Title of Publication: ON THE APPLICATION OF LINEAR AND BILINEAR TIME SERIES MODELS TO ESTIMATION OF REVENUE DATA
Author(s): Dr. A. E. Usoro, Dr. C. O. Omekara
Year of Publication: 2012
This paper considers application of linear and bilinear time series models in estimating revenue data. The data used were monthly revenue, which comprise the allocation from Federal Government and internally generated revenue of a Local Government Council in Akwa Ibom State. The motivation behind the comparison between the revenue estimates of linear and bilinear models was to find out if the assertions of Subba Rao (1984) and Maravall (1983) could be applicable to Nigerian system of revenue generation, by using available data at a Local Government level. The aim is to choose more suitable time series model for making projection and proposing feasible targets to revenue generation units or Departments of government establishments. Ordinary least squares method was adopted to estimate the parameters of both linear and bilinear models. From the empirical findings, it was observed that bilinear model fitted the revenue data better than the linear model with standard error difference of 62.66. This affirms the fact that bilinear time series models are more suitable in modeling revenue series, considering the dynamic nature of the time series data. Since the improvement and superiority of bilinear models over linear models are established, this paper recommends forecast of revenue series with bilinear models.
KEY WORDS: Autoregressive model, Linear and Bilinear Models.
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