The Relatıonshıp Between Foreıgn Dırect Investment and Economıc Growth ın Nıgerıa: Usıng Var,Vecm and Granger Causalıty Tests


Foreign Direct Investment

How to Cite

Faruku, A.Z., Harun, B.R., & Yusuf B. (2019). The Relatıonshıp Between Foreıgn Dırect Investment and Economıc Growth ın Nıgerıa: Usıng Var,Vecm and Granger Causalıty Tests. Research Journal of Science, 19(1), 60 - 71. Retrieved from


This research uses a Co-integration VAR model to study the contemporaneous long-run dynamics of the impact of Foreign Direct Investment (FDI) and Natural Gas Revenue (NGR) on Growth Domestic Products (GDP) in Nigeria. Secondary data for the period 1970 to 2014 was used for the study. The Unit Root Test suggests that all the variables are integrated of order 1. The VAR model was appropriately identified by using AIC information criteria and using Johansen Co-integrated test, the VECM model has exactly one co-integration relation. The study further investigates the causal relationship using the Granger causality analysis which indicates a uni-directional causality relationship between FDI and GDP, NGR and FDI while we observe a bi- directional relationship between NGR and GDP at 5% which is in line with other  studies



Ahn, S.K., &Reinsel, G.C. (1990). Estimation for Partially Non- stationary Multivariate Autoregressivemodel. Journal of the American Statistical Association 85: 815–823.

Akaike, H. (1974). New look at the Statistical Model Identification, Institute of Statistical Mathematics, Minato-ku, Japan

Banerjee, A., Dolado, J.J., Galbraith, J.W. & Hendry, D.F (1993). Co- integration, Error Correction and the Econometric Analysis of Non- stationary Data. Oxford University Press, Oxford.

Barnhill Jr., T.M., Joutz, F.L. & Maxwell, W.F. (2000). Factors Affecting the Yields on Non- investment Grade Bond Indices: A CointegrationAnalysis.Journal of Empirical Finance 7: 57–86

Box, G. E. P. & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control, Holden- Day, San Francisco.

Dickey, D. A., & Fuller, W.A., (1979). Distribution of the Estimators forAutoregressive Time Series with a Unit Root.Journal of the American StatisticalAssociation. 74: pp. 1057-72.

Engle, R.F. & Granger, C.W.J (1987). Co-integration and Error Correction: Representation, Estimation and Testing. Econometrica 55: 251-76.

Engle, R.F. &Yoo, S. B. (1987). Forecasting and Testing in Cointegrated Systems. Journal of Econometrics 35: 143-159.

Granger, C.W.J. (1981). Some Properties of Time Series Data and their use in Econometric Model Specification. Journal of Econometrics 23: 121-130.

Hamilton j. (1994) Time series analysis Oxford University Press ,Oxford.

Johansen, S. & Juselius, K. (1992).Testing Structural Hypotheses in a Multivariate Cointegration Analysis of the PPP and UIP for UK. Journal of Econometrics 53: 211-244.

Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegrating Vector in Gaussian Vector AutoregressionModels. Econometrica 59: 1551–1580.

Johansen, S. (1992a). A Representation of Vector Autoregressive Processes Integrated of Order 2. Econometric Theory 8: 188-202.

Johansen, S. (1995). Likelihood-based Inference in Cointegrated Vector Autoregressive Models.OxfordUniversity Press: Oxford.

Lesage, J.P. (1990). A Comparison of the Forecasting Ability of ECM and VAR Models. Review of Economics and Statistics 72:.664–71.

Lutkepohl, H. (1991). Introduction to Multiple Time Series Analysis, Springer Verlag: Berlin.

MacDonald, R. & Power, D. (1995). Stock Prices, Dividends and Retention: Long-term Relationships and Short-term Dynamics. Journal of Empirical Finance,235–151.

Phillips, P. C. B. and Perron, P. (1988) Testing for a unit root in time series regression, Biometrica, 75, 335-46.

Reinsel, G.C., &Ahn, S.K. (1992). Vector Autoregressive Models with Unit Rootsand Reduced Rank Structure: Estimation, Likelihood Ratio Test, and Forecasting. Journal of Time Series Analysis 13: 353-375.

Terence, C.M. & Raphael, N.M. (2008). The Econometric Modeling of Financial Time Series, 3rdedition, Cambridge University Press: New York.


Download data is not yet available.