When you transform from the log to the linear form, you have to adjust by the variance of the regression.
Need to make sure you have e(rmse) in ereturn before you make the calculation, or else save it as a local for later use.
Clyde's idea a clever solution since predict will give you what want directly. Jeff's proposal to simplify the first stage is probably a good one.
If you idea is to predict Yi, then it may make sense just to focus on that and not worry so much about selection bias, etc.. Prediction is a different game than hypothesis testing.
Need to make sure you have e(rmse) in ereturn before you make the calculation, or else save it as a local for later use.
Clyde's idea a clever solution since predict will give you what want directly. Jeff's proposal to simplify the first stage is probably a good one.
If you idea is to predict Yi, then it may make sense just to focus on that and not worry so much about selection bias, etc.. Prediction is a different game than hypothesis testing.
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