The Finite Sample Performance of Inference Methods for Propensity Score Matching and Weighting Estimators
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Publication:6626294
DOI10.1080/07350015.2018.1476247zbMATH Open1547.62628MaRDI QIDQ6626294
Hugo Bodory, Martin Huber, Lorenzo Camponovo, Michael Lechner
Publication date: 28 October 2024
Published in: Journal of Business and Economic Statistics (Search for Journal in Brave)
Cites Work
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- Irregular Identification, Support Conditions, and Inverse Weight Estimation
- On the Failure of the Bootstrap for Matching Estimators
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- Matching As An Econometric Evaluation Estimator
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- A Three-step Method for Choosing the Number of Bootstrap Repetitions
- Matching on the Estimated Propensity Score
- Some Practical Issues in the Evaluation of Heterogeneous Labour Market Programmes by Matching Methods
- A Martingale Representation for Matching Estimators
- Bias-Corrected Matching Estimators for Average Treatment Effects
- Large Sample Properties of Matching Estimators for Average Treatment Effects
- Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score
- A Generalization of Sampling Without Replacement From a Finite Universe
Related Items (3)
Nonparametric bootstrap for propensity score matching estimators ⋮ Estimation of causal effects with a binary treatment variable: a unified M-estimation framework ⋮ Review and comparison of treatment effect estimators using propensity and prognostic scores
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