Modelling Monthly Headline Consumer Price Index (HCPI) through Seasonal Box-Jenkins Methodology

Author(s): Emerson Abraham Jackson, Edmond Tamuke, Abdulai Sillah

In this empirical work, cognisance has been given to providing a review of literature on the seasonal Box-Jenkins modelling, particularly with reference to a univariate model. Seasonal pattern of Headline Consumer Price Index (HCPI) has been produced for Sierra Leone and with EVIEWS making use of best model selection of (6,0)(0,0). Data were seasonally adjusted with iteration and sufficient diagnostic test outcomes showing that forecast using Static method yielded best outcome, with Year-on-Year inflation over the three monthly period forecasted outcomes. The correlogram of the resultant series revealed very stable outcome of the results, while MAPE for the forecast evaluation revealing marginal error for the outcome, indicating that the model is quite adequate with the chosen methodology.

ARIMA Model, HCPI, Time Series, Sierra Leone

1. Box, G.E.P. and Jenkins, G.M. (1976). “Time Series Analysis, Forecasting and Control”, Holden-Day, San Francisco.
2. Etuk, E. H. (1987). On the Selection of Autoregressive Moving Average Models. An unpublished Ph. D. Thesis, Department of Statistics, University of Ibadan, Nigeria.
3. Etuk, E.H., Moffat, I.U and Chims, B.E. (2013). Modelling Monthly Rainfall Data of Port Harcourt, Nigeria by Seasonal Box-Jenkins Methods. International Journal of Science, Vol. 2 (July): pp. 60-67.
4. Jackson, E. A. (2017). Economic Methodology: Paradox of Ceteris Paribus (CP) Law in the Context of Sierra Leone. Method(e)s: African Review of Social Sciences Methodology, Vol. 2(1-2): pp. 31-4. DOI: 10.1080/23754745.2017.1354553.
5. Oyetunji, O. B. (1985).” Inverse Autocorrelations and Moving Average Time Series Modelling”. Journal of Official Statistics, 1, pp. 315 – 322.
6. Taneja, K., Ahmad, S., Ahmad, K. and Attri, S. D. (2016). Time series analysis of aerosol optical depth over New Delhi using BoxeJenkins ARIMA modeling approach. Atmospheric Pollution Research, Vol. 7 (2016): pp. 585-596.