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American Journal of Applied Mathematics and Statistics. 2014, 2(6), 376-385
DOI: 10.12691/AJAMS-2-6-4
Original Research

A Multivariate Time Series Modeling of Major Economic Indicators in Nigeria

C. E Onwukwe1, and G. O. Nwafor2

1Department of Mathematics, Statistics and Computer Science University of Calabar, P.M.B 1115, Cross River State, Nigeria

2Department of Mathematics and Statistics Cross River University of Technology Calabar, Nigeria

Pub. Date: November 23, 2014
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Cite this paper

C. E Onwukwe and G. O. Nwafor. A Multivariate Time Series Modeling of Major Economic Indicators in Nigeria. American Journal of Applied Mathematics and Statistics. 2014; 2(6):376-385. doi: 10.12691/AJAMS-2-6-4

Abstract

One of the key objectives of every good economy, whether or not developing or developed is to achieve a high and sustainable economic growth rate coupled with the economic indicators. The research on the Multivariate Time Series Modeling of Major Economic Indicators in Nigeria, aims at providing quantitative analysis of the dynamics on currency in circulation, exchange rate, external reserve, gross domestic product, money supply and price deflator. This study utilizes secondary data obtained from the Central Bank of Nigeria, Statistical Bulletin (vol. 21: 2010), of all variables investigated in the model. The sample covers quarterly data from 1981 to 2010. The study employed the newly developed multivariate time series estimation technique via Vector Autoregressive modeling to model the economic indicators in Nigeria. The empirical result yields a stable and sustainable economic model for the six economic variables in the study. The Granger causality analysis indicates that there exists unidirectional and bidirectional causality between the economic variables. Gross domestic product and external reserve was seen as a good predictor to other economic indicators. The relationship between these economic indicators is however significantly determined which is positive in either direction. The empirical model provides forecast value for the next two years.

Keywords

multivariate time series, economics indicators, modeling, vector autoregressive

Copyright

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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