Simulation of Population’s Reproductive Behaviour Patterns within an Agent-oriented Regional Model

Valeriy L. Makarov, Albert R. Bakhtizin, Elena D. Sushko

Abstract


The study focuses on the research on how the unevenness of demographic transition affects the social and demographic characteristics and their dynamics of a region’s population. The research was conducted by means of computerized experiments (simulations) set within an original agent-oriented model. The study features the structure of the model represented by an artificial society, with its members (agents) being attributed their personal characteristics in such a way that they would imitate the gender and age of the region’s population. The agents are divided into two groups which differ in their reproductive strategy. Agents from Group 1 adhere to the traditional strategy characterized by a high birth rate, while the agents from Group 2 follow the modern strategy resulting in a markedly low birth rate.

With the application of probabilistic mechanisms, the natural birth-death processes are imitated within the model. The extinction of agents occurs in accordance with the death rates adjusted for age and gender but remaining the same for the whole population. In the model, the appearance of new agents (birth of children) results from the choice made by reproductive-aged female agents, and their choice is influenced by the subjective traits determined by their group. The age and social structure of the regional population are generally formed as a result of the aggregation of particular agents’ activity.

The model has been applied in a range of experiments on forecasting the number and structure of the population in an assumed region. The results showed that despite the apparent simplification of the reality, the developed agent-oriented model correctly represents both the initial condition of the regional population including the gender, age and social structure and the dynamics of the population’s basic characteristics.


Keywords


agent-based modeling; demography; types of population reproduction; forecasting of population size and structure of the region

Full Text:

PDF

References


Vishnevskiy, A. G. (1982). Vosproizvodstvo naseleniya i obshchestvo. Istoriya, sovremennost, vzglyad v budushcheye [Society and population reproduction. History, present days, look into future]. Moscow: Finansy i statistika Publ., 287.

Makarov, V. L. & Bakhtizin, A. R. (2013). Sotsialnoye modelirovanie – novyy kompyuternyy proryv. Agent-orientirovannye modeli [Social simulation is a new computer breakthrough. Agent-based models]. Moscow: Ekonomika Publ., 295.

Trajkovski, G. & Collins, S.G. (Eds.). (2009). Handbook of Research on Agent-Based Societies: Social and Cultural Interactions. New York, NY: Information Science Reference Hershey, 412.

Silverman, E., Bijak, J., Hilton, J., Cao, V. D. & Noble, J. (2013). When Demography Met Social Simulation: A Tale of Two Modelling Approaches. Journal of Artificial Societies and Social Simulation (JASSS), 16 (4). Available at: http://jasss.soc.surrey.ac.uk/16/4/9.html.

Billari, F. C., Prskawetz, A., Diaz, B. A. & Fent, T. (2007). The “Wedding-Ring”: An agent-based marriage model based on social interaction. Demographic Research, 17, 59-82.

Diaz, B. A. (2010). Agent-Based Models on Social Interaction and Demographic Behaviour (Ph.D. Thesis). Wien: Technische Universität, 85.

Stillwell, J. & Clarke, M. (Eds). (2011). Population Dynamics and Projection Methods. Understanding Population Trends and Processes, 4, 222. DOI 10.1007/978-90-481-8930-4.

Heiland, F. (2003). The Collapse of the Berlin Wall: Simulating State-Level East to West German Migration Patterns. In: F.C. Billari & A. Prskawetz (Eds). Agent-Based Computational Demography, 73-96. Heidelberg: Springer.

Billari, F. C. & Prskawetz, A. (Eds). (2003). Agent-Based Computational Demography: Using Simulation to Improve Our Understanding of Demographic Behaviour. Heidelberg: Springer, 210.

Wu, B. M. & Birkin, M. H. (2012). Agent-Based Extensions to a Spatial Microsimulation Model of Demographic Change. In: A.J. Heppenstall et al. (Eds). Agent-Based Models of Geographical Systems, 347-360, DOI 10.1007/978-90-481-8927-4-16.

Makarov, V. L., Bakhtizin, A. R. & Sushko, E. D. (2014). Modelirovanie demograficheskikh protsessov s ispolzovaniem agent-orientirovannogo podkhoda [Demographic processes modeling using agent-based approach]. Federalizm [Federalism], 4, 37-46.

Maleva, T. M. & Sinyavskaya, O. V. (Eds). Roditeli i deti, muzhchiny i zhenshchiny v semye i obshchestve [Parents and children, men and women in a family and society]. Nezavisimyy institut sotsialnoy politiki [Independent Institute for Social Policy]. Moscow: NISP Publ., 640.

Shubat, O. M. & Bagirova, A. P. (2014). Prognozirovanie vtorykh rozhdeniy u rossiyskikh zhenshchin: sotsiologo-statisticheskiy podkhod [Forecasting second births among Russian women: sociological and statistical approach]. Problemy prognozirovaniya [Forecasting problems], 3, 131-140.

Tarasov, V. B. (2002). Ot mnogoagentnykh sistem k intellektualnym organizatsiyam: filosofiya, psikhologiya, informatika [From multiagent systems to intelligent organizations: philosophy, psychology, computer science]. Moscow: Editorial URSS Publ., 352.

Bakhmetova, G. Sh. (1982). Metody demograficheskogo prognozirovaniya [Methods of demographic forecasting]. Moscow: Finansy i statistika Publ., 159.

Shakhotko, L. P. & Tereshchenko, S. M. (1999). Kompyuternoye reshenie zadachi postroeniya demograficheskikh prognozov [Computer solution for demographic forecasts development]. Voprosy statistiki [Questions of statistics], 10, 57-65.




DOI: https://doi.org/10.15826/recon.2015.3.011

Copyright (c) 2018 Valeriy L. Makarov, Albert R. Bakhtizin, Elena D. Sushko

Сertificate of registration media Эл № ФС77-80764 от 28.04.2021
Online ISSN 2412-0731