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From |
"Martin Weiss" <martin.weiss1@gmx.de> |

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

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

Date |
Wed, 8 Jul 2009 15:19:15 +0200 |

<> 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/

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

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