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Shannon Entropy for Quantifying Uncertainty and Risk in Economic Disparity.
Saurabh Mishra1, Bilal M Ayyub2
1Human-Centered Artificial Intelligence Institute (HAI), Stanford University, CA, USA.
Summary
Shannon entropy offers a novel approach to measuring economic disparity and associated risks. This method quantifies uncertainty in income distribution, outperforming traditional metrics like the Gini coefficient in reliability and computational efficiency.
Area of Science:
- Economics
- Information Theory
- Sociology
Background:
- Economic disparity poses risks to social order and community resilience.
- Current measures like the Gini coefficient lack probabilistic insights into income distribution uncertainties.
- A need exists for advanced methods to quantify economic disparity and associated risks.
Purpose of the Study:
- To introduce and quantify Shannon entropy for measuring income inequality at various scales.
- To explore the relationship between entropy, uncertainty, risk, and potential social conflict.
- To develop a city risk profiling framework using spatial-temporal entropy mapping.
Main Methods:
- Quantification of Shannon entropy applied to national, subnational, and city-level income data.
- Probabilistic interpretation of entropy for uncertainty and risk assessment.
- Development of spatial-temporal entropy maps for U.S. cities.
Main Results:
- Shannon entropy provides a new interpretation of economic disparity and associated risks.
- Rising entropy correlates with income convergence and potential conflict.
- Low entropy indicates high-risk tipping points for anomaly detection.
- Analysis revealed income polarization in Baltimore, Washington D.C., and San Francisco.
- Entropy calculations are more computationally efficient than Gini coefficients.
Conclusions:
- Shannon entropy is a powerful tool for analyzing income inequality and socioeconomic risks.
- Entropy mapping offers a novel framework for city risk profiling.
- This approach enhances the understanding of uncertainty and conflict dynamics in economic disparity.
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