Study on Time Series Modeling and Forecasting Inflation: Evidence from Nigeria

Effective prediction of general price level trends has been a major concern of entrepreneurs and monetary authorities in Nigeria over the past decades. The results allow monetary authorities to prepare effectively and the profit drive on the part of entrepreneurs and investors continues. This research uses a univariate model developed by Box and Jenkins in the form of the Autoregressive Integrated Moving Average model and a multivariate time series model to forecast inflation for Nigeria in the form of the Vector Autoregressive model. Changes in the monthly use of this paper For the period 2003 to 2012, the consumer price index collected from the National Bureau of Statistics and the Central Bank of Nigeria forecast movements in the general price level. The best forecasting model for predicting inflation in Nigeria is defined on the basis of various diagnostic and evaluation parameters. The results would enable policymakers and businesses to monitor the output and stability of key macroeconomic indicators using the inflation forecast. For the month of 2012:10, the study expected core inflation using VAR to be 11.06 percent. A major drawback of this study is that the VAR method and the ARIMA method based on two major forecasting methods and ignored the use of neural network analysis. Furthermore, as an indicator of inflation, only core inflation was used. Subsequent inflation forecasting studies in Nigeria should aim to predict inflation through a broader variety of inflation steps.

Author (s) Details

Dr. Ikechukwu Kelikume
Lagos Business School, K.M 22 Lekki-Aja Expressway, Lagos Island, Lagos State, Nigeria.

Adedoyin Salami
Lagos Business School, K.M 22 Lekki-Aja Expressway, Lagos Island, Lagos State, Nigeria.

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