2023-02-10-IMF-需求还是不需求_量化CBDC的未来需求（英）_55页_4mb

Summary of IMF Working Paper: "To Demand or Not to Demand: On Quantifying the Future Appetite for CBDC"

1. Introduction and Purpose
This paper analyzes the potential impact and demand for Central Bank Digital Currency (CBDC) using a novel agent-based model. The goal is to quantify how CBDC adoption would affect monetary dynamics, bank profitability, central bank revenues, and monetary policy transmission under various behavioral assumptions and interest rate settings.

2. Methodology

• A structural, stock-flow consistent, agent-based model is developed, integrating choice theory, game theory, and reinforcement learning.
• The model simulates banks, non-bank agents, and the central bank, capturing behavioral choices and financial flows.
• Key inputs include macroeconomic data like total money stocks and deposit rates, calibrated to reflect country-specific conditions.
• A Thompson Sampling-based reinforcement learning algorithm enables banks to collectively find Nash equilibria for deposit rates in dynamic simulations.

3. Key Findings

• CBDC Demand: U.S. CBDC demand ranges from 5% to 25% of total money under "cash-like" or "deposit-like" perceptions; euro-area demand ranges from 1% to 20%. Actual adoption is likely lower than upper bounds.
• Deposit Rate Spreads: Bank deposit rates to policy rates decrease (e.g., 16-20 basis points in the U.S.), potentially strengthening monetary policy pass-through (up to 0.95 for the U.S., 0.97 for the euro area).
• Bank Profitability: Banks' net income and dividends decline due to rising reserve borrowing costs offsetting falls in deposit expenses.
• Central Bank Seigniorage: This is nonlinear with CBDC interest rates; it rises with low rates but falls as rates increase, affecting net income.
• Broader Effects: Falling CBDC demand crowds out cash or deposits; network effects and design features (e.g., interest rates, base utility) significantly influence outcomes.

4. Implications and Recommendations

• CBDC introduction could reduce bank profitability and increase central bank revenue at low interest rates, but risks include disintermediation concerns and behavioral uncertainties.
• Model-based insights can inform CBDC design, such as interest-bearing rates, to enhance monetary policy and financial stability.
• Replication tools are provided for policymakers to apply the model to other jurisdictions and refine counterfactuals.

5. Model Extensions and Limitations

• The model can be extended to incorporate factors like collateral requirements, sovereign bond markets, or heterogenous bank market power.
• Limitations include sensitivity to behavioral assumptions and estimation uncertainties in price sensitivity parameters.