From theory to simulation: the dynamic political hierarchy in country virtualisation models

Authored by Ian S. Lustick, Brandon Alcorn, Miguel Garces, Alicia Ruvinsky

Date Published: 2012

DOI: 10.1080/0952813x.2012.693841

Sponsors: Lockheed Martin

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

This article suggests that computer-assisted agent-based modelling has the ability to move beyond abstract representations of political problems to theoretically sound virtualisations of real-world polities capable of producing probabilistic forecasts from distributions of stochastically perturbed model trajectories. In contrast to statistical approaches, this technique encompasses both prediction and explanation, with every distinctive trajectory traceable backwards from the occurrence or non-occurrence of an event of interest through the branching points and mechanisms that led to it. In this article, we illustrate our technique for building a country-scale model from corroborated theories, focusing on the `dynamic political hierarchy' module that integrates theories of cross-cutting cleavages, nested institutions and dynamic loyalties. We present our forecasts for significant political events in Thailand for the year August 2010-July 2011. Drawing on this case we demonstrate how the challenges of internal validity can be met in complex formal models and conclude by emphasising the importance of advances in visualisation techniques for parsing large amounts of interrelated time-series data.

Tags

Simulation modelling ABM Scenario analysis Thailand Forecasting virtualisation