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Indices of Informational Association and Analysis of Complex Socio-Economic Systems
Paulo L Dos Santos1, Noé Wiener2
1Department of Economics, New School for Social Research, New York, NY 10003, USA.
Entropy (Basel, Switzerland)
|December 3, 2020
Summary
This study introduces new statistical indices to analyze complex associations in social and economic systems. These tools help researchers understand relationships between variables, even with large datasets and multiple factors, such as discrimination effects.
Area of Science:
- Social Science
- Economics
- Quantitative Analysis
Background:
- Quantitative observational studies of complex systems face analytical challenges.
- Understanding associations between variables in large datasets is difficult.
Purpose of the Study:
- Develop novel statistical indices for informational association.
- Provide robust methods for analyzing relationships with multiple covariates.
- Apply these indices to study economic discrimination.
Main Methods:
- Development of ordinary and piecewise indices of joint and incremental informational association.
- Application to quantitative observational data from the U.S. economy.
Main Results:
- The proposed indices offer a robust approach to analyzing complex associations.
- Demonstrated analytical usefulness in examining economic effects of social identity discrimination.
Conclusions:
- The developed indices enhance the ability to conduct quantitative observational inquiry.
- Provides a valuable tool for understanding systemic economic impacts of social factors.
Keywords:
complex socio-economic systemsinformation theorymathematical economicsmathematical sociologyMore Related Videos
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