Application of time-series analysis in predictive modelling of forest revenue sources in Akwa Ibom State, Nigeria

Abstract

This study assessed revenues generated from various forestry related sources and their trend between 2001 and 2015 using secondary data to develop a predictive model as a means of forecasting future generated revenues for Akwa Ibom State, Nigeria. Data were analyzed using bar cart, percentages and least square regression with SPSS. The results obtained indicated that revenue from general licensing of forest activities generated the highest forest revenue accounting for 56.41% (₦48,122,578.70) of the total forest revenue generated in the state for the period. All forest revenue sources except unspecified sources followed an increasing trend with a coefficient of determination (R2) ranging between 0.177 and 0.331. The predictive model showed that all the independent variables (revenue sources) had a positive and significant effect (p < 0.05) on revenue year except for unspecified sources which had a negative and significant effect (p < 0.05). The predictive model R was highly significant (p < 0.01) as all the regressors accounted for more than 91% of the variations in the revenue year. The study recommends government commitment to sustainable forest utilization as it explores all revenue opportunities in the State.

Keywords

• Forest Revenue Sources
• Time-series Analysis
• Predictive Model
• Akwa Ibom State
• NIgeria

References

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