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Treatment Choice, Mean Square Regret and Partial Identification

Toru Kitagawa, Sokbae Lee, Chen Qiu

arXiv 10 Oct 2023 · Econometrics · publishedJapanese Economic Review (2023) · 2 citations (OpenAlex)

arXiv:2310.06242 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We consider a decision maker who faces a binary treatment choice when their welfare is only partially identified from data. We contribute to the literature by anchoring our finite-sample analysis on mean square regret, a decision criterion advocated by Kitagawa, Lee, and Qiu (2022). We find that optimal rules are always fractional, irrespective of the width of the identified set and precision of its estimate. The optimal treatment fraction is a simple logistic transformation of the commonly used t-statistic multiplied by a factor calculated by a simple constrained optimization. This treatment fraction gets closer to 0.5 as the width of the identified set becomes wider, implying the decision maker becomes more cautious against the adversarial Nature.

Citation extraction

42
references
138
in-text mentions
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distinct cited
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self-citations
6,886
main-text words

appendix boundary found by appendix_command · 52% of the source is main text. Read the extracted text to check this.

Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Stoye, J (2012) Minimax regret treatment choice with covariates or with limited validity of experiments1.000143100%
2Yata, K (2021) Optimal Decision Rules Under Partial Identification, ArXiv:2111.04926 [econ.EM], https://doi.org/10.48550/arXiv.2111.049261.000143100%
3Kitagawa, T., S. Lee, and C. Qiu (2022) Treatment Choice with Nonlinear Regret self0.90037773%
4Donoho, D. L (1994) Statistical estimation and optimal recovery0.87452100%
5Tetenov, A (2012) a): Measuring precision of statistical inference on partially identified parameters0.87452100%
6Stoye, J (2009) a): Minimax regret treatment choice with finite samples0.81142100%
7Manski, C. F (2000) Identification problems and decisions under ambiguity: empirical analysis of treatment response and normative analysis of treatm…0.73732100%
8Manski, C. F (2007) b): Minimax-regret treatment choice with missing outcome data0.73732100%
9Adjaho, C. and T. Christensen (2022) Externally Valid Treatment Choice0.73732100%
10Brock, W. A (2006) Profiling problems with partially identified structure0.73732100%

Showing the top 10 of 42 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Optimal Decision Rules Under Partial Identification0.51121
2Statistical Decisions and Partial Identification: With Application to Boundary Discontinuity Design0.51121
3Treatment Choice with Nonlinear Regret0.40511
4Debiased Machine Learning of Aggregated Intersection Bounds and Other Causal Parameters0.40511
5Policy Learning with Distributional Welfare0.40511
6Robust Bayes Treatment Choice with Partial Identification0.40511
7Leave No One Undermined: Policy Targeting with Regret Aversion0.40511
8Inference on Optimal Policy Values and Other Irregular Functionals via Softmax Smoothing0.40511