IIARD International Institute of Academic Research and Development

IIARD International Journal of Economics and Business Management (IJEBM )

E-ISSN 2489-0065
P-ISSN 2695-186X
VOL. 3 NO. 8 2017

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Exchange rate fluctuations and foreign private investments in Nigeria

Mbanasor, Christian Okechukwu (Ph.D) and Obioma, James

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Abstract

The study intended to examine the impact of exchange rate fluctuations on foreign private investment in Nigeria. Giving what it takes to attract and retain foreign private investments in Nigeria, and the volatility of crude oil prices. The literature review took a conceptual, theoretical and empirical view of previous work done by scholars in the area. In the methodology of research, the design adopted was the ex-post facto research design. The data utilized were secondary in nature obtained from the Central of Nigeria Statistical Bulletin for the relevant periods. The model for the regression was specified in detail with the roles of the variables explained. The hypotheses stated will be tested using the two-stage least square (2LS). The statistical properties of the 2LS are contained in the popular Gauss- Markov theorem which sees the least squares estimators as unbiased linear estimator, having minimum variance. The model examines the relationship between a dependent variable and two or more regressor (independent variables). This suit the research since the intention of the researcher is to examine the impact of exchanges rate on these macro-economic variables on a variable by variable basis. The Granger Causality will also be employed to test the causal relationship between exchange rate and major macro-economic variables. The exchange rate fluctuations has negative and non-significant impact on Nigeria’s foreign private investment (coefficient of EXR = -0.015, t-value = -0.267). This indicates that a one percent increase in foreign private investment into Nigeria may be due to 0.015 percent decrease in exchange rate fluctuations. The probability value of 0.792 > 0.05 confirms the non-significance of the result. The coefficient of determination which measures the goodness fit of the model as revealed by R-square (R2) indicates that 83.6% of the variations observed in the dependent variable were explained by variations in the dependent variable. This is quite hi

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