Munich Personal RePEc Archive

Modelling and Forecasting Inflation in Tanzania: A Univariate Time Series Analysis.

Kimolo, Deogratius (2009): Modelling and Forecasting Inflation in Tanzania: A Univariate Time Series Analysis.

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Modelling and forecasting inflation remains a vital concern in most of developing country economies. Moreover, better understanding of country’s inflation situation and future inflation can facilitate the policy makers to adopt appropriate policy measures to curb the problem. The study supplements the financial programming framework of the Bank of Tanzania by ascertaining the model that incorporates some key behavioural properties that are necessary in forecasting inflation.

The study employs the Box-Jenkins (1976) methodology that involves stages of identification, estimation, diagnostic checking, and forecasting of a univariate time series.

Findings of the study suggest that during the sample period the monthly inflation rate in Tanzania was non-stationary at level but stationary after taking the first difference, results indicate also that the model that contains AR (1, 3, 8, and 15) and MA (1 and 12) components outperformed other models in both in-sample and out-sample forecasts. Six months out-of-sample inflation forecasts are also provided by the study.

The study recommends the government through the Bank of Tanzania to adopt the flexible form of inflation targeting so as to improve the design and performance of monetary policy towards attainment of price stability. Results also indicate that inflation is expected to rise in the next six months; hence there is a need for government to react immediately to these inflationary pressures through appropriate fiscal and monetary policies.

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