Survey methods for estimating the size of weak-tie personal networks

Dennis Feehan, Vo Hai Son and Abu Abdul-Quader

No z2t4p, SocArXiv from Center for Open Science

Abstract: Researchers increasingly use *aggregate relational data* to learn about the size and distribution of survey respondents' weak-tie personal networks. Aggregate relational data are collected by asking questions about respondents' connectedness to many different groups (e.g., "How many teachers do you know?"). This approach can be powerful but, to make use of aggregate relational data, researchers must locate external information about the size of each of these groups from a census or from administrative records (e.g., the number of teachers in the population). This need for external information makes aggregate relational data difficult or impossible to collect in many settings. Here, we show that relatively simple modifications can overcome this need for external data, significantly increasing the flexibility of the method and weakening key assumptions required by the associated estimators. Our methods are appropriate for using a sample survey to study the size and distribution of weak-tie network connections. Our methods can also be used as part of the network scale-up method to estimate the size of hidden populations. We illustrate our approach with two empirical studies: a large simulation study, and original household survey data collected in Hanoi, Vietnam.

Date: 2021-05-19
New Economics Papers: this item is included in nep-net, nep-sea and nep-tra
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://osf.io/download/60a576c02cb36e012cc14640/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:z2t4p

DOI: 10.31219/osf.io/z2t4p

Access Statistics for this paper

More papers in SocArXiv from Center for Open Science
Bibliographic data for series maintained by OSF ().