IDEAS home Printed from https://ideas.repec.org/f/pho810.html
   My authors  Follow this author

Takahiro Hoshino

Personal Details

First Name:Takahiro
Middle Name:
Last Name:Hoshino
Suffix:
RePEc Short-ID:pho810
[This author has chosen not to make the email address public]
https://researchmap.jp/read0077211?lang=en

Affiliation

Faculty of Economics
Keio University

Tokyo, Japan
http://www.econ.keio.ac.jp/
RePEc:edi:fekeijp (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Ryo Kato & Takahiro Hoshino & Daisuke Moriwaki & Shintaro Okazaki, 2022. "Mobile Targeting: Exploring the Role of Area Familiarity, Store Knowledge, and Promotional Incentives," Discussion Paper Series DP2022-10, Research Institute for Economics & Business Administration, Kobe University.
  2. Nobuyuki Hanaki & Takahiro Hoshino & Kohei Kubota & Fabrice Murtin & Masao Ogaki & Fumio Ohtake & Naoko Okuyama, 2022. "Comparing data gathered in an online and a laboratory experiment using the Trustlab platform," ISER Discussion Paper 1168r, Institute of Social and Economic Research, Osaka University, revised Jun 2022.
  3. Kazuhiko Shinoda & Takahiro Hoshino, 2022. "Orthogonal Series Estimation for the Ratio of Conditional Expectation Functions," Papers 2212.13145, arXiv.org.
  4. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian Instrumental Variables Estimation for Nonignorable Missing Instruments," Discussion Paper Series DP2020-06, Research Institute for Economics & Business Administration, Kobe University.
  5. Daisuke Moriwaki & Soichiro Harada & Jiyan Schneider & Takahiro Hoshino, 2020. "Nudging Preventive Behaviors in COVID-19 Crisis: A Large Scale RCT using Smartphone Advertising," Keio-IES Discussion Paper Series 2020-021, Institute for Economics Studies, Keio University.
  6. Ryo Kato & Takahiro Hoshino, 2020. "Unplanned Purchase of New Products," Discussion Paper Series DP2020-18, Research Institute for Economics & Business Administration, Kobe University.
  7. Satoshi Nakano & Ryo Kato & Makito Takeuchi & Takahiro Hoshino, 2020. "Efficiency and resistance to extinction of lottery-based incentives in human: Survey response behavior in 12-week real-world field experiment," Keio-IES Discussion Paper Series 2020-020, Institute for Economics Studies, Keio University.
  8. Takayuki Toda & Ayako Wakano & Takahiro Hoshino, 2019. "Regression Discontinuity Design with Multiple Groups for Heterogeneous Causal Effect Estimation," Papers 1905.04443, arXiv.org.
  9. Keisuke Takahata & Takahiro Hoshino, 2019. "Semiparametric estimation of heterogeneous treatment effects under the nonignorable assignment condition," Papers 1902.09978, arXiv.org.
  10. Takahiro Hoshino & Yuya Shimizu, 2019. "Doubly Robust-type Estimation of Population Moments and Parameters in Biased Sampling," Keio-IES Discussion Paper Series 2019-006, Institute for Economics Studies, Keio University.
  11. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Instrumental Variable Estimation with Many Weak Instruments," Discussion Paper Series DP2018-14, Research Institute for Economics & Business Administration, Kobe University.
  12. Ryosuke Igari & Takahiro Hoshino, 2018. "A Bayesian Gamma Frailty Model Using the Sum of Independent Random Variables: Application of the Estimation of an Interpurchase Timing Model," Keio-IES Discussion Paper Series 2018-021, Institute for Economics Studies, Keio University.
  13. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Multiple Imputation for Regression Models with Missing Mixed Continuous-Discrete Covariates," Discussion Paper Series DP2018-15, Research Institute for Economics & Business Administration, Kobe University.
  14. Takahiro Hoshino & Keisuke Takahata, 2018. "Identification of heterogeneous treatment effects as a function of potential untreated outcome under the nonignorable assignment condition," Keio-IES Discussion Paper Series 2018-005, Institute for Economics Studies, Keio University.
  15. Takahiro Hoshino & Ryosuke Igari, 2017. "Quasi-Bayesian Inference for Latent Variable Models with External Information: Application to generalized linear mixed models for biased data," Keio-IES Discussion Paper Series 2017-014, Institute for Economics Studies, Keio University.
  16. Igari Ryosuke & Takahiro Hoshino, 2017. "Semiparametric Quasi-Bayesian Inference with Dirichlet Process Priors: Application to Nonignorable Missing Responses," Keio-IES Discussion Paper Series 2017-020, Institute for Economics Studies, Keio University.
  17. ISHIKAWA Yoshiki & ITO Hirotake & UEMURA Aya & TABATA Shin & TOYAMA Risako & NAKAMURO Makiko & BUNJI Kyosuke & HOSHINO Takahiro & MATSUOKA Ryoji & YAMAGUCHI Kazuhiro, 2017. "The Prospects of Achievement Tests to Measure the Cognitive Skills of School-aged Children: The role of achievement tests to implement evidence-based policy making in education (Japanese)," Policy Discussion Papers (Japanese) 17010, Research Institute of Economy, Trade and Industry (RIETI).
  18. Ryosuke Igari & Takahiro Hoshino, 2017. "Bayesian Data Combination Approach for Repeated Durations under Unobserved Missing Indicators: Application to Interpurchase-Timing in Marketing," Keio-IES Discussion Paper Series 2017-015, Institute for Economics Studies, Keio University.

