TY  - JOUR
A1  - Lois, Daniel
T1  - Types of social networks and the transition to parenthood
Y1  - 2016/04/05
JF  - Demographic Research
JO  - Demographic Research
SN  - 1435-9871
SP  - 657
EP  - 688
DO  - 10.4054/DemRes.2016.34.23
VL  - 34
IS  - 23
UR  - https://www.demographic-research.org/volumes/vol34/23/
L1  - https://www.demographic-research.org/volumes/vol34/23/34-23.pdf
L2  - https://www.demographic-research.org/volumes/vol34/23/34-23.pdf
L3  - https://www.demographic-research.org/volumes/vol34/23/files/readme.34-23.txt
L3  - https://www.demographic-research.org/volumes/vol34/23/files/demographic-research.34-23.zip
N2  - Background: A growing body of literature acknowledges the importance of social interaction and ideational factors for generative behavior. Building on this research, the present study identifies specific types of social network and gauges their value for predicting fertility behavior. 

Methods: Based on data from the German Family Panel (N = 3,104 respondents aged 20 to 42), four types of ego-centric social networks were identified using cluster analyses. Clusters were used to prospectively predict the transition to parenthood using a discrete-time event history analysis. 

Results: In the event history analyses, the highest propensity to start a family was found for ‘family-centered’ social networks, which were characterized primarily by a high share of persons with young children, a high amount of network support in case of parenthood, and a high proportion of strong ties to members of the nuclear family. By contrast, respondents who were embedded in ‘family-remote’ networks had the lowest transition rate to parenthood. Family-remote networks were characterized by a high share of friends and acquaintances, a high proportion of weak ties, and a low amount of social support and social pressure. Regarding selection effects, a comparison of cluster affiliation over time does not consistently confirm that persons who start a family select themselves into ‘fertility-promoting’ network types. In sum, the results enhance our understanding of how mechanisms of social influence and structural features of ego-centric social networks are interlinked. 

ER  -