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Why Model?

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This address treats some enduring misconceptions about modeling. One of these is that the goal is always prediction. The lecture distinguishes between explanation and prediction as modeling goals, and offers sixteen reasons other than prediction to build a model. It also challenges the common assumption that scientific theories arise from and 'summarize' data, when often, theories precede and guide data collection; without theory, in other words, it is not clear what data to collect. Among other things, it also argues that the modeling enterprise enforces habits of mind essential to freedom. It is based on the author's 2008 Bastille Day keynote address to the Second World Congress on Social Simulation, George Mason University, and earlier addresses at the Institute of Medicine, the University of Michigan, and the Santa Fe Institute.

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  • Joshua M. Epstein, 2008. "Why Model?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(4), pages 1-12.
    • Handle: RePEc:jas:jasssj:2008-57-1
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    1. Philip Ball, 2007. "Social science goes virtual," Nature, Nature, vol. 448(7154), pages 647-648, August.
    2. Samuelson, Paul A, 1972. "Maximum Principles in Analytical Economics," American Economic Review, American Economic Association, vol. 62(3), pages 249-262, June.
    3. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
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    2. Rolf Barth & Matthias Meyer & Jan Spitzner, 2012. "Typical Pitfalls of Simulation Modeling - Lessons Learned from Armed Forces and Business," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 15(2), pages 1-5.
    3. Jakub Bijak & Jason D. Hilton & Eric Silverman & Viet Dung Cao, 2013. "Reforging the Wedding Ring," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(27), pages 729-766.
    4. Rixen, Martin & Weigand, Jürgen, 2014. "Agent-based simulation of policy induced diffusion of smart meters," Technological Forecasting and Social Change, Elsevier, vol. 85(C), pages 153-167.
    5. Ozge Dilaver, 2015. "From Participants to Agents: Grounded Simulation as a Mixed-Method Research Design," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-15.
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    7. Lawlor, Jennifer A. & McGirr, Sara, 2017. "Agent-based modeling as a tool for program design and evaluation," Evaluation and Program Planning, Elsevier, vol. 65(C), pages 131-138.
    8. Pawel Sobkowicz, 2009. "Modelling Opinion Formation with Physics Tools: Call for Closer Link with Reality," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-11.
    9. Siegmeier, Torsten & Blumenstein, Benjamin & Möller, Detlev, 2015. "Farm biogas production in organic agriculture: System implications," Agricultural Systems, Elsevier, vol. 139(C), pages 196-209.
    10. Hardt, Lukas & O'Neill, Daniel W., 2017. "Ecological Macroeconomic Models: Assessing Current Developments," Ecological Economics, Elsevier, vol. 134(C), pages 198-211.
    11. Wells, Victoria K. & Gregory Smith, Diana & Taheri, Babak & Manika, Danae & McCowlen, Clair, 2016. "An exploration of CSR development in heritage tourism," Annals of Tourism Research, Elsevier, vol. 58(C), pages 1-17.
    12. Sara McPhee-Knowles, 2015. "Growing Food Safety from the Bottom Up: An Agent-Based Model of Food Safety Inspections," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(2), pages 1-9.
    13. Felipe Hernández Crespo, 2014. "Modelos mentales y sistemas multiagentes: Gobernanza de la pesca en el corregimiento de Barú," Revista Economía y Región, Universidad Tecnológica de Bolívar, vol. 8(2), pages 139-156, December.
    14. Sobkowicz, Pawel, 2016. "Agent based model of effects of task allocation strategies in flat organizations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 17-30.
    15. Alexandre Flávio Silva Andrada, 2014. "Um Estudo Do Discurso Doutrinário De Robert E. Lucas Jr. Método E História Das Ideias Acerca Das Análises De Ciclos Econômicos," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41st Brazilian Economics Meeting] 005, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    16. Borg, Audun & Paulsen Husted, Bjarne & Njå, Ove, 2014. "The concept of validation of numerical models for consequence analysis," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 36-45.
    17. Nicholas S. Thompson & Patrick Derr, 2009. "Contra Epstein, Good Explanations Predict," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-9.
    18. Jakobsson, Kristofer & Söderbergh, Bengt & Snowden, Simon & Aleklett, Kjell, 2014. "Bottom-up modeling of oil production: A review of approaches," Energy Policy, Elsevier, vol. 64(C), pages 113-123.
    19. Bruce Edmonds, 2010. "Bootstrapping Knowledge About Social Phenomena Using Simulation Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-8.
    20. Lang, J.C. & De Sterck, H., 2014. "The Arab Spring: A simple compartmental model for the dynamics of a revolution," Mathematical Social Sciences, Elsevier, vol. 69(C), pages 12-21.

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