Modelling and Forecasting Malaysian Consumer Price Index

Consumer price index is measure the average of people spent for consumer goods and services, such as transportation, food and medical care. CPI also can affect an inflation that will reduce the rate of economic growth in the country. The main objective of this research was to determine the appropriate model, to compare the appropriate model for Malaysian consumer price index using RMSE, MAD and MAPE and to forecast Malaysian consumer price index for short period. Therefore, to come up with a model and forecasts of CPI, Box and Jenkins methodology were used which consists of three main steps; Model Identification, Parameter Estimation and Diagnostic Checking. Assumptions about linear regression model are relationship between response and predicted is linear, mean of is 0. Third was variance are independent of each other, variables are identically and independently distributed following N (0, σ^2) and predicted variable is a nonstochastic variable. Therefore, ARIMA (1, 1, 0) was selected as an appropriate model which can fits well data, as well as to make also accurate forecast. Hence, the forecast was made for 12 months ahead of the year 2017, and the findings have shown that the CPI was likely to continue rising up with time.