arXiv 28 Oct 2022 · Econometrics · 2 citations (OpenAlex)
arXiv:2210.15829 · PDF · DOI · OpenAlex · Extracted main text
We propose a new estimator for heterogeneous treatment effects in a partially linear model (PLM) with multiple exogenous covariates and a potentially endogenous treatment variable. Our approach integrates a Robinson transformation to handle the nonparametric component, the Smooth Minimum Distance (SMD) method to leverage conditional mean independence restrictions, and a Neyman-Orthogonalized first-order condition (FOC). By employing regularized model selection techniques like the Lasso method, our estimator accommodates numerous covariates while exhibiting reduced bias, consistency, and asymptotic normality. Simulations demonstrate its robust performance with diverse instrument sets compared to traditional GMM-type estimators. Applying this method to estimate Medicaid's heterogeneous treatment effects from the Oregon Health Insurance Experiment reveals more robust and reliable results than conventional GMM approaches.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Chernozhukov, V., D. Chetverikov, M. Demirer, E. Duflo, C. Hansen, W… (2018) Double/debiased machine learning for treatment and structural parameters | 0.974 | 13 | 4 | 92% |
| 2 | Antoine, B. and X. Sun (2021) Partially Linear Models with Endogeneity: a conditional moment based approach | 0.961 | 18 | 6 | 89% |
| escanciano2023debiased | unmatched citation key escanciano2023debiased | 0.874 | 8 | 2 | 100% |
| 4 | Lavergne, P. and V. Patilea (2013) Smooth minimum distance estimation and testing with conditional estimating equations: Uniform in bandwidth theory | 0.843 | 3 | 3 | 100% |
| 5 | Robinson, P. (1988, July) (1988) Root-n-consistent semiparametric regression | 0.811 | 4 | 2 | 100% |
| 6 | van de Geer, S (2016) Estimation and Testing Under Sparsity École d'Été de Probabilités de Saint-Flour XLV – 2015 / by Sara van de Geer.\/ (1st ed. 20… | 0.737 | 3 | 2 | 100% |
| 7 | Imbens, G. W. and D. B. Rubin (2015) Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction | 0.644 | 2 | 2 | 100% |
| 8 | Finkelstein, A., S. Taubman, B. Wright, M. Bernstein, J. Gruber, J.… (2012) The oregon health insurance experiment: Evidence from the first year | 0.585 | 3 | 1 | 100% |
| 9 | Hoeffding, W (1948) A class of statistics with asymptotically normal distribution | 0.511 | 2 | 2 | 50% |
| 10 | Baicker, K., A. Finkelstein, J. Song, and S. Taubman (2014) The impact of medicaid on labor market activity and program participation: Evidence from the oregon health insurance experiment | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 20 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Feasible IV Regression without Excluded Instruments | 0.644 | 2 | 2 |
| 2 | Clustered Covariate Regression | 0.000 | 1 | 1 |