------------------------------------------------------------------------------- help forseldum-------------------------------------------------------------------------------

Various inequality indicators

seldumvarlist[,replay]

Description

seldumis 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.

seldumtransforms 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 invarlist.At the moment,

seldumdoes not work for multiple-equation models, includingheckmanandtreatreg.

Option

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

DetailsConsider 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)

seldumcomputes 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

seldumreturns its results in r():r(b_varname) percentage impact of the varibale

varnamer(se_varname) standard error of the percentage impact of variable

varnameThe 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

ReferencesKennedy, 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 seelevpredict if installed (available via ssc)

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