Hi everyone!
This week at the Applied Statistics Workshop we will be welcoming *Emily
Breza*, Assistant Professor of Economics at Harvard University. She will be
presenting work entitled *Using Aggregated Relational Data to Feasibly
Identify Network Structure without Network Data*. Please find the abstract
below and on the Applied Stats website here
<https://projects.iq.harvard.edu/applied.stats.workshop-gov3009>.
As usual, we will meet at noon in CGIS Knafel Room 354 and lunch will be
provided. See you all there!
-- Dana Higgins
*Title:* * Using Aggregated Relational Data to Feasibly Identify Network
Structure without Network Data *
*Abstract:* Social network data is often prohibitively expensive to
collect, limiting empirical network research. Typical economic network
mapping requires (1) enumerating a census, (2) eliciting the names of all
network links for each individual, (3) matching the list of
social connections to the census, and (4) repeating (1)-(3) across many
networks. In settings requiring field surveys, steps (2)-(3) can be very
expensive. In other network populations such as financial intermediaries or
high-risk groups, proprietary data and privacy concerns may render (2)-(3)
impossible. Both restrict the accessibility of high-quality networks
research to investigators with considerable resources.
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 social connections have trait k?” Our method uses ARD to
recover the parameters of a general network formation model, which in turn,
permits the estimation of any arbitrary node- or graph-level statistic. The
method works well in simulations and in matching a range of network
characteristics in real-world graphs from 75 Indian villages. Moreover, we
replicate the results of two field experiments that involved collecting
network data. We show that the researchers would have drawn similar
conclusions using ARD alone. Finally, using calculations from J-PAL
fieldwork, we show that in rural India, for example, ARD surveys are 80%
cheaper than full network surveys.
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