High-Dimensional Model-Assisted Inference for Local Average Treatment Effects With Instrumental Variables
From MaRDI portal
Publication:6620989
DOI10.1080/07350015.2021.1970575zbMATH Open1547.62926MaRDI QIDQ6620989
Publication date: 17 October 2024
Published in: Journal of Business and Economic Statistics (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Model-assisted inference for treatment effects using regularized calibrated estimation with high-dimensional data
- On asymptotically optimal confidence regions and tests for high-dimensional models
- Nonparametric IV estimation of local average treatment effects with covariates
- Instrumental variables: an econometrician's perspective
- Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data
- Comment: Understanding OR, PS and DR
- Robust inference on average treatment effects with possibly more covariates than observations
- Statistics for high-dimensional data. Methods, theory and applications.
- Model assisted survey sampling.
- On the application of probability theory to agricultural experiments. Essay on principles. Section 9. Translated from the Polish and edited by D. M. Dąbrowska and T. P. Speed
- Semiparametric instrumental variable estimation of treatment response models.
- Semiparametric estimation of treatment effect in a pretest-posttest study with missing data (with comments and rejoinder)
- Bounded, efficient and doubly robust estimation with inverse weighting
- Lasso adjustments of treatment effect estimates in randomized experiments
- Identification of Causal Effects Using Instrumental Variables
- Doubly robust instrumental variable regression
- A Distributional Approach for Causal Inference Using Propensity Scores
- Estimation of Regression Coefficients When Some Regressors Are Not Always Observed
- Assessing the effect of an influenza vaccine in an encouragement design
- A GENERAL DOUBLE ROBUSTNESS RESULT FOR ESTIMATING AVERAGE TREATMENT EFFECTS
- Inverse Probability Tilting for Moment Condition Models with Missing Data
- Inference on Treatment Effects after Selection among High-Dimensional Controls
- High-dimensional regression adjustments in randomized experiments
- Causal Inference with Generalized Structural Mean Models
- Correcting for non-compliance in randomized trials using structural nested mean models
- Bounded, Efficient and Multiply Robust Estimation of Average Treatment Effects Using Instrumental Variables
- Double/debiased machine learning for treatment and structural parameters
- Robust estimation of causal effects via a high-dimensional covariate balancing propensity score
- Regularized calibrated estimation of propensity scores with model misspecification and high-dimensional data
- Marginal and Nested Structural Models Using Instrumental Variables
- Bias-Reduced Doubly Robust Estimation
- Doubly Robust Estimation of the Local Average Treatment Effect Curve
- Estimation And Selection Via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications
- Doubly robust inference with missing data in survey sampling
- Independence, Monotonicity, and Latent Index Models: An Equivalence Result
- Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
- Covariate Balancing Propensity Score
Related Items (2)
Model-Assisted Complier Average Treatment Effect Estimates in Randomized Experiments with Noncompliance ⋮ High-dimensional model-assisted inference for treatment effects with multi-valued treatments
This page was built for publication: High-Dimensional Model-Assisted Inference for Local Average Treatment Effects With Instrumental Variables