Measuring and Explaining Agricultural Total Factor Productivity Divergence Across Nigerian States: A Spatial Econometric Approach

This study measures agricultural total factor productivity levels and growth rates across Nigerian states and applies spatial econometric methods to explain the persistent productivity divergence observed between northern and southern states. Agricultural productivity divergence across Nigerian states represents one of the country's most important development challenges, with productivity gaps between the most and least productive states exceeding three-fold. Understanding the spatial dimensions of this divergence, including geographic spillover effects, spatial clustering of productivity, and spatially conditioned policy effectiveness, requires explicitly spatial analytical approaches that are largely absent from Nigerian agricultural productivity literature. This study constructs state-level agricultural TFP indices using a non-parametric sequential Malmquist index applied to a balanced panel of state agricultural input and output data from 2000 to 2023. Spatial autocorrelation analysis using Moran's I and LISA statistics characterises the spatial distribution of TFP. Spatial panel econometric models including spatial lag and spatial error specifications identify TFP determinants while accounting for spatial spillovers. Findings establish strong positive spatial autocorrelation in TFP, with high-productivity clusters concentrated in the South West and parts of the Middle Belt. Geographic spillover effects are significant, with a 10 percent productivity improvement in a reference state generating a 3 to 5 percent productivity improvement in contiguous states through knowledge spillovers and market integration effects. The study contributes an original spatial productivity analysis and recommends regional agricultural development corridor strategies to leverage spatial spillover potential.

Keywords: total factor productivity, spatial econometrics, Nigerian states, productivity divergence, spatial spillovers.