Articles

  1. Nishio, Kazuki & Hoshino, Takahiro, 2022. "Joint modeling of effects of customer tier program on customer purchase duration and purchase amount," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
  2. Kei Miyazaki & Takahiro Hoshino & Ulf Böckenholt, 2021. "Dynamic Two Stage Modeling for Category-Level and Brand-Level Purchases Using Potential Outcome Approach With Bayes Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 622-635, July.
  3. Kato, Ryo & Hoshino, Takahiro, 2021. "Unplanned purchase of new products," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
  4. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian multiple imputation for regression models with missing mixed continuous–discrete covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 803-825, June.
  5. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
  6. Yusuke Takahashi & Kensuke Okada & Takahiro Hoshino & Tokie Anme, 2015. "Developmental Trajectories of Social Skills during Early Childhood and Links to Parenting Practices in a Japanese Sample," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-14, August.
  7. Takahiro Hoshino, 2013. "Semiparametric Bayesian Estimation for Marginal Parametric Potential Outcome Modeling: Application to Causal Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(504), pages 1189-1204, December.
  8. Kei Miyazaki & Takahiro Hoshino & Shin-ichi Mayekawa & Kazuo Shigemasu, 2009. "A New Concurrent Calibration Method for Nonequivalent Group Design under Nonrandom Assignment," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 1-19, March.
  9. Hoshino, Takahiro, 2008. "A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1413-1429, January.
  10. Hoshino, Takahiro, 2008. "Bayesian significance testing and multiple comparisons from MCMC outputs," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3543-3559, March.
  11. Kurata, Hiroshi & Hoshino, Takahiro & Fujikoshi, Yasunori, 2008. "Allometric extension model for conditional distributions," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 1985-1998, October.
  12. Takahiro Hoshino, 2007. "Doubly Robust-Type Estimation for Covariate Adjustment in Latent Variable Modeling," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 535-549, December.
  13. Takahiro Hoshino & Hiroshi Kurata & Kazuo Shigemasu, 2006. "A Propensity Score Adjustment for Multiple Group Structural Equation Modeling," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 691-712, December.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Nobuyuki Hanaki & Takahiro Hoshino & Kohei Kubota & Fabrice Murtin & Masao Ogaki & Fumio Ohtake & Naoko Okuyama, 2022. "Comparing data gathered in an online and a laboratory experiment using the Trustlab platform," ISER Discussion Paper 1168r, Institute of Social and Economic Research, Osaka University, revised Jun 2022.

