Social networks and parental behavior in the intergenerational transmission of religion

Patacchini, Eleonora; Zénou, Yves

doi:10.3982/qe506

Cited by 69 publications

(39 citation statements)

References 54 publications

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“…Another approach in the education literature, pioneered by Hoxby (), and applied by Bifulco et al . () and Patacchini and Zenou (), makes use variation in the composition of peers in different cohorts in the same grades in a school. The underlying argument is that parents may choose a school based on the observed average composition of a cohort, but they will not know the actual composition of a new cohort: differences between the average and realized composition are an ‘unexpected shock’.…”

Section: Dealing With Endogeneity Of Network Formationmentioning

confidence: 99%

Credibly Identifying Social Effects: Accounting for Network Formation and Measurement Error

Advani

Malde

2018

Journal of Economic Surveys

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Understanding whether and how connections between agents (networks) such as declared friendships in classrooms, transactions between firms, and extended family connections, influence their socio-economic outcomes has been a growing area of research within economics. Early methods developed to identify these social effects assumed that networks had formed exogenously, and were perfectly observed, both of which are unlikely to hold in practice. A more recent literature, both within economics and in other disciplines, develops methods that relax these assumptions. This paper reviews that literature. It starts by providing a general econometric framework for linear models of social effects, and illustrates how network endogeneity and missing data on the network complicate identification of social effects. Thereafter, it discusses methods for overcoming the problems caused by endogenous formation of networks. Finally, it outlines the stark consequences of missing data on measures of the network, and regression parameters, before describing potential solutions.CREDIBLY IDENTIFYING SOCIAL EFFECTS 1017 unobserved dimensions could influence within-group interactions, and through this the actual outcome. Ignoring variation in interactions within such groups can lead to misleading conclusions and policy design, as shown in recent work by Carrell et al. (2013).More recently, a growing body of research within empirical economics uses data which directly measure interactions between pairs of agents (network data hereon) to sidestep these issues. This growth has been spurred by the increasing availability of such data, as well as the development of methods to identify and estimate social effects with such data. Starting with Bramoullé et al. (2009) andDe Giorgi et al. (2010), methods have been developed to overcome the reflection problem. They show how information on network structure can be used to break the simultaneity, and obtain the necessary exclusion restrictions for parameter identification. These methods, reviewed in detail by Advani and Malde (2014), Topa and Zenou (2015) and Boucher and Fortin (2015), impose strong restrictions on the network formation process and the quality of the data.In particular, the network is assumed to be exogenous conditional on observed agent-and network-level characteristics, and to be fully and perfectly observed by the researcher. Both assumptions are unlikely to hold in practice. In a schooling context, for example, personality traits which are rarely observed by a researcher might influence both a child's choice of friends and her schooling performance. Estimates of the influence of a child's friends' outcomes on her outcomes will be biased if her choice of friends is not accounted for. Similarly, accurately collecting fine-grained information on all connections is very costly and logistically challenging, making it rare to observe a complete, perfectly measured network. This has important implications for identification of social effects using restrictions based on the network struct...

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Section: Dealing With Endogeneity Of Network Formationmentioning

confidence: 99%

Credibly Identifying Social Effects: Accounting for Network Formation and Measurement Error

Advani

Malde

2018

Journal of Economic Surveys

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“…Proof of Proposition 1: To calculate the steady-state value of  * , we impose that:  +1 −   = 0 in (8) and obtain:…”

Section: Appendixmentioning

confidence: 99%

The role of cultural leaders in the transmission of preferences

Verdier

Zénou

2015

Economics Letters

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International audienceThis paper studies the population dynamics of preference traits in a model of intergenerational cultural transmission with cultural leaders who compete for oblique socialization. We show that by adding this new channel in the transmission of preferences, i.e. cultural leaders, in steady-state, there cannot be an equilibrium with total assimilation or total integration of the population

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“…Vertical transmission is related to social interaction within a scope of family or internal group, e.g from parents to children. Horizontal transmission is related to social interaction with external groups, e.g individual interaction, such as social networks [2].…”

Section: Methodsmentioning

confidence: 99%

Shia Muslim In Indonesia: Intellectual Transmission and Spreading Patterns in Indonesia

Halid¹

2018

Proceedings of the International Conference on Culture and Language in Southeast Asia (ICCLAS 2017)

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Social networks and parental behavior in the intergenerational transmission of religion

Cited by 69 publications

References 54 publications

Credibly Identifying Social Effects: Accounting for Network Formation and Measurement Error

Credibly Identifying Social Effects: Accounting for Network Formation and Measurement Error

The role of cultural leaders in the transmission of preferences

Shia Muslim In Indonesia: Intellectual Transmission and Spreading Patterns in Indonesia

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