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SUMMARY:Implementing Propensity Score Matching with Network Data: The effe
 ct of GATT on bilateral trade - Luca De Benedictis (Università di Macerat
 a)
DTSTART:20160825T135000Z
DTEND:20160825T143000Z
UID:TALK67058@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:Co-authors: Bruno Arpino\, Alessandra Mattei  <b>&nbsp\;</b> <
 br><span><br>Motivated by the evaluation of the causal effect of the Gener
 al Agreement on Tariffs</span>  and Trade on bilateral international trade
  flows\, we investigate the role of network structure  in propensity score
  matching under the assumption of strong ignorability. We study the  sensi
 tivity of causal inference with respect to the presence of characteristics
  of the network  in the set of confounders conditional on which strong ign
 orability is assumed to hold. We find  that estimates of the average causa
 l effect are highly sensitive to the presence of node-level  network stati
 stics in the set of confounders. Therefore\, we argue that estimates may s
 uffer  from omitted variable bias when the relational dimension of units i
 s ignored\, at least in our  application.
LOCATION:Seminar Room 1\, Newton Institute
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