    Cited by:

    1. Pin, Paolo & Rotesi, Tiziano, 2023. "App-based experiments," Journal of Economic Psychology, Elsevier, vol. 99(C).
    2. Masao Ogaki, 2023. "Economics of the Community Mechanism," Keio-IES Discussion Paper Series 2023-004, Institute for Economics Studies, Keio University.

  2. Daisuke Moriwaki & Soichiro Harada & Jiyan Schneider & Takahiro Hoshino, 2020. "Nudging Preventive Behaviors in COVID-19 Crisis: A Large Scale RCT using Smartphone Advertising," Keio-IES Discussion Paper Series 2020-021, Institute for Economics Studies, Keio University.

    Cited by:

    1. Fumio Ohtake, 2022. "Can nudges save lives?," The Japanese Economic Review, Springer, vol. 73(2), pages 245-268, April.
    2. Shusaku Sasaki & Hirofumi Kurokawa & Fumio Ohtake, 2021. "Effective but fragile? Responses to repeated nudge-based messages for preventing the spread of COVID-19 infection," The Japanese Economic Review, Springer, vol. 72(3), pages 371-408, July.
    3. Masayuki SATO & Shin KINOSHITA & Takanori IDA, 2022. "Subjective Risk Valuation and Behavioral Change : Evidence from COVID-19 in the U.K. and Japan," Discussion papers e-22-011, Graduate School of Economics , Kyoto University.
    4. Shin KINOSHITA & Masayuki SATO & Takanori IDA, 2022. "Bayesian Probability Revision and Infection Prevention Behavior in Japan : A Quantitative Analysis of the First Wave of COVID-19," Discussion papers e-22-004, Graduate School of Economics , Kyoto University.

  3. Ryo Kato & Takahiro Hoshino, 2020. "Unplanned Purchase of New Products," Discussion Paper Series DP2020-18, Research Institute for Economics & Business Administration, Kobe University.

    Cited by:

    1. Bhukya, Ramulu & Paul, Justin, 2023. "Social influence research in consumer behavior: What we learned and what we need to learn? – A hybrid systematic literature review," Journal of Business Research, Elsevier, vol. 162(C).
    2. Nigam, Achint & Dewani, Prem & Behl, Abhishek & Pereira, Vijay, 2022. "Consumer’s response to conditional promotions in retailing: An empirical inquiry," Journal of Business Research, Elsevier, vol. 144(C), pages 751-763.
    3. Li, Xi & Dahana, Wirawan Dony & Ye, Qiongwei & Peng, Luluo & Zhou, Jiaying, 2021. "How does shopping duration evolve and influence buying behavior? The role of marketing and shopping environment," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).

  4. Takayuki Toda & Ayako Wakano & Takahiro Hoshino, 2019. "Regression Discontinuity Design with Multiple Groups for Heterogeneous Causal Effect Estimation," Papers 1905.04443, arXiv.org.

    Cited by:

    1. 'Agoston Reguly, 2021. "Heterogeneous Treatment Effects in Regression Discontinuity Designs," Papers 2106.11640, arXiv.org, revised Oct 2021.

  5. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Instrumental Variable Estimation with Many Weak Instruments," Discussion Paper Series DP2018-14, Research Institute for Economics & Business Administration, Kobe University.

    Cited by:

    1. Pedro Saramago & Karl Claxton & Nicky J. Welton & Marta Soares, 2020. "Bayesian econometric modelling of observational data for cost‐effectiveness analysis: establishing the value of negative pressure wound therapy in the healing of open surgical wounds," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1575-1593, October.

  6. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Multiple Imputation for Regression Models with Missing Mixed Continuous-Discrete Covariates," Discussion Paper Series DP2018-15, Research Institute for Economics & Business Administration, Kobe University.

