2013/10/26 by Mason Wright, Wright, Mason, Pratim Sengupta +1 · 1 citation
Computer Science · Economics, Econometrics and Finance · Physics and Astronomy · #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #FOS: Physical sciences #I.2.11 #Multiagent Systems (cs.MA) #Physics and Society (physics.soc-ph) #cs.MA #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.1310.7134
appears in Journal of Artificial Societies and Social Simulations, 2014
openalex publication_date 2013/10/26 · arxiv created 2014/12/18 · arxiv updated 2014/12/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we investigate the interactions among oligarchs, political parties, and voters using an agent-based modeling approach. We introduce the OLIGO model, which is based on the spatial model of democracy, where voters have positions in a policy space and vote for the party that appears closest to them, and parties move in policy space to seek more votes. We extend the existing literature on agent-based models of political economy in the following manner: (1) by introducing a new class of agents- oligarchs - that represent leaders of firms in a common industry who lobby for beneficial subsidies through campaign donations; and (2) by investigating the effects of ideological preferences of the oligarchs on legislative action. We test hypotheses from the literature in political economics on the behavior of oligarchs and political parties as they interact, under conditions of imperfect information and bounded rationality. Our key results indicate that (1) oligarchs tend to donate less to political campaigns when the parties are more resistant to changing their policies, or when voters are more informed; and (2) if Oligarchs donate to parties based on a combination of ideological and profit motivations, Oligarchs will tend to donate at a lower equilibrium level, due to the influence of lost profits. We validate these outcomes via comparisons to real world polling data on changes in party support over time.