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Capturing Firm Behavior in Agent-based Models of Industry Evolution and Macroeconomic Dynamics

In: Evolution, Organization and Economic Behavior

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  • Herbert Dawid
  • Philipp Harting

Abstract

This new and original collection of papers focuses on the intersection of three strands of research: evolutionary economics, behavioral economics, and management studies. Combining theoretical and empirical contributions, the expert contributors demonstrate that the intersection of these fields provides a rich source of opportunities enabling researchers to find more satisfactory answers to questions that (not only evolutionary) economists have long been tackling. Topics discussed include individual agents and their interactions; the behavior and development of firm organizations; and evolving firms and their broader implications for the development of regions and entire economies.

Suggested Citation

  • Herbert Dawid & Philipp Harting, 2012. "Capturing Firm Behavior in Agent-based Models of Industry Evolution and Macroeconomic Dynamics," Chapters, in: Guido Buenstorf (ed.), Evolution, Organization and Economic Behavior, chapter 6, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:14183_6
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    File URL: https://www.elgaronline.com/view/9781849806282.00014.xml
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    References listed on IDEAS

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    Cited by:

    1. Dawid, H. & Harting, P. & Neugart, M., 2018. "Cohesion policy and inequality dynamics: Insights from a heterogeneous agents macroeconomic model," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 220-255.
    2. Dawid, H. & Harting, P. & Neugart, M., 2014. "Economic convergence: Policy implications from a heterogeneous agent model," Journal of Economic Dynamics and Control, Elsevier, vol. 44(C), pages 54-80.
    3. Herbert Dawid & Reinhold Decker & Thomas Hermann & Hermann Jahnke & Wilhelm Klat & Rolf König & Christian Stummer, 2017. "Management science in the era of smart consumer products: challenges and research perspectives," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 203-230, March.
    4. Sander van der Hoog, 2017. "Deep Learning in (and of) Agent-Based Models: A Prospectus," Papers 1706.06302, arXiv.org.

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