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Identification and estimation of outcome response with heterogeneous treatment externalities

Tiziano Arduini (), Eleonora Patacchini and Edoardo Rainone ()

No 974, Temi di discussione (Economic working papers) from Bank of Italy, Economic Research and International Relations Area

Abstract: This paper studies the identification and estimation of treatment response with heterogeneous spillovers in a network model. We generalize the standard linear-in-means model to allow for multiple groups with between and within-group interactions. We provide a set of identification conditions of peer effects and consider a 2SLS estimation approach. Large sample properties of the proposed estimators are derived. Simulation experiments show that the estimators perform well in finite samples. The model is used to study the effectiveness of policies where peer effects are seen as a mechanism through which the treatments could propagate through the network. When interactions among groups are at work, a shock on a treated group has effects on the non-treated. Our framework allows for quantifying how much of the indirect treatment effect is due to variations in the characteristics of treated peers (treatment contextual effects) and how much is because of variations in peer outcomes (peer effects).

Keywords: Networks; Heterogeneous Peer Effects; Spatial Autoregressive Model; Two-Stage Least Squares; Efficiency; Policy Evaluation; Treatment Response; Indirect Treatment Effect. (search for similar items in EconPapers)
JEL-codes: C13 C21 D62 (search for similar items in EconPapers)
Date: 2014-09
New Economics Papers: this item is included in nep-ure
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Citations: View citations in EconPapers (3) Track citations by RSS feed

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Related works:
Working Paper: Identification and Estimation of Outcome Response with Heterogeneous Treatment Externalities (2014) Downloads
Working Paper: Identification and Estimation of Outcome Response with Heterogeneous Treatment Externalities (2014) Downloads
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