FORECASTING THE CONSUMER PRICE INDEX OF GHANA USING EXPONENTIAL SMOOTHING METHODS

Abstract

Consumer price index is a social and economic indicator that measures changes over time in the general level of prices of consumer goods and services that households acquire, use or pay for consumption. Rising CPI also often leads to the central bank to raise interest rates, tightening money supply, reduce the money supply and other measures to tighten monetary policy, which flow into reduction of capital stock funds for greater returns, often accompanied by high inflation. The study seeks to determine a time series exponential smoothing method which fit the CPI and use it forecast the future values of CPI. Minitab software is used to analyze the CPI from March 2013 to November 2018. Out three exponential smoothing methods, it is realized that the method which best fit the series is the Winters’ additive method with exponential smoothing constants for the level, trend and seasonal variation as ,  and  respectively. This method is chosen on the basis that it has the lowest MAPE, MAD and MSD. The validity of the model is further checked by comparing the fitted values with the actual values. The errors in prediction were very minimal. The model is therefore recommended for forecasting CPI of Ghana in the next twelve months.

Key words: Consumer price index, exponential smoothing, ARIMA

DOI: 10.7176/MTM/9-3-01

Publication date: March 31^st 2019