 When a single treatment is interacted with mutually exclusive binary variables to investigate treatment effect heterogeneity, our result implies that the coefficient for a given subgroup may actually be contaminated by treatment effects in other subgroups. We propose an alternative estimator that does not suffer from those issues .
<coherence>  When a single treatment is interacted with mutually exclusive binary variables to investigate treatment effect heterogeneity, our result implies that the coefficient for a given subgroup may actually be contaminated by treatment effects in other subgroups. We propose an alternative estimator that does not suffer from those issues .
 We propose alternative estimators .