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Complex Systems Modeling of Community Inclusion Currencies

Author

Listed:
  • Andrew Clark

    (BlockScience Inc. and Monitaur Inc)

  • Alexander Mihailov

    (University of Reading)

  • Michael Zargham

    (Vienna University of Economics and Business and BlockScience Inc)

Abstract

This interdisciplinary paper blends knowledge from computer science and economics in proposing a complex dynamic system subpopulation model for a blockchain form of local complementary currency, generic to the Grassroots Economics Foundation’s Community Inclusion Currency (CIC) implemented in Kenya. Our contribution to the emerging economics literature is five-fold: (i) we take a novel meso-economic approach to elicit utility from actual transactions data and reveal an ‘optimal’ disaggregation number of typical community subgroups; (ii) we relate the local CIC functioning to a nation-wide currency board monetary regime to argue that such a credible CIC implementation ensures trust in the CIC and makes it a valuable market-based channel to alleviate poverty, in addition to humanitarian or government aid channels. However, (iii) we also find evidence in our data that substitutes for real-world money such as CICs are perceived as inferior, and hence CIC systems can only be transitional. Then, (iv) we reveal that, for a poor population, saving dominates as a use of a cluster’s CIC balance, accounting for 47%, followed by purchase of food and water, 25%. Despite these dominant patterns, (v) we uncover a considerable heterogeneity in CIC spending behavior. Our contribution to the related computer-science and Tokenomics literature is two-fold: (i) we provide an open-source scaffold for modeling CIC viability and net flows; (ii) to simulate a subpopulation mixing process, we employ a network-based dynamical system modeling approach that is better grounded in economic principles and monetary theory.

Suggested Citation

  • Andrew Clark & Alexander Mihailov & Michael Zargham, 2024. "Complex Systems Modeling of Community Inclusion Currencies," Computational Economics, Springer;Society for Computational Economics, vol. 64(2), pages 1259-1294, August.
    • Handle: RePEc:kap:compec:v:64:y:2024:i:2:d:10.1007_s10614-023-10445-9
    DOI: 10.1007/s10614-023-10445-9
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    Keywords

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    JEL classification:

    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Systems; Standards; Regimes; Government and the Monetary System
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G51 - Financial Economics - - Household Finance - - - Household Savings, Borrowing, Debt, and Wealth
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

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