Endogenous treatment effect estimation using high-dimensional instruments and double selection

DOI10.1016/j.spl.2020.108967zbMath1456.62032OpenAlexW3093030373MaRDI QIDQ826717

N. E. Zubov

Publication date: 6 January 2021

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2020.108967

zbMATH Keywords

endogeneityinstrumental variablehigh dimensionalitytreatment effectdouble selection

Mathematics Subject Classification ID

Applications of statistics to social sciences (62P25) Statistical ranking and selection procedures (62F07) Causal inference from observational studies (62D20)

Related Items (1)

Dummy endogenous treatment effect estimation using high‐dimensional instrumental variables

Uses Software

• naivereg

Cites Work

• Unnamed Item
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• The nonlinear two-stage least-squares estimator
• The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso)
• Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Characterizing Selection Bias Using Experimental Data
• Inference on Treatment Effects after Selection among High-Dimensional Controls
• Causal Inference for Statistics, Social, and Biomedical Sciences
• Regularization Methods for High-Dimensional Instrumental Variables Regression With an Application to Genetical Genomics
• Tuning parameter selectors for the smoothly clipped absolute deviation method

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