The nexus between foreign aid and foreign direct investment in Nigeria: Simultaneous equations approach / Mohammed Kabir Garba ... [et al.]

Undoubtedly, the choice of models for analyzing the relationship between level stationary Foreign Aid (FA) and Foreign Direct Investment (FDI) variables using single-equation modeling techniques such as Multiple Linear Regression (MLR) model produces non-spurious results in the sense that the coeffi...

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Bibliographic Details
Main Authors: Garba, Mohammed Kabir, Akanni, Saheed Busayo, Banjoko, Alabi Waheed, Oladele, Toluwa Celestine
Format: Article
Language:English
Published: Universiti Teknologi MARA Press (Penerbit UiTM) 2023
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Online Access:https://ir.uitm.edu.my/id/eprint/86390/1/86390.pdf
https://ir.uitm.edu.my/id/eprint/86390/
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Institution: Universiti Teknologi Mara
Language: English
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Summary:Undoubtedly, the choice of models for analyzing the relationship between level stationary Foreign Aid (FA) and Foreign Direct Investment (FDI) variables using single-equation modeling techniques such as Multiple Linear Regression (MLR) model produces non-spurious results in the sense that the coefficient of determination (R2) is always less than the Durbin-Watson (DW) statistic. However, non-spurious MLR in this case might not adequately fit the FA-FDI relationship because macroeconomic variables are usually prone to problems of simultaneity, serial correlation as well as autocorrelation. This study therefore shed light on the FA-FDI relationship in Nigeria using a system of simultaneous equation modelling techniques. The FA and FDI variables are proxied as endogenous variables while the Inflation (INF), Population Growth (PG), Trade (TR), and Real Interest Rate (RI) are proxied as instruments. Pre-tests analysis of these time series datasets extracted from the repository of World Governance Index did not only reveal that the six series are level stationary series I(0) but also shown that there was a two-way causation between FA and FDI variables. Results from the estimation techniques further showed that the Three-Stage Least Squares (3SLS) and Seemingly Unrelated Regression (SUR) outperformed the Ordinary Least Squares (OLS) and Two-Stage Least Squares (2SLS) estimators at estimating the structural parameters of the exactly identified and overidentified equations embedded in the model. Findings from the SUR estimates of the overidentified equation established that Nigeria’s FA is projected to increase by 0.217188 units on average for each one-unit increase in the FDI.