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Elements of Dynamic Economic Modeling: Presentation and Analysis

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  • Tesfatsion, Leigh

Abstract

The primary goal of these introductory notes is to promote the clear presentation and rigorous analysis of dynamic economic models, whether expressed in equation or agent-based form. A secondary goal is to promote the use of initial-value state-space modeling with its regard for historical process, for cause leading to effect without the external imposition of global coordination constraints on agent actions. Economists who claim to respect individual rationality should not be doing for their modeled economic agents what in reality these agents must do for themselves.

Suggested Citation

  • Tesfatsion, Leigh, 2016. "Elements of Dynamic Economic Modeling: Presentation and Analysis," ISU General Staff Papers 201601010800001018, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genstf:201601010800001018
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    1. H. Uzawa, 1971. "On a Two-Sector Model of Economic Growth," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 3, pages 19-26, Palgrave Macmillan.
    2. James Nicolaisen & Valentin Petrov & Leigh Tesfatsion, 2000. "Market Power and Efficiency in a Computational Electricity Market with Discriminatory Double-Auction Pricing," Computational Economics 0004005, University Library of Munich, Germany.
    3. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    4. Sinitskaya, Ekaterina & Tesfatsion, Leigh, 2015. "Macroeconomies as constructively rational games," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 152-182.
    5. John B. Davis & D. Wade Hands (ed.), 2011. "The Elgar Companion to Recent Economic Methodology," Books, Edward Elgar Publishing, number 13684.
    6. An, Li, 2012. "Modeling human decisions in coupled human and natural systems: Review of agent-based models," Ecological Modelling, Elsevier, vol. 229(C), pages 25-36.
    7. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    8. David Kendrick, 2007. "Teaching Computational Economics to Graduate Students," Computational Economics, Springer;Society for Computational Economics, vol. 30(4), pages 381-391, November.
    9. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
    10. Axelrod, Robert & Tesfatsion, Leigh, 2006. "A Guide for Newcomers to Agent-Based Modeling in the Social Sciences," Staff General Research Papers Archive 12515, Iowa State University, Department of Economics.
    11. Leigh Tesfatsion, 2011. "Agent-based Modeling and Institutional Design," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 37(1), pages 13-19.
    12. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
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    14. Mario J. Miranda & Paul L. Fackler, 2004. "Applied Computational Economics and Finance," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262633094, April.
    15. Tesfatsion, Leigh, 1986. "Time inconsistency of benevolent government economies," Journal of Public Economics, Elsevier, vol. 31(1), pages 25-52, October.
    16. Tesfatsion, Leigh & Jie, Yu & Rehmann, Chris R. & Gutowski, William J., 2015. "WACCShed: A Platform for the Study of Watersheds as Dynamic Coupled Natural and Human Systems," ISU General Staff Papers 201512160800001226, Iowa State University, Department of Economics.
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    Cited by:

    1. Erhard Glötzl & Florentin Glötzl & Oliver Richters, 2019. "From constrained optimization to constrained dynamics: extending analogies between economics and mechanics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 623-642, September.
    2. Múñoz, Féliz-Fernando & Encinar, María-Isabel & Cañibano, Carolina, 2016. "Agents, interaction, and economic laws: An analytical framework for understanding different economic theories," Working Papers in Economic Theory 2016/05, Universidad Autónoma de Madrid (Spain), Department of Economic Analysis (Economic Theory and Economic History).
    3. Leigh Tesfatsion, 2017. "Modeling economic systems as locally-constructive sequential games," Journal of Economic Methodology, Taylor & Francis Journals, vol. 24(4), pages 384-409, October.
    4. Tingting Liu & Randall J. F. Bruins & Matthew T. Heberling, 2018. "Factors Influencing Farmers’ Adoption of Best Management Practices: A Review and Synthesis," Sustainability, MDPI, vol. 10(2), pages 1-26, February.
    5. Thomas Beaussier & Sylvain Caurla & Véronique Bellon Maurel & Eléonore Loiseau, 2019. "Coupling economic models and environmental assessment methods to support regional policies : A critical review," Post-Print hal-02021423, HAL.
    6. Lorraine Eden & Charles F. Hermann & Stewart R. Miller, . "Evidence-based policymaking in a VUCA world," UNCTAD Transnational Corporations Journal, United Nations Conference on Trade and Development.
    7. Tesfatsion, Leigh, 2017. "Modeling Economic Systems as Locally-Constructive Sequential Games," ISU General Staff Papers 201703280700001022, Iowa State University, Department of Economics.
    8. Tesfatsion, Leigh, 2017. "Modeling Economic Systems as Locally-Constructive Sequential Games," ISU General Staff Papers 201702180800001022, Iowa State University, Department of Economics.
    9. Tesfatsion, Leigh, 2017. "Modeling Economic Systems as Locally-Constructive Sequential Games," ISU General Staff Papers 201704300700001022, Iowa State University, Department of Economics.

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    JEL classification:

    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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