IDEAS home Printed from https://ideas.repec.org/a/aft/journl/v1612019janjunp105-132.html
   My bibliography  Save this article

Armax And Var Econometric Methodologiesapplied To Total Tax Collection In The State Of Goiã S: A Predictive Accuracy Analysis

Author

Listed:
  • Flávio Henrique de Sarmento Seixas

    (Centro Universitário Alves Faria (UNIALFA))

  • Cleomar Gomes da Silva

    (Universidade Federal de Uberlândia (UFU))

Abstract

This paper aims to evaluate if the ARMAX econometric methodology offers predictive accuracy superior to the Autoregressive Vectors (VAR) methodology to estimate the Total Revenue free of extraordinary effects of the State of Goiás. The period analyzed is from January 2003 to December 2015 and, in both methodologies, the models with better adjustments identified the variable Formal Employment Level as statistically significant. The main predictive accuracy indicators for the year 2015, the Mean Absolute Percentage Error (MAPE), resulted in 1.70% for the best model of the ARMAX methodology and 3.11% for the correspondent VAR, results corroborated by the indicator of Square Root of Mean Squared Errors (RMSE), pointing to the ARMAX methodology as superior performance to the last one on this important aspect.

Suggested Citation

  • Flávio Henrique de Sarmento Seixas & Cleomar Gomes da Silva, 2019. "Armax And Var Econometric Methodologiesapplied To Total Tax Collection In The State Of Goiã S: A Predictive Accuracy Analysis," Revista de Economia Mackenzie (REM), Mackenzie Presbyterian University, Social and Applied Sciences Center, vol. 16(1), pages 105-132, January-J.
  • Handle: RePEc:aft:journl:v:16:1:2019:jan:jun:p:105-132
    DOI: -
    as

    Download full text from publisher

    File URL: http://editorarevistas.mackenzie.br/index.php/rem/article/view/12154
    Download Restriction: no

    File URL: https://libkey.io/-?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
    ---><---

    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:aft:journl:v:16:1:2019:jan:jun:p:105-132. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Instituto Presbiteriano Mackenzie (IPM) (email available below). General contact details of provider: https://edirc.repec.org/data/fcmacbr.html .

    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.