    Cited by:

    1. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian Instrumental Variables Estimation for Nonignorable Missing Instruments," Discussion Paper Series DP2020-06, Research Institute for Economics & Business Administration, Kobe University.

  7. Takahiro Hoshino & Ryosuke Igari, 2017. "Quasi-Bayesian Inference for Latent Variable Models with External Information: Application to generalized linear mixed models for biased data," Keio-IES Discussion Paper Series 2017-014, Institute for Economics Studies, Keio University.

    Cited by:

    1. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
    2. Ryosuke Igari & Takahiro Hoshino, 2018. "A Bayesian Gamma Frailty Model Using the Sum of Independent Random Variables: Application of the Estimation of an Interpurchase Timing Model," Keio-IES Discussion Paper Series 2018-021, Institute for Economics Studies, Keio University.

  8. Ryosuke Igari & Takahiro Hoshino, 2017. "Bayesian Data Combination Approach for Repeated Durations under Unobserved Missing Indicators: Application to Interpurchase-Timing in Marketing," Keio-IES Discussion Paper Series 2017-015, Institute for Economics Studies, Keio University.

    Cited by:

    1. Rungskunroch, Panrawee & Jack, Anson & Kaewunruen, Sakdirat, 2021. "Benchmarking on railway safety performance using Bayesian inference, decision tree and petri-net techniques based on long-term accidental data sets," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    2. Ryosuke Igari & Takahiro Hoshino, 2018. "A Bayesian Gamma Frailty Model Using the Sum of Independent Random Variables: Application of the Estimation of an Interpurchase Timing Model," Keio-IES Discussion Paper Series 2018-021, Institute for Economics Studies, Keio University.
    3. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian Instrumental Variables Estimation for Nonignorable Missing Instruments," Discussion Paper Series DP2020-06, Research Institute for Economics & Business Administration, Kobe University.
    4. Jiří Boháček & Zdeněk Linhart & Peter Matisko & Miroslav Špaček, 2021. "Marketing Dialogue With Pressure Groups," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 69(2), pages 211-220.

Articles

  1. Nishio, Kazuki & Hoshino, Takahiro, 2022. "Joint modeling of effects of customer tier program on customer purchase duration and purchase amount," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).

    Cited by:

    1. Hu, Xin & He, Liuyi & Liu, Junjun, 2022. "Status reinforcing: Unintended rating bias on online shopping platforms," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).

  2. Kei Miyazaki & Takahiro Hoshino & Ulf Böckenholt, 2021. "Dynamic Two Stage Modeling for Category-Level and Brand-Level Purchases Using Potential Outcome Approach With Bayes Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 622-635, July.

    Cited by:

    1. Gael M. Martin & David T. Frazier & Worapree Maneesoonthorn & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2022. "Bayesian Forecasting in Economics and Finance: A Modern Review," Papers 2212.03471, arXiv.org, revised Jul 2023.
    2. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
    3. Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Fast variational Bayes methods for multinomial probit models," Papers 2202.12495, arXiv.org, revised Oct 2022.

  3. Kato, Ryo & Hoshino, Takahiro, 2021. "Unplanned purchase of new products," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    See citations under working paper version above.
  4. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian multiple imputation for regression models with missing mixed continuous–discrete covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 803-825, June.

    Cited by:

    1. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian Instrumental Variables Estimation for Nonignorable Missing Instruments," Discussion Paper Series DP2020-06, Research Institute for Economics & Business Administration, Kobe University.

  5. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166. See citations under working paper version above.
  6. Takahiro Hoshino, 2013. "Semiparametric Bayesian Estimation for Marginal Parametric Potential Outcome Modeling: Application to Causal Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(504), pages 1189-1204, December.

