Abstract:
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Encouragement designs arise frequently with the purpose of increasing the uptake of the treatment of interest that cannot be enforced. By design, encouragements entail the complication of non-compliance and they can give rise to a variety of mechanisms. In particular, when they are assigned at cluster level social interactions can result in spillover effects. Disentangling the effect of encouragement through spillover effects from that through the enhancement of the treatment could be crucial for improving the program and planning the scale-up. We capitalize on the principal stratification framework to define stratum-specific causal effects, i.e., effects for specific latent subpopulations defined by the joint potential compliance statuses under both encouragement conditions. We provide alternative assumptions under which an extrapolation across principal strata allows to disentangle the effects. Estimation is performed using Bayesian hierarchical models to account for clustering. We illustrate the proposed methodology on a cluster randomized experiment implemented in Zambia to evaluate the impact on malaria prevalence of a loan program intended to increase bed net coverage.
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