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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 state-space modeling with its respect for historical process, for cause leading to effect without top-down imposition of global constraints. If economic modelers truly wish to respect the rationality of decision-makers, they should have the courage of their convictions; they should not be doing for their modeled decision-makers what in reality these decision-makers must do for themselves.

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  • Tesfatsion, Leigh, 2016. "Elements of dynamic economic modeling: presentation and analysis," ISU General Staff Papers 201602220800001018, Iowa State University, Department of Economics.
    • Handle: RePEc:isu:genstf:201602220800001018
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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. Sinitskaya, Ekaterina & Tesfatsion, Leigh, 2015. "Macroeconomies as constructively rational games," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 152-182.
    4. 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.
    5. Leigh Tesfatsion, 2011. "Agent-based Modeling and Institutional Design," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 37(1), pages 13-19.
    6. David Kendrick, 2007. "Teaching Computational Economics to Graduate Students," Computational Economics, Springer;Society for Computational Economics, vol. 30(4), pages 381-391, November.
    7. 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.
    8. 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.
    9. John B. Davis & D. Wade Hands (ed.), 2011. "The Elgar Companion to Recent Economic Methodology," Books, Edward Elgar Publishing, number 13684.
    10. 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.
    11. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    12. 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.
    13. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1.
    14. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, April.
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    16. Tesfatsion, Leigh, 1986. "Time inconsistency of benevolent government economies," Journal of Public Economics, Elsevier, vol. 31(1), pages 25-52, October.
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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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