Inference from Modelling FDI and Unemployment Rate in Nigeria

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Ikwuoche John David -
Danjuma Idi

Abstract

This research investigates foreign direct investment (FDI) impact on the unemployment rate (UPR) in Nigeria by employing an Autoregressive Distributed Lag (ARDL) model. The study made use of data from the period 1985-2021. Initial assessment of the data involved the application of rolling correlation to test the significance of signals between FDI and UPR. Subsequently, the research employs the ARDL bounds test methodology to examine cointegration among FDI and UPR. Additionally, an Error Correction Model (ECM) is utilized to explore the causal relationship between these economic variables in the short run. The Augmented Dickey Fuller unit root test suggests that the variables attain stationarity at first differences (I(1)). The findings indicate that at 5% FDI significantly impacted on UPR in the long run but not in the short run where it was significant at 10%. Also, the selected best fitted model for the sampled period is ARDL(1, 1) but the plot of the cumulative sum squared chart showed that the parameter estimates were unstable for the sampled period. The results suggest more investment in FDI is necessary for reducing Nigeria unemployment rate in the long run and stabilizing it in the short run.

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Article Details

How to Cite
David, I. J., & Idi, D. (2024). Inference from Modelling FDI and Unemployment Rate in Nigeria. Asian Journal of Science, Technology, Engineering, and Art, 2(4), 566-578. https://doi.org/10.58578/ajstea.v2i4.3444

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