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Economic Incentive Design

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The DIG Network implements a "Survival of the Most Diverse" economic model that creates optimal content distribution through market forces rather than central planning.

Core Economic Mechanism​

Fixed Reward Scarcity​

The network's fundamental innovation is using fixed epoch rewards that create scarcity dynamics:

Individual Reward = Tier Base Reward / Number of Providers

Where:
- Tier Base Reward is determined by handle registration cost
- Number of Providers is count of PlotCoins for that content
- Result: Natural economic pressure for even distribution

Dual Economic Commitment Structure​

Content publishers must complete two economic commitments for network propagation:

STEP 1: Handle Registration → Tier Assignment → Handle Reward Multiplier
Tier 1 (3 char): 5000 DIG cost → 5x base rewards
Tier 2 (4 char): 1000 DIG cost → 4x base rewards  
Tier 3 (5 char): 200 DIG cost → 3x base rewards
Tier 4 (6 char): 40 DIG cost → 2x base rewards
Tier 5 (7 char): 8 DIG cost → 1.5x base rewards
Tier 6 (8+ char): 1 DIG cost → 1x base rewards

STEP 2: CapsuleStakeCoin Creation → Per-Capsule Collateral + Size Reward Multiplier
256KB capsules: 64 DIG locked → 1x size multiplier
1MB capsules: 256 DIG locked → 1.2x size multiplier
10MB capsules: 1024 DIG locked → 1.5x size multiplier
100MB capsules: 4096 DIG locked → 2x size multiplier
1000MB capsules: 16384 DIG locked → 3x size multiplier

Combined Effect: Total rewards = base × handle_tier × capsule_size
Only economically-backed content propagates with dual reward incentives

Market Dynamics​

Provider Decision Algorithm​

Storage providers monitor blockchain events and optimize portfolios based on economic signals:

Monitoring Phase:
1. Monitor DIG Handle registrations (value signals)
2. Monitor CapsuleStakeCoin publications (collateral commitment)
3. Verify economic viability (handle tier + collateral amount)

Decision Phase (for each viable opportunity):
1. Query PlotCoin registry for current provider count
2. Calculate expected reward:
   reward = (handle_tier_multiplier × capsule_size_multiplier × base_reward) / (current_providers + 1)
3. Verify collateral covers hosting costs
4. Compare against opportunity cost of current portfolio
5. Select highest ROI content within capacity constraints

Equilibrium Mechanics​

The system naturally reaches optimal distribution through competition:

Phase 1: Discovery

  • New content registered with handle
  • Zero providers = maximum rewards
  • First mover captures 100% of tier rewards

Phase 2: Competition

  • High rewards attract additional providers
  • Individual rewards decrease with each new provider
  • Profitability declines toward equilibrium

Phase 3: Rebalancing

  • Providers continuously scan for better opportunities
  • Overserved content loses providers
  • Underserved content gains providers
  • Dynamic equilibrium maintained

Dual Incentive System​

Primary Incentives (DIG Rewards)​

Designed to encourage diverse storage across many providers:

  • Fixed rewards per content tier
  • Split equally among all providers
  • Encourages wide distribution
  • Creates natural redundancy

Secondary Incentives (Network Bribes)​

Allow content creators to optimize for performance:

  • Direct payments to storage providers
  • Encourages content consolidation
  • Improves retrieval speed
  • Market-based performance optimization

Strategic Provider Choice​

Providers face a strategic decision between two revenue models:

Option A: Diverse Storage Strategy
- Store many different capsules
- Earn DIG rewards from multiple sources
- Lower risk, steady returns
- Contributes to censorship resistance

Option B: Consolidation Strategy  
- Focus on high-bribe content
- Earn concentrated bribe rewards
- Higher risk, potentially higher returns
- Optimizes for performance

Censorship Resistance Through Economics​

Ephemeral Storage Patterns​

Economic incentives create constantly shifting storage patterns:

  1. Continuous Optimization: Providers constantly seek higher returns
  2. Unpredictable Movement: Content location changes based on market forces
  3. No Fixed Targets: Censors cannot predict where content will be stored
  4. Economic Counter-Pressure: Censorship attempts create profit opportunities

Attack Economics​

Attempting to censor content becomes economically irrational:

Censorship Attempt → Reduced Provider Count → Higher Individual Rewards
                                                       ↓
                             Economic Opportunity ← New Providers Enter

Result: Content naturally flows to willing providers in permissive jurisdictions.

PlotCoin Lifecycle Management​

Commitment Requirements​

Storage providers must carefully manage their PlotCoin lifecycle:

Active PlotCoin Rules:

  • Must maintain capsule while PlotCoin exists
  • Can melt PlotCoin to free storage
  • New capsules require plotting time before earning
  • Gap between melting and new earnings

Strategic Timing:

Current Earning → Melt Decision → Plot New Content → Resume Earning
      ↓                ↓                  ↓                ↓
  Known reward    Opportunity      Downtime cost    Future reward
                     cost

Portfolio Optimization​

Providers optimize across multiple dimensions:

  • Content Age: Newer content typically offers higher rewards
  • Geographic Distribution: Serve content where demand is highest
  • Risk Diversification: Balance across multiple content tiers
  • Capacity Utilization: Maximize storage efficiency

Network Health Metrics​

Distribution Score​

Measures how evenly content is distributed:

Distribution Score = 1 / (standard_deviation of provider counts)

Higher score = More even distribution = Better censorship resistance

Economic Velocity​

Tracks how dynamically content moves between providers:

Velocity = PlotCoin changes per epoch / Total PlotCoins

Higher velocity = More dynamic network = Harder to censor

Value Capture Efficiency​

Measures how effectively the network captures value from handle registrations:

Efficiency = Total rewards distributed / Total handle registration fees

Target: 80-120% (sustainable range with treasury growth)

Long-Term Sustainability​

Token Circulation​

The circular economy ensures sustainable operations:

Content Creators → DIG Tokens → Handle Registration
                                        ↓
Storage Providers ← Rewards ← Validation Success
        ↓
Market Sales → Token Liquidity → New Creators

Deflationary Pressure​

Multiple mechanisms create long-term value appreciation:

  • Fixed Supply: 100M token cap
  • Increasing Demand: More content requires more handles
  • Lock-Up Effects: Staking requirements reduce circulation
  • Network Growth: Success drives token demand

Economic Resilience​

The system self-corrects through market forces:

  • Over-Supply: Low rewards drive provider exit
  • Under-Supply: High rewards attract new providers
  • Price Shocks: Treasury buffers short-term volatility
  • Long-Term Growth: Network effects strengthen over time

Governance Parameters​

Key economic parameters subject to future DAO governance:

  • Base Reward Rates: DIG tokens per epoch per tier
  • Tier Multipliers: Reward scaling between tiers
  • Validation Frequency: How often content is validated
  • Staking Requirements: Minimum stake for providers
  • Penalty Structures: Consequences for misbehavior