IDEAS home Printed from https://ideas.repec.org/a/spr/aodasc/v11y2024i4d10.1007_s40745-023-00468-2.html
   My bibliography  Save this article

Bayesian Estimation of Multiple Covariate of Autoregressive (MC-AR) Model

Author

Listed:
  • Jitendra Kumar

    (Central University of Rajasthan)

  • Ashok Kumar

    (MIT Art, Design & Technology University)

  • Varun Agiwal

    (Indian Institute of Public Health)

Abstract

In present scenario, handling covariate/explanatory variable with the model is one of most important factor to study with the models. The main advantages of covariate are it’s dependency on past observations. So, study variable is modelled after explaining both on own past and past and future observation of covariates. Present paper deals estimation of parameters of autoregressive model with multiple covariates under Bayesian approach. A simulation and empirical study is performed to check the applicability of the model and recorded the better results.

Suggested Citation

  • Jitendra Kumar & Ashok Kumar & Varun Agiwal, 2024. "Bayesian Estimation of Multiple Covariate of Autoregressive (MC-AR) Model," Annals of Data Science, Springer, vol. 11(4), pages 1291-1301, August.
    • Handle: RePEc:spr:aodasc:v:11:y:2024:i:4:d:10.1007_s40745-023-00468-2
    DOI: 10.1007/s40745-023-00468-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40745-023-00468-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40745-023-00468-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kai Yang & Dehui Wang, 2017. "Bayesian estimation for first-order autoregressive model with explanatory variables," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(22), pages 11214-11227, November.
    2. Yoosoon Chang & Robin C. Sickles & Wonho Song, 2017. "Bootstrapping unit root tests with covariates," Econometric Reviews, Taylor & Francis Journals, vol. 36(1-3), pages 136-155, March.
    3. Juhl, Ted & Xiao, Zhijie, 2003. "Power Functions And Envelopes For Unit Root Tests," Econometric Theory, Cambridge University Press, vol. 19(2), pages 240-253, April.
    4. Hansen, Bruce E., 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Econometric Theory, Cambridge University Press, vol. 11(5), pages 1148-1171, October.
    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. Chang, Yoosoon, 2003. "Nonlinear IV Panel Unit Root Tests," Working Papers 2003-06, Rice University, Department of Economics.
    2. Sebastian Fossati, 2013. "Unit root testing with stationary covariates and a structural break in the trend function," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 368-384, May.
    3. Yang, Yang & Zhao, Zhao, 2020. "Quantile nonlinear unit root test with covariates and an application to the PPP hypothesis," Economic Modelling, Elsevier, vol. 93(C), pages 728-736.
    4. Astill, Sam & Taylor, A.M. Robert & Kellard, Neil & Korkos, Ioannis, 2023. "Using covariates to improve the efficacy of univariate bubble detection methods," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 342-366.
    5. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    6. Cláudia Duarte, 2015. "Covariate-augmented unit root tests with mixed-frequency data," Working Papers w201507, Banco de Portugal, Economics and Research Department.
    7. Eiji Kurozumi & Daisuke Yamazaki & Kaddour Hadri, 2012. "Covariate Unit Root Test for Cross-Sectionally Dependent Panel Data," Global COE Hi-Stat Discussion Paper Series gd12-256, Institute of Economic Research, Hitotsubashi University.
    8. Kaddour Hadri & Eiji Kurozumi & Daisuke Yamazaki, 2015. "Synergy between an Improved Covariate Unit Root Test and Cross-sectionally Dependent Panel Data Unit Root Tests," Manchester School, University of Manchester, vol. 83(6), pages 676-700, December.
    9. Chang, Yoosoon, 2004. "Bootstrap unit root tests in panels with cross-sectional dependency," Journal of Econometrics, Elsevier, vol. 120(2), pages 263-293, June.
    10. Gaia Garino & Lucio Sarno, 2004. "Speculative Bubbles in U.K. House Prices: Some New Evidence," Southern Economic Journal, John Wiley & Sons, vol. 70(4), pages 777-795, April.
    11. Terence C. Mills, 2012. "Semi-parametric modelling of temperature records," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(2), pages 361-383, May.
    12. Luis F. Melo & Álvaro Riascos, 2004. "Sobre los efectos de la política monetaria en Colombia," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 22(45), pages 172-221, June.
    13. Podivinsky, Jan M. & King, Maxwell L., 2000. "The exact power envelope of tests for a unit root," Discussion Paper Series In Economics And Econometrics 0026, Economics Division, School of Social Sciences, University of Southampton.
    14. Meng Ming & Lee Junsoo & Payne James E., 2017. "RALS-LM unit root test with trend breaks and non-normal errors: application to the Prebisch-Singer hypothesis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 31-45, February.
    15. Syed Tehseen Jawaid, 2014. "Trade Openness and Economic Growth," Foreign Trade Review, , vol. 49(2), pages 193-212, May.
    16. Chumacero Rómulo A., 2006. "On the Power of Absolute Convergence Tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(2), pages 1-25, May.
    17. Podivinsky, Jan M. & King, Maxwell L., 2000. "The exact power envelope of tests for a unit root," Discussion Paper Series In Economics And Econometrics 26, Economics Division, School of Social Sciences, University of Southampton.
    18. Tsong, Ching-Chuan & Wu, Chien-Wei & Chiu, Hsien-Hung & Lee, Cheng-Feng, 2013. "Covariate unit root tests under structural change and asymmetric STAR dynamics," Economic Modelling, Elsevier, vol. 33(C), pages 101-112.
    19. Engel, Charles, 2000. "Local-currency pricing and the choice of exchange-rate regime," European Economic Review, Elsevier, vol. 44(8), pages 1449-1472, August.
    20. Pesaran, M. Hashem & Vanessa Smith, L. & Yamagata, Takashi, 2013. "Panel unit root tests in the presence of a multifactor error structure," Journal of Econometrics, Elsevier, vol. 175(2), pages 94-115.

    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:spr:aodasc:v:11:y:2024:i:4:d:10.1007_s40745-023-00468-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.