Modeling and Forecasting Inflation in Nigeria: A Time Series Regression with ARIMA Method

Emwinloghosa Kenneth Guobadia; Pamela Owamagbe Omoruyi; Paschal Nnamdi Izuogu; Eloho Sophia Omodio; Agu Chidera

doi:10.52589/AJESD-HFYC2BNW

Modeling and Forecasting Inflation in Nigeria: A Time Series Regression with ARIMA Method | AB Journals

Modeling and Forecasting Inflation in Nigeria: A Time Series Regression with ARIMA Method

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African Journal of Economics and Sustainable Development

Vol. 6Issue 32023pp. 42–53Published 14 August 2023

DOI 10.52589/AJESD-HFYC2BNW

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Abstract:

This study uses time series regression with autoregressive integrated moving average (ARIMA) modeling to establish a model for forecasting inflation in Nigeria for the period 1981-2020. Akaike Information Criterion Corrected (AICC) and Bayesian Information Criterion (BIC) were used to select the best model among competing models. Through these methods, regression with ARIMA (0,0,1) error was selected as the most parsimonious model for inflation forecasting in Nigeria. The results of the out-sample-forecast show that a high inflation rate will be experienced by the end of 2023, and between 2024 and 2030, the inflation rate will be alternating but will maintain a lower rate than that of 2023.

Keywords:Inflation Forecasting Time Series Multiple Regression Regression with ARIMA Error

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