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Revising the Human Development Sequence Theory Using an Agent-Based Approach and Data

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Abstract

Agent-based models and computer simulations are promising tools for studying emergent macro-phenomena. We apply an agent-based approach in combination with data analysis to investigate the human development sequence (HDS) theory developed by Ronald Inglehart and Christian Welzel. Although the HDS theory is supported by correlational evidence, the sequence of economic growth, democracy and emancipation stated by the theory is not entirely consistent with data. We use an agent-based model to make quantitative predictions about several different micro-level mechanisms. Comparison to data allows us to identify important inconsistencies between HDS and the data, and propose revised agent-based models that modify the theory. Our results indicate the importance of elites and economic inequality in explaining the data available on democratisation.

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  • Viktoria Spaiser & David J. T. Sumpter, 2016. "Revising the Human Development Sequence Theory Using an Agent-Based Approach and Data," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(3), pages 1-1.
    • Handle: RePEc:jas:jasssj:2015-95-3
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    Cited by:

    1. Gao, Lin, 2016. "Trust and Performance: Exploring Socio-Economic Mechanisms in the “Deep” Network Structure with Agent-Based Modeling," MPRA Paper 75214, University Library of Munich, Germany.

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