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help for seldum
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Various inequality indicators

    seldum varlist [, replay]


Description

seldum is a post-estimation command to be used after the estimation of a linear
regression model with a logarithmic dependent variable. This means that it has
to be used immediately after a call to an estimation command as e.g. regress.

seldum transforms the coefficients estimated by the model so that they can be
interpreted as percentage effects on the dependent variable. The calculations
are made for coefficients relating to the variables specified in varlist .

At the moment, seldum does not work for multiple-equation models, including
heckman and treatreg.


Option

replay requests the display of the results of the last estimation model, i.e.
the model to be used in the calculations.


Details

Consider the following semilogarthmic regression model:

ln(Y) = a + b*X + e 

If the independent variable X is continous, b gives the percentage change in Y
implied by a small change in X. In the case where X is a dummy varibale, the
same interpretation is frequently used. However, if X is a dummy variable, this
interpretation is only approximative. Kennedy (1981) has proposed the following
estimator:

p = exp(b - 0.5*V(b)) - 1    (1)

where V(b) is the variance of b. In principle, the variance of p could be
computed by using the delta method. Alternatively, Van Garderen and Shah (2002)
have derived the following estimator for the variance of p, which they claim to
be more accurate than the delta method:

V(p) = exp(2*b)*(exp(-V(b)) - exp(-2*V(b)))    (2)

seldum computes Kennedy's estimator as given by equation (1) as well as its
standard error, as given by equation (2).

The paper by Van Garderen and Shah (2002) provides a more detailed discussion
on this topic.


Saved Results

seldum returns its results in r():

    r(b_varname) percentage impact of the varibale varname

    r(se_varname) standard error of the percentage impact of variable varname

The advantage of saving the results in r() is that the results saved by the
preceeding regression are not modified. These results remain available after a
call to seldum.

        
Example

    . sysuse nlsw88, clear

    . generate lwage = ln(wage)

    . regress lwage collgrad smsa union south race ttl_exp

    . seldum collgrad union

    . seldum collgrad union, replay



References

Kennedy, P. E. (1981). Estimation with Correctly Interpreted Dummy Variables in
    Semilogarithmic Equations. American Economic Review, 71(4):801.

van Garderen, K. and Shah, C. (2002). Exact Interpretation of Dummy Variables
    in Semilogarithmic Equations. The Econometrics Journal, 5(1):149-159.


Also see

levpredict if installed (available via ssc)


Author

Jean Ries
STATEC, Luxembourg
jean.ries@statec.etat.lu