Using Aggregated Relational Data to Feasibly Identify Network Structure without Network Data
Emily Breza, Arun G. Chandrasekhar, Tyler H. McCormick, Mengjie Pan
American Economic Review · 2020 · Volume 110 · Issue 8
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.
Keywords
Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Data Access, Field Experiments, Network Formation and Analysis: Theory, Economic Sociology, Economic Anthropology, Language, Social and Economic Stratification
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