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Family policies in the context of low fertility and social structure

Author

Listed:
  • Thomas Fent

    (Österreichische Akademie der Wissenschaften)

  • Belinda Aparicio Diaz

    (Österreichische Akademie der Wissenschaften)

  • Alexia Prskawetz

    (Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna))

Abstract

Objective: In this paper we investigate the effectiveness of family policies in the context of the social structure of a population. Methods: We use an agent-based model to analyse the impact of policies on individual fertility decisions and on fertility at the aggregate level. The crucial features of our model are the interactions between family policies and social structure, the agents’ heterogeneity, and the structure and influence of the social network. This modelling framework allows us to disentangle the direct effect (the alleviation of resource constraints) from the indirect effect (the diffusion of fertility intentions via social ties) of family policies. Results: Our results indicate that family policies have a positive and significant impact on fertility. In addition, the specific characteristics of the social network and social effects do not only relate to fertility, but also influence the effectiveness of family policies. Conclusions: Family policies can only be successful if they are designed to take into account the characteristics of the society in which they are implemented.

Suggested Citation

  • Thomas Fent & Belinda Aparicio Diaz & Alexia Prskawetz, 2013. "Family policies in the context of low fertility and social structure," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(37), pages 963-998.
    • Handle: RePEc:dem:demres:v:29:y:2013:i:37
    DOI: 10.4054/DemRes.2013.29.37
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    Cited by:

    1. Francesca Modena & Concetta Rondinelli & Fabio Sabatini, 2014. "Economic Insecurity and Fertility Intentions: The Case of Italy," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(S1), pages 233-255, May.
    2. Theresa Grafeneder-Weissteiner & Ingrid Kubin & Klaus Prettner & Alexia Prskawetz & Stefan Wrzaczek, 2012. "Coping with Inefficiencies in a New Economic Geography Model," VID Working Papers 1204, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    3. Tom Warnke & Oliver Reinhardt & Anna Klabunde & Frans Willekens & Adelinde M. Uhrmacher, 2017. "Modelling and simulating decision processes of linked lives: An approach based on concurrent processes and stochastic race," Population Studies, Taylor & Francis Journals, vol. 71(0), pages 69-83, October.
    4. Nasibeh Esmaeili & Mohammad Jalal Abbasi Shavazi, 2024. "Impact of family policies and economic situation on low fertility in Tehran, Iran: A multi-agent-based modeling," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 51(5), pages 107-154.
    5. Pau Baizan & Bruno Arpino & Carlos Eric Delclòs, 2016. "The Effect of Gender Policies on Fertility: The Moderating Role of Education and Normative Context," European Journal of Population, Springer;European Association for Population Studies, vol. 32(1), pages 1-30, February.
    6. Anna Klabunde & Frans Willekens, 2016. "Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges," European Journal of Population, Springer;European Association for Population Studies, vol. 32(1), pages 73-97, February.

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    More about this item

    Keywords

    family policy; social networks; low fertility; social structures; agent-based computational demography; social effects;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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