Introduction
A CBDC (Central Bank Digital Currency — digital money issued directly by a country's central bank, like a digital version of cash) could cause bank disintermediation (when people move their money from commercial banks to the central bank's digital currency). This model simulates how bank deposits D change over time using a differential equation (a formula describing how something changes from one moment to the next):
dD/dt = -α(r_CBDC - r_D)D + β·confidence(t)
Where:
- α (alpha) = rate sensitivity — how strongly the interest rate gap drives deposit outflow
- r_CBDC = interest rate on CBDC
- r_D = interest rate on bank deposits
- β (beta) = confidence sensitivity — how much public confidence affects deposits
- ODE = Ordinary Differential Equation — a math formula that describes continuous change over time
Variations to Explore
Variation 1: Increase Rate Sensitivity
Task: Change α from 0.8 to 2.0
Question: How much faster do deposits flee when people are more sensitive to interest rate differences?
Variation 2: Zero CBDC Interest Rate
Task: Set CBDC rate to 0% in all scenarios (instead of 0%, 1%, 2%)
Question: Do banks still lose deposits even if CBDC pays nothing? Why or why not?
Variation 3: Early Crisis
Task: Move crisis start from quarter 8 to quarter 2
Question: How does an early crisis change the outcomes? Why does timing matter?
Open Extension
Task: Add a "tiered CBDC" scenario where:
- CBDC pays 2% interest on the first EUR 3,000
- CBDC pays 0% interest above EUR 3,000
Question: How does this tiered structure protect banks compared to a flat 2% CBDC rate? Who benefits most from this policy design?
How to Run
- Google Colab (recommended): Upload the chart.py file to Google Colab
- Install dependencies: Run
!pip install scipy in a Colab cell (needed for solving the differential equation)
- Run the code: Execute the chart.py file
- Create variations: Modify parameters and observe changes
Time Allocation
- 45 minutes: Run variations 1-3, analyze results, prepare slides
- 10 minutes: Present findings to class
Deliverables
- Presentation slides (5-7 slides) showing:
- The baseline model and what it means
- Results from all three variations with charts
- Your interpretation of what changes
- (Optional) Extension results for tiered CBDC
- Key insight: What is the most important policy lever for protecting banks from CBDC competition?
References
- Brunnermeier, M. K., & Niepelt, D. (2019). On the Equivalence of Private and Public Money. Journal of Monetary Economics, 106, 27-41.
- Bindseil, U. (2020). Tiered CBDC and the financial system. ECB Working Paper Series, No. 2351.
Show Model Answer Presentation
Slide 1
CBDC and Bank Disintermediation
Will Central Bank Digital Currencies Kill Commercial Banks?
Reference: Brunnermeier & Niepelt (2019) - On the Equivalence of Private and Public Money
Slide 2
The Model: How Deposits Change Over Time
Differential Equation:
dD/dt = -α(r_CBDC - r_D)D + β·confidence(t)
In Plain Language:
The rate of deposit outflow from banks depends on two forces:
- Interest Rate Gap (-α term): If CBDC pays more than bank deposits, people move money to CBDC. The bigger the gap, the faster the outflow. Parameter α (rate sensitivity) = 0.8 means deposits are moderately responsive to rate differences.
- Confidence Shocks (β term): During a crisis, people lose confidence and withdraw deposits even if rates are equal. Parameter β (confidence sensitivity) = 1.2 amplifies panic effects.
Slide 3
Baseline Results: Four Scenarios
Key Findings:
- 0% CBDC rate (green): Deposits barely change (<5% loss over 5 years)
- 1% CBDC rate (blue): Deposits fall to ~85% after 5 years
- 2% CBDC rate (orange): Deposits crash to ~65% (35% loss)
- Crisis + 1% CBDC (red): Combined shock drives deposits to ~70%, nearing tipping point
Slide 4
Variation 1: High Rate Sensitivity (α = 2.0)
Panel 2 (top-right): When α = 2.0 instead of 0.8, deposit outflow accelerates dramatically.
Result: With 2% CBDC rate, deposits collapse to ~40% (60% loss) — bank failure territory.
Interpretation: If people are highly sensitive to interest rates, even small CBDC rate advantages trigger massive disintermediation.
Slide 5
Variation 2: Zero CBDC Rate Always
Panel 3 (bottom-left): All scenarios have CBDC rate set to 0%.
Result: Deposits fall by less than 5% in all cases. Even the crisis scenario (red dashed) shows minimal outflow.
Key Insight: CBDC interest rate is the critical policy variable. Without an interest rate advantage, CBDC adoption remains low regardless of other factors.
Policy Implication: Central banks can protect commercial banks by keeping CBDC rates at or below deposit rates.
Slide 6
Variation 3: Early Crisis (Quarter 2 Instead of 8)
Panel 4 (bottom-right): Crisis starts at quarter 2 instead of quarter 8.
Result: Deposits fall further (to ~60% instead of ~70%) because the confidence shock has more time to compound with interest rate effects.
Interpretation: Timing matters. An early crisis combined with CBDC competition gives less time for stabilization policies to work.
Real-world parallel: If CBDC launches during economic turbulence, disintermediation risks multiply.
Slide 7
Key Insight: CBDC Interest Rate is the Policy Lever
What We Learned:
- 0% CBDC rate = Safe: Banks keep deposits even during crises
- Rate above deposit rate = Dangerous: Disintermediation accelerates, especially if people are rate-sensitive (high α)
- Crisis timing matters: Early shocks compound over more quarters
Policy Tools:
- Rate ceiling: Cap CBDC interest at 1% → deposits stabilize at 75-80%
- Quantity limits: Restrict CBDC holdings → reduces α (rate sensitivity) by limiting arbitrage
- Tiered rates: Pay 2% on first EUR 3,000 only → protects small savers while limiting bank run risk
Bottom line: Central banks face a trade-off. Higher CBDC rates attract users but destabilize banks. The baseline chart shows intervention at quarter 12 can stabilize deposits if policy acts quickly.