Estimation of Conditional Average Treatment Effects With High-Dimensional Data
Bibliographic Data
| ID | 19418447 |
|---|---|
| Authors | Qingliang Fan (0000-0001-9560-3311, Department of Economics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, corresponding author), Yu‐Chin Hsu (National Central University), Yu-Chin Hsu (Institute of Economics, Academia Sinica, Taipei, Taiwan), Robert P Lieli (Central European University), Yichong Zhang (0000-0002-0677-7203, Singapore Management University) |
| Year | 2022 |
| Volume | 40 |
| Issue | 1 |
| Pages | 313-327 |
| Publication date | 2022-01-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2020.1811102 |
| OpenAlex | W3050159347 |
| Language | EN |
| Citations received | 8 |
| References cited | 38 |
Given the unconfoundedness assumption, we propose new nonparametric estimators for the reduced dimensional conditional average treatment effect (CATE) function. In the first stage, the nuisance functions necessary for identifying CATE are estimated by machine learning methods, allowing the number of covariates to be comparable to or larger than the sample size. The second stage consists of a low-dimensional local linear regression, reducing CATE to a function of the covariate(s) of interest. We consider two variants of the estimator depending on whether the nuisance functions are estimated over the full sample or over a hold-out sample. Building on Belloni at al. and Chernozhukov et al., we derive functional limit theory for the estimators and provide an easy-to-implement procedure for uniform inference based on the multiplier bootstrap. The empirical application revisits the effect of maternal smoking on a baby’s birth weight as a function of the mother’s age
Average treatment effect · Conditional expectation · Covariate · Econometrics · Estimating equations · Estimator · Inference · Nonparametric statistics · Sample size determination · Statistics · Advanced Causal Inference Techniques · Computer Science · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference · Artificial Intelligence
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On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
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On the Effect of Bias Estimation on Coverage Accuracy in Nonparametric Inference
Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score
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| Citations per year | 2 |
|---|---|
| Citation span | 2022 - 2026 (5) |
| Highly cited | No |