Analysis of the Impact of Deforestation on Agricultural Productivity in Nigeria: An Error Correction Modeling Approach

Abstract

This study analyzed the impacts of deforestation on agricultural productivity in Nigeria. The specific objectives were to assess the trend of deforestation and the impact of deforestation on agricultural productivity. Time series data on all the variables in the study spanning from 1975 to 2010 were used.  Descriptive statistic and Error Correction Model were the analytical techniques used for the study. The Unit root test results reveal that all the variables of deforestation, agricultural productivity, average rainfall and number of tractors were found to be non-stationary at 5% level but stationary at first difference, which give way for long-run co-integration. Analysis of Error Correction Model (ECM) results indicated an inverse long- run relationship between deforestation and agricultural productivity. The result reveals that 1% increase in deforestation will result in 1.7% decrease in agricultural productivity. Average rainfall and number of tractors show a long-run positive relationship with agricultural productivity. With 1% increase in average rainfall and number of tractors, agricultural productivity will increase by 0.5% and 2.4%, respectively. The result of the short- run analysis shows positive relationship between previous year’s agricultural productivity and rainfall on current agricultural productivity with elasticity of 0.9 and 0.2, while deforestation portrayed a negative effect on agricultural productivity with elasticity of -0.7. Error Correction Model shows a permanent impact of deforestation and agricultural productivity. Policies should gear up towards finding alternative sources of energy, while unnecessary clearing of forests should be legislated against to minimized causes of deforestation and its impacts on agricultural productivity.

Keywords: Deforestation, Productivity, Error- correction and Nigeria