RE: st: RE: RE: estimation with a time trend.

["Nick Cox" <n.j.cox@durham.ac.uk>]

Good question, but clearly 

1. Most postings in the thread, and the specific suggestions you received, were sent _before_ you made it clear that you were using -xtreg-. 

2. If the question is, how best to estimate a time trend, with nothing else said, then translating time to a sensible origin remains good general advice. 

Nick 
n.j.cox@durham.ac.uk 

natasha agarwal

On Mon, Jul 5, 2010 at 2:22 PM, Martin Weiss <martin.weiss1@gmx.de> wrote:
>
> <>
>
> The coeff for "t" will stay the same, then, no matter how you "center" it:
>
> *************
> use http://www.stata-press.com/data/r11/nlswork, clear
> egen t=group(year)
> xtreg  ln_wage wks_work tenure south nev_mar age t, fe vce(robust)
> replace t=t-7
> xtreg  ln_wage wks_work tenure south nev_mar age t, fe vce(robust)
> replace t=t-3
> xtreg  ln_wage wks_work tenure south nev_mar age t, fe vce(robust)
> *************

I tried this and as you said the coefficient stays the same. I was
wondering then what is the point in doing this then?

natasha agarwal
>
> On Mon, Jul 5, 2010 at 2:01 PM, Nick Cox <n.j.cox@durham.ac.uk> wrote:
>> Your original question was
>>
>> "I was trying to estimate a production function with an unbalanced
>> firm-year panel data and wanted to include a time trend. However I was
>> not sure if the time trend was created correctly.
>>
>> egen t=group(year)
>>
>> I was wondering if anyone could please tell me if this was correct?"
>>
>> Who knows whether the commands you are using "mean center" the data if
>> you do not tell us what they are?
>
> I am sorry about this.
>
> I issue the following line of commands:
>
> egen t=group(year)
> xtreg lnrval lnk lnw lnvfdi t, fe vce(robust)

>> natasha agarwal
>>
>> On Mon, Jul 5, 2010 at 1:14 PM, Maarten buis <maartenbuis@yahoo.co.uk>
>> wrote:
>>
>>> --- On Mon, 5/7/10, natasha agarwal wrote:
>>>> I am afraid I did not understand "year- (or -year-
>>>> MINUS> midpoint) for interpretability?"
>>>
>>> Say you have a variable representing year of birth
>>> ranging between 1910 and 1980. I would then usually
>>> have a line like this in my do-file:
>>>
>>> gen c_year = year - 1910
>>>
>>> Afterwards I would use c_year instead of year. In
>>> this case "midpoint" is 1910, and makes sure that
>>> your new variable is shifted to the left such that
>>> it has the value zero in 1910. This makes sure
>>> that the baseline in your models refer to a point
>>> at the beginning of your observed period. This is
>>> particularly important if you include interactions
>>> or if you care about the constant (e.g. in a random
>>> effects model)
>>
>> I am estimating the model with a within estimator. I thought that they
>> mean center the data anyways?

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