Impact of Foreign Direct Investment on Sustainable Growth in the Nigerian Agricultural Sector (1984–2023)

This study investigates the impact of Foreign Direct Investment (FDI) on sustainable growth in Nigeria’s agricultural sector, employing annual time-series data spanning 1984 to 2023. The Autoregressive Distributed Lag (ARDL) model is applied to examine short-run and long-run dynamics between agricultural productivity and four key variables: FDI inflows to agriculture, agricultural employment, agricultural machinery, and CO₂ emissions from agriculture. The ARDL bounds test reveals no evidence of a long-run cointegrating relationship, indicating that FDI has not exerted a statistically significant influence on agricultural productivity over the long term. In the short run, agricultural employment exhibits a significant but negative effect on agricultural output, while FDI inflows, agricultural machinery, and CO₂ emissions are statistically insignificant. Drawing on the absorptive capacity framework of Borensztein, De Gregorio, and Lee (1998), the study argues that Nigeria’s agricultural sector lacks the human capital, institutional quality, and technological readiness required to convert FDI inflows into measurable productivity gains. The findings have direct policy relevance: sustainable agricultural growth in Nigeria requires structural reforms that build absorptive capacity rather than simply attracting more foreign capital. HuberWhite heteroskedasticity-consistent standard errors are employed throughout to ensure robust inference.