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  • Honkapohja, Seppo & Mitra, Kaushik, 2020. "Price level targeting with evolving credibility," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 88-103.
  • Handle: RePEc:eee:moneco:v:116:y:2020:i:c:p:88-103
    DOI: 10.1016/j.jmoneco.2019.09.009
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    Cited by:

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    3. George W. Evans & Seppo Honkapohja & Kaushik Mitra, 2022. "Expectations, Stagnation, And Fiscal Policy: A Nonlinear Analysis," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1397-1425, August.
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    9. Elfsbacka Schmöller, Michaela & Spitzer, Martin, 2022. "Lower for longer under endogenous technology growth," Bank of Finland Research Discussion Papers 6/2022, Bank of Finland.
    10. Cole, Stephen J., 2020. "The influence of learning and price-level targeting on central bank forward guidance," Journal of Macroeconomics, Elsevier, vol. 65(C).
    11. Olena Kostyshyna & Luba Petersen & Jing Yang, 2022. "A Horse Race of Monetary Policy Regimes: An Experimental Investigation," Staff Working Papers 22-33, Bank of Canada.
    12. Bodenstein, Martin & Hebden, James & Winkler, Fabian, 2022. "Learning and misperception of makeup strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
    13. Paloviita, Maritta & Haavio, Markus & Jalasjoki, Pirkka & Kilponen, Juha, 2017. "What does "below, but close to, two percent" mean? Assessing the ECB's reaction function with real time data," Bank of Finland Research Discussion Papers 29/2017, Bank of Finland.
    14. Evans, David & Evans, George W. & McGough, Bruce, 2022. "Bounded rationality and unemployment dynamics," Economics Letters, Elsevier, vol. 210(C).
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    16. Maritta Paloviita & Markus Haavio & Pirkka Jalasjoki & Juha Kilponen, 2021. "What Does "Below, but Close to, 2 Percent" Mean? Assessing the ECB's Reaction Function with Real-Time Data," International Journal of Central Banking, International Journal of Central Banking, vol. 17(2), pages 125-169, June.
    17. Dobrew, Michael & Gerke, Rafael & Giesen, Sebastian & Röttger, Joost, 2023. "Make-up strategies with incomplete markets and bounded rationality," Discussion Papers 01/2023, Deutsche Bundesbank.
    18. Smith, Thomas & Tadesse, Amanuel F. & Vincent, Nishani Edirisinghe, 2021. "The impact of CIO characteristics on data breaches," International Journal of Accounting Information Systems, Elsevier, vol. 43(C).
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    23. Michał Brzoza-Brzezina & Jacek Suda, 2021. "Are DSGE models irreparably flawed?," Bank i Kredyt, Narodowy Bank Polski, vol. 52(3), pages 227-252.
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    More about this item

    Keywords

    Adaptive learning; Limited credibility; Inflation targeting; Zero interest rate lower bound;
    All these keywords.

    JEL classification:

    • 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
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies

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