agent based simulation

The divisio​n of gender roles within households has been identified as a critical factor influencing fertility decisions and behaviors, as evidenced by the decline in fertility rates below the replacement level. The objective of this paper is to investigate and anticipate the impact of the division of gender roles in households on the reproductive behavior of women in Tehran province using agent-based modeling (ABM) tools. Data from the 2017 Iran Fertility Transition Survey (IFTS) has been utilized for this purpose. The simulation results suggest that the Total Fertility Rate (TFR) in Tehran province will decrease to 1.06 children by 2029, with a projected precipitous decline in fertility rates over the next decade. Furthermore, the AnyLogic software was employed to implement scenarios that examined the consequences of both reducing and increasing men's involvement in domestic work division. According to these simulations, if male participation decreases by 15%, the TFR could fall to 1.03 children. Conversely, if male participation increases by 15%, the TFR could rise to 1.09 children by 2029. Based on these findings, the recommendations section underscores the necessity for family-friendly policies that prioritize cultural and social values that encourage males to participate in household responsibilities. The objective of this method is to mitigate gender inequality and establish an environment that is conducive to the growth of fertility rates.

Estimating and projecting population size in future is utmost important for governments, because  majority of government programs and plans have a close  relationship with population and its dynamics. The aim of this paper is to project the trend of population changes and population structure over the next 50 years using Agent-Based Simulation model. The model enables to analyse different scenarios of population changes, provide as strcutural model of changes,  modeling with heterogeneous entities and provide more realistic results because of probabilistic modeling. Simulation results was compared to projection results under different scenarios conducted by the Statistical Center of Iran. The results showed a significant correlation between the two which indicates the validity of simulation model. The results also indicated that  age at marriage does not have a significant correlation with the trend of population growth in next 15 year, while  in longer term, there will be a significant correlation  Analysis of the model indicate that Agent-Based Simulation can create probabilistic, heterogeneous with policy analysis features analytical framework which can simulate annual data with minimum cost and in a virtual mean.