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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: AW: Economic Significance and Logged Independent Variables |

Date |
Wed, 8 Jul 2009 16:28:38 +0200 |

Thanks Martin. I try to explain in detail what I do I run a regression of Debt/Total Assets on logged Total Assets (TA) and other variables. Then I multiply the coefficient estimate on logged TA by the standard deviation of logged TA. This product is equal to 0.15. Then I repeat the same exercise except that I replace logged TA with TA. I multiply the coefficient on TA by the standard deviation of TA. This product is equal to 0.0002. I am puzzled by the fact that the economic effect drops from 0.15 with logged TA to 0.0002 when TA is not logged. Thanks, Erasmo On Wed, Jul 8, 2009 at 4:10 PM, Martin Weiss<martin.weiss1@gmx.de> wrote: > > <> > > > > Since I did not know about this research strategy of yours when I initially > posted, I could not possibly suggest that it is not correct. What is it, > though, that you read into the result of this calculation? With this > information in hand, I _may_ be able to give you a hint whether the strategy > is valid... > > > > HTH > Martin > > > -----Ursprüngliche Nachricht----- > Von: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Erasmo Giambona > Gesendet: Mittwoch, 8. Juli 2009 15:44 > An: statalist@hsphsun2.harvard.edu > Betreff: Re: st: AW: Economic Significance and Logged Independent Variables > > Thanks Martin. Sorry, I think something is not completely clear to me. > What I am doing to get the economic effect in the case of the logged > covariate is to multiply the raw coefficient (on the logged covariate) > by the standard deviation of the logged covariate. Are you suggesting > that this is not correct? > > Thanks, > > Erasmo > > On Wed, Jul 8, 2009 at 3:19 PM, Martin Weiss<martin.weiss1@gmx.de> wrote: >> >> <> >> >> You put a covariate into logs, right? So the interpretation should be that > a >> one percent increase (not standard deviation) in this covariate causes an >> absolute increase in the dependent to the tune of the respective >> coefficient. The huge difference can be traced back to this different >> interpretation of the output, as the example shows: >> >> >> *** >> sysuse auto, clear >> reg we pr len he >> loc level=_b[pr] >> gen lnpr=log(pr) >> reg we lnpr len he >> >> di in red "Coeff in levels: " /* >> */ `level' ", in logs: `=_b[lnpr]'" >> *** >> >> >> >> HTH >> Martin >> >> >> -----Ursprüngliche Nachricht----- >> Von: owner-statalist@hsphsun2.harvard.edu >> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Erasmo > Giambona >> Gesendet: Mittwoch, 8. Juli 2009 15:09 >> An: statalist >> Betreff: st: Economic Significance and Logged Independent Variables >> >> Dear Statalist, >> >> I have a panel dataset for a sample of publicly listed firms. >> >> I am fitting the following model using OLS: Debt/Total Assetsi = a + >> b*ln_Total_Assets + control variables + firm dummies + year dummies + >> ei. - where i is a subscript for firm i. >> >> The dependent variable is total Debt divided by Total Assets (both >> expressed in millions), which is a ratio ranging between 0 and 1; >> ln_Total_Assets is the natural logarithm of total assets. >> >> The output of the above regression shows that ln_Total_Asset is >> statistically significant at the 1% level. This variable has also a >> huge economic effect. In fact, a 1 standard deviation increase in >> ln_Total Assets causes Debt/Total Assetsi to increase by 0.15 (while >> its average is 0.202). >> >> Then, I run Debt/Total Assetsi = a + b*Total_Assets + control >> variables + firm dummies + year dummies + ei. This model differs from >> the above one only because I am not logging Total_Assets. In this >> case, I find that Total Assets is still highly statistically >> significant at the 1% level. However, its economic effect is >> negligible. In fact, a 1 standard deviation increase in Total Assets >> causes Debt/Total Assetsi to increase by 0.0002 (while its average is >> 0.202). >> >> I can see that logging a variable can make a difference on its >> economic effect. However, changing the economic effect from 0.15 to >> 0.0002 seems really a big difference. Can somebody provide some hints >> on why this might be happening? Is that an indicatio that there might >> be something special about the structure of my data? >> >> I would really appreciate any suggestions. >> >> Thanks, >> >> 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/ >> > > * > * 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/ > * * 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**:**AW: st: AW: Economic Significance and Logged Independent Variables***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**AW: st: AW: Economic Significance and Logged Independent Variables***From:*"Martin Weiss" <martin.weiss1@gmx.de>

**References**:**st: Economic Significance and Logged Independent Variables***From:*Erasmo Giambona <e.giambona@gmail.com>

**Re: st: AW: Economic Significance and Logged Independent Variables***From:*Erasmo Giambona <e.giambona@gmail.com>

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