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The aim is to examine the long run and short run linear and non-linear impact of foreign direct investment (FDI) inflows on poverty in Nigeria from 1980 to 2019.

The Augmented Dickey Fuller, Phillips Perron and Kwiatkowski-Phillips-Schmidt-Shin unit root tests and bounds test were used to tests the series stationarity and co-integration, respectively. Autoregressive Distributive Lag (ARDL) and non-linear and linear autoregressive Distributive Lag (NARDL) estimators are employed to examine the long run and short run impact of the coefficients of the variables and diagnostic check.

The study finds that the variables are integrated at a level I(0) and the first difference I(I) and co-integrated. The ARDL estimator indicates that FDI significantly reduces poverty in the long and short run. The findings under NARDL shows FDI positive shock and FDI negative shock reduces poverty substantially in the long-short run, respectively. The error correction term is negative and significant.

This study is limited to a single country (time series) and less informative compared with the panel data study with much informative and free from hetero-scedasticity. Future studies should consider panel data using a similar or dissimilar approach.

FDI inflows stimulate growth, thereby creating job openings, transfer of modern technology and reduce poverty and demonstrate that, if the finding integrated into policy actions, the government would attract FDI inflows for the real sector of the economy.

FDI inflows lead to environmental degradation if inferior technology is use in the host economy, especially the weak environmental regulations in Nigeria.

The authors find no study that applied both ARDL and NARDL estimator, selection of variables measurement and time frame for the study in the context of Nigeria.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2020-0530.