    Cited by:

    1. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
    2. Takahiro Hoshino & Ryosuke Igari, 2017. "Quasi-Bayesian Inference for Latent Variable Models with External Information: Application to generalized linear mixed models for biased data," Keio-IES Discussion Paper Series 2017-014, Institute for Economics Studies, Keio University.
    3. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Multiple Imputation for Regression Models with Missing Mixed Continuous-Discrete Covariates," Discussion Paper Series DP2018-15, Research Institute for Economics & Business Administration, Kobe University.
    4. Dandan Xu & Michael J. Daniels & Almut G. Winterstein, 2018. "A Bayesian nonparametric approach to causal inference on quantiles," Biometrics, The International Biometric Society, vol. 74(3), pages 986-996, September.
    5. Ryo Kato & Takahiro Hoshino, 2018. "Semiparametric Bayes Instrumental Variable Estimation with Many Weak Instruments," Discussion Paper Series DP2018-14, Research Institute for Economics & Business Administration, Kobe University.
    6. Ryo Kato & Takahiro Hoshino, 2020. "Semiparametric Bayesian multiple imputation for regression models with missing mixed continuous–discrete covariates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(3), pages 803-825, June.

  7. Kei Miyazaki & Takahiro Hoshino & Shin-ichi Mayekawa & Kazuo Shigemasu, 2009. "A New Concurrent Calibration Method for Nonequivalent Group Design under Nonrandom Assignment," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 1-19, March.

    Cited by:

    1. Sandip Sinharay & Paul Holland, 2010. "The Missing Data Assumptions of the NEAT Design and their Implications for Test Equating," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 309-327, June.

  8. Hoshino, Takahiro, 2008. "A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1413-1429, January.

    Cited by:

    1. Fernando A. B. Colugnati & Sergio Firpo & Paula F. Drummond Castro & Juan E. Sepulveda & Sergio L. M. Salles-Filho, 2014. "A propensity score approach in the impact evaluation on scientific production in Brazilian biodiversity research: the BIOTA Program," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 85-107, October.
    2. Edler, Lutz & Lee, Jae Won & Mittlböck, Martina & Niland, Joyce & Victor, Norbert, 2009. "Computational statistics within clinical research," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 583-585, January.
    3. David Kaplan & Jianshen Chen, 2012. "A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study," Psychometrika, Springer;The Psychometric Society, vol. 77(3), pages 581-609, July.
    4. Hoshino, Takahiro, 2008. "Bayesian significance testing and multiple comparisons from MCMC outputs," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3543-3559, March.
    5. Igari, Ryosuke & Hoshino, Takahiro, 2018. "A Bayesian data combination approach for repeated durations under unobserved missing indicators: Application to interpurchase-timing in marketing," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 150-166.
    6. Takahiro Hoshino & Ryosuke Igari, 2017. "Quasi-Bayesian Inference for Latent Variable Models with External Information: Application to generalized linear mixed models for biased data," Keio-IES Discussion Paper Series 2017-014, Institute for Economics Studies, Keio University.
    7. Ryosuke Igari & Takahiro Hoshino, 2018. "A Bayesian Gamma Frailty Model Using the Sum of Independent Random Variables: Application of the Estimation of an Interpurchase Timing Model," Keio-IES Discussion Paper Series 2018-021, Institute for Economics Studies, Keio University.
    8. Olli Saarela & David A. Stephens & Erica E. M. Moodie & Marina B. Klein, 2015. "On Bayesian estimation of marginal structural models," Biometrics, The International Biometric Society, vol. 71(2), pages 279-288, June.
    9. Kei Miyazaki & Takahiro Hoshino & Shin-ichi Mayekawa & Kazuo Shigemasu, 2009. "A New Concurrent Calibration Method for Nonequivalent Group Design under Nonrandom Assignment," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 1-19, March.
    10. Corwin Matthew Zigler, 2016. "The Central Role of Bayes’ Theorem for Joint Estimation of Causal Effects and Propensity Scores," The American Statistician, Taylor & Francis Journals, vol. 70(1), pages 47-54, February.

  9. Hoshino, Takahiro, 2008. "Bayesian significance testing and multiple comparisons from MCMC outputs," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3543-3559, March.

