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This study tried to investigate the impact of agriculture and manufacturing on economic growth using time series data from (1987-2019). To analyze the link between the variables, the researchers utilized the ADF to test for stationarity, the Ordinary Least Square Method, the Error Correction Model, and the Granger Causality Test. The result shows that, the coefficient of agricultural output has a positive sign, indicating a favorable association. The AGRQ coefficient is (0.045142), implying that a 5% change in AGRQ will result in a 5% change in Manufacturing Value Added. At the 0.05 percent level, the finding is statistically significant, with a probability of (0.0000). The coefficient of determination R-Squared (R2) is 0.817974, indicating that variations in the explanatory variables account for nearly 82 percent of the variation in Manufacturing Value Added. The ECM's coefficient (-1) is (0.619202). The coefficient indicates that the short run adjustment annually offsets 62% of the system's disequilibrium in order to restore long-run equilibrium. This means that the system will reach equilibrium at a 62 percent rate the following year. At the 5% level of significance, Granger causality demonstrates that there is no causal link between Manufacturing Value Added and Real Gross Domestic Product. However, manufacturing value-added and agricultural output have a one-way relationship. The study recommends that government must urgently expand the Nigerian agricultural sector by allocating more financing to the industry and ensuring that the funds are used wisely and to further support increased industrial productivity and expansion, the government should work to strengthen its incentives to the manufacturing sector.

Impact Assessment of Agriculture and Manufacturing Sectors on economic Growth in Nigeria.