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Monetary Policy And Debt Deflation: Some Computational Experiments

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  • Chiarella, C.
  • Di Guilmi, C.

Abstract

The paper presents an agent-based model to study the possible effects of different fiscal and monetary policies in the context of debt deflation. We introduce a modified Taylor rule that includes the financial position of firms as a target. Monte Carlo simulations provide a representation of the complex feedback effects generated by the interaction among the different transmission channels of monetary policy. The model also reproduces the evidence of low inflation during stock market booms and shows how it can lead to overinvestment and destabilize the system. The paper also investigates the possible reasons behind this stylized fact by testing different behavioral rules for the central bank. We find that, in a context of sticky prices and volatile expectations, endogenous credit creation can be identified as the main source of the divergent dynamics of prices in the real and financial sectors.

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  • Chiarella, C. & Di Guilmi, C., 2017. "Monetary Policy And Debt Deflation: Some Computational Experiments," Macroeconomic Dynamics, Cambridge University Press, vol. 21(1), pages 214-242, January.
    • Handle: RePEc:cup:macdyn:v:21:y:2017:i:01:p:214-242_00
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    References listed on IDEAS

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    Cited by:

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    2. Deryugina, Elena & Ponomarenko, Alexey & Rozhkova, Anna, 2020. "When are credit gap estimates reliable?," Economic Analysis and Policy, Elsevier, vol. 67(C), pages 221-238.
    3. Marco Bardoscia & Adrian Carro & Marc Hinterschweiger & Mauro Napoletano & Lilit Popoyan & Andrea Roventini & Arzu Uluc, 2024. "The impact of prudential regulations on the UK housing market and economy: Insights from an agent-based model," Working Papers 118, Queen Mary, University of London, School of Business and Management, Centre for Globalisation Research.
    4. repec:hal:cepnwp:hal-01527740 is not listed on IDEAS
    5. Reissl, Severin, 2020. "Minsky from the bottom up – Formalising the two-price model of investment in a simple agent-based framework," Journal of Economic Behavior & Organization, Elsevier, vol. 177(C), pages 109-142.
    6. Michel Alexandre & Gilberto Tadeu Lima, 2020. "Combining monetary policy and prudential regulation: an agent-based modeling approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(2), pages 385-411, April.
    7. Popoyan, Lilit & Napoletano, Mauro & Roventini, Andrea, 2020. "Winter is possibly not coming: Mitigating financial instability in an agent-based model with interbank market," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    8. Isabelle Salle & Pascal Seppecher, 2017. "Stabilizing an Unstable Complex Economy," Working Papers hal-01527740, HAL.
    9. Roberto Veneziani & Luca Zamparelli & Corrado Di Guilmi, 2017. "The Agent-Based Approach To Post Keynesian Macro-Modeling," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1183-1203, December.
    10. Guilmi, Corrado Di & Fujiwara, Yoshi, 2022. "Dual labor market, financial fragility, and deflation in an agent-based model of the Japanese macroeconomy," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 346-371.
    11. Carl Chiarella & Corrado Di Guilmi, 2014. "Financial instability and debt deflation dynamics in a bottom-up approach," Economics Bulletin, AccessEcon, vol. 34(1), pages 125-132.

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    More about this item

    JEL classification:

    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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