Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/150380 
Year of Publication: 
2015
Citation: 
[Journal:] Quantitative Economics [ISSN:] 1759-7331 [Volume:] 6 [Issue:] 1 [Publisher:] The Econometric Society [Place:] New Haven, CT [Year:] 2015 [Pages:] 49-83
Publisher: 
The Econometric Society, New Haven, CT
Abstract: 
This paper studies (nonparametric) partial identification of treatment response with social interactions. It imposes conditions motivated by economic theory on the primitives of the model, that is, the structural equations, and shows that they imply shape restrictions on the distribution of potential outcomes via monotone comparative statics. The econometric framework is tractable and allows for counterfactual predictions in models with multiple equilibria. Under three sets of assumptions, we identify sharp distributional bounds on the potential outcomes given observable data. We illustrate our results by studying the effect of police per capita on crime rates in New York state.
Subjects: 
Treatment effects
social interactions
nonparametric bounds
supermodular games
monotone comparative statics
first order stochastic dominance
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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