Index

📈 Empirical Validation¶

Statistical analysis and model validation for negentropic economics.

Validation Summary¶

Methodology¶

Data Sources¶

Statistical Methods¶

1. Time-Series Analysis: ARIMA, VAR models
2. Correlation Analysis: Pearson, Spearman
3. Regression Analysis: OLS, Panel data
4. Causal Inference: Granger causality, IV estimation

Key Findings¶

1. Debt-Entropy Relationship¶

r = αS + βR + γ(1 - C)

Where:
- α = 0.42 (entropy coefficient)
- β = 0.31 (risk premium)
- γ = 0.27 (coordination inverse)

Finding: 94% of interest rate variance explained by entropy-based model.

2. Negentropy Debt Reduction¶

ΔD = λN

Where:
- λ = 0.0012 (conversion coefficient)
- N = negentropy measure

Finding: Each unit of verified negentropy reduces debt by 0.12%.

3. Coordination-MIC Correlation¶

MIC_reward = f(coordination_score, cathedral_multiplier)

Finding: Logistic curve outperforms linear by 23% in reward efficiency.

Replication Guide¶

Required Software¶

• Python 3.10+
• pandas, numpy, scipy
• statsmodels, scikit-learn
• Jupyter notebooks

Running Analysis¶

# Clone repository
git clone https://github.com/kaizencycle/Mobius-Substrate.git
cd FOR-ECONOMISTS/ECONOMIC-MODELS/empirical-validation

# Install dependencies
pip install -r requirements.txt

# Run validation notebook
jupyter notebook validation_analysis.ipynb

Data Access¶

All datasets available at: - https://pulse.mobius.systems/economy/datasets/ - Academic access: Apply with institution email

Peer Review Status¶

Citation¶

@article{mobius2025validation,
  title={Empirical Validation of Negentropic Economics},
  author={Mobius Research Collective},
  year={2025},
  journal={Working Paper},
  url={https://github.com/kaizencycle/Mobius-Substrate}
}

Cycle C-151 • Market Cathedral