No abstract

The paper examined univariate time series forecast of consumer price index on the consumption of food and nonalcoholic beverages in Nigeria. It filled the knowledge gap by explicitly modeling and forecasting consumer price index in Nigeria using the univariate ARIMA model. The work was restricted to Nigerian Consumer Price Index. It was also restricted to food consumption (FC) data and food & nonalcoholic beverages consumption (FNBC) data from 1995-2021. This paper analyses were carried out using gretl 2019c, Minitab 16 and Micro software Excel (2010). The monthly and yearly means plots were done, so as to have a better understanding of the series behaviours. The series plots points to the fact that there is possibility that the time series are integrated of order 1 for food consumption series with no seasonality, while integrated of order 1 for food & nonalcoholic beverages consumption series with seasonality of order 12. Stationarity after second difference of the first differencing was obtained for both series. A suitable ARIMA Model was obtained for both series and was used for models forecast computation. Hence, the computed result suggested that ARIMA(0,1,1) and ARIMA(0,1,1)(0,0,0)12 model were the best model for estimating and forecasting the two time series, using model selection criteria and accuracy measures. The plots of the forecasts generated for the FC and FNBC shows that the two variables are dependent and also shows that any gradual increase in the food consumption tends to pave way for increase in the food & nonalcoholic beverages consumption or a drastic drop in the food consumption will also drop the food & nonalcoholic beverages consumption in the same manner. It seems reasonable to conclude that there is significant relationship between the food consumption and food & nonalcoholic beverages consumption series. It was recommended that more detailed work should be carried out in the area of co-integration analysis of the two variables to enhance a better understanding and prediction distribution in Nigeria.

Between 1981 and 2021, this research work looked at the test for equality of regression models employing some service expenditures on the Nigerian GDP. This study has five particular objectives that were created and used. Relevant related literatures were reviewed based on the factors in the objectives. This study used secondary data acquired from the National Bureau of Statistics and the Central Bank of Nigeria statistical bulletin, which included 46 activity sectors. The data was analyzed using multiple regression models. MINITAB 16 and Microsoft Excel 2010 were used for all calculations. The series plot results for each service expenditures indicate an upward trend for the whole plot, implying a linear link between expenditures and Nigeria's total GDP. To find the significant parameters and test for model equality, the Durbin method of estimating a multiple regression model was used; this revealed that all of the models' parameters estimates were not significant at 5%, which appears biased. Model (1), the Military Government Period Model, was found to be the "best" of the three regression models, with the highest R2 and Adj. R2 values of 99.8%, the smallest AIC and BIC values of 170.356 and 174.134, and the highest F-value of 4494.669 determined. According to the findings, the government should devote a smaller amount of its budget to recurrent spending and focus more on capital spending, such as agriculture, education, and health, as it is the primary driver of economic growth.