Abstract
Research has indicated that fertility spreads through social networks and attributed this phenomenon to social interaction effects. It remains unclear, however, whether the findings of previous studies reflect the direct influence of network partners or contextual and selection factors, such as shared environment and common background characteristics. The present study uses instrumental variables to improve the identification of social interaction effects on fertility. Using data from the System of social statistical data sets (SSD) of Statistics Netherlands, we identify two networks—the network of colleagues at the workplace and the network of siblings in the family—to examine the influence of network partners on individual fertility decisions. Discrete-time event-history models with random effects provide evidence for social interaction effects, showing that colleagues’ and siblings’ fertility have direct consequences for an individual’s fertility. Moreover, colleague effects are concentrated in female-female interactions, and women are more strongly influenced by their siblings, regardless of siblings’ gender. These results are the first to demonstrate spillover effects across network boundaries, suggesting that fertility effects accumulate through social ties not only within but also across different domains of interaction.
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Notes
In this study, the term social interaction effects refers to the direct influence of network partners on an individual.
Ciliberto et al. (2016) used a dummy variable indicating whether any colleague’s sibling had a baby within the last two years and examined the impact of this variable on total number of children that women in a workplace had. Because this instrument should first influence the colleague’s fertility and then the focal person’s fertility through the colleague, it is likely that the effects are not captured within a two-year period.
Extending the risk period to more than one year would increase the risk of unidentified workers who left the workplace before September. Our restrictions ensured that people identified as colleagues were working at the firm in a given period.
Using a colleague’s sibling’s fertility as an instrument restricted the sample to only colleagues with siblings, who account for 87.5% of our target group. Accordingly, we additionally checked whether the fertility intentions of the excluded group differed from the individuals with siblings. Analyses using the Netherlands Kinship Panel Study (NKPS; Dykstra et al. 2012) showed that the intention to have a child—regardless of having a child or not—did not differ significantly between singletons and individuals with siblings in our study cohort. The only significant difference observed was that the desire to have three children was higher for individuals with two or three siblings compared with singletons.
We alternatively relaxed the matching criteria by excluding mother’s age at first birth and using a three-category measure of parental income to increase the number of matches. The findings are very similar to those presented in Fig. 4.
The findings are robust to increasing the threshold to 10,000 and 15,000 respectively.
We were not able to replicate these analyses for colleague effects because of colleagues with siblings living distant and also colleagues with siblings living close present within the same firm.
References
Asphjell, M. K., Hensvik, L., & Nilsson, P. (2013). Businesses, buddies, and babies: Fertility and social interactions at work (Working Paper No 2013:8). Uppsala, Sweden: Uppsala University, Center for Labor Studies.
Axinn, W. G., Clarkberg, M. E., & Thornton, A. (1994). Family influences on family size preferences. Demography, 31, 65–79.
Bakker, B. F., Van Rooijen, J., & Van Toor, L. (2014). The system of social statistical datasets of Statistics Netherlands: An integral approach to the production of register-based social statistics. Statistical Journal of the IAOS, 30, 411–424.
Balbo, N., & Barban, N. (2014). Does fertility behavior spread among friends? American Sociological Review, 79, 412–431.
Bandura, A. (1977). Social learning theory. Englewood Cliffs, NJ: Prentice Hall.
Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71–81). New York, NY: Academic Press.
Barber, J. S. (2000). Intergenerational influences on the entry into parenthood: Mothers’ preferences for family and nonfamily behavior. Social Forces, 79, 319–348.
Bernardi, L. (2003). Channels of social influence on reproduction. Population Research and Policy Review, 22, 427–555.
Bernardi, L., & Klärner, A. (2014). Social networks and fertility. Demographic Research, 30, 641–670. https://doi.org/10.4054/DemRes.2014.30.22
Bongaarts, J., & Watkins, S. C. (1996). Social interactions and contemporary fertility transitions. Population and Development Review, 22, 639–682.
Brase, G. L., & Brase, S. L. (2012). Emotional regulation of fertility decision making: What is the nature and structure of “baby fever”? Emotion, 12, 1141–1154.
