[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Reconcile Log Transformed with Untransformed Results |

Date |
Sat, 13 Feb 2010 19:10:31 +0100 |

Thanks Austin. This is really helpful. Assuming I want to use the log specification, can I still compuet economic significance? That is, in the example, could I say that a 1 IQR change in X (i.e., 0.85) is approximately associated with a 0.008*0.85=0.0068 change in Y? Thanks you, Erasmo On Sat, Feb 13, 2010 at 2:03 PM, Austin Nichols <austinnichols@gmail.com> wrote: > Erasmo Giambona <e.giambona@gmail.com>: > No, not correct: a regression of ln(y+1) on ln(x+1) does not estimate > an elasticity, and a change from -0.45 to +0.4 does not correspond to > any well-defined percentage point change. If you are unsure of the > correct functional form, consider -lpoly- or -fracpoly- or -mkspline- > or -pspline- (on SSC). > > On Sat, Feb 13, 2010 at 7:10 AM, Erasmo Giambona <e.giambona@gmail.com> wrote: >> 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/ > * * 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:*Maarten buis <maartenbuis@yahoo.co.uk>

**References**:**st: Reconcile Log Transformed with Untransformed Results***From:*Erasmo Giambona <e.giambona@gmail.com>

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

- Prev by Date:
**st: RE: How to treat a variable that switches from being endogenous to exogenous in a dynamic panel data model** - Next by Date:
**st: RE: heckprob dropping observations** - Previous by thread:
**Re: st: Reconcile Log Transformed with Untransformed Results** - Next by thread:
**Re: st: Reconcile Log Transformed with Untransformed Results** - Index(es):

© Copyright 1996–2015 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |