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

To |
statalist@hsphsun2.harvard.edu |

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

Date |
Thu, 25 Feb 2010 18:32:17 +0100 |

Thanks Tony. Actually, I take the log of 1+y. Yes, i tried glm with a log link and that helps as well. The issue is that i found it difficult to interpret the results in economic terms. All the details are in the previous emails. Erasmo On Thu, Feb 25, 2010 at 6:24 PM, Lachenbruch, Peter <Peter.Lachenbruch@oregonstate.edu> wrote: > Since one of your y's is negative, -0.03, why should taking logs help? Would a glm with a log link help? > > Tony > > Peter A. Lachenbruch > Department of Public Health > Oregon State University > Corvallis, OR 97330 > Phone: 541-737-3832 > FAX: 541-737-4001 > > > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Erasmo Giambona > Sent: Thursday, February 25, 2010 4:32 AM > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: Reconcile Log Transformed with Untransformed Results > > Thanks Austin. I have been traveling so it has been difficult to look > into this issue. To answer your question. I am using a two-step > procedure that is used sometime in monetary policy research. My y is a > coefficient estimated from a panel regression using firm level data. > This is the first step. y ranges from -0.03 to +0.07 (with mean=0.023, > median=0.024, st dev=0.028, skew=-.37, kurt= 2.52). I have 16 y's, one > per year. In the secon step i regress y on x, where x is an annual > interest rate spread ranging from -.95% to 1.15% (with mean=3.96e-07, > median=.0004551, st dev=.6426913, skew=.1102487, kurt= 2.15). The > scatter of y on x clearly shows that y increase with x, but there is > one obs (out of the 16) with a very low x and a very high y. I am > taking the logs to try to reduce the effetc of this obs. Thought this > is more parimonious relative to the alternative of dropping hte obs > and winsorizing seems unfeasible with 16 obs. > > Any additional thoughts would be appreciated, > > Erasmo > > On Tue, Feb 16, 2010 at 6:11 PM, Austin Nichols <austinnichols@gmail.com> wrote: >> Erasmo Giambona <e.giambona@gmail.com>: >> As I already pointed out, I doubt your estimates correspond to any >> well-defined percentage point change. Perhaps you can give us a >> better sense of the distributions of the untransformed y and x (and >> what they measure and in what units), and what the scatterplot of y >> against x looks like. You may also prefer to state your effects in >> terms of standard deviations rather than the interquartile range. >> >> On Tue, Feb 16, 2010 at 9:39 AM, Erasmo Giambona <e.giambona@gmail.com> wrote: >>> Thanks Maarten. In this example, OLS and GLM give very similar >>> econimic effects. In fact, 74 cents for the OLS is really 9.52% >>> relative to the mean wage of 7.77. This 9.52% is very much in line >>> with the 9.7% found with GLM. In my case, the coeff. on X for the OLS >>> is 0.0064. Relative to the mean for the LHS variable of 0.02. This is >>> an economic effect of about 28%. With the GLS, using exactly your >>> code, X gets a coefficient of 2.025 or a 102.5% increase in Y. Or >>> perhaps, I am misinterpreting this coefficient. >>> >>> Thanks, >>> >>> Erasmo >>> >>> On Mon, Feb 15, 2010 at 9:22 AM, Maarten buis <maartenbuis@yahoo.co.uk> wrote: >>>> --- On Sun, 14/2/10, Erasmo Giambona wrote: >>>>> I ran the regressions with both RHS and LHS untransformed >>>>> using both OLS and GLM with link(log). With the OLS the >>>>> coeff on X is 0.006 while with the GLM the coefficient is >>>>> 0.700. I find a bit hard to intepret the GLM coefficient. >>>> >>>> Consider the example below: >>>> >>>> *--------------- begin example ----------------- >>>> sysuse nlsw88, clear >>>> gen byte baseline =1 >>>> >>>> reg wage grade >>>> glm wage grade baseline, /// >>>> link(log) eform nocons >>>> *--------------- end example -------------------- >>>> >>>> >>>> The -regress- results are interpreted as follows: >>>> People without education can expect a wage of >>>> -1.96 dollars an hour (substantively we know that >>>> people hardly ever pay for the privelege to work, >>>> so this is a sign of bad model fit), and they get >>>> 74 cents an hour more of every additional year of >>>> education. >>>> >>>> The -glm- results are interpreted as follows: >>>> People without education can expect a wage of >>>> 2.25 dollars an hour, and for every additional >>>> year of education they can expect an increase >>>> of 9.7%. >>>> >>>> Hope this helps, >>>> Maarten >> >> * >> * 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**:**Re: st: Reconcile Log Transformed with Untransformed Results***From:*Austin Nichols <austinnichols@gmail.com>

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

**Re: st: Reconcile Log Transformed with Untransformed Results***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: 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>

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

**RE: st: Reconcile Log Transformed with Untransformed Results***From:*"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>

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