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# PS6.8 for Example 6.6
open data6-4
logs WAGE
# generate square of education
square EDUC
# estimate linear model
ols WAGE 0 sq_EDUC EXPER
# estimate log-linear model
ols l_WAGE 0 sq_EDUC EXPER
# save fitted log values
genr lwhat = l_WAGE - $uhat
# save ess for bias correction
genr sgmasq=$ess/$df
# generate adjusted fitted value
genr what = exp(lwhat+(sgmasq/2))
# compute error in new fitted value
genr error = WAGE -what
# compute new ess
genr ess = sum(error*error)
# learn about the "criteria" function
help criteria
# compute selection criteria
criteria(ess, 49, 3)
# compute correlation between observed WAGES and adjusted predictions
corr WAGE what
genr c1 = corr(WAGE,what)
genr rsq = c1*c1
print rsq
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