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Exact P-values for Network Interference

Susan Athey, Dean Eckles and Guido Imbens

No 21313, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We study the calculation of exact p-values for a large class of non-sharp null hypotheses about treatment effects in a setting with data from experiments involving members of a single connected network. The class includes null hypotheses that limit the effect of one unit's treatment status on another according to the distance between units; for example, the hypothesis might specify that the treatment status of immediate neighbors has no effect, or that units more than two edges away have no effect. We also consider hypotheses concerning the validity of sparsification of a network (for example based on the strength of ties) and hypotheses restricting heterogeneity in peer effects (so that, for example, only the number or fraction treated among neighboring units matters). Our general approach is to define an artificial experiment, such that the null hypothesis that was not sharp for the original experiment is sharp for the artificial experiment, and such that the randomization analysis for the artificial experiment is validated by the design of the original experiment.

JEL-codes: C01 C1 (search for similar items in EconPapers)
Date: 2015-07
New Economics Papers: this item is included in nep-ecm, nep-exp and nep-net
Note: IO LS PE TWP
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

Published as Susan Athey & Dean Eckles & Guido W. Imbens, 2018. "Exact -Values for Network Interference," Journal of the American Statistical Association, vol 113(521), pages 230-240.

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Journal Article: Exact p-Values for Network Interference (2018) Downloads
Working Paper: Exact P-Values for Network Interference (2015) Downloads
Working Paper: Exact P-Values for Network Interference (2015) Downloads
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