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From |
Erasmo Giambona <e.giambona@gmail.com> |

To |
statalist <statalist@hsphsun2.harvard.edu> |

Subject |
st: Reconcile Log Transformed with Untransformed Results |

Date |
Sat, 13 Feb 2010 13:10:22 +0100 |

Dear All, I am estimating the following model using simple OLS: Y=a+bX+e. The b coefficient is equal to 0.006. The 25th percentile of X=-0.45 and the 75th percentile of X=0.40. The mean of Y is equal to 0.026. I use this information to gauge a sense of the economic effect of X on Y. I find that a 1 interquartile range (IQR) change in X =(0.40+0.45) has an effect on Y equal to 0.006*0.85=0.0051, which is a 20% change in Y (obtained as 0.0051/0.026) and seems quite sizable. Next, I re-estimate the same model, but first I log transform both RHS and LHS as follows: LNY=ln(1+Y) and LNX=ln(1+X). Therefore, I estimate the following model: LNY=A+B*LNX+E. The B coefficient is equal to 0.008 in this case. It seems the interpretation of this coefficient is the following: a 1% change in X casuses a 0.008% increase in Y. Alternatively, if I consider a 189% change in X (i.e., the percentage increase from the 25th to the 75 percentile) I find that this causes a 1.51% increase in Y (obtained as 189*0.008). My question is: is this calculation correct? I find it hard to reconcile it with the untransformed results, where a 1 IQR change in X causes Y to increase by 20%. Thanks for any suggestions on the issue, Erasmo * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Reconcile Log Transformed with Untransformed Results***From:*Austin Nichols <austinnichols@gmail.com>

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