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Application of Artificial Intelligence for Monetary Policy-Making

Author

Listed:
  • Mariam Dundua

    (Financial and Supervisory Technology Development Department, National Bank of Georgia)

  • Otar Gorgodze

    (Head of Financial and Supervisory Technologies Department, National Bank of Georgia)

Abstract

The recent advances in Artificial Intelligence (AI), in particular, the development of reinforcement learning (RL) methods, are specifically suited for application to complex economic problems. We formulate a new approach looking for optimal monetary policy rules using RL. Analysis of AI generated monetary policy rules indicates that optimal policy rules exhibit significant nonlinearities. This could explain why simple monetary rules based on traditional linear modeling toolkits lack the robustness needed for practical application. The generated transition equations analysis allows us to estimate the neutral policy rate, which came out to be 6.5 percent. We discuss the potential combination of the method with state-of-the-art FinTech developments in digital finance like DeFi and CBDC and the feasibility of MonetaryTech approach to monetary policy.

Suggested Citation

  • Mariam Dundua & Otar Gorgodze, 2022. "Application of Artificial Intelligence for Monetary Policy-Making," NBG Working Papers 02/2022, National Bank of Georgia.
    • Handle: RePEc:aez:wpaper:2022-02
    as

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    File URL: https://nbg.gov.ge/fm/wp/nbg-wp-2022-02.pdf
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    References listed on IDEAS

    as
    1. Sinitskaya, Ekaterina & Tesfatsion, Leigh, 2015. "Macroeconomies as constructively rational games," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 152-182.
    2. Milton Friedman & Anna J. Schwartz, 1963. "A Monetary History of the United States, 1867–1960," NBER Books, National Bureau of Economic Research, Inc, number frie63-1, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Artificial Intelligence; Reinforcement Learning; Monetary policy;
    All these keywords.

    JEL classification:

    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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