Centraal Bureau voor de Statistiek. (n.d.-a). Average age of the mother at the birth of first child in the Netherlands in 2014 (Statista report). Retrieved from https://www.statista.com/statistics/520290/average-age-mother-at-the-first-birth-in-the-netherlands/
Centraal Bureau voor de Statistiek. (n.d.-b). Economic position of women has improved (Statista report). Retrieved from https://www.cbs.nl/en-gb/news/2018/50/economic-position-of-women-has-improved
Ciliberto, F., Miller, A. R., Nielsen, H. S., & Simonsen, M. (2016). Playing the fertility game at work: An equilibrium model of peer effects. International Economic Review, 57, 827–856.
Ciliberto, F., & Tamer, E. (2009). Market structure and multiple equilibria in airline markets. Econometrica, 77, 1791–1828.
Coale, A. J., & Watkins, S. C. (1986). The decline of fertility in Europe. Princeton, NJ: Princeton University Press.
Cools, S., & Kaldager, R. H. (2017). Identifying fertility contagion using random fertility shocks (Working Paper No 861). Oslo: Statistics Norway Research Department.
de Vuijst, E., Poortman, A.-R., Das, M., & van Gaalen, R. (2017). Cross-sibling effects on divorce in the Netherlands. Advances in Life Course Research, 34, 1–9.
Dykstra, P. A., Kalmijn, M., Knijn, T. C., Komter, A. E., Liefbroer, A. C., & Mulder, C. H. (2012). Codebook of the Netherlands Kinship Panel Study: A multi-actor, multi-method panel study on solidarity in family relationships, Wave 2 (Version 2.0). The Hague, the Netherlands: NKPS.
Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7, 117–140.
Fokkema, T., de Valk, H., de Beer, J., & van Duin, C. (2008). The Netherlands: Childbearing within the context of a “Poldermodel” society. Demographic Research, 19, 743–794. https://doi.org/10.4054/DemRes.2008.19.21
Heckman, J. J. (1979). Sample selection bias as a specification error. Econometrica, 47, 153–161.
Keim, S. (2011). Social networks and family formation processes. Wiesbaden, Germany: VS-Verlag.
Keim, S., Klärner, A., & Bernardi, L. (2013). Tie strength and family formation: Which personal relationships are influential? Personal Relationships, 20, 462–478.
Kohler, H. P., Billari, F. C., & Ortega, J. A. (2002). The emergence of lowest-low fertility in Europe during the 1990s. Population and Development Review, 28, 641–680.
Kotte, M., & Ludwig, V. (2011). Intergenerational transmission of fertility intentions and behaviour in Germany: The role of contagion. Vienna Yearbook of Population Research, 9, 207–226.
Kuziemko, I. (2006). Is having babies contagious? Estimating fertility peer effects between siblings. Unpublished manuscript, Graduate Business School, Columbia Business School, New York, NY. Retrieved from https://www0.gsb.columbia.edu/mygsb/faculty/research/pubfiles/5799/fertility_11_29_06.pdf
Lois, D., & Becker, O. A. (2014). Is fertility contagious? Using panel data to disentangle mechanisms of social network influences on fertility decisions. Advances in Life Course Research, 21, 123–134.
Lyngstad, T. H., & Prskawetz, A. (2010). Do siblings’ fertility decisions influence each other? Demography, 47, 923–934.
Manski, C. F. (1993). Identification of endogenous social effects: The reflection problem. Review of Economic Studies, 60, 531–542.
Manski, C. F. (1999). Identification problems in the social sciences. Cambridge, MA: Harvard University Press.
Montgomery, M. R., & Casterline, J. B. (1996). Social learning, social influence, and new models of fertility. Population and Development Review, 22(Suppl.), 151–175.
Pink, S., Leopold, T., & Engelhardt, H. (2014). Fertility and social interaction at the workplace: Does childbearing spread among colleagues? Advances in Life Course Research, 21, 113–122.
Wooldridge, J. M. (2005). Instrumental variables estimation with panel data. Econometric Theory, 21, 865–869.
Acknowledgments
This study was supported by the German Research Foundation (Grant Number EN 424/10-1) and the NORFACE DIAL project EQUALLIVES.
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Buyukkececi, Z., Leopold, T., van Gaalen, R. et al. Family, Firms, and Fertility: A Study of Social Interaction Effects. Demography 57, 243–266 (2020). https://doi.org/10.1007/s13524-019-00841-y
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DOI: https://doi.org/10.1007/s13524-019-00841-y