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ISSN: 1549-3644 (Print)
ISSN: 1558-6359 (Online)
Research Article Open Access

Residual Analysis for Auto-Correlated Econometric Model

Habib Ahmed Elsayir1
  • 1 Umm Al Qura University, Saudi Arabia

Abstract

The aim of this article is to provide residual analysis for a time series data of Gross Domestic Product (GDP) of the Sudan. An econometric time series model with macroeconomic variables is conducted to examine the goodness of fit using residual. Many statistical tests are used in time series models in order to make it a stationary series. After applying these tests, the time series became stationary and integrated; thus, Box-Jenkins procedure is used for the determination of ARIMA, AR (0,1,0) in this study. This identified technique is useful for analyzing this study.

Journal of Mathematics and Statistics
Volume 15 No. 1, 2019, 99-111

DOI: https://doi.org/10.3844/jmssp.2019.99.111

Submitted On: 15 November 2018 Published On: 1 June 2019

How to Cite: Elsayir, H. A. (2019). Residual Analysis for Auto-Correlated Econometric Model. Journal of Mathematics and Statistics, 15(1), 99-111. https://doi.org/10.3844/jmssp.2019.99.111

Open AccessCopyright: © 2019 Habib Ahmed Elsayir. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • ARIMA Model
  • Autocorrelation
  • GDP
  • Residual Analysis