Optimal Algorithmic Monetary Policy
This work addresses the challenge of designing predictable and consistent monetary policies for decentralized finance, though it appears incremental as it builds on existing algorithmic stablecoin concepts.
The paper tackles the problem of optimizing rule-based monetary policies for algorithmic stablecoins by proposing a model that balances price and supply stability, and it explores design variations and their implications for both private stablecoins and Central Bank Digital Currencies.
Centralized monetary policy, leading to persistent inflation, is often inconsistent, untrustworthy, and unpredictable. Algorithmic stablecoins enabled by blockchain technology are promising in solving this problem. Algorithmic stablecoins utilize a monetary policy that is entirely rule-based. However, there is little understanding of how to optimize the rule. We propose a model that trade-off the price for supply stability. We further study the comparative statics by varying several design features. Finally, we discuss the empirical implications for designing stablecoins by the private sector and Central Bank Digital Currency (CBDC) by the public sector.