2022
DOI: 10.1186/s41937-022-00093-5
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Partial identification of nonlinear peer effects models with missing data

Abstract: This paper examines inference on social interactions models in the presence of missing data on outcomes. In these models, missing data on outcomes imply an incomplete data problem on both the endogenous variable and the regressors. However, getting a sharp estimate of the partially identified coefficients is computationally difficult. Using a monotonicity property of the peer effects and a mean independence condition of individual decisions on the missing data, I show partial identification results for the bin… Show more

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