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International Journal of Innovation and Applied Studies
ISSN: 2028-9324     CODEN: IJIABO     OCLC Number: 828807274     ZDB-ID: 2703985-7
 
 
Sunday 17 November 2019

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  Call for Papers - November 2019     |     Now IJIAS is indexed in EBSCO, ResearchGate, ProQuest, Chemical Abstracts Service, Index Copernicus, IET Inspec Direct, Ulrichs Web, Google Scholar, CAS Abstracts, J-Gate, UDL Library, CiteSeerX, WorldCat, Scirus, Research Bible and getCited, etc.  
 
 
 

Modeling Regression with Time Series Errors of Gross Domestic Product on Government Expenditure


Volume 18, Issue 4, December 2016, Pages 990–996

 Modeling Regression with Time Series Errors of Gross Domestic Product on Government Expenditure

Emmanuel Alphonsus Akpan1, Imoh Udo Moffat2, and Ntiedo Bassey Ekpo3

1 Department of Mathematics and Statistics, University of Uyo, Nigeria
2 Department of Mathematics and Statistics, University of Uyo, Nigeria
3 Department of Banking and Finance, University of Uyo, Nigeria

Original language: English

Received 13 July 2016

Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract


The study examined the relationship between Gross Domestic Product (GDP) and Government Expenditure between 1981 and 2012. The motivation was, in fitting regression model to time series data, autocorrelation in the error terms should be expected. Utilizing data from the Central Bank of Nigeria Statistical Bulletin, we found that regression model could capture the linear relationship between the dependent variable (GDP) and the independent (Government Expenditure). However, the error terms of the regression model were found to be autocorrelated and could be corrected by ARIMA(1,0,1) model. Moreover, regression model with an ARIMA(1,0,1) error was able to capture the linear relationship between GDP and the Government Expenditure alongside the autocorrelated errors. Evidence from the model revealed that Gross Domestic Product is a linear function of Government Expenditure at present and immediate previous year. The policy implication of this study is that if Government Expenditure is kept constant from immediate previous year to the present year, then, the GDP would tend to decrease, as such; Government should vary its expenditures in order to improve the GDP.

Author Keywords: ARIMA model, autocorrelated errors, Government Expenditure, Gross Domestic Product, regression model.


How to Cite this Article


Emmanuel Alphonsus Akpan, Imoh Udo Moffat, and Ntiedo Bassey Ekpo, “Modeling Regression with Time Series Errors of Gross Domestic Product on Government Expenditure,” International Journal of Innovation and Applied Studies, vol. 18, no. 4, pp. 990–996, December 2016.