  This note develops a simple two-stage least squares (2SLS) procedure to
estimate the causal effect of some endogenous regressors on a randomly right
censored outcome in the linear model. The proposal replaces the usual ordinary
least squares regressions of the standard 2SLS by weighted least squares
regressions. The weights correspond to the inverse probability of censoring. We
show consistency and asymptotic normality of the estimator. The estimator
exhibits good finite sample performances in simulations.
