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

Authors : Daniel JACOB, Imaobong NELSON

Pages : 50-58

View : 17 | Download : 13

Publication Date : 2021-06-30

Article Type : Research Paper

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% insert ignore into journalissuearticles values(₦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 insert ignore into journalissuearticles values(R2); ranging between 0.177 and 0.331. The predictive model showed that all the independent variables insert ignore into journalissuearticles values(revenue sources); had a positive and significant effect insert ignore into journalissuearticles values(p < 0.05); on revenue year except for unspecified sources which had a negative and significant effect insert ignore into journalissuearticles values(p < 0.05);. The predictive model R was highly significant insert ignore into journalissuearticles values(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