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Optimal identification of ARIMA model for Predicting CPI in Nigeria using output based criterion

Abstract

The sum of squares deviation forecast criterion (SSDFC) is as output based model selection criterion employed to identify the best fitted ARIMA (p, d, q) models for predicting consumer price index (CPI) in Nigeria. The data set covering the period of 1995M1 to 2018M12 was used in the analysis. Unit root test used indicates that CPI is integrated order zero (I (0)) after first difference. The correlogram plots indicated that CPI follows an ARIMA (p, 1, 0) process. And out of the five subclasses of ARIMA (p, 1, 0) models compared, SSDFC chose ARIMA (5, 1, 0) as the best fitted model. The diagnostic test on the model residuals showed that ARIMA (5, 1, 0) is adequate. Hence, the model can be recommended for predicting the dynamics of CPI in Nigeria.

Forecasting Techniques and ApplicationsAutoregressive integrated moving averageCorrelogramStatisticsMathematicsModel selectionEconometricsBox–JenkinsUnit rootAkaike information criterionSelection (genetic algorithm)
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