TABLE 16-13 A Local Store Developed a Multiplicative Time-Series Model to Forecast

TABLE 16-13
A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 4-year period from 1998 to 2002. The following is the resulting regression equation:
log₁₀Y^{^} = 6.102 + 0.012 X - 0.129 Q₁ - 0.054 Q₂ + 0.098 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 1998.
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 16-13, the best interpretation of the coefficient of Q₂ (- 0.054) in the regression equation is

A) the revenues in the second quarter of a year is approximately 5.4% lower than it would be during the fourth quarter.
B) the revenues in the second quarter of a year is approximately 5.4% lower than the average over all 4 quarters.
C) the revenues in the second quarter of a year is approximately 11.69% lower than the average over all 4 quarters.
D) the revenues in the second quarter of a year is approximately 11.69% lower than it would be during the fourth quarter.