An Econometric Time Series GDP Model Analysis: Statistical Evidences and Investigations - Journal of Applied Mathematics and Physics

JAMP > Vol.6 No.12, December 2018

Journal of Applied Mathematics and Physics

Volume 6, Issue 12 (December 2018)

ISSN Print: 2327-4352 ISSN Online: 2327-4379

Google-based Impact Factor: 0.70 Citations

An Econometric Time Series GDP Model Analysis: Statistical Evidences and Investigations ()

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Download as PDF (Size: 496KB) PP. 2635-2649

DOI: 10.4236/jamp.2018.612219 1,670 Downloads 14,782 Views Citations

Author(s)

Habib Ahmed Elsayir

Affiliation(s)

Department of Mathematics, Al Qunfudha University College, Umm Al Qura University, Al Qunfudha, Saudi Arabia.

ABSTRACT

This article aims to provide an analysis for a time series data of gross domestic product (GDP) of the Sudan. An econometric time series model with macroeconomic variables is conducted. Since a non-stationary time series must be made stationary, some statistical tests are followed so that the time series become stationary series. After applying these tests, the time series became stationary and integrated of order I. Box-Jenkins procedure is used to determine ARMA. OLS is used to estimate the models parameters. Performances chosen ARIMA model are verified on the basis of classical statistical tests and forecasting. The model features are interpreted on the basis of standard measures of forecasting performance.

KEYWORDS

ARIMA Model, GDP, Box-Jenkins Models, Stationary Time Series

Share and Cite:

Elsayir, H. (2018) An Econometric Time Series GDP Model Analysis: Statistical Evidences and Investigations. Journal of Applied Mathematics and Physics, 6, 2635-2649. doi: 10.4236/jamp.2018.612219.

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[3]	China Economic Growth Rate and its Forecast after COVID-19 Eruption
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