Hoshino, Takahiro



Faculty of Economics (Mita)



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Academic Degrees 【 Display / hide

  • 博士(経済学), 名古屋大学

  • 博士(学術), 東京大学


Research Areas 【 Display / hide

  • Informatics / Statistical science

  • Humanities & Social Sciences / Economic statistics

  • Humanities & Social Sciences / Commerce

Research Keywords 【 Display / hide

  • marketing science

  • consumer behavior

  • decision making

  • Causal Inference

  • Behavioral economics

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Books 【 Display / hide

Papers 【 Display / hide

  • Semiparametric Bayesian Estimation for Marginal Parametric Potential Outcome Modeling: Application to Causal Inference

    Takahiro Hoshino

    Journal of the American Statistical Association (Journal of the American Statistical Association)  108 ( 504 ) 1189 - 1204 2013.12

    Research paper (scientific journal), Single Work, Accepted,  ISSN  01621459

     View Summary

    We propose a new semiparametric Bayesian model for causal inference in which assignment to treatment depends on potential outcomes. The model uses the probit stick-breaking process mixture proposed by Chung and Dunson (2009), a variant of the Dirichlet process mixture modeling. In contrast to previous Bayesian models, the proposed model directly estimates the parameters of the marginal parametric model of potential outcomes, while it relaxes the strong ignorability assumption, and requires no parametric model assumption for the assignment model and conditional distribution of the covariate vector. The proposed estimation method is more robust than maximum likelihood estimation, in that it does not require knowledge of the full joint distribution of potential outcomes, covariates, and assignments. In addition, the method is more efficient than fully nonparametric Bayes methods. We apply this model to infer the differential effects of cognitive and noncognitive skills on the wages of production and nonproduction workers using panel data from the National Longitudinal Survey of Youth in 1979. The study also presents the causal effect of online word-of-mouth onWeb site browsing behavior. Supplementary materials for this article are available online. © 2013 American Statistical Association.

  • Real-Time Survey of Vaccine Safety of the mRNA-1273 SARS-CoV-2 Vaccine in Workplace Vaccination at Keio University

    Kaho Okumura, Azusa Hara, Isa Inada, Daisuke Sugiyama, Takahiro Hoshino, Takahiro Yakoh, Hirokatsu Yokoyama, Hisashi Urushihara

    Vaccines (Vaccines)  10 ( 9 ) 1461 2022.09


     View Summary

    The mRNA-1273 Moderna COVID-19 vaccine was introduced to combat the COVID-19 global pandemic in 2020. Although the safety of the vaccine has been investigated worldwide, real-world safety data is scarce in Japan. An online, real-time survey of adverse events following immunization (AEFIs) with mRNA-1273 was conducted in the setting of a workplace vaccination program at the School of Pharmacy, Keio University from 26 June 2021, to 11 June 2022. Participants were requested to take four surveys during a seven-day follow-up period after each of the first, second, and third booster doses. The maximum number of responses, from 301 respondents, was obtained on day 0 (vaccination date) for the first dose. 98% of respondents reported local and systemic AEFIs for the second dose on day 1. No noticeable difference in local reactions was seen among the three doses. Females reported more AEFIs than males, and the young group (18–29 years) reported a higher rate than the middle age group (≥30 years) after the first dose. Age and gender differences in rates decreased at the second and third doses. This survey confirmed that the safety profile of mRNA-1273 in a real-world setting was similar to that derived from the clinical trials, and that the agent was well-tolerated.

  • Joint Modeling of Effects of Customer Tier Program on Customer Purchase Duration and Purchase Amount

    Kazuki Nishio, Takahiro Hoshino

    Journal of Retailing and Consumer Services (Journal of Retailing and Consumer Services)  66 2022.05

    Last author, Corresponding author, Accepted,  ISSN  09696989

     View Summary

    Nowadays, many supermarkets implement a customer tier program to increase their profits because it is expected to raise customers' willingness to purchase by setting thresholds. However, designing an appropriate program is difficult because each customer's heterogeneous purchase behavior is difficult to capture. Therefore, we simultaneously modeled purchase frequency and amount through a marked point process approach while considering program effects and customer characteristics. The results clarified that the points pressure effect was particularly strong among customers who originally visited the store infrequently and had not attained the threshold set up in the customer tier program many times in the past. In addition, we found that the three-tier customer tier program was superior to the two-tier program with respect to the operating income in supermarkets.

