Two-Stage Least Squares with a Randomly Right-Censored Outcome

  title={Two-Stage Least Squares with a Randomly Right-Censored Outcome},
  author={Jad Beyhum},
  journal={ERN EM Feeds},
  • Jad Beyhum
  • Published 11 October 2021
  • Mathematics, Economics
  • ERN EM Feeds
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… 


Nonparametric Instrumental Regression With Right Censored Duration Outcomes
This paper analyzes the effect of a discrete treatment Z on a duration T and proposes an estimation procedure to solve this system and derive rates of convergence and conditions under which the estimator is asymptotically normal.
Treatment Effects With Censoring and Endogeneity
This article develops a nonparametric approach to identification and estimation of treatment effects on censored outcomes when treatment may be endogenous and have arbitrarily heterogenous effects.
Quantile Regression with Censoring and Endogeneity
In this paper we develop a new censored quantile instrumental variable (CQIV) estimator and describe its properties and computation. The CQIV estimator combines Powell (1986) censored quantile
Distributional Convergence under Random Censorship when Covariables are Present
Assume that (Xi, Yi), 1 < i < n, is an i.i.d. sample of (p + 1)-variate vectors, where each Yi is at risk of being censored from the right and Xi is a vector of observable covariables. Under weak
Instrumental variable estimation in a survival context.
This article develops the IV approach for regression analysis in a survival context, primarily under an additive hazards model, for which it is established that analogous strategies can also be used under a proportional hazards model specification, provided the outcome is rare over the entire follow-up.
Correcting for Selective Compliance in a Re-employment Bonus Experiment
We propose a two-stage instrumental variable estimator that is consistent if there is selective compliance in the treatment group of a randomized experiment and the outcome variable is a censored
Consistent estimation under random censorship when covariables are present
Abstract Assume that ( X i , Y i ), 1 ≤ i ≤ n , are independent ( p + 1)-variate vectors, where each Y i is at risk of being censored from the right and X i is a vector of observable covariables. We
Bounds on Average and Quantile Treatment Effects on Duration Outcomes Under Censoring, Selection, and Noncompliance
Abstract We consider the problem of assessing the effects of a treatment on duration outcomes using data from a randomized evaluation with noncompliance. For such settings, we derive nonparametric
Reader reaction: Instrumental variable additive hazards models with exposure-dependent censoring.
This work presents another extension of 2SLS that can address the limitation that the censoring distribution is unrelated to the endogenous exposure variable and proposes a method to address this limitation.
Nonparametric binary instrumental variable analysis of competing risks data.
A simple, plug-in estimator is introduced using nonparametric estimators of the cumulative incidence function, with confidence intervals derived using asymptotic theory to provide an overall test of the treatment effect, and an integrated weighted difference statistic is suggested.