The study investigated the effect of foreign direct investment on agricultural output in Somalia. The study utilized time-series secondary data sourced from the World Bank Indicators and the United Nations Data website, SESRIC, the Central Banks of Somalia, and the IMF between 1970 and 2020. The study adopted “Cobb-Douglas production function” to estimate the effect of FDI on agricultural output in Somalia. Before estimation, the augmented Dickey-Fuller test was used to make sure that the data was stationary. The study employed the ARDL model to evaluate the co-integration approach for estimating long-run and short-run associations and dynamic interaction between the variables. FMOLS and DOLS were also used in the research to figure out how sensitive and stable the long-run characteristics were. The result of the Johansen cointegration analysis showed the presence of three cointegrating equations in the long-run dynamics. The correlation findings demonstrate that the variables possessed a correlation coefficient that was higher than the threshold of 0.8. The major regression findings of this study show that all explanatory variables' outcomes from all applied models (ARDL, DOLS, and FMOLS) have a strong positive relationship with agriculture output in Somalia. All the study's three models' coefficients are positive, and all their t-statistics are statistically significant and greater than the 5% critical value. In the short term, Somalia's agricultural output is positively affected by all the estimated explanatory variables in this study. The study suggests that, to enhance the sustainability of the country's economic growth, the government should create sufficient investment incentives to stimulate foreign investment in the agriculture sector's development process.

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