  • Estimation of Local Average Treatment Effect by Data Combination

    Kazuhiko Shinoda, Takahiro Hoshino

    Proceedings of the AAAI Conference on Artificial Intelligence 36 2022

    Last author, Accepted

     View Summary

    It is important to estimate the local average treatment effect (LATE) when
    compliance with a treatment assignment is incomplete. The previously proposed
    methods for LATE estimation required all relevant variables to be jointly
    observed in a single dataset; however, it is sometimes difficult or even
    impossible to collect such data in many real-world problems for technical or
    privacy reasons. We consider a novel problem setting in which LATE, as a
    function of covariates, is nonparametrically identified from the combination of
    separately observed datasets. For estimation, we show that the direct least
    squares method, which was originally developed for estimating the average
    treatment effect under complete compliance, is applicable to our setting.
    However, model selection and hyperparameter tuning for the direct least squares
    estimator can be unstable in practice since it is defined as a solution to the
    minimax problem. We then propose a weighted least squares estimator that
    enables simpler model selection by avoiding the minimax objective formulation.
    Unlike the inverse probability weighted (IPW) estimator, the proposed estimator
    directly uses the pre-estimated weight without inversion, avoiding the problems
    caused by the IPW methods. We demonstrate the effectiveness of our method
    through experiments using synthetic and real-world datasets.

  • Effects of web-based learning for nurses on their care for pregnant women with hiesho (sensitivity of hands or feet to cold): A randomized controlled trial

    Sachiyo Nakamura, Shoko Takeuchi, Takahiro Hoshino, Naoko Okubo, Shigeko Horiuchi

    Japanese Journal of Nursing Science in press 2022


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Papers, etc., Registered in KOARA 【 Display / hide

Reviews, Commentaries, etc. 【 Display / hide

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Presentations 【 Display / hide

  • ポイントプログラムの長期効果:目標勾配仮説は成立するのか

    星野 崇宏



    Oral presentation (general)

  • Causal Inference for Multilevel Modeling Under Nonrandom Allocation to Level-2 Units: Moderated causal effect as a function of macro-level variables

    HOSHINO Takahiro

    IMPS2012, The 77nd Annual and the 18th International Meetings of the Psychometric Society, 


    Oral presentation (general)

  • Causal Inference Framework for Latent Variable Modeling

    HOSHINO Takahiro

    IMPS2011,The 76th Annual and the 17th International Meetings of the Psychometric Society, 


    Oral presentation (invited, special)

  • プロスペクト理論を考慮した同時購買行動での価格プロモーション戦略

    星野 崇宏



    Oral presentation (general)

  • 欠測データと因果効果の推定

    星野 崇宏



    Public lecture, seminar, tutorial, course, or other speech

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Research Projects of Competitive Funds, etc. 【 Display / hide

  • 因果効果を識別する実行可能な研究デザインの探索と推定法の開発


    MEXT,JSPS, Grant-in-Aid for Scientific Research, 基盤研究(B), Principal investigator

  • 異質性を考慮した因果効果の推定法の開発とその応用


    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), Principal investigator

  • Research of discrepancy between behavior logs and survey responses and intervention for reduction of discrepancies


    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Challenging Research (Exploratory) , Principal investigator

  • General studies and applications for Treatment effect estimation under non-experimental studies


    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), Principal investigator

Awards 【 Display / hide

  • JPSP Prize

    2017.02, Japan Society for the Promotion of Science, 日本学術振興会賞

    Type of Award: International academic award (Japan or overseas)

  • 義塾賞

    2018.11, 慶應義塾大学

    Type of Award: Keio commendation etc.

  • The Japan Statistical Society Achievement Award

    2017.09, The Japan Statistical Society, The Japan Statistical Society Achievement Award

    Type of Award: Award from Japanese society, conference, symposium, etc.

  • 慶應義塾大学 印東太郎賞

    2012.09, 慶應義塾大学, 慶應義塾大学 印東太郎賞

    Type of Award: Other

  • 日本行動計量学会 出版賞 調査観察データの統計科学

    2011.09, 日本行動計量学会, 日本行動計量学会 出版賞 調査観察データの統計科学

    Type of Award: Award from Japanese society, conference, symposium, etc.

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Courses Taught 【 Display / hide











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Memberships in Academic Societies 【 Display / hide

  • The Japan Statistical Society

  • Association of Behavioral Economics and Finance

  • Japanese Economic Associaion

  • The Japanese Psychological Association

  • The Japanese Association of Educational PSychology


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