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Interpreting Social Accounting Matrix (SAM) as an Information Channel
Mateu Sbert1, Shuning Chen2, Miquel Feixas1
1Graphics and Imaging Laboratory, University of Girona, 17003 Girona, Spain.
Entropy (Basel, Switzerland)
|December 3, 2020
Summary
This study applies information theory to Social Accounting Matrices (SAMs), interpreting SAM coefficients as an information channel. This framework optimizes SAM aggregation and analyzes economic shock evolution.
Area of Science:
- Economics
- Information Theory
- Econometrics
Background:
- Social Accounting Matrices (SAMs) represent economic actor transactions.
- Information theory quantifies information flow between systems.
- Existing SAM analysis lacks dynamic and optimization perspectives.
Purpose of the Study:
- To interpret Social Accounting Matrices (SAMs) using information channel theory.
- To develop new methods for optimizing SAM aggregation.
- To analyze the dynamic evolution and stability of SAMs.
Main Methods:
- Applying information channel concepts to SAM coefficients.
- Utilizing Markov chain and ergodic chain interpretations of SAMs.
- Calculating information measures to analyze SAM evolution and structure.
Main Results:
- SAM coefficients are interpreted as an information channel, enabling optimization.
- Information measures accurately describe SAM evolution over time.
- The framework confirms SAM matrix construction (irreducibility, aperiodicity) and aids balancing.
Conclusions:
- Information theory provides a novel framework for SAM analysis.
- This approach enhances understanding of economic systems and allows for improved SAM construction and analysis.
- Empirical examples validate the information channel concept for SAMs.
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