Hello everyone,

I am working on cross section data and I am trying to run a simulation of the impact of climate change on farmers' incomes based on climate scenarios, but I am not sure how to proceed. I am using a log specification and took account the logarithmic transformation but I have somme issues to determine the predicted change.

Here is the code I used :


Code:
regress logrevpast plumoymensV sqplumoymensV plumoyssecV sqplumoyssecV tempmoy sqtempmoy age ib0.sexehead taillemen densite distville distforage patexpss ib3.agrozone, vce(robust)

quietly predict lyhat0

generate yhatnormal0 = exp(lyhat0)*exp(0.5*e(rmse )^2)
regress logrevpast precsmp1 sqprecsmp1 plumoyssecV sqplumoyssecV tempsmp1 sqtemsmp1 age ib0.sexehead taillemen densite distville distforage patexpss ib3.agrozone, vce(robust)

quietly predict lyhat1

generate yhatnormal1 = exp(lyhat1)*exp(0.5*e(rmse )^2)

regress logrevpast precspp1 sqprecspp1 plumoyssecV sqplumoyssecV tempspp1 sqtemspp1 age ib0.sexehead taillemen densite distville distforage patexpss ib3.agrozone, vce(robust)

quietly predict lyhat2

generate yhatnormal2 = exp(lyhat2)*exp(0.5*e(rmse )^2)
Code:
sum yhatnormal0 yhatnormal1 yhatnormal2

Code:
sum yhatnormal0 yhatnormal1 yhatnormal2

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
 yhatnormal0 |        918     1858089     1107744   373023.8    4974372
 yhatnormal1 |        918     1842156     1299330     246173    7328710
 yhatnormal2 |        918     1842156     1299330     246173    7328710
What I don't understand is why I get the same results for the predicted values yhatnormal2 and yhatnormal3 while the climate variables of these models are completely different. Is there a condition to indicate in the Stata command line.

Thank you in advance for your help