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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | # PS7.7, for the Application in Section 7.8
open data7-5
ols Q const P HS SHC OC L PL
# Above command estimates Model A. Now generate monthly dummies
genr dummy
# estimate Model B with monthly dummies
ols Q const P HS SHC OC L PL dm2 dm3 dm4 dm5 dm6 \
dm7 dm8 dm9 dm10 dm11 dm12
# reset sample range to the first period only
smpl 1983.01 1986.06
# Next estimate Model C
ols Q const P HS SHC OC dm2 dm3 dm4 dm5 dm6 \
dm7 dm8 dm9 dm10 dm11 dm12
# omit variables with highest p-values, a few at a time
omit dm2 dm3
omit HS
omit dm8 dm9
omit dm10 dm11
omit dm4
omit dm5 dm7
# This is Model D, the final model with all significant coefficients
omit dm12
# obtain predicted values for the loss and post loss periods
fcast 1986.07 1990.05 Qhat
# reset sample range to the second and third periods
smpl 1986.07 1990.05
# compute loss in sales for each month
genr Qloss = Qhat - Q
# compute loss in revenues for each month
genr dolrloss = P*Qloss
# print values
print -o Q Qhat Qloss dolrloss
# set sample range to the middle period
smpl 1986.07 1988.10
# compute sum of losses during the litigation period
genr totqloss = 28*mean(Qloss)
genr totdloss = 28*mean(dolrloss)
# print the values
print totqloss totdloss
# reset sample range for the post loss period
smpl 1988.11 1990.05
# compute sum of losses for this period
genr qloss2 = 19*mean(Qloss)
genr dloss2 = 19*mean(dolrloss)
# print the values
print qloss2 dloss2
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