Nigeria’s agricultural sector continues to struggle with two persistent challenges: limited access to finance and high inflation. This study explores how these factors, alongside broader economic drivers, shape agricultural output growth in both the short and long run. Using annual data from 1981 to 2024 drawn from the World Development Indicators, we apply an autoregressive distributed lag (ARDL) model with an error-correction framework. Preliminary tests confirm the suitability of this approach. The results show that in the short run, inflation and GDP per capita growth have a small but positive influence on agricultural output, though the system quickly adjusts back to equilibrium. Over the long run, however, broad bank credit does not significantly support agricultural growth, while persistent inflation reduces performance. Sustained GDP per capita growth is also associated with slower agricultural expansion, reflecting the ongoing shift of resources away from farming as economies develop. The significant negative error-correction term suggests rapid adjustment towards balance. This paper contributes new insights by extending the analysis up to 2024 and by jointly examining credit, inflation, and structural transformation in Nigeria’s agriculture within a unified ARDL framework. Policy lessons point to the importance of stabilizing prices, designing credit specifically for agriculture, and investing in productivity improvements to achieve durable growth and strengthen food security.

Keywords: Agricultural growth, ARDL, Credit, Error correction, Structural transformation.