Testing and Revising the Human Development Sequence Theory using Agent-Based Simulation and Data

Abstract

Agent-based modeling is a promising tool for studying emergent macro-phenomena from micro-level mechanisms. We propose a methodology for converting theories about social change into mathematical agent-based models. These models are then analyzed to identify specific relationships between macro and micro variables, allowing us to identify which micro-level mechanisms are best supported by the available data. We apply our method to the human development sequence theory, showing that although the 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 then use the data and agent-based modeling to propose several plausible modifications of the theory, including the role of elites and economic inequality, which better explain the data. In general, we provide a framework in which macro-level non-linearities allow to derive and test theory's micro-level implications empirically and formally.

Keywords: democratization, Human Development Sequence Theory, agent-based modeling, emancipation, economic development, inequality

JEL Classification: C6, O1, Y80