A SARIMA Model for Forecasting Consumer Price Index in Tanzania

People must be well-informed on market swings in today's difficult economic times in order to cut excessive spending. Rising expenditures in a variety of sectors, including business, education, and healthcare can be burdensome for consumers, and accurate forecasting of household is necessary given the current technological innovation. The Consumer Price Index (CPI) is one of the statistical indicators used to estimate the changes in prices for commodities. Forecasting CPI can assist individuals in developing a plan for making decisions on their daily consumption. This study seeks to develop a SARIMA model for forecasting consumer price indices (CPI) in Tanzania by using data collected from International Monetary Fund (IMF) website from January 2010 to December 2022. Data were evaluated using time series methods such as time plots and stationarity tests. It was discovered that there is seasonality in the CPI index. However, a serial correlogram test was performed using a residual correlogram after which the variable was estimated using the SARIMA model and SARIMA (0, 1, 0) (1, 1, 1)12 was fitted to the time series variable. The residual analysis was explored and because almost all correlations are zero, the SARIMA (1,1,1) (0,1,2)12 model was appropriate for forecasting CPI index in Tanzania. Consumer price index was predicted for the next eighteen months and it has been observed that the trend of CPI is likely to increase in the next eighteen months.