arXiv 28 Aug 2023 · Econometrics · publishedJapanese Economic Review (2023) · 1 citations (OpenAlex)
arXiv:2308.14375 · PDF · DOI · OpenAlex · Extracted main text
This study considers the treatment choice problem when outcome variables are binary. We focus on statistical treatment rules that plug in fitted values based on nonparametric kernel regression and show that optimizing two parameters enables the calculation of the maximum regret. Using this result, we propose a novel bandwidth selection method based on the minimax regret criterion. Finally, we perform a numerical analysis to compare the optimal bandwidth choices for the binary and normally distributed outcomes.
appendix boundary found by appendix_titled_section at “Appendix 1: Proofs of Theorem \ref{thm:main} and Lemma \ref{lem:s-d}” · 81% of the source is main text. Read the extracted text to check this.
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 | Yata, K (2021) Optimal decision rules under partial identification | 1.000 | 5 | 3 | 100% |
| 2 | Ishihara, T. and T. Kitagawa (2021) Evidence aggregation for treatment choice self | 0.969 | 11 | 6 | 91% |
| 3 | Stoye, J (2012) Minimax regret treatment choice with covariates or with limited validity of experiments | 0.874 | 7 | 2 | 100% |
| 4 | Manski, C. F (2007) Minimax-regret treatment choice with missing outcome data | 0.644 | 2 | 2 | 100% |
| 5 | Manski, C. F (2004) Statistical treatment rules for heterogeneous populations | 0.644 | 2 | 2 | 100% |
| 6 | Stoye, J (2009) Minimax regret treatment choice with finite samples | 0.644 | 2 | 2 | 100% |
| 7 | Tetenov, A (2012) Statistical treatment choice based on asymmetric minimax regret criteria | 0.644 | 2 | 2 | 100% |
| 8 | Li, Q. and J. S. Racine (2007) Nonparametric Econometrics: Theory and Practice | 0.405 | 1 | 1 | 100% |
Showing the top 8 of 8 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Evidence Aggregation for Treatment Choice | 0.405 | 1 | 1 |
| 2 | Treatment Choice with Nonlinear Regret | 0.405 | 1 | 1 |
| 3 | Leave No One Undermined: Policy Targeting with Regret Aversion | 0.405 | 1 | 1 |
| 4 | Optimal estimation for regression discontinuity design with binary outcomes | 0.000 | 1 | 1 |