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Interpreting Social Accounting Matrix (SAM) as an Information Channel.

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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.

Keywords:
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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.