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From |
Kit Baum <baum@bc.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Re: log transformations of dependent and independent variables |

Date |
Wed, 7 Sep 2005 07:36:08 -0400 |

This kind of specification (log Y vs log X) is a constant elasticity model (see mfx, eyex) in which the coefficients represent the effect of a percent change in X in terms of percent changes of Y. If you leave some variables untransformed (including dummies) then those coefficients are semi-elasticities (d ln Y / dX) in which you examine the effect of a one unit change in X in terms of percent changes of Y (see mfx, eydx). You may have reason to believe that a unit change in some (non-dummy) Xs has a proportional effect on Y. An obvious example is a log trend model, ln Y = a + b t; each unit of time changes Y by approximately b percent (rather than b units of Y, as would be the case without logs).

Kit Baum, Boston College Economics

http://ideas.repec.org/e/pba1.html

On Sep 7, 2005, at 2:33 AM, Chriswrote:

yes, this is a common thing to do. wage regressions are a good example.=20

economists usually take the log of the dependent variable (wages). and=20

then some regressors (such as education) typically enter the equation=20

linearly -- including some dummy variables like race or sex dummies.=20

while other regressors (such as parents' income) typically enter in log=20

form.

chris

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