Agent-Based Modeling for Rural Migration Decision and Action in China

Lingxin Hao, Johns Hopkins University
Charlie Mitchell, Johns Hopkins University

This study develops mathematical models and computational techniques from the principles of agent-based modeling (ABM) to study rural migration decision and action. We first establish a conceptual model on rural migration in China by modifying migration theories to fit the China reality. The framework emphasizes the role of capital from foreign direct investment, migrant networks, and urban employment prospect in determining rural migration decision and action in China. Second, this framework is tested using ABM based on data from the census with provincial statistics. Internal updates of macro-states are allowed to have a feedback loop for the next month’s migration decision and action of individuals. The agent simulation goal is to re-generate the rural migration prevalence observed in 2000 Census according to theory-based rules. Step-by-step mathematical models and computational procedures are established and tested with hypothetical data first and then 1% of the China 2000 census data.