Toru Kitagawa, Sokbae Lee, Chen Qiu
arXiv 19 Jun 2025 · Econometrics
arXiv:2506.16430 · PDF · Extracted main text
While the importance of personalized policymaking is widely recognized, fully personalized implementation remains rare in practice. We study the problem of policy targeting for a regret-averse planner when training data gives a rich set of observable characteristics while the assignment rules can only depend on its subset. Grounded in decision theory, our regret-averse criterion reflects a planner's concern about regret inequality across the population, which generally leads to a fractional optimal rule due to treatment effect heterogeneity beyond the average treatment effects conditional on the subset characteristics. We propose a debiased empirical risk minimization approach to learn the optimal rule from data. Viewing our debiased criterion as a weighted least squares problem, we establish new upper and lower bounds for the excess risk, indicating a convergence rate of 1/n and asymptotic efficiency in certain cases. We apply our approach to the National JTPA Study and the International Stroke Trial.
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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 | Kitagawa, Toru and Tetenov, Aleksey (2018) Who should be treated? Empirical welfare maximization methods for treatment choice self | 1.000 | 7 | 4 | 100% |
| 2 | Resnjanskij, Sven and Ruhose, Jens and Wiederhold, Simon and Woessma… (2024) Can mentoring alleviate family disadvantage in adolescence? A field experiment to improve labor market prospects | 0.874 | 7 | 2 | 100% |
| 3 | Susan Athey and Stefan Wager (2021) Efficient policy learning with observational data | 0.811 | 4 | 2 | 100% |
| 4 | Atkinson, Anthony B (1970) On the measurement of inequality | 0.811 | 4 | 2 | 100% |
| 5 | Newey, Whitney K (1994) The asymptotic variance of semiparametric estimators | 0.737 | 4 | 3 | 50% |
| 6 | Kitagawa, Toru and Lee, Sokbae and Qiu, Chen (2022) Treatment choice with nonlinear regret self | 0.644 | 2 | 2 | 100% |
| 7 | Manski, Charles F (2022) Patient-centered appraisal of race-free clinical risk assessment | 0.644 | 2 | 2 | 100% |
| 8 | Michael Kohler (2000) Inequalities for uniform deviations of averages from expectations with applications to nonparametric regression | 0.585 | 3 | 3 | 33% |
| 9 | Manski, Charles F (2000) Identification problems and decisions under ambiguity: empirical analysis of treatment response and normative analysis of treatm… | 0.585 | 3 | 1 | 100% |
| 10 | Manski, Charles F (2004) Statistical treatment rules for heterogeneous populations | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 93 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Better Measurement or Larger Samples? Data Collection for Policy Learning with Unobserved Heterogeneity | 0.405 | 1 | 1 |
| 2 | Nonparametric Bayesian Policy Learning | 0.405 | 1 | 1 |