TABLE 16-5 a Contractor Developed a Multiplicative Time-Series Model to Forecast the Forecast

TABLE 16-5
A contractor developed a multiplicative time-series model to forecast the number of contracts in future quarters, using quarterly data on number of contracts during the 3-year period from 1996 to 1998. The following is the resulting regression equation:
ln Y^{^} = 3.37 + 0.117 X - 0.083 Q₁ + 1.28 Q₂ + 0.617 Q₃
where
Y^{^} is the estimated number of contracts in a quarter
X is the coded quarterly value with X = 0 in the first quarter of 1996.
Q₁ is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.
Q₂ is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.
Q₃ is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise.
-Referring to Table 16-5 , the best interpretation of the constant 3.37 in the regression equation is

A) the fitted value for the first quarter of 1996, after to seasonal adjustment, is 10^{3. 37}.
B) the fitted value for the first quarter of 1996, prior to seasonal adjustment, is 10^3.37.
C) the fitted value for the first quarter of 1996, prior to seasonal adjustment, is log₁₀ 3.37.
D) the fitted value for the first quarter of 1996, after to seasonal adjustment, is log₁₀ 3.37.