Interpretation of logarithms in a regression
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Taken from Introduction to Econometrics from Stock and Watson, 2003, p. 215:
Y=B0 + B1*ln(X) + u ~ A 1% change in X is associated with a change in Y of 0.01*B1
ln(Y)=B0 + B1*X + u ~ A change in X by one unit (∆X=1) is associated with a (exp(B1) - 1)*100 % change in Y
ln(Y)=B0 + B1*ln(X) + u ~ A 1% change in X is associated with a B1% change in Y, so B1 is the elasticity of Y with respect to X.
Out-of sample test
“predict can be used to make in-sample or out-of-sample predictions:
6) predict calculates the requested statistic for all possible
observations, whether they were used in fitting the model or not.
predict does this for the standard options (1) through (3) and
generally does this for estimator-specific options (4).
7) predict newvar if e(sample), ... restricts the prediction to the
8) Some statistics make sense only with respect to the estimation
subsample. In such cases, the calculation is automatically
restricted to the estimation subsample, and the documentation for
the specific option states this. Even so, you can still specify
if e(sample) if you are uncertain.
9) predict can make out-of-sample predictions even using other
datasets. In particular, you can
. use ds1
(fit a model)
. use two /* another dataset */
. predict yhat, ... /* fill in the predictions */”