Identifying Treatment and Spillover Effects Using Exposure Contrasts

To report spillover effects, a common practice is to regress outcomes on statistics capturing treatment variation among neighboring units. This paper studies the causal interpretation of nonparametric analogs of these estimands, which we refer to as exposure contrasts. We demonstrate that their signs can be inconsistent with those of the unit-level effects of interest even under unconfounded assignment. We then provide interpretable restrictions under which exposure contrasts are sign preserving and therefore have causal interpretations. We discuss the implications of our results for cluster-randomized trials, network experiments, and observational settings with peer effects in selection into treatment.