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Naoya Sueishi

Personal Details

First Name:Naoya
Middle Name:
Last Name:Sueishi
Suffix:
RePEc Short-ID:psu510
[This author has chosen not to make the email address public]
https://sites.google.com/site/naoyasueishi/

Affiliation

Faculty of Economics
Kobe University

Kobe, Japan
http://www.econ.kobe-u.ac.jp/
RePEc:edi:fekobjp (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Naoya Sueishi, 2022. "A Misuse of Specification Tests," Papers 2211.11915, arXiv.org.
  2. Naoya Sueishi, 2015. "A Simple Derivation of the Efficiency Bound for Conditional Moment Restriction Models," Discussion Papers 1531, Graduate School of Economics, Kobe University.
  3. Naoya Sueishi & Arihiro Yoshimura, 2014. "Focused Information Criterion for Series Estimation in Partially Linear Models," Discussion papers e-14-001, Graduate School of Economics Project Center, Kyoto University.

Articles

  1. Yoshiki Nakajima & Naoya Sueishi, 2022. "Forecasting the Japanese macroeconomy using high-dimensional data," The Japanese Economic Review, Springer, vol. 73(2), pages 299-324, April.
  2. Ando, Tomohiro & Sueishi, Naoya, 2019. "Regularization parameter selection for penalized empirical likelihood estimator," Economics Letters, Elsevier, vol. 178(C), pages 1-4.
  3. Tomohiro Ando & Naoya Sueishi, 2019. "On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator," Econometrics, MDPI, vol. 7(1), pages 1-14, March.
  4. Ichiro Sasaki & Katsunori Kondo & Naoki Kondo & Jun Aida & Hiroshi Ichikawa & Takashi Kusumi & Naoya Sueishi & Yuichi Imanaka, 2018. "Are pension types associated with happiness in Japanese older people?: JAGES cross-sectional study," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-14, May.
  5. Sueishi, Naoya, 2017. "A Note On Generalized Empirical Likelihood Estimation Of Semiparametric Conditional Moment Restriction Models," Econometric Theory, Cambridge University Press, vol. 33(5), pages 1242-1258, October.
  6. Naoya Sueishi & Arihiro Yoshimura, 2017. "Focused Information Criterion for Series Estimation in Partially Linear Models," The Japanese Economic Review, Japanese Economic Association, vol. 68(3), pages 352-363, September.
  7. Sueishi, Naoya, 2016. "A simple derivation of the efficiency bound for conditional moment restriction models," Economics Letters, Elsevier, vol. 138(C), pages 57-59.
  8. Sueishi, Naoya, 2013. "Identification problem of the exponential tilting estimator under misspecification," Economics Letters, Elsevier, vol. 118(3), pages 509-511.
  9. Naoya Sueishi, 2013. "Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-16, July.

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. Naoya Sueishi, 2015. "A Simple Derivation of the Efficiency Bound for Conditional Moment Restriction Models," Discussion Papers 1531, Graduate School of Economics, Kobe University.

    Cited by:

    1. Yaroslav Mukhin, 2018. "Sensitivity of Regular Estimators," Papers 1805.08883, arXiv.org.
    2. Tomohiro Ando & Naoya Sueishi, 2019. "On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator," Econometrics, MDPI, vol. 7(1), pages 1-14, March.

Articles

  1. Yoshiki Nakajima & Naoya Sueishi, 2022. "Forecasting the Japanese macroeconomy using high-dimensional data," The Japanese Economic Review, Springer, vol. 73(2), pages 299-324, April.

    Cited by:

    1. Kohei Maehashi & Mototsugu Shintani, 2020. "Macroeconomic Forecasting Using Factor Models and Machine Learning: An Application to Japan," CIRJE F-Series CIRJE-F-1146, CIRJE, Faculty of Economics, University of Tokyo.
    2. Liu, Ying & Wen, Long & Liu, Han & Song, Haiyan, 2024. "Predicting tourism recovery from COVID-19: A time-varying perspective," Economic Modelling, Elsevier, vol. 135(C).

  2. Ando, Tomohiro & Sueishi, Naoya, 2019. "Regularization parameter selection for penalized empirical likelihood estimator," Economics Letters, Elsevier, vol. 178(C), pages 1-4.

    Cited by:

    1. Tomohiro Ando & Naoya Sueishi, 2019. "On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator," Econometrics, MDPI, vol. 7(1), pages 1-14, March.

  3. Sueishi, Naoya, 2017. "A Note On Generalized Empirical Likelihood Estimation Of Semiparametric Conditional Moment Restriction Models," Econometric Theory, Cambridge University Press, vol. 33(5), pages 1242-1258, October.

    Cited by:

    1. Tao, Jing, 2020. "Trinity tests of functions for conditional moment models," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
    2. Chen, Xiaohong & Pouzo, Demian & Powell, James L., 2019. "Penalized sieve GEL for weighted average derivatives of nonparametric quantile IV regressions," Journal of Econometrics, Elsevier, vol. 213(1), pages 30-53.

  4. Sueishi, Naoya, 2016. "A simple derivation of the efficiency bound for conditional moment restriction models," Economics Letters, Elsevier, vol. 138(C), pages 57-59.
    See citations under working paper version above.
  5. Sueishi, Naoya, 2013. "Identification problem of the exponential tilting estimator under misspecification," Economics Letters, Elsevier, vol. 118(3), pages 509-511.

    Cited by:

    1. Siddhartha Chib & Minchul Shin & Anna Simoni, 2021. "Bayesian Estimation and Comparison of Conditional Moment Models," Papers 2110.13531, arXiv.org.
    2. Lavergne, Pascal, 2015. "Assessing the Approximate Validity of Moment Restrictions," TSE Working Papers 15-562, Toulouse School of Economics (TSE), revised May 2020.
    3. Luo, Yu & Graham, Daniel J. & McCoy, Emma J., 2023. "Semiparametric Bayesian doubly robust causal estimation," LSE Research Online Documents on Economics 117944, London School of Economics and Political Science, LSE Library.
    4. Siddharta Chib & Minchul Shin & Anna Simoni, 2016. "Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models," Working Papers 2016-21, Center for Research in Economics and Statistics.

  6. Naoya Sueishi, 2013. "Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging," Econometrics, MDPI, vol. 1(2), pages 1-16, July.

    Cited by:

    1. Toru Kitagawa & Chris Muris, 2015. "Model averaging in semiparametric estimation of treatment effects," CeMMAP working papers CWP46/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Lewbel, Arthur & Choi, Jin Young & Zhou, Zhuzhu, 2023. "Over-identified Doubly Robust identification and estimation," Journal of Econometrics, Elsevier, vol. 235(1), pages 25-42.
    3. Liu, Chu-An & Kuo, Biing-Shen, 2014. "Model Averaging in Predictive Regressions," MPRA Paper 54198, University Library of Munich, Germany.
    4. Shou-Yung Yin & Chu-An Liu & Chang-Ching Lin, 2016. "Focused Information Criterion and Model Averaging for Large Panels with a Multifactor Error Structure," IEAS Working Paper : academic research 16-A016, Institute of Economics, Academia Sinica, Taipei, Taiwan.

More information

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Statistics

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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 2 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 (2) 2015-11-21 2022-12-12

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