Dummy variables assign the numbers ‘0’ and ‘1’ to indicate membership in any mutually exclusive andexhaustive category. The number of dummy variables necessary to represent a single attribute variable is equal to the number of categories in that variable minus one. In this study, dummy variables regression analysis was applied to estimate the average GDP at various quarters; the GDP data was described and graphically presented. A regression model was estimated to determine the average value for each quarter, the seasonal component, and average GDP confidence interval. The study provides the seasonal prediction and revealed that the average GDP in the second, third and fourth quarters are not statistically difference except the first quarter. The result of the studies showed that Nigeria realised the highest income generated by productions and services in the country in the fourth quarter of every year.
INCORPORATING DUMMY VARIABLES IN REGRESSION MODEL TO DETERMINE THE AVERAGE INTERNALLY GENERATED REVENUE AND WAGE BILLS OF THE SIX GEOPOLITICAL ZONES IN NIGERIA (Published)
This paper compare the year 2012 Internally Generated Revenue (IGR) and Wage bills of the six (6) Geopolitical zones in Nigeria. The Internally Generated Revenue and wage bills from the thirty six (36) states were categorized to six (6) Geopolitical zones (Southwest, Southsouth, Southwest, north central, northeast and northwest) and proxy with dummy variables. The average Internally Generated Revenue and Wage bills of each Geopolitical zone were derived from the expectation of the regression model and the estimated coefficient of its slope indicate which of the averages is statistically significant different. It also appraised which of the six geopolitical