A Data-Driven Approach for Agent-Based Modeling: Simulating the Dynamics of Family Formation

Abstract

In this paper, we propose a data-driven agent-based modeling approach that boosts the strength of agent-based models (ABM) in the dynamics of family formation. The proposed model analyzes the impact of socioeconomic factors on individual decisions about family formations. The key features of our model are the heterogeneous nature regarding agent’s age and socioeconomic factors: income and education. Based on these attributes, agents take decisions about acceptable partners and transition to family formation. One of our objectives is to fill the gap that exists between the methodologies of demography and agent-based social simulation. Making such a connection between these two approaches, this model attempts to incorporate empirical data into agent-based social simulation which enables us to analyze the transition of family formation effectively. Further, our simulated results depict the patterns of the hazards of family formation that are observed at micro-level dynamics and explains how marriage patterns change overtime. The proposed work gives a strong insight to strengthen the extent of demographic analysis through data-driven agent-based approach.