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ASPEN: A Microsimulation Model of the Economy

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  • Basu, N
  • Pryor, R
  • Quint, T

Abstract

In this report we present ASPEN, a new agent-based microeconomic simulation model of the U.S. economy being developed at Sandia National Laboratories (SNL). The model is notable because it allows a large number of individual economic agents to be modeled at a high level of detail and with a great degree of freedom. Some of the features of ASPEN are (a) a sophisticated message-passing system which allows individual pairs of agents to communicate with one another, (b) the use of genetic algorithms to simulate certain agents' learning, and (c) a detailed financial sector which includes a banking system and a bond market. Results from runs of the model are also presented. Citation Copyright 1998 by Kluwer Academic Publishers.

Suggested Citation

  • Basu, N & Pryor, R & Quint, T, 1998. "ASPEN: A Microsimulation Model of the Economy," Computational Economics, Springer;Society for Computational Economics, vol. 12(3), pages 223-241, December.
    • Handle: RePEc:kap:compec:v:12:y:1998:i:3:p:223-41
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    Cited by:

    1. Ebrahim Bagheri & Ali A. Ghorbani, 2010. "UML-CI: A reference model for profiling critical infrastructure systems," Information Systems Frontiers, Springer, vol. 12(2), pages 115-139, April.
    2. Cincotti, Silvano & Raberto, Marco & Teglio, Andrea, 2010. "Credit money and macroeconomic instability in the agent-based model and simulator Eurace," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 4, pages 1-32.
    3. Ashraf, Quamrul & Gershman, Boris & Howitt, Peter, 2017. "Banks, market organization, and macroeconomic performance: An agent-based computational analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 135(C), pages 143-180.
    4. James Sprigg & Mark Ehlen, 2007. "Comparative dynamics in an overlapping-generations model: the effects of quasi-rational discrete choice on finding and maintaining Nash equilibrium," Computational Economics, Springer;Society for Computational Economics, vol. 29(1), pages 69-96, February.
    5. Marco Raberto & Andrea Teglio & Silvano Cincotti, 2008. "Integrating Real and Financial Markets in an Agent-Based Economic Model: An Application to Monetary Policy Design," Computational Economics, Springer;Society for Computational Economics, vol. 32(1), pages 147-162, September.
    6. Howitt, Peter, 2012. "What have central bankers learned from modern macroeconomic theory?," Journal of Macroeconomics, Elsevier, vol. 34(1), pages 11-22.
    7. Ouyang, Min & Dueñas-Osorio, Leonardo, 2011. "An approach to design interface topologies across interdependent urban infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1462-1473.
    8. van de Ven, J., 2001. "Simulating Cohort Demographic Characteristics for Australia," Department of Economics - Working Papers Series 779, The University of Melbourne.
    9. Chopra, Shauhrat S. & Khanna, Vikas, 2015. "Interconnectedness and interdependencies of critical infrastructures in the US economy: Implications for resilience," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 865-877.
    10. van de Ven, J., 2001. "Simulating Cohort Earnings for Australia," Department of Economics - Working Papers Series 780, The University of Melbourne.
    11. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.

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