IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v7y2019i6p504-d236618.html
   My bibliography  Save this article

A Bayesian Equal Part Regression Analysis of the Influencing Factors of Taiwanese People’s Regime Acceptance of Mainland China and U.S. Governments

Author

Listed:
  • Shianghau Wu

    (School of Business, Macau University of Science and Technology, Macau 999078, China)

Abstract

This study utilized the newly-designed Bayesian equal part regression (BEPR) model to analyze the Taiwan National Security surveyed data from 2015 in order to construct a model of Taiwanese people’s regime acceptance of Mainland China and U.S governments. The study also used the Bayesian Regression model to make a comparison with the BEPR model results and attempted to explore the fluctuations of post mean and post probability of non-zero coefficients for each independent variable in the BEPR model. The major findings are as follows: First, the first equal part of respondents who believe that China would coerce Taiwan to make concessions have the lesser negative level of the regime acceptance of Mainland China, while the second equal part of the respondents who have the same attitude have the higher negative regime acceptance level. The second equal part of respondents who deem the higher possibility of unification have the lesser positive view on the regime acceptance level. Additionally, the first equal part of respondents who have higher evaluation of cross-strait relations have lesser positive impact on the regime acceptance of Mainland China. Second, we obtain the results that the second-third of Taiwanese respondents who have the optimistic household economic outlook or agree to reduce the purchase of U.S. military weapons if Mainland China withdraws its missiles have a higher negative impact on the regime acceptance of the U.S. However, the third equal part of Taiwanese respondents who agree with the current “R.O.C.” country name have a higher negative regime acceptance level of the U.S.

Suggested Citation

  • Shianghau Wu, 2019. "A Bayesian Equal Part Regression Analysis of the Influencing Factors of Taiwanese People’s Regime Acceptance of Mainland China and U.S. Governments," Mathematics, MDPI, vol. 7(6), pages 1-19, June.
  • Handle: RePEc:gam:jmathe:v:7:y:2019:i:6:p:504-:d:236618
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/7/6/504/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/7/6/504/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wen-Tsao Pan & Yungho Leu, 2016. "An Analysis of Bank Service Satisfaction Based on Quantile Regression and Grey Relational Analysis," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-9, April.
    2. Yukiko Omata & Hajime Katayama & Toshi. H. Arimura, 2017. "Same concerns, same responses? A Bayesian quantile regression analysis of the determinants for supporting nuclear power generation in Japan," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 19(3), pages 581-608, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohit Batham & Soudeh Mirghasemi & Mohammad Arshad Rahman & Manini Ojha, 2021. "Modeling and Analysis of Discrete Response Data: Applications to Public Opinion on Marijuana Legalization in the United States," Papers 2109.10122, arXiv.org, revised May 2023.
    2. Georges Bresson & Guy Lacroix & Mohammad Arshad Rahman, 2021. "Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada," Empirical Economics, Springer, vol. 60(1), pages 227-259, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:7:y:2019:i:6:p:504-:d:236618. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may 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.