TITLE:
Modeling Consumer Price Index in Zambia: A Comparative Study between Multicointegration and Arima Approach
AUTHORS:
Stanley Jere, Alick Banda, Rodgers Chilyabanyama, Edwin Moyo
KEYWORDS:
Consumer Price Index, Multicointegration, ARIMA, ECM, Forecast
JOURNAL NAME:
Open Journal of Statistics,
Vol.9 No.2,
April
23,
2019
ABSTRACT: Consumer Price Index (CPI) is an important indicator used to determine inflation.
The main objective of this research was to compare the forecasting ability of
two time-series models using Zambia Monthly Consumer Price Index. We used
monthly CPI data which were collected from January 2003 to December 2017. The models that were
compared are the Autoregressive Integrated Moving average (ARIMA) model and
Multicointegration (ECM) model. Results show that the ECM was the best fit
model of CPI in Zambia since it showed smallest errors measures. Lastly, a
forecast was done using the ECM and results show an average
growth rate for food CPI at 6.63% and an average growth rate for nonfood CPI at
7.41%. Forecasting CPI is an important factor for any economy because it is
essential in economic planning for the future. Hence, identifying a more
accurate forecasting model is a major contribution to the development of
Zambia.