International Journal of Statistics and Applied Mathematics
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International Journal of Statistics and Applied Mathematics

2022, Vol. 7, Issue 4, Part B

Predicting inflation rate in Nigeria and Ghana using a suitable autoregressive integrated moving average (ARIMA)


Author(s): Seun Adebanjo, Pius Sibeate and ELISA EHINMILORIN

Abstract:
A persistent increase in the average price of goods and services is called inflation, and it is typically bad for a country's economy. The data for the inflation rates of Nigeria and Ghana examined in this paper were taken from World Bank annual publications covering the years 1970 to 2021. This study used a quantitative research design. The main goal of this study is to use an appropriate autoregressive integrated moving average (ARIMA) model to forecast the inflation rate in Nigeria and Ghana. The unit root test with augmented dickey fuller (ADF) was applied to the examined inflation rate in Nigeria, and the results show that the series are integrated of order one. As a result, a time series autoregressive integrated moving average (ARIMA) analysis was carried out. The results show that ARIMA (1,1,2) and ARIMA (1,1,1) are the best-fitting ARIMA models based on the number of significant coefficients, volatility, adjusted R-squared, Akaike Information Criterion, and Schwarz Criterion.
The future inflation rate forecast for Nigeria and Ghana indicates a downward trend, which is a positive economic indicator. Despite this, the government should develop appropriate monetary policy measures to mitigate inflation's effects on the economy.


Pages: 160-164 | Views: 59 | Downloads: 5

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How to cite this article:
Seun Adebanjo, Pius Sibeate, ELISA EHINMILORIN. Predicting inflation rate in Nigeria and Ghana using a suitable autoregressive integrated moving average (ARIMA). Int J Stat Appl Math 2022;7(4):160-164.
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