Application of Artificial Intelligence for Monetary Policy-Making

Mariam Dundua () and Otar Gorgodze ()
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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

No 02/2022, NBG Working Papers from 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.

Keywords: Artificial Intelligence; Reinforcement Learning; Monetary policy (search for similar items in EconPapers)
JEL-codes: C45 C60 C61 C63 E17 E52 (search for similar items in EconPapers)
Pages: 60 pages
Date: 2022-11
New Economics Papers: this item is included in nep-ain, nep-big, nep-cmp, nep-mon and nep-tra
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Persistent link: https://EconPapers.repec.org/RePEc:aez:wpaper:2022-02

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