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The Role of Social Interactions in Demography: An Agent-Based Modelling Approach

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Agent-Based Modelling in Population Studies

Part of the book series: The Springer Series on Demographic Methods and Population Analysis ((PSDE,volume 41))

Abstract

Individual demographic behaviour cannot be understood in isolation from the social network one is linked to. However, formal models of demographic behaviour lag behind the empirical evidence. In this chapter we demonstrate how agent-based models can be applied to investigate the role of social interactions to explain macro-level demographic patterns like the age-at-marriage curve, age-specific fertility rates and the role of family policies for fertility. Based on these three examples we discuss the various steps that need to be followed when building up an agent-based model. These include the choice of the characteristics and rules of the agents together with the definition of how agents may interact and how macroeconomic behaviour may feed back on the micro-level decision processes.

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Notes

  1. 1.

    Age-specific birth probabilities are not available for the time before 1984.

  2. 2.

    If p r 3 is the probability of increasing intended fertility due to meeting one peer with a higher parity, then (1 − p r 3) is the probability of not increasing intended fertility despite this one peer, \((1 - pr_{3})^{\pi _{i}^{+}}\) is the probability of not increasing intended fertility despite π i + peers with higher parities, and \(1 - (1 - pr_{3})^{\pi _{i}^{+}}\) is the probability of increasing intended fertility when being exposed to π i + peers with higher parities.

  3. 3.

    In contrast to the class of toy and mid-range models presented in this paper, there exist highly data-driven ABMs that model real situations, e.g. the study by Axtell et al. (2002) on a historical population and studies on household dynamics and land use change by Entwisle et al. (2008).

  4. 4.

    See also Baroni et al. (2009) for the integration of policies to explain fertility in an agent-based modelling framework.

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Acknowledgements

I would like to thank Bernhard Rengs and Thomas Fent for their comments and suggestions and Werner Richter for proof reading.

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Authors and Affiliations

  1. Institute of Statistics and Mathematical Methods in Economics, Vienna University of Technology, Wiedner Hauptstrasse 8-10, E105-3, Vienna, Austria

    Alexia Prskawetz

  2. Wittgenstein Centre for Demography and Global Human Capital (IIASA, VID/ÖAW, WIC), Welthandelsplatz 2, 1020, Vienna, Austria

    Alexia Prskawetz

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  1. Alexia Prskawetz
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Correspondence to Alexia Prskawetz .

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Editors and Affiliations

  1. Centre for Sociological Research, University of Leuven, Leuven, Belgium

    André Grow

  2. Centre for Sociological Research, University of Leuven, Leuven, Belgium

    Jan Van Bavel

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Prskawetz, A. (2017). The Role of Social Interactions in Demography: An Agent-Based Modelling Approach. In: Grow, A., Van Bavel, J. (eds) Agent-Based Modelling in Population Studies. The Springer Series on Demographic Methods and Population Analysis, vol 41. Springer, Cham. https://doi.org/10.1007/978-3-319-32283-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-32283-4_3

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