12 citations · 28 across the 11 of their papers we have counts for
11 papers
Bandwidth Selection for Treatment Choice with Binary Outcomes
Takuya Ishihara
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 kerne…
Asymptotically Optimal Fixed-Budget Best Arm Identification with Variance-Dependent Bounds
Masahiro Kato, Masaaki Imaizumi, Takuya Ishihara +1
We investigate the problem of fixed-budget best arm identification (BAI) for minimizing expected simple regret. In an adaptive experiment, a decision maker draws one of multiple tr…
Shrinkage Methods for Treatment Choice
Takuya Ishihara, Daisuke Kurisu
This study examines the problem of determining whether to treat individuals based on observed covariates. The most common decision rule is the conditional empirical success (CES) r…
Best Arm Identification with Contextual Information under a Small Gap
Masahiro Kato, Masaaki Imaizumi, Takuya Ishihara +1
We study the best-arm identification (BAI) problem with a fixed budget and contextual (covariate) information. In each round of an adaptive experiment, after observing contextual i…
Adaptively Robust Small Area Estimation: Balancing Robustness and Efficiency of Empirical Bayes Confidence Intervals
Daisuke Kurisu, Takuya Ishihara, Shonosuke Sugasawa
Empirical Bayes small area estimation based on the well-known Fay-Herriot model may produce unreliable estimates when outlying areas exist. Existing robust methods against outliers…
Evidence Aggregation for Treatment Choice
Takuya Ishihara, Toru Kitagawa
Consider a planner who has limited knowledge of the policy's causal impact on a certain local population of interest due to a lack of data, but does have access to the publicized i…
Efficient Adaptive Experimental Design for Average Treatment Effect Estimation
Masahiro Kato, Takuya Ishihara, Junya Honda +1
We study how to efficiently estimate average treatment effects (ATEs) using adaptive experiments. In adaptive experiments, experimenters sequentially assign treatments to experimen…
Panel Data Quantile Regression for Treatment Effect Models
Takuya Ishihara
In this study, we develop a novel estimation method for quantile treatment effects (QTE) under rank invariance and rank stationarity assumptions. Ishihara (2020) explores identific…
Identification and Estimation of Time-Varying Nonseparable Panel Data Models without Stayers
Takuya Ishihara
This paper explores the identification and estimation of nonseparable panel data models. We show that the structural function is nonparametrically identified when it is strictly in…
Partial Identification of Nonseparable Models using Binary Instruments
Takuya Ishihara
In this study, we explore the partial identification of nonseparable models with continuous endogenous and binary instrumental variables. We show that the structural function is pa…
Leptogenesis in SUSY GUT model
Takuya Ishihara, Nobuhiro Maekawa, Mao Takegawa +1
We study the thermal leptogenesis in the SUSY GUT model in which realistic masses and mixings of quarks and leptons can be realized. We show that the sufficient…