Spillover effects within randomized clusters pose a challenge for identifying impacts of an individualized treatment. The paper proposes a solution. Longitudinal and intra-household observations are combined in estimating the direct knowledge gain from watching an info-movie in rural India, while randomized village assignment identifies knowledge sharing. Simulations on synthetic data and econometric tests provide support for the estimation method. We find evidence of information sharing, but far less so for disadvantaged groups, such as illiterate and lower-caste individuals; these groups rely more on actually seeing the movie. Our results are consistent with sizeable biases in ordinary least squares, matching or instrumental variable impact estimators that ignore within-cluster spillovers.
