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Multi-agent modeling and simulation of a sequential monetary production economy

Author

Listed:
  • Marco Raberto

    (DIBE-CINEF, University of Genoa)

  • Andrea Teglio

    (DIBE-CINEF, University of Genoa)

  • Silvano Cincotti

    (DIBE- CINEF, University of Genoa)

Abstract

This paper presents a heterogeneous agent model of a sequential monetary production economy. A deterministic dynamic flow model is employed. The model is characterized by three classes of agents: a single homogeneous representative consumer, heterogeneous firms and a banking sector. There are three asset classes (or debts): a single homogeneous physical good, money and debt securities. The homogeneous commodity is produced by firms and, if saved, increases their capital stock. Firms issue debts to finance growth. Firms are homogeneous as regarding production technology but are heterogeneous relative to expected in°ation. Consumers provide labor force and make the decision of consumption and saving of their income. They own all the equities of firms and banks. The banking sector collects consumer savings and provides credit supply to firms. The main result of the model is that real economic variables are strongly affected by the level of credit supply in relation to the level of savings.

Suggested Citation

  • Marco Raberto & Andrea Teglio & Silvano Cincotti, 2005. "Multi-agent modeling and simulation of a sequential monetary production economy," Computational Economics 0503002, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpco:0503002
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    References listed on IDEAS

    as
    1. Cincotti, Silvano & M. Focardi, Sergio & Marchesi, Michele & Raberto, Marco, 2003. "Who wins? Study of long-run trader survival in an artificial stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 227-233.
    2. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    3. Nasseh, Alireza & Strauss, Jack, 2000. "Stock prices and domestic and international macroeconomic activity: a cointegration approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 40(2), pages 229-245.
    4. Martin Lettau & Sydney Ludvigson, 2001. "Consumption, Aggregate Wealth, and Expected Stock Returns," Journal of Finance, American Finance Association, vol. 56(3), pages 815-849, June.
    5. Marco Raberto & Silvano Cincotti & Sergio Focardi & Michele Marchesi, 2003. "Traders' Long-Run Wealth in an Artificial Financial Market," Computational Economics, Springer;Society for Computational Economics, vol. 22(2), pages 255-272, October.
    6. Bruce C. Greenwald & Joseph E. Stiglitz, 1993. "Financial Market Imperfections and Business Cycles," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 77-114.
    7. Fama, Eugene F, 1990. "Stock Returns, Expected Returns, and Real Activity," Journal of Finance, American Finance Association, vol. 45(4), pages 1089-1108, September.
    8. Chen, Nai-Fu, 1991. "Financial Investment Opportunities and the Macroeconomy," Journal of Finance, American Finance Association, vol. 46(2), pages 529-554, June.
    9. Delli Gatti, Domenico & Gallegati, Mauro & Giulioni, Gianfranco & Palestrini, Antonio, 2003. "Financial fragility, patterns of firms' entry and exit and aggregate dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 51(1), pages 79-97, May.
    10. Ferson, Wayne E & Harvey, Campbell R, 1993. "The Risk and Predictability of International Equity Returns," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 527-566.
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    More about this item

    Keywords

    Heterogeneous agents; financial markets and the macroeconomy; computer simulation;
    All these keywords.

    JEL classification:

    • D92 - Microeconomics - - Micro-Based Behavioral Economics - - - Intertemporal Firm Choice, Investment, Capacity, and Financing
    • E17 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Forecasting and Simulation: Models and Applications
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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