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All Journal Asian Journal of Science, Technology, Engineering, and Art
Ogunmola, Adeniyi
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Arts Computer Science & IT Engineering Social Sciences

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Comparative Study on Forecast Performance from Decomposition, Winter’s and Sarima Models Stephen, Mathew; Ogunmola, Adeniyi; Akobi, Clement Ogbeche; Michael, Ibrahim
Asian Journal of Science, Technology, Engineering, and Art Vol 2 No 6 (2024): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v2i6.4040

Abstract

This study investigates the forecasting accuracy of three univariate time series models—Decomposition, Winter’s method, and Seasonal Autoregressive Integrated Moving Average (SARIMA) to predict the Agricultural GDP of Nigeria. Quarterly data on Nigeria's Agricultural GDP from 2010 to the first quarter of 2023, obtained from the National Bureau of Statistics, were analyzed. The study applied Box-Jenkins SARIMA modeling, time series decomposition, and Winter’s method to compare their forecasting accuracy using Root Mean Square Error (RMSE) as the selection criterion. The results revealed that the SARIMA (0, 0, 2)(2, 1, 0) model outperformed the other methods, with the lowest RMSE, indicating its superior accuracy in forecasting Agricultural GDP. Winter’s method and the Decomposition method. The forecast from the SARIMA model indicated a positive trend in Nigeria’s Agricultural GDP over the study period, reinforcing the sector’s critical role in economic growth.
Application of ARIMA Methods on Unemployment and Inflation Rates in Nigeria Akobi, Clement; Ogunmola, Adeniyi
Asian Journal of Science, Technology, Engineering, and Art Vol 2 No 6 (2024): Asian Journal of Science, Technology, Engineering, and Art
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/ajstea.v2i6.4087

Abstract

In Nigeria, Unemployment and inflation rate are some of the problems bedeviling the economy. The inability of Job seekers to secure gainful employment tends to create disaffection among these people and cause some of them especially the youth, to resort to social vices. In the motivation to experience low unemployment rate and inflation rate which are economic indicators in Nigeria, deriving appropriate ARIMA model to give insight into future occurrence of these indicators for intervention calls for the application of ARIMA model. This study seek to fit ARIMA model to unemployment rate and inflation rate and forecast future values for both unemployment rate and inflation rate. Utilizing secondary data sourced from the National Bureau of Statistics (NBS) from 1991 to 2020. The findings reveal that, for each of the two series, to obtain the appropriate ARIMA model that fits the data, ten closely suitable ARIMA models were identified. Using the least values of AIC, AICc and BIC as selection criteria, ARIMA (0, 1, 1) was found to be the best fitted model for each of the two series. Subsequent diagnostic checks confirm the adequacy of the fitted models, with residual analyses indicating no significant autocorrelation or heteroscedasticity. The forecasted values for the unemployment rate series and inflation rate series maintain a constant point forecast. This implies that unemployment rate and inflation rate in Nigeria does not reveal a noticeable increase nor decrease but will be constant in Nigeria. Due to the unchanging forecasted value which appears not to be decreasing, there is need for interventions that will lead to the visible reduction of present unemployment rate and inflation rate in Nigeria.
Co-Authors Akobi, Clement Akobi, Clement Ogbeche Michael, Ibrahim Stephen, Mathew