#  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 command 
help criteria
# compute criteria statistics 
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 


