This research was conducted to estimate compensation of employee using least square dummy variable (LSDV) regression model. The data used in this work were secondary data sourced from National Bureau of Statistics (NBS) from 1981 to 2006. The variables considered were compensation of employee as the dependent variable, fixed capital, price of goods, tax and surplus as the independent variables. The data were analyzed using (STATA 13). The results obtained revealed that F-value of 3874.05 was statistically high suggesting the overall model was good fitted. The R2 -value 0.9989 was also high which indicated that 99.89% of the total variation was accounted for by the independent variables included in model while the remaining 0.11% unexplained was accounted for by the white noise. Again, all the differential intercept coefficients have negative signs. Also, several differential slope coefficients have negative signs which implied that they were negatively related to compensation. Again, the result revealed that compensation is not statistically significantly related to fixed capital, price, tax and surplus. However, none of the differential slope coefficients is statistically significant. Of all the three differential intercept coefficients only was statistically significant. Since none of the differential slope coefficients was statistically significant, it concluded that the differential slope coefficients are not different from the slope coefficient of the base/comparison group (power sector.
Keywords: Compensation, Dummy Variable, Panel Data, fixed effect and employee
