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Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data.

ABSTRACT: Social network data are often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD): responses to questions of the form "how many of your links have trait k ?" Our method uses ARD to recover parameters of a network formation model, which permits sampling from a distribution over node- or graph-level statistics. We replicate the results of two field experiments that used network data and draw similar conclusions with ARD alone.

SUBMITTER: Breza E

PROVIDER: S-EPMC8439392 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data.

Breza Emily E Chandrasekhar Arun G AG McCormick Tyler H TH Pan Mengjie M

The American economic review 20200801 8

Social network data are often prohibitively expensive to collect, limiting empirical network research. We propose an inexpensive and feasible strategy for network elicitation using Aggregated Relational Data (ARD): responses to questions of the form "how many of your links have trait k ?" Our method uses ARD to recover parameters of a network formation model, which permits sampling from a distribution over node- or graph-level statistics. We replicate the results of two field experiments that us ...[more]

PMID: 34526729

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