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Re: st: Demeaning TFP
SAM MCCAW <firstname.lastname@example.org>
Re: st: Demeaning TFP
Tue, 23 Oct 2012 13:01:40 -0400
Thanks a lot for your comments and help.
I went back to the Stata Journal and realized the plight of not
So I'm going to go ahead and point out the mistake I made as I assume
that a lot of people using levpet might run into the same issue. At
the end of the levpet article in the SJ, the authors clearly note that
the predict option for levpet predicts the estimated TFP. So, the
command "predict TFP, omega" would give the predicted values for TFP
and not the predicted output. The command also assumes that the
production function is in logs and adjusts for it so the predict
option does not give ln(TFP) either, but TFP itself, so one has to
take logs of the predicted values to get lnTFP.
If one misses to read that important note, they would assume that the
predict command gives you the predicted value of output from the
production function. This is the mistake I made.
Thanks again for replying to my query.
On Wed, Oct 10, 2012 at 5:53 PM, SAM MCCAW <email@example.com> wrote:
> Dear All,
> I am trying to assess productivity spillovers from foreign to domestic
> firms and am using levpet as my productivity estimation technique.
> After I run levpet (both on pooled sample and then industry by
> industry) I get some gigantic values for lnTFP.
> My sample for running levpet includes both domestic and foreign firms,
> i.e. I am not running levpet for domestic firms only.
> The summary stats for lnTFP are as follows:
> Variable | Obs Mean Std. Dev. Min Max
> lnTFP_pooled | 21923 -1247.003 106482.5 -1.43e+07 17.18935
> lnTFP_industry | 18710 -5587274 3.56e+08 -4.57e+10 24.17001
> Now I would like to demean TFP but since I have so many really high
> negative values, would demeaning lnTFP by country and industry just
> make it worse?
> Also, I am afraid to restrict the sample to a certain level of lnTFP,
> for example as far as - 100.
> Preferably I would just restrict the sample to exclude outliers but I
> have about 3000 firms which have lnTFP less than -50 in a total sample
> of 21923.
> Also, if I go ahead and use these lnTFP values in my regression, by
> elasticity magnitudes turn up to be 4 digits long. Yikes.
> I have tried data transformations and so on but am at a loss. Any
> thoughts would be greatly appreciated.
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