    Cited by:

    1. Marín, J.M. & Rodríguez-Bernal, M.T., 2012. "Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1898-1907.

  10. Kurata, Hiroshi & Hoshino, Takahiro & Fujikoshi, Yasunori, 2008. "Allometric extension model for conditional distributions," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 1985-1998, October.

    Cited by:

    1. Shun Matsuura & Hiroshi Kurata, 2014. "Principal points for an allometric extension model," Statistical Papers, Springer, vol. 55(3), pages 853-870, August.

  11. Takahiro Hoshino, 2007. "Doubly Robust-Type Estimation for Covariate Adjustment in Latent Variable Modeling," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 535-549, December.

    Cited by:

    1. Takahiro Hoshino & Yuya Shimizu, 2019. "Doubly Robust-type Estimation of Population Moments and Parameters in Biased Sampling," Keio-IES Discussion Paper Series 2019-006, Institute for Economics Studies, Keio University.
    2. Kazuki Kamimura & Shohei Okamoto & Kenichi Shiraishi & Kazuto Sumita & Kohei Komamura & Akiko Tsukao & Shinya Kuno, 2023. "Financial incentives for exercise and medical care costs," International Journal of Economic Policy Studies, Springer, vol. 17(1), pages 95-116, February.
    3. Kei Miyazaki & Takahiro Hoshino & Shin-ichi Mayekawa & Kazuo Shigemasu, 2009. "A New Concurrent Calibration Method for Nonequivalent Group Design under Nonrandom Assignment," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 1-19, March.
    4. Sakaue, Katsuki & Wokadala, James, 2022. "Effects of including refugees in local government schools on pupils’ learning achievement: Evidence from West Nile, Uganda," International Journal of Educational Development, Elsevier, vol. 90(C).

  12. Takahiro Hoshino & Hiroshi Kurata & Kazuo Shigemasu, 2006. "A Propensity Score Adjustment for Multiple Group Structural Equation Modeling," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 691-712, December.

    Cited by:

    1. Hoshino, Takahiro, 2008. "Bayesian significance testing and multiple comparisons from MCMC outputs," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3543-3559, March.
    2. Kei Miyazaki & Takahiro Hoshino & Shin-ichi Mayekawa & Kazuo Shigemasu, 2009. "A New Concurrent Calibration Method for Nonequivalent Group Design under Nonrandom Assignment," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 1-19, March.
    3. Hoshino, Takahiro, 2008. "A Bayesian propensity score adjustment for latent variable modeling and MCMC algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1413-1429, January.
    4. Takahiro Hoshino, 2007. "Doubly Robust-Type Estimation for Covariate Adjustment in Latent Variable Modeling," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 535-549, December.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 17 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (12) 2017-06-11 2017-06-11 2017-08-06 2018-05-14 2018-05-28 2019-01-14 2019-01-28 2019-03-04 2019-04-15 2019-05-20 2020-02-17 2023-01-16. Author is listed
  2. NEP-ORE: Operations Research (5) 2017-06-11 2017-06-11 2017-08-06 2019-01-14 2019-04-15. Author is listed
  3. NEP-EXP: Experimental Economics (4) 2019-03-04 2021-01-18 2022-04-25 2022-07-11
  4. NEP-CBE: Cognitive and Behavioural Economics (2) 2021-01-18 2022-07-11
  5. NEP-DCM: Discrete Choice Models (2) 2019-01-28 2022-07-11
  6. NEP-PAY: Payment Systems and Financial Technology (2) 2021-01-18 2022-07-11
  7. NEP-BEC: Business Economics (1) 2019-05-20
  8. NEP-BIG: Big Data (1) 2023-01-16
  9. NEP-CMP: Computational Economics (1) 2023-01-16
  10. NEP-EDU: Education (1) 2017-04-09
  11. NEP-EVO: Evolutionary Economics (1) 2022-07-11
  12. NEP-MKT: Marketing (1) 2019-01-14
  13. NEP-SOC: Social Norms and Social Capital (1) 2022-07-11

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Takahiro Hoshino should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.