*Interpretation of logarithms in a
regression*

*If you do not see the menu on the
left please **click here*

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*

SOURCE: http://www.stata.com/help.cgi?predict

“**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

estimation subsample.

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 */”