Efficient estimation with missing data and endogeneity

Bhavna Rai

Econometric Reviews, 2023, vol. 42, issue 2, 220-239

Abstract: I study the problem of missing values in the outcome and endogenous covariates in linear models. I propose an estimator that improves efficiency relative to a complete cases 2SLS. Unlike traditional imputation, my estimator is consistent even if the model contains nonlinear functions – like squares and interactions – of the endogenous covariates. It can also be used to combine data sets with missing outcome, missing endogenous covariates, and no missing variables. It includes the well-known “Two-Sample 2SLS” as a special case under weaker assumptions than the corresponding literature.

Date: 2023
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DOI: 10.1080/07474938.2023.2178089

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