Modeling and forecasting inflation in Tanzania using ARIMA models
Thabani Nyoni
Abstract
Open-access reader
Thabani Nyoni
Abstract
Open-access reader
This research uses annual time series data on inflation rates in Tanzania from 1966 to 2017, to model and forecast inflation using the Box – Jenkins ARIMA technique. Diagnostic tests indicate that the T series is I (1). The study presents the ARIMA (1, 1, 2) model for predicting inflation in Tanzania. The diagnostic tests further imply that the presented optimal model is actually stable and acceptable for predicting inflation in Tanzania. The results of the study apparently show that inflation in Tanzania is likely to continue on an upwards trajectory in the next decade. The study basically encourages policy makers to make use of tight monetary and fiscal policy measures in order to control inflation in Tanzania.
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This research uses annual time series data on inflation rates in Tanzania from 1966 to 2017, to model and forecast inflation using the Box – Jenkins ARIMA technique. Diagnostic tests indicate that the T series is I (1). The study presents the ARIMA (1, 1, 2) model for predicting inflation in Tanzania. The diagnostic tests further imply that the presented optimal model is actually stable and acceptable for predicting inflation in Tanzania. The results of the study apparently show that inflation in Tanzania is likely to continue on an upwards trajectory in the next decade. The study basically encourages policy makers to make use of tight monetary and fiscal policy measures in order to control inflation in Tanzania.
Key concepts: Tanzania, Autoregressive integrated moving average, Inflation (cosmology), Economics, Econometrics, Time series, Macroeconomics, Statistics