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Modeling of Internally Generated Revenue Using Autoregressive and Moving Average of a Time Series Models: A Case Study of Akwa Ibom State

Apakhade, Gilbert Ekhasemomhe and Usoro, Anthony Effiong and Ekong, Akaninyene Okon (2024) Modeling of Internally Generated Revenue Using Autoregressive and Moving Average of a Time Series Models: A Case Study of Akwa Ibom State. European Journal of Statistics and Probability, 12 (2). pp. 11-25. ISSN 2055-0154(Print), 2055-0162(Online)

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Abstract

Modelling of Internally Generated Revenue using error variances for model comparison was the main focused of this research. This procedure varies from the familiar information criteria used to compare alternative models. The autocorrelation and Partial autocorrelation function of the stationary series give basis for the choice of Autoregressive Integrated Moving Average, ARIMA (1 1 1), ARIMA (1 1 2) and ARIMA (2 1 1) for the revenue series. From the estimates, Akaike Information and Schwartz’s Information Criteria (AIC and SIC) suggested ARIMA (2 1 1), while the error variance suggested ARIMA (1 1 2) respectively as the best model. The advantage in the use of error variance for model comparison is that the variance measures are positive. (not less than zero). The positive and negative signs in the AIC and SIC values are sometimes confusing, since absolute values are not considered in the BIC, SIC and AIC. Hence, this research relies on error variance for the model selection, which reputes ARIMA (1,1,2) to be the best model for the Akwa Ibom State Internally Generated Revenue Series.

Item Type: Article
Subjects: Q Science > QA Mathematics
Depositing User: Professor Mark T. Owen
Date Deposited: 23 Jul 2024 20:33
Last Modified: 23 Jul 2024 20:33
URI: https://tudr.org/id/eprint/3203

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