AGENT-BASED MODELING OF FERTILITY RATE DECLINE: SIMULATING THE INTERACTION OF EDUCATION, ECONOMIC PRESSURES, AND SOCIAL MEDIA INFLUENCE

Abstract

Introduction: Fertility rates have fallen below replacement level in numerous countries, presenting a profound demographic challenge with far-reaching societal and economic consequences. While traditional explanations cite factors like increased educational attainment and economic pressures, the rapid, global nature of the decline suggests the involvement of complex, non-linear interactions and emerging influences, such as social media. This research aims to develop a novel agent-based model (ABM) to simulate how the interplay between individual life-course decisions, macro-level socioeconomic factors, and pervasive social influence drives fertility outcomes.

Methodology: We developed an agent-based model where autonomous agents represent individuals within a simulated society. Each agent possesses attributes such as age, educational level, income, and personal fertility desires. The model formalizes rules governing key life events: pursuing education, entering the labor market, forming partnerships, and deciding to have children. Agents are influenced by three primary drivers:Economic Pressures: Including the direct and opportunity costs of childbearing.

Educational Pathways: Which delay family formation and alter career and lifestyle aspirations.
Social Media Influence: Modeled as a network effect that disseminates and normalizes low-fertility norms, lifestyles, and consumption ideals.

Simulations were calibrated using empirical data to establish baseline scenarios.
Findings: Our simulation results demonstrate several key insights:
While rising education and economic strain independently suppress fertility rates, their combination produces a stronger-than-additive, synergistic effect.
Crucially, the inclusion of social media as a vector for normative change accelerates the fertility decline and lowers the long-term fertility equilibrium.

social media effectively "locks in" low fertility rates by shifting societal values and aspirations more rapidly than economic conditions alone would predict.
Conclusion: This study provides a generative explanation for the persistent and self-reinforcing nature of low fertility, highlighting the necessity of a multi-level, dynamic approach that accounts for the evolving informational and social landscape. The ABM framework offers a powerful tool for policymakers, enabling them to test the potential efficacy of interventions such as family benefits, housing subsidies, or pro-natalist information campaigns in a virtual environment that captures the complex feedback loops between economic structure, culture, and individual choice. This approach also elucidates how minor shifts in socioeconomic conditions can lead to significant changes in fertility rates, revealing critical points in fertility transitions.