Agent-based Simulation Modeling of Low Fertility Trap Hypothesis

Abstract

Advances in information technology enable researchers to utilize big data in analyzing social behaviors in scientific ways. While an interest to evaluate economically effective policies is increasing worldwide, testing hypothesized policies with a real society is highly risky. To overcome this difficulty, we present an agent-based social simulation model based on the low fertility trap hypotheses, which includes human network, social heterogeneity, demographic condition, and economic activity. We aim to 1) analyze the interaction between economic state transitions and demographic events in terms of ageing, low fertility, and economic instability and 2) use the social simulation model to support political decision making based on real case study data from South Korea. An initial designed experiment shows that ageing and low fertility are mutually related to individual economic capability. Low fertility is also found to be a consequence of creating an economic buffer against consumption and well-being of people in a society, especially with a high number of elderly. This current study is the first phase of the hybrid simulation model integrating the statistical-based micro simulation and system dynamics simulation approaches in our on-going work to create the hybrid demographic simulation model using South Korean case study to better understand social phenomena and to provide economic solutions during crises.